1. health and fitness
2. disease
3. cancer

IDENTIFICATION OF METASTASIS-ASSOCIATED GENES
IN PROSTATE CANCER
by
DONG LIN
M.D., China Medical University, 2000
M.Sc., China Medical University, 2003
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
in
THE FACULTY OF GRADUATE STUDIES
(Pathology and Laboratory Medicine)
THE UNIVERSITY OF BRITISH COLUMBIA
(Vancouver)
March 2010
© Dong Lin, 2010
ABSTRACT
Metastasis is thought to be based on genetic and epigenetic alterations. The mechanisms
underlying prostate cancer metastasis are not clear. Studies aimed at identifying genes with key
roles in this process have been impeded by lack of clinically relevant models. The heterogeneity
of primary prostate cancer specimens from patients, consisting of non-metastatic and metastatic
subpopulations, hampers identification of metastasis-associated genes by direct comparison of
primary and secondary cancers. To overcome such hurdles, metastatic and non-metastatic tumor
sublines have been developed from one patient‟s primary prostate cancer specimen using
subrenal capsule grafting into NOD-SCID mice. Chromosomal alterations present in the
metastatic subline, but not in non-metastatic counterparts, were identified in a small percentage
of cells in the parental tissue, suggesting that metastatic potential of primary cancers can be
associated with a small cancer cell subpopulation. Sublines with different metastatic potential
derived from same patient‟s multifocal primary cancer provide valuable materials for identifying
metastasis-associated genes and predictive markers. To identify metastasis-associated genes,
differential gene expression analysis of metastatic PCa1-met and non-metastatic PCa2 prostate
cancer sublines was carried out. Among various differentially expressed genes identified,
ASAP1, a gene not previously associated with prostate cancer, was upregulated in the metastatic
subline as confirmed by qRT-PCR and immunohistochemical staining. In clinical specimens,
ASAP1 protein staining was elevated in 80% of primary prostate cancers and substantially
higher in metastatic lesions compared to benign prostate tissue. Extra ASAP1 gene copies were
detected in 58% of primary prostate cancer specimens. Increased ASAP1 protein expression was
ii
correlated with prostate cancer metastasis and PSA recurrence. siRNA- and shRNA-induced
reduction of levels of ASAP1 protein markedly suppressed in vitro PC-3 cell migration, matrigel
invasion and metastasis in vivo. These results indicate that ASAP1 plays an important role in
prostate cancer invasion and metastasis and suggest that it provides a potential predictive marker
and therapeutic target for the disease. Furthermore, the approach used to identify metastasisassociated genes by comparison of gene profiles of paired metastatic and non-metastatic sublines
was validated. The subrenal capsule xenograft system provides a valuable platform for studying
various aspects of prostate cancer metastasis.
iii
TABLE OF CONTENTS
ABSTRACT …………..……..……………………………………………..…………………... ii
TABLE OF CONTENTS …………………..……….……………………………..………….. iv
LIST OF TABLES ……………………..…………………………………………………….. viii
LIST OF FIGURES ………………………………….…………………………..………….... ix
LIST OF ABBREVIATIONS ……………………………………………………...……….… xi
ACKNOWLEDGEMENTS ………………………………………………………..……..….. xiv
DEDICATION …………………………………………………..…………………..………… xv
CO-AUTHORSHIP STATEMENT………………………………………………………....xvi
CHAPTER 1
INTRODUCTION …………………………………………………………… 1
1.1 PROSTATE GLAND AND PROSTATE CANCER ……………………….……… 1
1.1.1
Prostate gland …………………………………………...…………….. 1
1.1.2
Prostate cancer …………….………………………………………... 3
1.2 CANCER INVASION AND METASTASIS ……………………………...………… 5
1.2.1
Overview ………………..………………………………...…………… 5
1.2.2
Cancer invasion …………………….……………………...………..… 5
1.2.3
Adhesive structures associated with tissue invasion and
cell migration ………………………………………………………...… 8
1.2.4
Genes associated with prostate cancer invasion and
metastasis...................................................................................…. 9
1.3 PROSTATE CANCER MODELS ………………………………………..…...……17
1.3.1
Rat model ……………………………………..……………………… 17
1.3.2
Canine model ………………………….…….…………………...….. 17
1.3.3
Mouse model ………………………….……….……...………………18
1.3.4
Xenograft model ………………..………………….…………...……. 20
1.4 SERIAL ANALYSIS OF GENE EXPRESSION (SAGE) ……………...…..…… 23
iv
1.5 HYPOTHESES AND SPECIFIC AIMS ………………………………………..… 26
CHAPTER 2
DEVELOPMENT OF METASTATIC AND NON-METASTATIC
SUBLINES FROM A PATIENT’S PROSTATE CANCER SPECIMEN
– IDENTIFICATION OF A SMALL SUBPOPULATION WITH
METASTATIC POTENTIAL IN THE PRIMARY TUMOR ……….… 28
2.1. INTRODUCTION ……………...…………………………………………………… 28
2.2. MATERIALS AND METHODS ………………………...………….……………… 30
2.2.1.
Materials and animals ……………….…………….………………… 30
2.2.2.
Prostate cancer tissue acquisition …………………...……..……... 30
2.2.3.
Subrenal capsule grafting and development of transplantable
tumor tissue lines …………………………...………………........… 31
2.2.4.
In vivo orthotopic metastatic assay………….……………………… 31
2.2.5.
Histopathological and immunohistochemical staining ………….... 32
2.2.6.
Spectral karyotyping (SKY)……………………………………….... 33
2.2.7.
Fluorescence in situ hybridization ……………………………..…... 33
2.3. RESULTS ……………………………………………………………………….….. 34
2.3.1.
Development of metastatic and non-metastatic sublines
from primary prostate cancer tissue via xenografting and
in vivo metastatic assay ……………..…………………………….... 34
2.3.2.
Identification by SKY of unique chromosomal aberrations
in tumor tissue lines ………..………………………………………... 38
2.3.3.
Detection of cancer cells in parental tissues carrying the
metastatic clone signature (10q and 6p alterations) ……….…..… 38
2.4. DISCUSSION …………………………………………………………..………….. 42
CHAPTER 3
IDENTIFICATION OF ASAP1, A PROSTATE CANCER
METASTASIS-ASSOCIATED GENE …………………………………… 45
3.1. INTRODUCTION ………………….……………..……………………………..…. 45
v
3.2. MATERIALS AND METHODS ……………………….…………………………... 48
3.2.1.
Materials and animals ……….………………..…………………….. 48
3.2.2.
Xenografts ………..…………………………………..………………. 48
3.2.3.
SAGE library construction and comparative analysis ………….… 48
3.2.4.
Quantitative real-time polymerase chain reaction (qRT-PCR) ….. 49
3.2.5.
Clinical prostate cancer tissues ……………………………….….... 50
3.2.6.
Post-operative follow-up ………………………………………….…. 51
3.2.7.
Histopathological and immunohistochemical staining …………… 51
3.2.8.
ASAP1 scoring ……………………………………………………….. 51
3.2.9.
Fluorescence in situ hybridisation (FISH) analysis for
determination of ASAP1 gene copy number ………………….….. 52
3.2.10. Statistical analysis …………………………………………………… 52
3.3. RESULTS ……………………………………………………………………...…… 53
3.3.1.
Comparative analysis of SAGE libraries of metastatic
and non-metastatic prostate cancer sublines …………………….. 53
3.3.2.
Differential ASAP1 gene expression in PCa1-met
and PCa2 tumor sublines …………………………………………… 57
3.3.3.
Differential expression of ASAP1 protein in xenograft tissues .…. 57
3.3.4.
Expression of ASAP1 protein in clinical prostate samples …...…. 59
3.3.5.
Association of ASAP1 protein expression in primary tumors
with clinicopathological parameters …………………………..…… 62
3.3.6.
ASAP1 gain/amplification in clinical prostate samples ……….. 62
3.4. DISCUSSION ………………………………………………………………………..66
CHAPTER 4
FUNCTIONAL VALIDATION OF ASAP1 AS A METASTASISASSOCIATED GENE IN PROSTATE CANCER ..................................71
4.1. INTRODUCTION …………………………………………………………….……...71
4.2. MATERIALS AND METHODS ……………………………………………….……74
4.2.1.
Materials and animals ……………………………..………………….74
vi
4.2.2.
Cell cultures …………………………..……………………………….74
4.2.3.
Small interfering RNA (siRNA) and cell transfection ………………74
4.2.4.
Generation of the lentiviral constructs …………………………..….75
4.2.5.
Virus production and transductions …………………..……………..76
4.2.6.
Western blotting ………………..……………………………………..77
4.2.7.
In vitro cell proliferation assay …………………...…………………..78
4.2.8.
Scratch wound healing migration assay …………………………....78
4.2.9.
Matrigel invasion assays ………………………………………..……78
4.2.10. In vivo orthotopic metastatic assay ………………………………….79
4.2.11. Histopathological and immunohistochemical staining ……………79
4.2.12. Statistical analysis …………………………………………………….80
4.3. RESULTS ……………………………………………………………………..……..80
4.3.1.
Knockdown of ASAP1 protein by siRNA decreases PC-3 cell
migration and invasion …………………………………..……...……80
4.3.2.
Effect of reduced ASAP1 expression on in vitro invasion and
in vivo metastatic ability of PC-3 cells stably transduced with
shRNA ……………………………………………….…………...……82
4.3.3.
Effect of ASAP1 overexpression on invasiveness of LNCaP
cells ……….…………………..………………………………….……84
4.4. DISCUSSION ………………………………………………………………………..88
CHAPTER 5
SUMMARY AND SPECULATIONS ………………………………...…..92
REFERENCES ………………………………………………………………………………. 99
APPENDIX …………………………………...………………………………………………121
A1. Animal Care Certificate……………………………………………………………..122
A2. UBC Ethics Board Approval………………………………………………………..124
vii
LIST OF TABLES
Table 1.1
Metastasis-related genes in prostate cancer …………………………. 10
Table 2.1
Biological characteristics of tumor lines LTL-220M,
LTL-220N and LTL-221N……..…………………………………………36
Table 3.1
Characteristics of LongSAGE tag frequency distribution …………… 54
Table 3.2
Compositions of human specific tags in PCa1-met and PCa2
libraries……………………………………………………………………...56
Table 3.3
ASAP1 expression in clinical prostate tissues …………..…….………63
Table 3.4
Association between ASAP1 expression and clinicopathological
parameters …………………...……………………………………………64
Table 4.1
Decreased metastasis of PC-3 cells in vivo by reduction of ASAP1
expression……………...…………………………………...……………..86
viii
LIST OF FIGURES
CHAPTER 1
Figure 1.1
Normal adult prostate glands ………………………………………………2
Figure 1.2
Cancer metastasis cascades ………………………………………………6
Figure 1.3
An outline of the regular SAGE and LongSAGE methods ……………25
CHAPTER 2
Figure 2.1
Development of metastatic and non-metastatic tumor tissue sublines
from a primary prostate cancer tissue….....……………………….…… 35
Figure 2.2
Different local invasive and metastatic abilities of the LTL-220M,
LTL-220N and LTL-221N sublines ……………………………………….37
Figure 2.3
SKY analysis of the LTL-220M, LTL-220N and LTL-221N
sublines ……………………………………………………….……………39
Figure 2.4
FISH detection of 10q and 6p alterations in the LTL-220M, LTL-220N,
LTL-221N sublines and their parental (early-generation) grafts ………40
CHAPTER 3
Figure 3.1
Different local invasive ability of PCa1-met and PCa-2…………………47
Figure 3.2
Confidence intervals highlight expressed tag types with non-linear
relationships between LongSAGE libraries derived from PCa1-met
and PCa2.……………………………………….…………………..………55
Figure 3.3
Differential ASAP1 expression in PCa1-met and PCa2 sublines…..… 58
Figure 3.4
Immuno-histochemical staining of ASAP1 in a tissue microarray
of clinical prostate samples ………………………………………………60
Figure 3.5
ASAP1 protein expression in clinical samples of invasive and
metastatic prostate cancer …………………………………………….….61
Figure 3.6
Probabilities of Prostate-Specific Antigen (PSA) recurrence-free
survival in patients treated with radical prostatectomy according
to ASAP1 expression ……………………………...………...……………65
ix
Figure 3.7
Gain and/or amplification of ASAP1 shown by dual-color FISH
in human primary prostate cancer tissues ………………………………67
CHAPTER 4
Figure 4.1
Schematic representation of ASAP1 and ASAP1b proteins………… 72
Figure 4.2
Effects of siRNA-reduced ASAP1 protein expression on cell
migration and matrigel invasiveness of PC-3 cells …………….……….81
Figure 4.3
Effects of stable ASAP1 knockdown on cell invasiveness of PC-3
cells …………………………………………..……………………………...83
Figure 4.4
Effects of stable ASAP1-knockdown on metastatic activity of PC-3
cells in NOD-SCID mice …………………………………………….…... 85
Figure 4.5
Effects of stable ASAP1 protein overexpression on cell
invasiveness of LNCaP cells…….….……………………………………. 87
x
LIST OF ABBREVIATIONS
ADP
adenosine diphosphate
ANK
ankyrin repeats
AR
androgen receptor
ARF
ADP ribosylation factor
Arf GAP
ADP ribosylation factor GTPase-activating protein
ASAP1
ArfGAP with SH3 domain, ankyrin repeat and PH domain 1
ATP
adenosine triphosphate
BAC
bacterial artificial chromosome
BAR
Bin–Amphiphysin–Rvs domain
BCA
bicinchoninic acid
BMPs
bone morphogenetic proteins
BPH
benign prostatic hyperplasia
BRCA2
breast cancer 2
CAMs
cell adhesion molecules
cDNA
complementary deoxyribonucleic acid
CI
confidence interval
c-Met
mesenchymal-epithelial transition factor
CMOST
comprehensive mapping of SAGE tags
CTL
cytotoxic T-lymphocyte
CO2
carbon dioxide
CXCR4
CXC chemokine receptor 4
DAB
3,3'-diaminobenzidine tetrahydrochloride
DAPI
4',6-diamidino-2-phenylindole
DARC
Duffy antigen receptor for chemokines
DMEM
Dulbecco's Modified Eagle Medium
DNA
deoxyribonucleic acid
ECM
extracellular matrix
EDTA
ethylenediaminetetraacetic acid
xi
EmGFP
emerald green fluorescent protein
EMT
epithelial - mensenchymal transition
ET-1
endothelin-1
ETV6
E26 transformation-specific family variant 6
EZH2
enhancer of zeste homolog 2
FAK
focal adhesion kinase
FBS
fetal bovine serum
FFPE
formalin-fixed and paraffin-embedded
FISH
fluorescence in situ hybridization
GAP
GTPase-activating protein
GEM
genetically engineered mouse
GFP
green fluorescent protein
GSTP1
glutathione S-transferase pi 1
H&E
hematoxylin and eosin
IDC
invasive ductal carcinoma
IGF
insulin-like growth factor
IGFBP3
IGF-binding protein 3
L.N.
lymph node
kDa
Kilodaltons
MHC
major histocompatibility
MKK
mitogen-activated protein kinase-kinase
MMPs
matrix metalloproteinases
MPR
mouse prostate reconstitution
MSR1
macrophage scavenger receptor 1
MTT
methylthiazolyldiphenyl tetrazolium
NKX3.1
NK3 homeobox 1
NOD-SCID
nonobese diabetic/severe combined immunodeficiency
PAR1
protease-activated receptor 1
PBS
phosphate buffered saline
PCR
polymerase chain reaction
PH
pleckstrin homology domain
xii
PIN
prostatic intraepithelial neoplasia
PRD
proline rich domain
PIP2
phosphatidylinositol-4,5-bisphosphate
PSA
Prostate-specific antigen
PTEN
phosphatase and tensin homolog
PVDF
polyvinylidene difluoride
qRT-PCR
quantitative real-time polymerase chain reaction
RefSeq
Reference Sequences database
RIPA
Radioimmunoprecipitation assay
RNA
Ribonucleic acid
RNASEL
ribonuclease L
RPMI
Roswell Park Memorial Institute
SAGE
serial analysis of gene expression
SD
standard deviation
SDS
sodium dodecyl sulfate
SH3
Src homology 3
SHH
sonic hedgehog homolog
siRNA
small interfering RNA
SKY
spectral karyotyping
TGF
transforming growth factor
TMA
tissue microarrays
TMPRSS2/ETS transmembrane protease, serine 2/ E26 transformation-specific family
TNM
Tumor/Nodes/Metastases
TRAMP
transgenic mouse model of prostate
UGS
urogenital sinus
VEGF
vascular endothelial growth factor
xiii
ACKNOWLEDGEMENTS
First, I would like to express my heartfelt gratitude to Dr. Yuzhuo Wang for all his
guidance, encouragement and efforts during the course of my graduate studies. I extend my
gratitude to the supervisory committee members, Drs. Marianne D. Sadar, C. Blake Gilks,
Cheryl D. Helgason and Cheryl Wellington, for their time and valuable input during my
research.
I would like to acknowledge many members of the Dr. Wang‟s laboratory for helpful
advice and support throughout my studies: Yuwei Wang, Akira Watahiki, Fang Zhang, Peter W.
Gout, Hui Xue, Rebecca Wu, Takashi Kagami, Jun Guan, Margaret Sutcliffe, Hisae Nakamura
and Chris Low.
I would also like to thank my professional collaborators who have made so many of my
experiments possible, especially Drs. Martin E. Gleave, Alan I. So, Ladan Fazli, Antonio
Hurtado-Coll and Dieter Fink at The Vancouver Prostate Centre; Dr. Jeremy A. Squire and Jane
Bayani at The Ontario Cancer Institute; Drs. Victor Ling and Lin Liu at the BC Cancer Research
Centre and Dr. John C. English at Vancouver General Hospital. I would like extend my
appreciation to the financial support from The Cancer Research Society and The Prostate Cancer
Foundation of British Columbia.
Last but not least, I would especially like to profoundly thank my family: my wife Xin
Dong, whose constant support and devotion allowed me to get the project finished, and my
parents who dedicated most of their lives to my education.
xiv
To my parents
and my wife, Xin Dong
&
In memory of my grandma
xv
CO-AUTHORSHIP STATEMENT
The experiments described within this thesis were conceived, designed, conducted and
analyzed by me, Dong Lin, and Dr. Yuzhuo Wang. All manuscripts were written by myself and
Dr. Yuzhuo Wang. A number of additional people contributed to the work as outlined below:
Lin Liu was responsible for SAGE library construction under the guidance of Dr. Victor
Ling. Dr. Akira Watahiki aided in bioinformatic analysis. Drs. Martin E. Gleave, Alan I. So and
John C. English provided the clinical samples and guided the data analysis associated with
clinical information. Technical assistance was contributed by Yuwei Wang (animal
experiments), Dr. Jeremy A. Squire, Jane Bayani (spectral karyotyping and fluorescence in situ
hybridization), Drs. Peter W. Gout and Marianne D. Sadar (data interpretation and presentation),
Dr. Fang Zhang (RNA preparation and cloning) and Dr. Ladan Fazli (tissue microarray
construction and evaluation).
xvi
Chapter 1
INTRODUCTION
1.1.
PROSTATE GLAND AND PROSTATE CANCER
1.1.1. Prostate gland
The prostate is an accessory reproductive gland. Its function is to produce and secrete a
slightly alkaline (pH 7.3) fluid that usually constitutes 25-30% of seminal fluid. The alkalinity
helps neutralize the acidity of the vaginal tract, prolonging the lifespan of sperm (Cunha et al.,
1987). The prostate is a retroperitoneal organ encircling the neck of the bladder and urethra and
is devoid of a distinct capsule. Prostatic parenchyma can be divided into four anatomically and
biologically distinct zones or regions: the peripheral, central, and transitional zones and the
region of the anterior fibromuscular stroma (McNeal, 1988). Histologically, the prostate is a
compound tubuloalveolar organ which shows small to fairly large glandular structures lined by
epithelium. The structures are characteristically lined by two layers of cells: a basal layer of low
cuboidal epithelium covered by a layer of columnar secretory cells, with rare neuroendocrine
cells scattered throughout the basal layer (Fig.1.1). The prostate glands have a distinct basement
membrane and are separated by abundant fibromuscular stroma, which itself is composed of
multiple cell types (e.g., fibroblasts, smooth muscle cells) (McNeal, 1998; Ware, 1994). Prostatic
growth is clearly controlled by testicular androgens since castration leads to atrophy of the
prostate. Common diseases of the prostate include prostatitis, benign prostatic hyperplasia (BPH)
1
Figure1.1. Benign adult prostate glands. (A). In this benign gland, the tall secretory epithelial cells (arrow)
have uniform round or oval nuclei. Prominent nucleoli are not seen. (B). Anti-P63 antibody shows that
basal cells are present in a continuous pattern (arrow head).
2
and cancer (Kumar, 2007). BPH occurs so often in advanced age that it can almost be regarded
as part of the aging process. Prostatic carcinoma is also a common phenomenon and merits
careful consideration.
1.1.2. Prostate cancer
Prostate cancer is the most commonly diagnosed non-skin cancer among Canadian men,
and is a major cause of cancer-related deaths. The Canadian Cancer Society estimated that, in
2008, 24,700 new cases of prostate cancer would be diagnosed, constituting about 26% of all
new male cancer cases, and that 4,300 men would die of the disease. Currently, 1 in 7 men will
develop prostate cancer during their lifetime and 1 in 27 will die of it, a ratio of 1 death per 4
diagnosed cases, which is very similar to the ratio observed for breast cancer in women.
Prostate cancers are mostly adenocarcinomas developed primarily within the luminal
epithelium of the peripheral zone. Prostate cancer is a heterogeneous disease that progresses
from prostatic intraepithelial neoplasia (PIN), commonly considered as a precursor of prostatic
adenocarcinoma, to invasive adenocarcinoma and ultimately to metastatic carcinoma.
Heterogeneity of this disease at histological and molecular levels is commonly observed,
especially in multifocal prostate cancers (in ~80% of clinical cases) arising independently within
the same prostate (Barry et al., 2007; Cheng et al., 1998; Mehra et al., 2007; Ruijter et al., 1999).
Little is known about the causes of prostatic cancer. Several risk factors, such as age,
race, family history, hormone levels, viruses and diet are suspected to play significant roles in its
development (Damber and Aus, 2008; Nelson et al., 2003). At present, little evidence exists for a
clearly defined series of genetic events leading to prostate cancer development, although
molecular studies have identified several candidate genes involved in sporadic prostate cancer
3
pathogenesis and progression, such as GSTP1, PTEN, NKX3.1, AR, SHH, EZH2 and
TMRPSS2/ETS (Deutsch et al., 2004; Morris et al., 2007). In addition, inherited prostate cancer
susceptibility genes have been identified, including RNASEL, MSR1 and BRCA2 (Deutsch et al.,
2004; Dong, 2006; Edwards and Eeles, 2004).
Digital rectal examination and prostate-specific antigen (PSA) screening are commonly
used for prostate cancer detection. At present, final diagnosis is based on examination of
histopathological or cytological biopsy specimens. An important part of evaluating prostate
cancer is determining the stage and grade, which helps define prognosis and is useful when
selecting therapies. The most common stage system is the four-stage TNM system (abbreviated
from Tumor/Nodes/Metastases). Its components include tumor size, number of involved lymph
nodes and any other metastases. Gleason scoring is the most commonly used system for grading
prostatic adenocarcinoma based on microscopic appearance of the cancers (Gleason and
Mellinger, 2002). Malignancies with higher Gleason scores are more aggressive and have poor
prognosis.
Depending on factors such as tumor characteristics and patients‟ life expectancy,
treatments of localized prostate cancer include active monitoring, radical prostatectomy and
radiotherapy. Currently the treatments of choice for metastatic or advanced prostate cancer
include androgen ablation and chemotherapy, which can lead to substantial remissions. However,
metastatic prostate cancer inevitably progresses to a castration-resistant stage and is essentially
incurable (Coffey, 1993; Greenlee et al., 2000).
4
1.2.
CANCER INVASION AND METASTASIS
1.2.1. Overview
Metastasis is defined as the spread of tumor cells from one tissue to another, not directly
connected with it, where they form secondary tumors. Most cancer related deaths are from
metastasis (Fidler, 2002a; Fidler, 2002b). There are three major routes for metastasis: lymphatic
vessels, blood vessels and serosal membranes. Lymphatic and hematogenous dissemination are
commonly observed in epithelial malignancies, including prostate cancers (Wong and Hynes,
2006). The metastatic cascade is an ordered sequence of events required for metastasis to occur
(Chambers et al., 2002; Fidler, 2003). To initiate a metastatic colony, a tumor cell must (a)
detach from the primary mass; (b) invade local tissue stroma; (c) intravasate; (d) survive in the
circulation; (e) extravasate at other organs; (f) penetrate parenchyma; and (g) adapt to the new
microenvironment and form a new tumor (Bacac and Stamenkovic, 2008; Gupta and Massague,
2006) (Fig.1.2).
1.2.2. Cancer invasion
Local tissue invasion is one of the fundamental early steps in metastasis. In this step, a
cancer cell must have the ability to invade through the basement membrane of a tissue layer and
the interstitial stroma (Bogenrieder and Herlyn, 2003; Gupta and Massague, 2006). To develop
invasive potential, cancer cells often: (1) require a decrease in their cell-cell attachments; and (2)
acquire an ability to break down the extracellular matrix (ECM) (Liotta, 1986).
Lowering cell-cell affinity is largely due to loss of intercellular adhesion proteins, e.g., Ecadherin, which are crucial for maintenance of epithelial tissue architecture and polarity (Foty
and Steinberg, 2004). In epithelial cancer, E-cadherin can be replaced by other cadherins, most
5
Figure 1.2. Cancer metastasis cascade. See text section 1.2.2.
6
commonly N-cadherin, a cadherin family member predominantly expressed in mesenchymal
tissue. This process is a crucial event in “epithelial to mesenchymal transition” (EMT), defined
as the conversion of epithelial cell to motile, fibroblast-like cells that express mesenchymal
rather than epithelial cell markers. EMT is observed when epithelial cells progress through stages
of carcinogenesis in vitro and is thought to reflect invasive and metastatic properties of
transformed epithelial cells (Yang and Weinberg, 2008). However, it is still a controversial
concept, as EMT is difficult to prove in vivo.
Degradation of the ECM is initiated by proteases secreted by different types of cells,
including cancer cells, cancer-associated fibroblasts and infiltrating immune cells. It has been
reported that the invasive and metastatic potential of cancer is associated with activity of
plasminogen activators, Cathepsin B and matrix metalloproteinases (MMPs) (Baricos et al.,
2003; Birkedal-Hansen et al., 1993; Lah and Kos, 1998; Nemeth et al., 2002). In addition to the
degradation of the ECM, protease-induced cleavage of matrix proteins also serves to generate
binding sites for integrins, cell-substrate adhesion molecules which are required to anchor cells
during tissue invasion. Furthermore, cleavage and activation of extracellular growth factors and
chemokines enhance the motion of cancer cells (Koblinski et al., 2000).
MMPs are the most widely studied proteases involved in tissue invasion. They comprise
a family of highly homologous zinc-dependent endopeptidases. MMPs can degrade a variety of
ECM components, such as collagen and gelatin, once they are activated (Nemeth et al., 2002).
MMPs have been implicated in normal processes such as wound healing and inflammation. In
addition, their activity has been correlated with deregulated ECM degradation and metastasis in a
variety of cancers including prostate cancer (Bellezza et al., 2005; Dong et al., 2005).
7
1.2.3. Adhesive structures associated with tissue invasion and cell migration
Focal adhesion: Focal adhesions are large multiprotein complexes generated by cells
which provide anchorage of stationary and migratory cells to underlying substrate. They are
characterized by clusters of integrins through which a mechanical link between the actin
cytoskeleton and the ECM are formed (Geiger et al., 2001). Anchorage of the cytoskeleton to the
cell membrane involves a variety of structural molecules and signaling components (CavalcantiAdam et al., 2007). Although focal adhesions are thought to be involved in cell adhesion and
migration-dependent invasive processes, they do not appear to support ECM degradation in
tissue invasion (Gimona and Buccione, 2006).
Podosomes: Podosomes are highly dynamic, actin-rich adhesion structures, which are
found in macrophages, endothelial cells, certain transformed fibroblasts, osteoclasts and invasive
cancer cells (Buccione et al., 2004; Gimona and Buccione, 2006). Consistent with their function
in adhesion of cells to solid substrates, podosomes consist of a densely packed actin core
surrounded by a protein complex commonly observed in focal adhesion structures (Buccione et
al., 2004; Chellaiah et al., 2000; Linder and Aepfelbacher, 2003). In addition, podosomes govern
tissue invasion and matrix remodeling by controlling focal activation of MMPs and degradation
of the ECM. The level of ECM degradation is limited and may only involve part of the matrix in
the immediate vicinity of the podosomes since these structures have a short half-life (2-12 min)
(Linder, 2007). The formation, maintenance and turnover of podosomes are regulated by nonreceptor tyrosine kinases (e.g. Src and FAK) and Rho GTPases with involvement of
microtubules and the intermediate filament cytoskeleton (Chellaiah, 2005; Moreau et al., 2006;
Ory et al., 2002; Tanaka et al., 1995).
8
Invadopodia: Invadopodia are actin-based protrusions of cancer cells and transformed
cells which mediate proteolysis of ECM constituents (Chen, 1989; Kelly et al., 1998).
Invadopodia are highly enriched with actin filaments (F-actin) and components required for actin
assembly, including the Arp2/3 actin nucleation complex, N-WASP and cortactin, as well as
signaling proteins (Buccione et al., 2004; Clark et al., 2007; Linder, 2007; Lorenz et al., 2004;
Mizutani et al., 2002). The proteolytic potential of invadopodia is mainly due to MMPs, such as
MT1-MMP, MMP-2 and MMP-9 (Artym et al., 2006; Chen and Wang, 1999; Deryugina et al.,
2001; Monsky et al., 1994). The ASAP1 protein identified in this study has been found to form a
complex with cortactin and play a role in invadopodia formation (Onodera et al., 2005).
Compared with podosomes, invadopodia are more commonly observed in highly invasive cancer
cells, including PC-3 prostate cancer cells (Desai et al., 2008). Invadopodia are less dynamic,
have a larger structure and importantly are more aggressive in ECM degradation than podosomes
(Buccione et al., 2009).
1.2.4. Genes associated with prostate cancer invasion and metastasis
At present, metastasis is poorly understood at the molecular and mechanistic level in
most cancers, including prostate cancer. It has been suggested that multiple genetic and/or
epigenetic changes are required to enable establishment of a cancer at an extra-prostatic site
(Bernards and Weinberg, 2002). Some genes have been linked to regulation of the various steps
of metastatic development (Table 1.1), including the following.
9
Table 1.1. Metastasis-related genes in prostate cancer.
Gene
Symbol
Locus
Function
References
Bone
morphogenetic
protein 6
Caveolin 1
TGFβ superfamily; stimulate osteoblastic
differentiation of pluripotent mesenchymal
cells
Membrane protein; molecular transport
and signal transduction
8p22
E-cadherin;
Cadherin 1
Cathepsin B
CTSD
11p15.5
Cathepsin D
Adherens junction protein; promotes cellcell adhesion; prevent cell detachment
Lysosomal cysteine proteinases; degrade
collagen IV, fibronectin and laminin
Lysosomal aspartyl protease
(Autzen et al., 1998; Bentley et
al., 1992; Ebisawa et al., 1999;
Masuda et al., 2003)
(Li et al., 2001; Tahir et al., 2001;
Williams et al., 2005; Yang et al.,
1998)
(Bussemakers et al., 2000; Day et
al., 1999; Tran et al., 1999)
(Fernandez et al., 2001; Sinha et
al., 2001)
(Miyake et al., 2003)
CXCL12
10q11.1
CXCR4
2q21
EDN1
6p24.1
Chemokine (C-X-C
motif) ligand 12
Chemokine (C-X-C
motif) receptor 4
Endothelin 1
EZH2
7q35-q36
Enhancer of zeste
homolog 2
F2R
5q13
HPN
19q11q13.2
Protease-activated
receptor 1 (PAR1)
Hepsin
ITGA6;
ITGB1
2q31.1;
10p11.2
α6 β1-integrin
ITGAV;
ITGB3
2q31-q32;
17q21.32
αv β3-integrin
Bind to components of extracellular
matrix; promote migration and invasion
(Murant et al., 1997; Zheng et al.,
1999)
KAI1/CD82
2q31.1;
11p11.2
Type III transmembrane protein; inhibit
cancer cell invasion and migration
MAP2K4
17p11.2
Metastasis suppressor gene; activate JNK
and P38
(Dong et al., 1995; Dong et al.,
1996; Marreiros et al., 2005;
Sridhar and Miranti, 2006)
(Kim et al., 2001; Vander Griend
et al., 2005)
MAP2K7
19p13.3p13.2
Metastasis suppressor gene; activate JNK
(Vander Griend et al., 2005)
MMP9
PLAU
20q11.2q13.1
10q24
Prostate cancer
anti-metastasis
gene
Mitogen-activated
protein kinasekinase 4; MKK4
Mitogen-activated
protein kinase
kinase 7; MKK7
Matrix
metallopeptidase 9
Urokinase-type
plasminogen
activator; uPA
Degrade extracellular matrix (type IV and
V collagens)
Serine proteinases; conver plasminogen
to plasimin; promote degradation of
extracellular matrix components
S100A4
1q21
S100 calcium
binding protein A4
Calcium-binding protein; accelerate
tumorigenesis and invasion of human
prostate cancer through the transcriptional
regulation of MMP9.
(Lichtinghagen et al., 2002; Wood
et al., 1997)
(Festuccia et al., 1998; Hoosein
et al., 1991; Miyake et al., 1999a;
Miyake et al., 1999b; Van
Veldhuizen et al., 1996; Xing and
Rabbani, 1999) (McCabe et al.,
2000)
(Gupta et al., 2003; Saleem et al.,
2006)
BMP6
6p24-p23
CAV1
7q31.1
CDH1
16q22.1
CTSB
Name
Chemokine; manipulate chemotactic
response of metastatic cancer cells
Receptor of CXCL12
Mitogenic factor for osteoblasts, promote
the growth of osteoblasts and contribute
to the osteoblastic reaction
Polycomb repressive complex 2/3; gene
transcription repressor; promote
proliferation and invasion
Regulate thrombotic response; increase
cell adhesion to platelets
Type II transmembrane serine protease;
weaken epithelia-stromal adhesion;
activate pro-urokinase (pro-uPA), Laminin332 and pro-hepatocyte growth factor
(pro-HGF).
Bind to components of extracellular
matrix; promote migration and invasion;
10
(Arya et al., 2004; Sun et al.,
2003)
(Arya et al., 2004; Sun et al.,
2003)
(Nelson and Carducci, 2000)
(Bachmann et al., 2006; Bryant et
al., 2007; Saramaki et al., 2006;
Varambally et al., 2002)
(Chay et al., 2002; Trikha and
Nakada, 2002)
(Chen et al., 2003; Klezovitch et
al., 2004; Stamey et al., 2001;
Tripathi et al., 2008) (Landers et
al., 2005; Stephan et al., 2004)
(Edlund et al., 2001; Schmelz et
al., 2002; Vafa et al., 1998)
Detachment from the primary tumor mass
Detachment of cancer cells from the primary tumor mass is associated with the functional
down-regulation of intercellular adhesion, which is promoted by a lower expression of cell
adhesion molecules (CAMs) in metastatic cells. Amongst the most studied of the CAMs are the
cadherins. Cadherins are transmembrane molecules with an extracellular domain for calciumdependent homotypic binding, while the intracellular carboxyl terminal is anchored to the
cytoskeleton by the complex of α-, β- and γ-catenin molecules (Ozawa et al., 1989). Loss or
down-regulation of E-cadherin is a common feature of high-grade, late-stage prostate cancer
(Murant et al., 2000; Umbas et al., 1992) and of prostate cancer cell lines, including PC-3,
LNCaP and C4-2 (Bussemakers et al., 2000; Day et al., 1999; Tran et al., 1999). Downregulation
of E-cadherin mRNA and protein was observed in bone or lymph node metastases of prostate
cancers. (Bryden et al., 2002; Junior et al., 2008; Pontes-Junior et al., 2009; Pontes Junior et al.,
2008)
Invasion of local stroma
Local stromal interactions: Integrins, another important group of CAMs, are a family of
transmembrane glycoprotein heterodimers with α and β subunits which can form a large number
of heterodimers. Integrins mediate interactions between tumor cells and the ECM during cell
invasion and migration by binding to components of the basement membrane and interstitial
stroma such as fibronectin, laminin, thrombospondin and collagens. LNCaP and C4-2 prostate
cancer cell lines primarily use integrins for binding matrix components (Edlund et al., 2001).
Up-regulation of α6β1 integrin pair has been associated with increased metastatic behavior and
enhanced cell migration of prostate cancer cells (Schmelz et al., 2002; Vafa et al., 1998). In
patients‟ tumor tissues, increased α6β1-integrin expression has been associated with invasion of
11
seminal vesicles by prostate cancer cells (Schmelz et al., 2002) and there is a trend toward
increased expression of the αvβ3 integrin pair in metastatic prostate carcinomas (Murant et al.,
1997; Zheng et al., 1999).
Degradation of local stroma: ECM is degraded by several groups of proteinases,
including MMPs (e.g., MMP-9), serine proteinases (e.g., hepsin, urokinase-type plasminogen
activator (uPA)), cysteine proteinases (e.g., Cathepsin B) and aspartyl proteinases (e.g.,
Cathepsin D). Studies demonstrated higher MMP-9 protein levels in cancerous prostate tissue
compared to benign prostate tissue and an association between changes in expression of specific
MMPs and aggressiveness and progression of human prostate cancers (Lichtinghagen et al.,
2002; Wood et al., 1997). DNA microarray studies of gene expression in human prostate cancer
have revealed the elevated expression of hepsin, a type II transmembrance serine protease (Chen
et al., 2003; Dhanasekaran et al., 2001; Ernst et al., 2002; Stamey et al., 2001; Stephan et al.,
2004). Hepsin mRNA was found to be up-regulated in more than 90% of human prostate cancer
cases (Landers et al., 2005; Stephan et al., 2004), although the mechanism of regulation of its
activity remains unknown. By binding to specific membrane-bounded or soluble cell surface
uPA receptors (uPAR), uPA catalyses the conversion of inactive plasminogen to plasmin, which
can degrade many ECM components. uPA expression has been associated with the malignant
phenotype of prostate cancer cell lines (Festuccia et al., 1998; Hoosein et al., 1991). Elevated
serum levels of uPA and/or uPAR have been correlated with serum PSA levels, development of
metastasis, and overall survival rate among prostate cancer patients (McCabe et al., 2000;
Miyake et al., 1999a; Miyake et al., 1999b; Van Veldhuizen et al., 1996). Cysteine proteinases
include several cathepsins including cathepsin B, K and S. Aspartyl proteinases include
cathepsins D and E. Both Cathepsin B and cathepsin D have been associated with prostate cancer
12
invasion and metastasis in clinical samples and in cancer cell models (Fernandez et al., 2001;
Miyake et al., 2003; Sinha et al., 2001).
Tumor microenvironment: Stromal cells can produce and secrete many soluble factors,
such as growth factors and cytokines, and mediate the intercellular communication between
stroma and epithelium that controls cancer progression. Vascular endothelial growth factor
(VEGF) secreted by cancer cells and surrounding stromal cells binds to its receptors on
endothelial cells, thereby promotes cancer angiogenesis and contributes to cancer cell growth
and intravastion (Nguyen and Massague, 2007). The overexpression of insulin-like growth
factor-I (IGF-I) by stromal cells has been shown to drive malignant transformation of prostate
epithelium in mouse, while antisense RNA to IGF-I receptor inhibits prostate cancer
proliferation and invasion (Chung et al., 2005). Members of the transformation growth factor
(TGF)-β family secreted by cancer cells and fibroblasts promote cancer cell invasion by inducing
EMT via activation of Smad signaling pathways (Keller et al., 2001). Moreover, TGF-β can
induce the trans-differentiation of cells of a stromal fibroblastic phenotype to a myofibroblastic
phenotype, i.e. reactive stroma. The reactive stroma, in turn, can promote cancer cell motility and
metastasis (Bhowmick and Moses, 2005). Many experiments have shown that tumor-infiltrating
immune cells, such as tumor-associated macrophages, dendritic cells and lymphocytes, can
promote carcinogenesis, local tissue invasion and metastasis (Bunt et al., 2007; Wyckoff et al.,
2007; Yu and Fu, 2006). Tumor-infiltrating M2 macrophages and dendritic cells produce
immunosuppressive cytokines such as IL-5, IL-10 and TGF-β, which inhibit the antigen-specific
immune response and the formation of an adaptive anti-tumor immunity (Dhodapkar et al.,
2001). Neutrophils and mast cells can also promote cancer progression by secreting tumorpromoting growth factors, cytokines and proteases. It has been reported that neutrophils play an
13
important role in ras-driven tumor progression (Ji et al., 2006). Granulocytes were also identified
as a source of MMP-9 expression in skin cancer models (Coussens et al., 2000).
Survival in the circulation
To escape intense host immunological assault, malignant cells circulating in blood or
lymphatic vessels often down-regulate expression of class I human Leucocyte Antigen (HLA)
that interferes with cytotoxic T-lymphocyte (CTL)-mediated killing. Downregulation of Major
Histocompatibility (MHC) class I molecule expression and alteration of intracellular processing
of presented antigens, leading to interference of tumor recognition by antigen-specific cytotoxic
T-lymphocytes, have been observed in some prostate cancers (Sanda et al., 1995). The ability of
circulating malignant cells to withstand mechanical stress, such as blood turbulence, is another
important aspect allowing survival in the circulation. Activation of protease-activated receptor 1
(PAR1, thrombin receptor, F2R) expressed by prostate cancer cells, including cell lines, has been
shown to increase cell adhesion to platelets, a coupling which protects cancer cells from the
significant shear stresses in the circulation (Chay et al., 2002; Trikha and Nakada, 2002).
Extravasation
PAR1 and integrin αvβ3 are highly expressed in prostate cancer cells. These proteins
may contribute to bony metastases by facilitating attachment of cancer cells to blood vessel walls
and the process of extravasation (Chay et al., 2002; Cooper et al., 2002). KAI1/CD82, the first
prostate cancer metastasis suppressor gene identified (Dong et al., 1995), is thought to be
involved in inhibiting cancer cell migration and invasion. A loss of KAI1 expression has been
correlated with poor prognosis in human prostate cancer (Dong et al., 1996; Ichikawa et al.,
1991a). Down-regulation of KAI1 mRNA levels was reported to be correlated with an absence
14
of wild-type p53, and/or a loss of expression of other transcription factors, i.e. junB and AP2, in
a number of prostate cancer cell lines (Marreiros et al., 2005). The loss of KAI1 may promote
metastasis by removing a negative regulator of c-Met and Src signaling (SC Sridhar and CK
Miranti, oncogene, 2006). KAI1 may also arrest the cancer cells at a later stage in the metastatic
cascade by binding to the Duffy antigen receptor for chemokines (DARC), a seven
transmembrane protein expressed on endothelial cells (Bandyopadhyay et al., 2006).
Homing in on distal organs and formation of new colonies
Expression of CXCL12, a chemokine, and CXCR4, receptor of CXCL12, was
significantly elevated in metastatic prostate cancer compared to normal or benign prostate tissue
(Sun et al., 2003). It was found that human prostate cancer cell lines expressed functional
chemokine CXCR4 receptors and that the CXCL12 ligand enhanced their migratory capabilities
(Arya et al., 2004). Loss of functions of two metastasis-suppressor genes, mitogen-activated
protein kinase-kinase 4 (MKK4) and 7 (MKK7), may also be linked to prostate cancer
metastasis. The MKK4 protein is highly expressed in benign prostate tissue whereas reduced in
neoplastic prostate tissue and there was an inverse relationship between the reduction of MKK4
expression and metastatic potential of prostate cancer cells (Kim et al., 2001). Findings that
overexpression of MKK4 or MKK7 in rat prostate cancer cell line AT6.1 could suppress lung
metastasis in vivo and have no effect on the growth of primary tumor suggest that the kinase
activities of MKK4 and MKK7 are essential for disseminated cells to colonize the lung
(secondary site). It was also suggested that the JNK pathway, rather than the p38 pathway
mediates the metastasis suppression by MKK4 (Vander Griend et al., 2005).
15
Osteoblastic metastases in bone are commonly observed in advanced prostate cancer.
Interaction between cancer cells and bone stromal cells, especially osteoblasts is thought play an
important role in colonization of prostate cancer in bone. Elevated expression of bone
morphogenetic proteins (BMPs) in prostate cancer cells has been implicated in bone metastasis.
In clinical samples, BMP6 was detected in 50% of metastatic prostate cancer samples, but not
non-metastatic or benign samples (Autzen et al., 1998). Secretion of BMP6 was thought to
contribute to osteoblastic lesions by stimulating osteoblastic differentiation of pluripotent
mesenchymal cells (Ebisawa et al., 1999). Endothelin-1 (ET-1), a mitogenic factor for
osteoblasts, could be secreted by prostate cancer cells, promote the growth of osteoblasts and
contribute to the osteoblastic reaction when cancer cells colonize in bone (Nelson and Carducci,
2000). It has been shown that co-culturing prostate cancer cells with osteoblasts led to increased
proliferation of the cancer cells relative to the culture without osteoblasts (Gleave et al., 1991).
Co-culture of prostate cancer cells with osteoblasts showed decreased expression of IGF-binding
protein 3 (IGFBP3), a putative growth suppressor, and increased expression of MDM2, a protein
regulates p53 (Fizazi et al., 2003). These observations indicate that bone-derived factors can
promote the progression of prostate cancer metastasis, although these factors have yet to be
identified.
Although many genes have been linked to prostate cancer metastasis, the majority of the
key elements of metastasis are still not clear. This is largely due to lack of clinically relevant
models which develop spontaneous metastasis.
16
1.3.
PROSTATE CANCER MODELS
Preclinical prostate cancer models currently used mainly include those derived from rat,
canine, mouse and human sources.
1.3.1 Rat model
Rats are one of the few species that develop prostate cancer spontaneously (Pollard,
1973; Shain et al., 1975). One of the best known rat models of prostate cancer was the Dunning
rat model; it exists in various forms, including well-differentiated, non-metastatic and multiple
highly metastatic variants (Cooke et al., 1988; Isaacs, 1982). Cell fusion of its variants resulted
in a non-metastatic heterokaryon (Ichikawa et al., 1991b). The system was therefore suitable for
identification of metastasis suppressor genes and its use led to the discovery of metastasis-related
foci at 8p, 10q, 11p and 17p and a number of metastasis suppressor genes, including KAI (11p12)
and MKK4 (17p11.2). Prostate cancers have been induced in Lobund-Wistar and Noble rats by
administration of sex hormone, illustrating the role of androgen in prostate cancer progression
and providing a valuable tool for studies of chemoprevention and dietary modulation (Noble,
1977; Pollard et al., 1982). Some limitations of rat models include long latency periods and low
tumor incidence.
1.3.2 Canine model
Prostate cancer also occurs spontaneously in canines (Waters et al., 1998). Canine
prostate cancer mimics several characteristics of its human counterpart with regard to
heterogeneity, prevalence in elderly populations and association with skeletal metastasis
(Bostwick et al., 2000). Dogs develop osteoblastic bone lesions that mimic the human disease,
thus making this model relevant for preclinical testing of bone-targeted therapies (Bostwick et
17
al., 2000). However, the canine prostate is lack of zonal differences observed in human but
rather is histologically homogenous consisting predominantly of epithelium with minimal
stromal elements (McNeal, 1984). The long latency associated with the emergence of prostate
cancer in canine models also presents a major obstacle for their use in research. Furthermore,
experiments with the models are rather costly (Navone et al., 1998).
1.3.3 Mouse model
Mouse prostate reconstitution model
Timothy Thompson et al. reported a model for prostate disease research that is now
referred to as the mouse prostate reconstitution (MPR) model (Thompson et al., 1989). This
model is based on an investigational „„organ reconstitution‟‟ model of prostate gland
development engineered by Cunha and Chung, which involved isolation of pure populations of
fetal mouse urogenital sinus (UGS) epithelial and mesenchymal cells, followed by their
recombination and reimplantation under the renal capsule of a host mouse (Cunha and Chung,
1981). In this MPR model, isolated mouse cells can be genetically manipulated (e.g., by
transduction with recombinant retroviruses prior to reimplantation) to investigate how specific
genetic changes can affect the development of the prostate structure. Use of p53-knockout mice
as recipients of myc and ras oncogenes resulted in development of prostate cancer micrometastases in bone and other tissues (Thompson et al., 1995). CAV1 (Caveolin-1), a metastasisrelated gene, was identified by comparing mRNA expression patterns in cell lines derived from
primary versus metastatic mouse prostate cancers (Thompson, 1998).
18
Transgenic mouse models or genetically engineered mouse (GEM) models
Transgenic animals carry an exogenous vector construct (transgene) inserted into the
genome of all their cells, allowing germ line transmission to offspring (Sigmund, 1993). GEM
models can be divided into two categories, those generated by overexpression of an oncogene
with a prostate-specific promoter and those with targeted deletion of specific genes.
The transgenic mouse model of prostate (TRAMP) was one of the first effective models
for studying malignant progression of prostate cancer. It is based on use of the minimal rat
probasin promoter to drive prostate epithelium-specific expression of SV40 early genes (T and t
antigens) in the dorsolateral lobe of the mice (the murine equivalent of the peripheral zone)
(Greenberg et al., 1995). By 12 weeks of age, TRAMP mice typically develop PIN lesions and
invasive cancer. By 24 to 30 weeks of age, 100% of the mice develop poorly differentiated
prostate cancer associated with metastasis predominantly to lymph nodes and lungs (KaplanLefko et al., 2003). However, there is currently no evidence that the SV40 early genes are
involved in the development of human prostate cancer.
Several murine models have been generated by overexpression or disruption of genes that
are deregulated in human prostate cancer. Of these models, phosphatase and tensin homologue
(PTEN) knockout models are the best characterized (Carver and Pandolfi, 2006; Liao et al.,
2007; Shen and Abate-Shen, 2007). A loss of one or both PTEN alleles, observed in
approximately 70% of human primary prostate cancers, is associated with metastatic disease
(Gray et al., 1998). In mice, loss of one PTEN allele is associated with the development after a
long latency period of high-grade PIN with no invasive adenocarcinoma (Di Cristofano et al.,
1998; Podsypanina et al., 1999). Prostate-specific loss of PTEN expression using the Cre-loxP1
19
recombination strategy leads to invasive prostate cancer within 12 weeks, with subsequent
metastases to lymph nodes and lung in some animals (Wang et al., 2003).
Compound mutational mouse models incorporate at least two mutations of prostate
cancer-related genes. NKX3.1 encodes a homeodomain transcription factor that is frequently
deleted in human PIN and prostate cancer. Loss of Nkx3.1 function only leads to PIN in mice
(Mogal et al., 2007). Nkx3.1+/- and Pten+/- compound mutant mice show development of invasive
prostate cancer and lymph node metastasis (Abate-Shen et al., 2003). Mice nullizygous for
PTEN and p53 in the prostate also develop locally invasive prostate cancer (Chen et al., 2005).
The advantages of GEMs are that (1) various stages of tumor progression can be studied
over time; (2) specific genetic abnormalities can be induced in a tissue-specific manner; (3)
tumors developed in mice with an intact immune system (immunocompetent mice) which can
mirror the tumor-stroma interaction occurring in human tumors. GEMs have expanded our
understanding of the molecular mechanisms for the development of prostate cancer. However,
the GEMs can not reliably mimic the complexity of the human tumor. There are also significant
biological and histopathological differences between human and mouse prostates (Roy-Burman
et al., 2004), which warrant caution in the extrapolation of results obtained with these models to
the human situation. Thus, despite the advantages of GEMs, their use in the preclinical
anticancer drug discovery is still very limited.
1.3.4 Xenograft model
Nude (athymic) and severe combined immuno-deficient (SCID) mice are commonly used
as hosts for inoculation of established cancer cell lines or direct grafting of cancer tissues. The
classic human prostate cancer cell lines, PC-3, LNCaP, and DU145, are the three most widely
20
used cell lines. PC-3 cells, originally derived from a bone metastasis, show much stronger
invasive and metastatic ability compared to LNCaP and DU145 cells and thus are favored for
metastasis studies (Hoosein et al., 1991). Metastatic sublines of the LNCaP cell line, originally
derived from a lymph node metastasis, are also used (Thalmann et al., 2000). The ability of the
sublines to colonize metastatic sites was found to be modulated by the presence of human stroma
(Gleave et al., 1991). These established cell lines provide valuable sources for gene isolation and
functional analysis. However, their relevance to human disease is not optimal, as long-term
culturing likely decreases their biological relevance. A NCI retrospective study showed
anticancer drugs activity in tumor cell lines xenograft did not correlate with their activity against
the same human tumor histology in phase II clinical trials (Johnson et al., 2001) In contrast,
xenografts derived from primary human tumors/biopsies showed similarities in clinical outcome,
treatment sensitivity and resistance when compared to their clinical human tumor counterparts
(Scholz et al., 1990).
Xenograft models can be established by injection of primary cancer cell suspensions
mixed with Matrigel into mice. The CWR series and LAPC series of xenografts were developed
using this strategy (Klein et al., 1997; Pretlow et al., 1991). To identify metastasis-associated
genes, a variety of sublines of the CWR22 xenograft have been employed (Chen et al., 1998;
Mousses et al., 2002). However, the effects of Matrigel components on the original patient
material are likely to be considerable, especially with regard to differentiation, and thus can alter
the original characteristics of the cancer specimens (Fong et al., 1991; Freeman et al., 1994).
Furthermore, similar to cell line-based models, these models lack a proper stroma component
and structural micro-environment essential for stromal-epithelial interactions which have been
21
shown to be important in the regulation of prostate cancer progression (Chung et al., 2005;
Chung et al., 2006).
Models based on grafting of human tissues which retain proper stromal-epithelial
interactions should present a more accurate picture of prostate cancer biology than isolated cell
suspension and cultured cell populations. The Rotterdam PC-Models were developed by simply
cutting primary tissues into small fragments and transplanting them subcutaneously in both
shoulders of athymic nude mice (van Weerden et al., 1996). Xenografts of human primary
cancer feature the molecular heterogeneity and histological complexity that exist in the clinical
human cancer. Early generations of these xenografts have the added advantage of containing
stroma from the original human tumor and can mimic the cell-to-cell interactions of the human
tumor microenvironment, albeit exception of interactions involving certain immune cells.
Orthotopic xenografts using human primary tumors are thought to be more clinically relevant
compared with cell lines, as there is a stronger predictive response value for anticancer drug test.
One disadvantage associated with xenografts obtained directly from patient primary tumors is the
low take rates. The engraftment rate in prostate cancer is particularly low (~5%) and in
subsequent xenograft tumors, no significant metastases are observed (Rembrink et al., 1997).
Recently, our laboratory has developed a number of clinically relevant prostate cancer
models based on subrenal capsule grafting of histologically intact human prostate cancer tissue
into NOD-SCID mice (Wang et al., 2005a). Comparison of three graft sites (subcutaneous,
subrenal capsule and orthotopic) demonstrated that the subrenal capsule graft site has a superior
engraftment rate. This site not only allows survival of high grade prostate cancers, but also of
low grade cancers and even benign prostate tissue, probably a result of high tissue perfusion of
the kidney providing superior nutrient supply. Human cancer tissue is highly heterogeneous,
22
containing various cancer subpopulations. Subrenal capsule grafting makes it possible to retain
such heterogeneity in the xenografts - a condition crucial for a clinically relevant model.
Therefore, models based on early generations of subrenal capsule xenografts hold promise for
application in personalized chemotherapy. This model system has been shown to be suitable for
quick assessment of the chemosensitivity of patients' cancers and selection of the most effective
regimens in NSCLC patients (Dong et al., 2010). On the other hand, relatively homogeneous
tumor tissue lines developed from same patient‟s primary cancer tissue by serial transplantation,
demonstrated difference in tissue invasiveness and spontaneous metastatic ability and provided
valuable tools for studying prostate cancer metastasis.
1.4.
SERIAL ANALYSIS OF GENE EXPRESSION (SAGE)
Metastasis is thought to stem from accumulated genetic/epigenetic alterations leading to
changes at the transcriptional and post-transcriptional level. Recent advances in comprehensive
gene expression profiling techniques have provided important information for identification of
potential diagnostic and prognostic cancer markers. Serial Analysis of Gene Expression (SAGE)
is a gene expression profiling method that allows for global, unbiased and quantitative
characterization of transcriptomes (Velculescu et al., 1995) and has been used in studies of a
variety of cancers including prostate cancer (Minagawa et al., 2008; Peters et al., 2005;
Untergasser et al., 2002; Waghray et al., 2001; Weeraratna et al., 2004). This technique is based
on the following concepts: (1) a short nucleotide sequence called a SAGE „tag‟, derived from a
defined position of mRNA, is almost always sufficient to map to the transcriptome, and (2) the
number of a tag observed is related to the expression level of the transcript (Velculescu et al.,
1995) (Fig. 1.3). Compared with other gene profiling methods such as microarray-based
23
analyses, advantages of SAGE include: (1) SAGE does not require prior knowledge of gene
sequences and, hence, is useful for identification of novel transcripts; (2) the data exists in
absolute units (i.e. tag counts) and is easy to expand upon comparison of results from different
experiments (Saha et al., 2002; Velculescu and Kinzler, 2007) and (3) human and mouse
transcripts in xenografts used in this study can be distinguished via comparison with human and
mouse sequences in genomic databases. The LongSAGE method uses 17 bp SAGE tags
compared with regular SAGE, which uses 10 bp tags, and therefore leads to greater precision in
the mapping of genes (Saha et al., 2002).
The outline of the regular SAGE and LongSAGE methods was shown in Fig 1.3. cDNA
is synthesized from mRNA isolated from cells or tissues and then digested by an anchoring
enzyme, commonly Nla III to generate CATG overhang. Following Nla III digestion, linkers that
contain a recognition site for the tagging enzyme are ligated to the 3′ cDNA ends. Linker-cDNAs
are digested with a tagging enzyme, Bsmf I (for regular SAGE) or Mme I (for LongSAGE), that
recognizes and binds to a sequence in the adapters and cuts the cDNA14 bp (in regular SAGE) or
21 bp (in LongSAGE) downstream to generate linker-tag fragments. Free linker-tag fragments
are ligated together into „ditags‟ and amplified by PCR with primers specific to the unique
adapters. Ditags are released from adapters by digestion with Nla III, then are concatenated into
long chain and subcloned into a vector. The cloned concatamers are sequenced to generate a
series of tags which can be quantified and analyzed by a computer program such as
DiscoverySpace.
24
Figure 1.3. An outline of the regular SAGE and LongSAGE method. (Adapted from Porter, D. et
al., 2006). See text section 1.4.
25
1.5.
HYPOTHESES AND SPECIFIC AIMS
The ultimate goals of the studies described in this thesis were (i) to investigate the
contribution of tumor heterogeneity to prostate cancer metastasis and (ii) to identify genes
associated with this process. The hypotheses underlying this work were: (1) Sublines with
different metastatic abilities, characterized by unique chromosomal alterations, can be developed
from a patient‟s primary prostate cancer tissue; (2) Prostate cancer metastasis-associated genes
can be discovered via differential gene expression analysis of paired metastatic and nonmetastatic sublines derived from the same patient‟s primary cancer tissue; (3) Certain genes/gene
products identified by this method play an important role in prostate cancer metastasis and
potentially provide predictive markers and/or therapeutic targets for the disease.
The specific aims of this study were:
1. To develop sublines from a patient‟s primary prostate cancer tissue using subrenal
capsule grafting techniques and determine the metastatic ability of the sublines by in vivo
metastatic assays.
2. To identify unique chromosomal aberrations of metastatic tumor tissue subline(s) and
determine if small or large numbers of cells carry such aberrations in the parental tissues.
3. To identify potential metastasis-associated genes by differential LongSAGE analysis of
paired metastatic and non-metastatic tumor sublines.
4. To verify differential expression of candidate gene(s) in pairs of metastatic and nonmetastatic tumor lines and clinical prostate cancer samples and to check for correlations
of candidate gene expression with clinicopathological factors.
26
5. To investigate the role of candidate gene(s) in prostate cancer metastasis by in vitro and
in vivo functional assays.
27
Chapter 2
Development of metastatic and non-metastatic sublines from
a patient’s prostate cancer specimen
– Identification of a small subpopulation with metastatic potential in
the primary tumor
2.1.
INTRODUCTION
The majority of prostate cancer death is caused by metastatic dissemination of the
primary tumor (Jemal et al., 2005). Metastasis is a complex multi-step process thought to be
driven by changes in the expression of multiple genes caused by genetic or/and epigenetic
alterations (Fidler, 2003; Gupta and Massague, 2006). Prostate cancer has been recognized as a
multifocal disease that generally consists of a dominant (index) tumor and one or more
independent tumors of smaller volume with different histological features and a wide spectrum
of biological behavior (Arora et al., 2004; Bostwick et al., 1998; Ruijter et al., 1996; Wise et al.,
2002). The histological, biological and genetic heterogeneity of multifocal prostate cancers
suggests that they arise independently from different clones (Barry et al., 2007; Cheng et al.,
1998; Mehra et al., 2007; Ruijter et al., 1999). Experimental assays based on a mouse cancer cell
line demonstrated that only a small portion of cancer cells was endowed with metastasispromoting functions, indicating that metastatic lesions are derived from descendants of a rare cell
in the primary tumor (Fidler, 2003). On the other hand, recent advances in molecular profiling of
cancers suggest that the metastatic potential of human tumors is encoded in the bulk of a primary
A version of this chapter will be submitted for publication. Dong Lin, Jane Bayani, Yuwei Wang et.al. Development
of metastatic and non-metastatic sublines from a patient‟s prostate cancer specimen. (Submitted).
28
tumor, thus challenging the above hypothesis (Gupta and Massague, 2006). It is still
controversial as to whether a minority or a majority of cancer cells in primary tumors has
metastatic potential.
Studies of prostate cancer metastasis at the cellular and tissue level have been impeded by
a lack of optimal experimental models. While established cultured cancer cell lines representing
different stages of cancer progression can be very useful for identifying mechanisms underlying
metastasis, they do not adequately mimic clinical disease (Sharpless and Depinho, 2006;
Voskoglou-Nomikos et al., 2003). Efforts have been therefore focused on use of prostate cancer
specimens from patients. However, the significant differences in microenvironment between
primary and secondary prostate cancers and the typical heterogeneity of such specimens (e.g.
consisting of both non-metastatic and potentially metastatic subpopulations) make it difficult to
identify genes underlying the development of metastasis (Fidler, 2002a). To overcome the above
hurdles, our laboratory recently developed experimental prostate cancer models that resembles
the clinical situation and allows establishment of transplantable prostate cancer sublines that
differ in metastatic ability and as such can be useful for investigating development of metastasis
at the cellular and molecular level. The model is based on subrenal capsule grafting of a patient‟s
primary prostate cancer tissue in immuno-deficient mice leading to establishment of a
transplantable, heterogeneous tumor line retaining major growth and histopathological features
of the original cancer (Cutz et al., 2006; Lee et al., 2005; Wang et al., 2005a; Wang et al.,
2005b).
The present study was aimed at examining whether metastatic potential of cells is
associated with a minority of the cells in a primary tumor or with the bulk of the tumor. The
approach used was based on establishing metastatic and non-metastatic sublines from a patient‟s
29
prostate cancer specimen, generating a marker(s) for the metastatic subline and identifying cells
with such markers in the primary tumor. To achieve this, a number of transplantable prostate
cancer sublines were developed via subrenal capsule grafting in NOD-SCID mice from different
foci of a prostate cancer. Tissue invasive or metastatic abilities of the sublines were then
determined in vivo via orthotopic grafting and monitoring organs/tissues of the hosts. Each
subline was then investigated for chromosomal alterations. Such alterations exclusively present
in a metastatic subline were further investigated in parental cancer tissues by fluorescence in situ
hybridization (FISH) to identify how many cells carrying the same chromosomal alterations
existed in the primary prostate cancer specimen.
2.2.
MATERIALS AND METHODS
2.2.1. Materials and animals
Chemicals, stains, solvents and solutions were obtained from Sigma-Aldrich Canada Ltd,
Oakville, ON, Canada, unless otherwise indicated. Male 6- to 8-week old NOD-SCID mice were
bred by the BC Cancer Research Centre Animal Resource Centre, BC Cancer Agency,
Vancouver, Canada. Mice were housed in groups of three in microisolators with free access to
food and water and their health was monitored daily. Animal care and experiments were carried
out in accordance with the guidelines of the Canadian Council on Animal Care.
2.2.2. Prostate cancer tissue acquisition
Prostate cancer tissue specimens were obtained via prostatectomy from a 70-year-old
male, with informed consent, at the Urology Research Unit, Carlton Centre, San Fernando,
Trinidad. The patient, diagnosed with advanced prostate cancer (Gleason grade 5+5), had not
30
received neoadjuvant therapy prior to prostatectomy. The specimens were examined by
pathologists and shipped overnight, immersed in cold Hanks' balanced salt solution
supplemented with antibiotics, to Vancouver, Canada.
2.2.3. Subrenal capsule grafting and development of transplantable tumor tissue
lines
Xenografting was performed as previously described (Wang et al., 2005b). In brief,
within 24 hrs of its arrival, tumor tissue was cut into small pieces about 1×3×3 mm3 in size. The
tumor pieces were grafted under the kidney capsules of male NOD/SCID mice supplemented
with testosterone (10 mg/mouse) via subcutaneously implanted testosterone pellets. After 90
days of growth (or earlier if required by the health status of the hosts), the animals were
sacrificed by CO2 for necropsy. Tumors were harvested, measured, photographed and fixed for
histopathological analysis. Some of the rapidly growing tumors were cut into pieces and
maintained for up to five transplant generations by serial subrenal capsule transplantation into
testosterone-supplemented male NOD-SCID mice. Three transplantable lines derived from this
patient were used for the study presented here.
2.2.4. In vivo orthotopic metastatic assay
Orthotopic grafting was performed as previously described (Wang et al., 2005b). In brief,
tumor tissues were harvested and were then grafted into the anterior prostates of male,
testosterone-supplemented NOD-SCID mice (two per mouse). After 5 weeks, mice were
sacrificed for gross examination of lymph nodes. Lymph nodes, lungs, livers, kidneys, spleens
and bone (femur) of the hosts were fixed for examination of metastases using histological and
immunohistochemical techniques.
31
2.2.5. Histopathological and immunohistochemical staining
Tissues of the original tumor specimen, its transplants and metastases were fixed in 10%
neutral buffered formalin and then embedded in paraffin. Sections (5 m thick) were cut on a
microtome and mounted on glass slides. For histopathological examination, every fourth section
was de-waxed in Histoclear (National Diagnostic, Atlanta, GA) and hydrated in graded alcohol
solutions and distilled water for H&E staining and examination under a light microscope. For
immunohistochemical staining, endogenous peroxidase activity was blocked with 0.5%
hydrogen peroxide in methanol for 30 min followed by washing in phosphate buffered saline
(PBS), pH 7.4. Five percent normal goat serum in PBS was applied to the sections for 30 min to
block non-specific sites. The sections were then incubated with primary antibodies overnight at
4°C or with control IgG from non-immunized mice or rabbits. Mouse anti-human mitochondria
monoclonal antibody was obtained from Chemicon International (Temecula, CA). Following
incubation with the primary antibodies, sections were washed with PBS and incubated for 30
min at room temperature with biotinylated secondary anti-mouse secondary antibody (Amersham
International, Arlington Heights, IL). After incubation with the secondary antibodies, sections
were washed in PBS (three 10-min washes), and then incubated for 30 min at room temperature
with avidin-biotin complex (Vector Laboratories, Burlingame, CA). Following a further 30 min
of
washing
in
PBS,
immunoreactivity
was
visualized
using
3,3'-diaminobenzidine
tetrahydrochloride (DAB) in PBS and 0.03% hydrogen peroxide. Sections were counterstained
with 5% (w/v) Harris hematoxylin and dehydrated in graded alcohols. Control sections were
processed in parallel with rabbit non-immune IgG (Dako, Carpinteria, CA) used at the same
concentrations as the primary antibodies.
32
2.2.6. Spectral karyotyping
Standard metaphase spreads were prepared from actively growing xenograft cultures as
previously described (Bayani and Squire, 2004; Cutz et al., 2006). The slides were hybridized
with SKYPaints (Applied Specrtral Imaging Inc. Vista, CA) according to the manufacturer‟s
instructions. The hybridized slides were imaged and analyzed using Applied Spectral Imaging
HiSKY analysis software (ASI Inc, Vista,CA).
2.2.7. Fluorescence in situ hybridization (FISH)
For copy number analysis, a bacterial artificial chromosome (BAC) clone RP11-464P23,
covering FBXO9 (6p12), was obtained from the The Centre for Applied Genomics (TCAG,
Toronto, Canada). DNA was extracted from this BAC clone and directly labeled with Spectrum
Green dUPT (Vysis/Abbott Laboratories, Des Plaines, IL) by nick translation, using the Vysis
Nick Translation Kit (Vysis/Abbott Laboratories). To confirm the proper mapping location and
hybridization efficiency, the labeled BAC clone was hybridized to normal human metaphase
spreads. A SpectrumOrange labeled probe for PTEN was obtained from Vysis (Vysis/Abbott
Laboratories) as well as a SpectrumAqua labeled centromere 6 probe (Vysis/Abbott
Laboratories). Five micron formalin-fixed, paraffin-embedded (FFPE) tissue sections,
representing early xenografts derived from individual tumor foci and the later derived sublines,
were dewaxed in xylene and dehydrated in 100% ethanol. The tissue sections were incubated in
10 mM citrate buffer at 80oC for 1 hour, rinsed in water, pepsin digested and dehydrated and codenatured for 10 minutes at 80oC using the Vysis Hybrite Hybridization System (Vysis/Abbott
Laboratories) and then allowed to hybridize overnight at 37oC. The following day, the slides
were processed using a wash of 0.3% NP-40/0.4×SSC for 2 minutes at 72oC and a wash of
33
0.1%NP-40/2×SSC for 5 minutes at RT. The slides were rinsed in 1xPBS and mounted with
DAPI/Antifade medium (Vectashield/ Vector Laboratories Canada). Two hundred nuclei per
slide were scored using a fluorescence microscope (Carl Zeiss Canada).
2.3.
RESULTS
2.3.1. Development of metastatic and non-metastatic sublines from primary
prostate cancer tissue via xenografting and in vivo metastatic assay
The procedures for development of these sublines and assessing their metastatic ability
are briefly illustrated in Figure 2.1. Tissues derived from different foci in a prostate cancer
specimen from one patient were grafted under kidney capsules of NOD-SCID mice
supplemented with testosterone and propagated by serial subrenal capsule grafting. Three tumor
tissue lines were developed from parental tissues with tumor volume doubling times of 4, 4 and 7
days (Table 2.1). All three lines were poorly differentiated and histologically similar to the
parental tissues (Fig. 2.2A-C). The human origin of the tumor lines was confirmed by
immunohistochemistry using anti-human mitochondria antibody (Fig. 2.2D-F). The metastatic
ability of each tumor tissue line was determined by examination of tissues/organs of mice
carrying xenografts in the orthotopic site (anterior prostate). At 5 weeks after grafting, apparent
local tissue invasion was observed in mice carrying a tumor line designated LTL-220M (Fig. 2.2
A, D). In addition, major metastatic foci were observed in local lymph nodes and distal
metastases were found in lung, liver, kidney and spleen (Fig.2.2G, J). In contrast, the other
tumor lines, i.e. LTL-220N and LTL-221N, derived from different foci, did not show significant
local tissue invasion or distal metastases (Fig. 2.2B, C, E, F, H, I, K, L and Table 2.1).
34
Figure 2.1. Development of metastatic and non-metastatic tumor tissue sublines from a primary prostate
cancer tissue. H&E staining show the similar histological morphology between parental tissue and
developed tumor lines. Arrows show the tumor tissues grafted in the prostates of NOD-SCID mice.
35
Table 2.1. Biological characteristics of tumor lines LTL-220M, LTL-220N and LTL-221N
LTL-220M
LTL-220N
LTL-221N
Doubling time
4 days
4 days
7 days
Local invasion
Yes
Yes/No
No
Local lymph node
metastasis
Distal metastasis
Yes
No
No
Yes
No
No
36
Figure 2.2. Different local invasive and metastatic abilities of the LTL-220M, LTL-220N and LTL-221N
sublines. A-C: hematoxylin and eosin (H&E) staining. D-L: immunohistochemical staining with humanspecific anti-mitochondria antibody. Column 1: when grafted orthotopically, the LTL-220M showed
extensive invasion into host prostate (A, D) and distant metastases to host lung (G) and liver (J). Column
2 and 3: when grafted orthotopically, the LTL-220N and LTL-221N did not show apparent invasion to host
prostate and no metastasis to distant organs including lung (H), spleen (I), liver (K) and kidney (L). Mouse
prostate are indicated with arrows. (original magnification: A, B, D, E, G-J x200; C, F, K, L x400)
37
2.3.2. Identification by SKY of unique chromosomal aberrations in tumor tissue
lines
SKY analysis was performed to identify unique chromosomal aberrations present in the
metastatic tumor line but not in the two non-metastatic tumor lines. It was found that all three
tumor lines were diploid in nature but had different chromosomal alterations (Fig.2.3A-C). LTL220M:46,
XY,
+der(1;14)
(14p11->14q:1p11->1qter),
del2p23,
der(3)t(2;3)(?;p24),
der(6)t(6,10)(p;q23), -14; LTL-220N: 46,der (X;16)(qter;p11),Y,der(21)?t(?;21)(?;p11); LTL221N:47,XY,der(14)t(13or18;14)(q?;p11),der(14)(6?;14)(?;qter),der(20)dup(20)(q13qter)t(4;20)(
q22;qter),der(21)?t(?;21)(?:?). There was a marked difference between the metastatic LTL-220M
and the non-metastatic LTL-220N and LTL-221N tumor lines in a net gain of 10q and net loss of
6p. Based on the SKY data, the gain of 10q22.1-10qter and loss of 6p can in this case be used as
a signature for distinguishing metastatic populations from non-metastatic populations.
2.3.3. Detection of cancer cells in parental tissues carrying the metastatic clone
signature (10q and 6p alterations)
To determine the presence of the 10q and 6p alterations previously identified by SKY,
the three tumor tissue lines were examined by FISH, using a SpectrumGreen-labeled probe for
FBXO9 (6p12), SpectrumAqua-labeled probe for centromere 6, and a SpectrumOrange-labeled
probe for PTEN (10q23). As expected, FISH identified 2 copies for PTEN (10q23), centromere
6, and FBXO9 (6p12) per cell in both the LTL-220N and LTL-221N non-metastatic tumor lines
(Fig. 2.4 B, C). The metastatic LTL-220M tumor line showed a net loss of FBXO9 (6p12) and
38
Figure 2.3. SKY analysis of the LTL-220M, LTL-220N and LTL-221N sublines. The metastatic LTL-220M
(A) showed the primary clone with an unbalanced translocation der(6)t(6,10)(p;q23) resulting in the net
loss of 6p and gain of 10q. The non-metastatic LTL-220N (B) and LTL-221N (C) showed no changes in
copy number of chromosomes 6 or 10, but aberrations of other chromosomes.
39
Figure 2.4. FISH detection of 10q and 6p alterations in the LTL-220M, LTL-220N, LTL-221N sublines and
their parental (first-generation) grafts. (A). The metastatic LTL-220M tumor line showed a net loss of
FBXO9 (6p12) and gain of PTEN (10q23). Insets represent three detected clones: i) gain of PTEN, loss of
FBXO9,2 copies of centromere 6; ii) gain of PTEN, 3 copies of centromere 6, 2 copies of FBXO9; iii) gain
of PTEN, 2 copies of centromere 6, 1 copy of FBXO9. (B, C). The non metastatic LTL-220N and LTL221N sublines were consistently identified with 2 copies of PTEN, centromere 6 and FBXO9 per cell. (D).
The parental xenograft of the metastatic LTL-220M line showed heterogeneity in copy number for each of
the genomic loci tested: (a) The majority of cells (60%) possessed 2 copies of PTEN (10q23), centromere
6 and FBXO9 (6p12); (b) a small population (~20%) possessed 2 copies of PTEN (10q23), centromere 6
and one copy of FBXO9 (6p12); (c) the rest (~20%) showed gain of PTEN (10q23), 2 copies of
centromere 6 and one copy of FBXO9 (6p12) (E, F). The parental xenografts of the non-metastatic LTL220N and LTL-221N showed 2 copies each for PTEN (10q23), centromere 6 and FBXO9 (6p12) as
observed in the established tumor lines. (PTEN: red; FBXO9: green; centromere 6: blue)
40
gain of PTEN (10q23). In the LTL-220M line, three different subpopulations of about the same
size were identified showing similar chromosome alterations: (i) a gain of PTEN (10q23), loss of
FBXO9 (6p12), 2 copies of centromere 6; (ii) a gain of PTEN (10q23), 3 copies of centromere 6,
and 2 copies of FBXO9 (6p12); (iii) a gain of PTEN, 2 copies of centromere 6 and one copy of
FBXO9 (6p12) (Fig. 2.4A). For PTEN, a 10q23 copy number gain was due to the gain of 1-5
copies. For FBXO9 (6p12), the majority of the cells only showed one copy for the locus (~60%),
but in cells where there were 2 copies for FBXO9 (6p12), there was a concomitant extra copy of
centromere 6. Thus the 2 copies of FBXO9 (6p12) were likely a result of polysomy for normal
chromosome 6. Taken together, net gain of PTEN(10q23) and loss of FBXO9(6p12) are
exclusively observed in most of the cells in the metastatic LTL-220M subline instead of LTL220N and LTL-221, indicating that this molecular signature could be used as a marker to identify
the presence of such a subpopulation in the parental tissues.
Screening of cells in sections of parental xenografts of the non-metastatic LTL-220N and
LTL-221N showed 2 copies each for PTEN (10q23), centromere 6 and FBXO9 (6p12) as
observed in the established tumor lines (Fig. 2.4 E, F). However, the parental xenograft of the
metastatic LTL-220M line showed heterogeneity in copy number for each of the genomic loci
tested: (i) The majority of cells (60%) possessed 2 copies of PTEN (10q23), centromere 6 and
FBXO9 (6p12); (ii) a small population (~20%) possessed 2 copies of PTEN (10q23), centromere
6 and one copy of FBXO9 (6p12); (iii) the rest (~20%) showed gain of PTEN (10q23), 2 copies
of centromere 6 and one copy of FBXO9 (6p12) (Fig. 2.4 D). This last subpopulation in the
parental xenograft showed the same PTEN, centromere 6 and FBXO9 copy number changes as
the type iii subpopulation in the metastatic LTL-220M subline.
41
2.4.
DISCUSSION
Subrenal capsule xenografting in immuno-deficient mice was used to develop the patient-
derived prostate cancer sublines since this method has a very high engraftment rate (>90%)
(Wang et al., 2005a) in contrast to more commonly used subcutaneous grafting (take rates of 2040%) (Fichtner et al., 2008; Johnson et al., 1995; Mattern et al., 1985; Merk et al., 2009; PerezSoler et al., 2000). The high engraftment rate is likely a result of high tissue perfusion of the
kidney, providing superior nutrient supply for better graft survival and development of graft
microvascularity (Cutz et al., 2006; Lee et al., 2005; Sharpless and Depinho, 2006; VoskoglouNomikos et al., 2003; Wang et al., 2005a). This is especially important to minimize loss of
tumor subpopulations during grafting.
Although the three sublines were generated from one patient‟s prostate cancer specimen,
they showed significant differences in growth rate and karyotype (Fig. 2.3 and Table 2.1). This
diversity is consistent with the widely accepted heterogeneous nature of prostate cancers.
Importantly, the sublines also showed marked differences in local tissue invasiveness and
metastatic ability as shown by an in vivo metastatic assay (Fig. 2.2). This provides functional
evidence of the presence in the primary tumor of subpopulations with different metastatic
potential.
SKY was instrumental in identifying chromosomal aberrations (gain of 10q and loss of
6p) present in the metastatic LTL-220M subline in contrast to the non-metastatic sublines. The
FISH probes, based on gain of 10q (i.e. PTEN) and loss of 6p (i.e. FBXO9), could be used to
specifically identify the metastatic LTL-220M subline cells, as such alterations were expressed
by all three subpopulations of the LTL-220M cells. The small differences observed with the
probes in the three LTL-220M subline subpopulations are probably a result of genomic
42
instability. It should be noted that the PTEN and FBXO9 probes were only used to identify cells
with 10q gain and 6p loss for proof-of-hypothesis in this particular case. The gene copy number
changes do not appear to be suitable as general markers of metastasis, since loss of the PTEN
gene, rather than its gain, is usually observed in prostate cancer development and metastasis
(Gray et al., 1998). Actually no PTEN protein expression was detected in LTL-220M cells by
immunohistochemistry in spite of PTEN copy number gain (data not shown), which is consistent
with the reports of PTEN inactivation by epigenetic regulation or mutation in advanced prostate
cancers (Li et al., 1997; Whang et al., 1998). Studies aimed at identifying metastatic markers
may benefit from further studies with these and other paired patient-derived metastatic and nonmetastatic tumor sublines at the RNA or protein level.
The small percentage of cancer cells in the parental tissues that were identified with the
“metastatic signature” indicates that metastatic ability was associated with a minority rather than
a majority of the cells at least in some primary tumors. This finding is consistent with the clonal
selection hypothesis of metastasis as supported by other groups which used cultured mouse cell
lines (Fidler and Kripke, 1977; Fidler and Talmadge, 1986). However, it is in contrast with a
report that the metastatic potential of human tumors is encoded in the bulk of a primary tumor
(Ramaswamy et al., 2003). In that study, pools of cancer cells were analyzed with an array-based
method, involving a signature composed of 17 genes that could not distinguish cells with full
metastatic ability from cells that responded only partially to the gene probing. As a result more
cells could have been identified as being metastatic than were actually present in the primary
tumor. In the present study, the finding that metastatic potential is associated with a
subpopulation in the primary tumor was made by screening of individual cells with a signature
that had been successfully used to distinguish cells with metastatic ability as shown by an in vivo
43
assay. While the present study indicates that metastatic potential of cells in a primary tumor may
be associated with a small subpopulation, it is recognized that in some cases primary tumors may
contain a large subpopulation of metastatic cells due to the fast outgrowth of a metastatic clone.
In any case, it is essential to establish signatures for specific identification of cells with
metastatic potential.
The metastatic and non-metastatic prostate cancer sublines used in the present study were
established from one patient‟s fresh primary tumor tissue which highly favored retention of
properties of the original cancer, using identical experimental conditions (e.g., microenvironment). As such they are very similar in genetic background. Some genetic differences
that they do display are likely related to metastatic ability. In view of this, the sublines could
provide useful tools for identifying metastasis-associated genes via, for example, comparative
gene expression analysis. It is likely that genes, found to be differentially expressed in metastatic
and non-metastatic prostate cancer sublines, will include some with critical roles in metastasis.
Such genes and/or their products could serve as potential targets for therapy of metastatic
prostate cancer.
44
Chapter 3
IDENTIFICATION OF ASAP1, A PROSTATE CANCER
METASTASIS-ASSOCIATED GENE
3.1.
INTRODUCTION
Prostate cancer is the most common cancer as well as the second leading cause of cancer-
related deaths for North American males. Once prostate cancer has metastasized it is incurable,
and most deaths from this disease are due to metastases that are highly resistant to conventional
therapies. Metastatic prostate cancer is hence a terminal disease. Development of new
therapeutic targets, as well as reliable biomarkers for detection of metastatic potential in primary
tumors, is of critical importance for improved disease survival and management (Foley et al.,
2004; Glinsky et al., 2004; Isaacs, 2005).
Metastasis is a multi-step process thought to be based on changes in expression of
specific genes (Fidler, 2003). In view of this, changes in the expression of certain genes may
serve as metastatic biomarkers and/or new targets for therapy of metastatic disease (Foley et al.,
2004). Although effort have been made towards identification of metastatic biomarkers for
prostate cancer (Foley et al., 2004; Glinsky et al., 2004; Paris et al., 2005; Varambally et al.,
2005), few prognostic assays have so far been submitted to the US Food and Drug
Administration (Gutman and Kessler, 2006). This is largely due to a lack of optimal models for
A version of this chapter has been published. Dong Lin, Akira Watahiki, Jane Bayani et al (2008). ASAP1, a gene at
8q24, is associated with prostate cancer metastasis. Cancer Res 68: 4352-9.
45
studying the development of prostate cancer metastasis. While prostate cancer cell lines
representing different stages of tumor progression can be useful for identifying mechanisms
underlying metastasis and developing novel therapeutics, they do not adequately mimic clinical
disease (Sharpless and Depinho, 2006; Voskoglou-Nomikos et al., 2003). Efforts have therefore
focused on models based on prostate cancer specimens from patients. However, the typical
heterogeneity of such specimens, consisting of both non-metastatic and metastatic
subpopulations, makes it difficult to identify genes with critical roles in the development of
metastasis (Fidler, 2002a; Wang et al., 2005b).
To overcome such a hurdle, a pair of metastatic (PCa1-met) and a non-metastatic (PCa2)
sublines were generated from a patient‟s prostate cancer specimen (Lin et al., 2008; Wang et al.,
2005b) (Fig. 3.1). Using a modified version of Serial Analysis of Gene Expression (SAGE), i.e.
LongSAGE (Saha et al., 2002), orthotopically grown xenografts of these two closely related
sublines were compared with a view to identifying genes that were differentially expressed and
as such could play a role in the development of metastatic ability. A number of differentially
expressed genes were identified, including genes previously reported to have a role in tissue
invasion and metastasis of prostate cancer cells. Differentially expressed genes that had not
previously been associated with prostate cancer were also identified, including ASAP1
(AMAP1/DDEF1), a gene encoding an Arf GTPase-activating protein reported to have a role in
breast cancer invasive activities (Onodera et al., 2005). Expression of ASAP1 protein was
examined in primary and metastatic prostate cancer specimens in comparison with benign
prostate samples. A correlation was sought between expression of ASAP1 protein and a variety
of clinicopathological parameters.
46
Figure 3.1. Different local invasive ability of PCa1-met and PCa2. Tissue sections showing (i) differences
in host tissue invasiveness between PCa1-met and PCa2 orthotopic xenografts during an 8-week assay
and (ii) human origin of the cancer cells. A, PCa1-met cells have penetrated smooth muscle surrounding
a mouse host prostatic duct (arrow) and grown around it; B, in contrast, host tissue is apparently not
invaded by PCa2 cells. C, D, IHC staining with anti-human mitochondria antibody shows that human
cancer cells are positively stained in contrast to the mouse host's prostatic ductal epithelial cells. (original
magnification x100)
47
3.2.
MATERIALS AND METHODS
3.2.1. Materials and animals
Chemicals, stains, solvents and solutions were obtained from Sigma-Aldrich Canada Ltd,
Oakville, ON, unless otherwise indicated. Six- to eight-week old NOD-SCID mice were obtained
from the breeding program at the BC Cancer Research Centre Animal Resource Centre, BC
Cancer Agency, Vancouver.
3.2.2. Xenografts
The prostate cancer tissue sublines were maintained by serial transplantation of subrenal
capsule xenografts into male NOD-SCID mice supplemented with testosterone (10 mg/mouse);
metastatic and non-metastatic abilities of tumor sublines were confirmed using orthotopic
grafting, as described in Chapter 2. In this chapter, a pair of metastatic (PCa1-met) and nonmetastatic (PCa2) sublines developed from another patient‟s primary tumor were used for SAGE
and following studies. Orthotopically grafted tissues were harvested for SAGE, qRT-PCR and
immunohistochemical analysis. Animal care and experiments were carried out in accordance
with the guidelines of the Canadian Council on Animal Care.
3.2.3. SAGE library construction and comparative analysis
Total RNA was extracted from orthotopically grafted PCa1-met and PCa2 tissues (16th
generations) using TRIZOL Reagent (Invitrogen, Burlington, ON) following the manufacturer‟s
instructions. The quality of the RNA samples was analyzed using Agilent Bioanalyzer (Agilent
48
Technologies, Santa Clara, CA). SAGE libraries were constructed using an I-SAGE kit
(Invitrogen). The libraries‟ clones were sequenced by the BC Genome Sciences Centre
(BCGSC). Sequenced tags of the two tumor sublines were analyzed using DiscoverySpace, a
BCGSC-developed
SAGE
gene
expression
(http://www.bcgsc.ca/bioinfo/software/discoveryspace/).
analysis
The
tags
software
were
filtered
tool
by
“Experimental SAGE Tags Quality” (quality factor (QT) ≥95%) and annotated using the human
and mouse gene and genome data “CMOST” integrated database. Since the transplantable
xenograft tissues contain both human (tumor) and mouse (stroma) tissue, the SAGE tags were
categorized as human-specific, mouse-specific, shared by human and mouse, and unmapped. In
the present study, only human-specific tags were analyzed. Audic and Claverie p-statistics
(DiscoverySpace) was used to establish whether differences found for selected tags between
PCa1-met and PCa2 tissues were statistically significant. Each tag‟s ratio was calculated from
frequencies per 100,000 human tags.
3.2.4. Quantitative real-time polymerase chain reaction (qRT-PCR)
Total RNA was isolated from xenograft tissues using the RNeasy mini kit (Qiagen,
Mississauga, ON) following the manufacturer‟s suggestions. The quality of the RNA samples
was analyzed using Agilent Bioanalyzer (Agilent Technologies). RNA (1 µg) was treated with
0.5 units deoxyribonuclease I (amplification grade, Invitrogen) and then annealed with 50 ng
random hexamer oligonucleotide. The cDNA was synthesized using the Superscript first strand
synthesis system for RT-PCR (Invitrogen) following the manufacturer‟s suggestions. The cDNA
products were diluted 20-fold prior to PCR amplification. Expression of selected genes was
analyzed using a 7900HT Sequence Detection System (Applied Biosystems, Inc., Foster City,
49
CA). The qRT-PCR reaction was carried out in a 10 µL volume using cDNA (converted from
2.5 ng total RNA), a 150 nM gene-specific primer pair and Platinum SYBR Green qPCR
SuperMix-UDG with ROX (Invitrogen). Duplicate reactions were performed for each sample,
and data averaged and normalized to a geometric mean of the expression of two housekeeping
genes, hprt and K-alpha-1, reported to be stably expressed in prostate tissue (Ohl et al., 2005).
Gene expression data are presented as fold-change of one subline relative to the other subline.
Since the xenograft samples consisted of both human and mouse cells, the following humanspecific primers were designed for the ASAP1, hprt and K-alpha-1 genes, to ensure that only
human cDNA, and not mouse cDNA, was amplified in qRT-PCR reactions. ASAP1: forward 5‟CCCCTTTTGCAGCAACTTACA and reverse 5‟- TCCTATGTCCCACAGTAAGCTGG; hprt:
forward
5‟-GGTCAGGCAGTATAATCCAAAG
CGATGTCAATAGGACTCCAGAT;
K-alpha-1:
and
reverse
forward
5‟5‟-
GAGGTTGGTGTGGATTCTGTT and reverse 5‟-AGCTGAAATTCTGGGAGCAT. Gene
expression levels are expressed as mean ±SD.
3.2.5. Clinical prostate cancer tissues
Specimens were obtained from patients, with their informed consent, following a
protocol approved by the Clinical Research Ethics Board of the University of British Columbia
(UBC) and the BC Cancer Agency. Tissue microarrays (TMAs) were constructed (Lee et al.,
2005) at the Prostate Centre, Vancouver General Hospital (VGH) of 10 benign prostatic
hyperplasia (BPH) and 66 paraffin-embedded radical prostatectomy specimens from randomly
selected cancers (Dept Pathology, VGH/UBC) that had not been subjected to any treatment
before surgery. Areas with sufficient amounts of carcinoma and normal prostatic epithelium in
50
the original, diagnostic H&E-stained tissue sections were identified by a pathologist. Using a
Tissue Microarrayer (Beecher Instruments, Silver Spring, MD), four tissue cores were taken
from each BPH and malignant specimen for TMA construction. All patients were clinically
staged as TNM (UICC system) based on clinical and radiological features (i.e., bone and
computerized tomography scans). In addition, sections from 11 lymph node, 2 lung and 5 bone
metastatic prostate cancers were obtained for ASAP1 protein analysis.
3.2.6. Post-operative follow-up
Following surgery, patients were tested every 6 months for serum PSA levels. PSA
recurrence was defined as a sustained elevation, on two or more occasions, of serum total PSA
>0.2 ng/ml and was assigned to the date of the first elevated value. All patients receiving any
form of neoadjuvant or adjuvant therapy were excluded from the study.
3.2.7. Histopathological and immunohistochemical staining
Preparation of paraffin-embedded tissue sections and immunohistochemical analyses
were carried out as previously described (see Chapter 2). For ASAP1 protein staining, rabbit
polyclonal anti-ASAP1 primary antibody was obtained from Abcam (Cambridge, UK).
Biotinylated anti-rabbit secondary antibody was obtained from Amersham International
(Arlington Heights, IL). All tissue sections were lightly counterstained with 5% (w/v) Harris
hematoxylin. Control sections were processed in parallel with rabbit non-immune IgG (Dako,
Carpinteria, CA) used at the same concentrations as the primary antibodies.
3.2.8. ASAP1 scoring
Cytoplasmic ASAP1 protein staining in tissue samples was evaluated by two independent
pathologists in blinded analyses. Specimens were graded from 0 to +3 intensity to represent a
51
range from no staining to strong staining. The analyses were performed on the mean value of
ASAP1 protein expression for each specimen.
3.2.9. Fluorescence in situ hybridisation (FISH) analysis for determination of
ASAP1 gene copy number
Dual-color FISH karyotypic analysis of paraffin-embedded tumor tissue (5 µm sections)
was performed as described in Section 2.2.7. To determine ASAP1 gene copy numbers, two
bacterial artificial chromosome (BAC) clones (RP11-582G12 and RP11-140N11) containing
specific ASAP1 sequences were used; chromosome 8 was identified using a CEP 8 centromere
probe. BAC DNAs were extracted by standard methods and labelled with Spectrum Orange
(Abbott Molecular Inc./Vysis Inc., Des Plaines, IL). The chromosome localization and sequence
identity of the BAC clones was confirmed by normal metaphase FISH and PCR analyses.
3.2.10.
Statistical analysis
The Chi-square test was used to evaluate the association between ASAP1 protein
expression and clinicopathological parameters. Differences of ASAP1 expression in benign,
primary and metastatic cancer tissues were assessed using the Mann-Whitney U-test. The
Kaplan-Meier method was used to calculate survival probability functions, and the differences
were assessed with the log-rank test. Multivariate survival analyses were performed using the
Cox proportional hazards regression mode. Statistical significance in this study was set as
P≤0.05.
52
3.3.
RESULTS
3.3.1. Comparative analysis of SAGE libraries of metastatic and non-metastatic
prostate cancer sublines
Tissues from PCa1-met and PCa2 sublines, maintained as xenografts in mice, were
grafted orthotopically (16th generation) and after seven tumor volume doublings harvested for
SAGE. LongSAGE libraries of the PCa1-met and PCa2 sublines were prepared, containing
132,163 and 134,206 useful tags respectively, after removing tags with poor quality (quality
factor <95%). Mapping of the tags to a Reference Sequences database (RefSeq) revealed that
88,001 (21,290 tag types) of the PCa1-met tags and 66,383 (17,206 tag types) of the PCa2 tags
were of specific human origin; 15,678 tags (6,878 tag types) in PCa1-met and 38,943 tags
(11,582 types tag) in PCa2 library were of specific mouse origin; 23,201 tags (2,623 types tag) in
PCa-1 met and 20,949 tags (2,627 types tag) in PCa2 are mapped both human and mouse
database; 5,283 (4,395 types tag) and 7,931 tags (6,231 types tag) did not map to either human
and mouse database (Table 3.1). In this study, only human specific tags were analyzed in
following steps. A scatter plot illustrates differential expressed tags between PCa1-met library
and PCa2 library by Audic and Claverie statistics (Fig.3.2). A significant number of tags were
differentially expressed between two libraries (P≤0.05), including 27,130 tags (419 tag types)
upregulated and 22,545 tags (412 tag types) downregulated in PCa1-met library compared with
PCa2 library (Table 3.2). Tags that were mapped ambiguously to more than one gene and
differed by less than two-fold were excluded from further analysis. Application of this filter
reduced differentially expressed tag types to 646 (340 upregulated tag types and 306
downregulated tag types). These 646 tag types represented 596 genes, including 318 genes upregulated and 278 genes down-regulated in the PCa1-met library, relative to the PCa2 library.
53
Table 3.1 Characteristics of LongSAGE tag frequency distribution
Human
specific
Mouse
specific
Human & mouse
Shared
Unmapped
Total
Total tags
88,001
15,678
23,201
5,283
132,163
Tag types
21,290
6,878
2,623
4,395
35,168
Total tags
66,383
38,943
20,949
7,931
134,206
Tag types
17,206
11,582
2,627
6,231
37,646
Library
PCa1-met
PCa2
54
Figure 3.2. Confidence intervals highlight expressed tag types with non-linear relationships between
LongSAGE libraries derived from PCa1-met and PCa2. Scatter plot dots represent tag types and their
placement indicates their counts in either libraries. Dots that fall outside the confidence interval (CI) lines
are statistically significantly differentially expressed (Audic and Claverie statistics). Green line, 95% CI;
yellow line, 99% CI and black line, 99.9% CI.
55
Table 3.2. Compositions of human specific tags in PCa1-met and PCa2 libraries.
Total tags
Tag types
Expressed at similar level in both libraries*
104,709
29,633
Up-regulated in PCa1-met library+
27,130
419
+
Up-regulated in PCa2 library
22,545
412
Total
154,384
30,464
* Audic and Claverie statistics, P>0.05.
+ Audic and Claverie statistics, P≤0.05.
56
Some of these differentially expressed genes have previously been reported to play a role in
cancer with regard to tissue invasion and metastasis, including, EZH2, CCL2, CCR7 and S100A4.
Of the differentially expressed genes not previously associated with prostate cancer, the ASAP1
gene was of particular interest, since its tags in the metastatic library (10.33/100,000) were found
to be more prevalent than in the non-metastatic library (1.55/100,000) (P=0.04) and it is
localized at 8q24, a commonly amplified region in advanced prostate cancer.
3.3.2. Differential ASAP1 gene expression in PCa1-met and PCa2 tumor sublines
To validate differential ASAP1 expression in the PCa1-met and PCa2 tumor sublines,
expression of the ASAP1 gene was measured using qRT-PCR in samples of the two sublines
derived from 12th, 14th and 16th generations harvested at 27-35 days post-grafting. The ASAP1mRNA levels were significantly higher in the metastatic PCa1-met than in the non-metastatic
PCa2 subline, showing 2.3±0.4, 2.3±0.1 and 2.1±0.3 fold differences in the 12th, 14th and 16th
generations, respectively (P<0.01, Fig.3.3A). The fold-change was essentially the same for the
three generations examined, indicating that there was no major change in differential ASAP1
gene expression through five consecutive passages of the sublines.
3.3.3. Differential expression of ASAP1 protein in xenograft tissues
Using immunohistochemistry, levels of ASAP1 protein were determined in xenografts of
non-metastatic PCa2 and metastatic PCa1-met tissue, as well as benign and slow growing
malignant tissue. The PCa2 and PCa1-met sublines showed moderate and strong cytoplasmic
staining for ASAP1 protein, respectively (Fig.3.3B, C). The much stronger staining for ASAP1
protein in PCa1-met tissue compared to PCa2 tissue was consistent with the higher levels of
57
Figure 3.3. Differential ASAP1 expressions in PCa1-met and PCa2 sublines. A. Levels of ASAP1 mRNA
in PCa1-met were consistently higher than those in paired PCa2 xenograft tissues in different generations
(P<0.01). B-E. Immunohistochemistry showed ASAP1 protein expression in PCa1-met, PCa2, xenografts
of benign and slow growing malignant prostate tissues: B, non-metastatic PCa2 cells showing moderate
cytoplasmic expression and C, metastatic PCa1-met cells showing strong cytoplasmic expression of the
ASAP1 protein. D, benign prostate tissue showing weak cytoplasmic expression of ASAP1. E, slow
growing prostate cancer grafts showing moderate cytoplasmic expression of ASAP1. Mouse kidney is
indicated with arrow. Original magnifications: 200x, inserts: 400x.
58
ASAP1-mRNA found in the PCa1-met subline. ASAP1 protein expressions were also detected in
benign prostate tissue grafts (Fig.3.3D) and slow growing prostate cancer grafts (Fig.3.3E) which
had survived transplantation into testosterone-supplemented NOD-SCID mice but did not show
significant growth even after 6 months of grafting. In these cases, the benign tissue showed weak
or no cytoplasmic ASAP1 protein staining; the slow growing malignant tumor grafts showed
weak or moderate cytoplasmic ASAP1 protein staining similar to that observed in the nonmetastatic PCa2 subline. Taken together, the xenograft-derived data suggest that highly elevated
ASAP1 protein expression is associated with cancer cell aggressiveness and metastatic potential.
3.3.4. Expression of ASAP1 protein in clinical prostate samples
A tissue microarray (TMA) of clinical prostate samples, i.e. 10 BPH and 66 primary
cancer tissues, was examined for ASAP1 protein expression. Nine out of the 10 benign prostate
tissues showed negative or only weak ASAP1 protein expression (Fig. 3.4D arrow), a finding
consistent with the observations with benign prostate tissue xenografts (Fig.3.3D). In 53 out of
the 66 prostate cancer tissues (80%) moderate to strong ASAP1 protein expression was observed.
The intensity of ASAP1 protein staining in these prostate cancer tissues (2.1±0.6) (Fig. 3.4B-D)
was significantly higher than in the benign tissues (0.9±0.3) (P<0.01) (Table 3.3). In 32 cancer
cases, different cores obtained from the same patient‟s tissue showed varying ASAP1 staining
levels. Strong ASAP1 expression was observed in perineural and vascular invasive prostate
cancers (Fig. 3.5A, B).
Individual metastatic prostate cancer tissues, i.e. 11 lymph node, 2 lung and 5 bone
metastatic tissues, were also examined for ASAP1 protein expression. In all the tissues
examined, ASAP1 protein expression (2.6±0.6) was very high (Fig. 3.5C-F) and significantly
59
Figure 3.4. Immuno-histochemical staining of ASAP1 in a tissue microarray of clinical prostate samples.
A. Prostate cancer cells showed weak cytoplasmic staining for ASAP1, scored 1; B. Prostate cancer cells
showed moderate cytoplasmic staining for ASAP1, scored 2; C. Prostate cancer cells showed strong
cytoplasmic staining for ASAP1, scored 3; D. Tissues of prostate cancers showed much stronger staining
for ASAP1 compared with adjacent benign tissue (arrow). Original image magnifications: 200x.
60
Figure 3.5. ASAP1 protein expression in clinical samples of invasive and metastatic prostate cancer. A,
B: strong ASAP1 expression in perineural invasive and intravascular prostate cancer cells; arrow head
indicates a blood vessel. C: lymph-node metastatic prostate cancer tissues showing strong ASAP1
protein expression. D: lung metastatic prostate cancer tissue showing strong ASAP1 expression; lung
tissue is indicated with an asterisk. E, F: bone metastatic prostate cancer tissue showing strong ASAP1
protein expression; bone matrices are indicated with an asterisk, prostate cancer cells with an arrow.
Original magnifications: 100x (D, E), 200x (A, C, F) and 400x (B).
61
stronger than in the primary prostate cancer tissues (P<0.01), indicating that increased ASAP1
protein expression is associated with metastatic ability (Table 3.3).
3.3.5. Association of ASAP1 protein expression in primary tumors with
clinicopathological parameters
In examining whether ASAP1 expression in primary tumors was linked to
clinicopathological factors, 66 cases were divided into two groups on the basis of ASAP1
staining intensity levels using a division point of 25% of the cancer cells showing strong ASAP1
staining in view of the heterogeneous ASAP1 expression observed in TMA. There was no
correlation between ASAP1 levels and Gleason grade, margin and clinical stage. A significant
association was found between strong ASAP1 expression and positive clinical stage of
metastasis (M+) (P=0.04). There was a clear trend towards a higher frequency of PSA recurrence
in patients whose samples showed strong ASAP1 expression (P=0.05) (Table 3.4). Kaplan-Meier
analysis showed that strong ASAP1 staining was coupled to increased risk of PSA recurrence
after surgery, although statistical significance using the log-rank test was not fully reached
(P=0.07) (Fig. 3.6). In a multivariate Cox proportional hazards regression analysis, strong
ASAP1 is not an independent risk factor of PSA recurrence.
3.3.6. ASAP1 gain/amplification in clinical prostate samples
The ASAP1 gene is located at 8q24. Gain of this region is one of the most common
chromosomal alterations in advanced prostate cancer. To investigate whether gain/amplification
of the ASAP1 gene was a common event in prostate cancer and whether it was correlated with
increased ASAP1 protein expression, two ASAP1-specific BAC probes were used together for
interphase FISH analysis of 10 benign and 38 primary prostate cancer samples. Chromosome 8
62
Table 3.3. ASAP1 expression in clinical prostate tissues.
number of cases
ASAP1 staining
P value
Benign
10
0.9±0.3
Primary cancer
66
2.1±0.6
<0.01a
Metastatic cancer
16
2.6±0.6
<0.01b
a
ASAP1 expression in primary prostate cancer tissue is significantly increased compared to expression in
benign prostate tissue (Mann-Whitney U-test).
b
ASAP1 expression in metastatic prostate cancer tissue is significantly increased compared to
expression in primary prostate cancer tissue (Mann-Whitney U-test).
63
Table 3.4. Association between ASAP1 expression and clinicopathological parameters.
ASAP1 expression
(-)~(++)a
+++a
Total
P valueb
Gleason grade
Gleason<7
Gleason≥7
18
19
12
17
30
36
0.56
T2
T3
30
7
25
4
55
11
0.60
MM+
36
1
24
5
60
6
0.04
negative
positive
25
12
21
8
46
20
0.67
negative
positive
17
0
16
4
33
4
0.05
Clinical stage
Margin
PSA recurrence
a
(-)~(++): less than 25% cancer cells showed ASAP1 strong staining
(+++): ≥25% cancer cells showed ASAP1 strong staining
b
Chi-squared analysis.
64
Figure 3.6. Probabilities of PSA recurrence-free survival in patients treated with radical prostatectomy
according to ASAP expression. (log-rank test, p=0.07)
65
was identified using a CEP 8 centromere probe. As expected, the 10 benign prostate tissues did
not show any increase in ASAP1 copy number per cell. In contrast, there was a significant
increase in ASAP1 copy number in 22 of the 38 primary prostate cancer cases (57.9%). Among
the 22 cases, 21 cases showed ASAP1 gain resulting from polysomy of chromosome 8, i.e. 20
cases showed low-level gain (3-4 copies of ASAP1 per cell; Fig. 3.7A), whereas one showed a
high copy number gain (≥ 5 copies of ASAP1 per cell; Fig. 3.7B). The remaining case (4.5%)
showed amplification of ASAP1 (cells with gain of ASAP1 signals relative to CEP 8 signals; Fig.
3.7C). Of the 38 cases there were only 31 where both ASAP1 protein expression and copy
numbers were determined. In 17 cases where copy numbers had increased, 13 (76.4%) showed
increased ASAP1 expression. However, in the remaining 14 cases with normal ASAP1 copy
numbers, increased ASAP1 expression was also observed in 12 cases (85.7%), indicating that
there was no correlation between gain/amplification of ASAP1 and elevated ASAP1 protein
expression (P=0.52). Taken together, the data suggest that gain/amplification of ASAP1 is a quite
common occurrence in prostate cancer, but is not associated with increased ASAP1 protein
expression.
3.4.
DISCUSSION
Most deaths from prostate cancer are due to metastases that are highly resistant to
conventional therapies. So far, few metastasis-associated genes have been discovered that could
be used as reliable metastatic biomarkers, or therapeutic targets, to improve management of the
disease (Foley et al., 2004; Glinsky et al., 2004; Gutman and Kessler, 2006). In this study, gene
expression of the metastatic PCa1-met and non-metastatic PCa 2 sublines, derived from the same
patient‟s cancer, were compared by SAGE. One of the advantages of SAGE analysis is that
66
Figure 3.7. Gain and/or amplification of ASAP1 shown by dual-color FISH in human primary prostate
cancer tissues. A. Nuclei showing a balanced increase in ASAP1 gene (red) and chromosome 8 number
(green) indicating low polysomic copy gain (three to four copies). B Nuclei showing a balanced increase
in ASAP1 gene and chromosome 8 number indicating high polysomic copy gain (five or more copies). C
Nuclei showing an increase in ASAP1 copies relative to chromosome 8 copies indicating ASAP1 gene
amplification. Original magnification, 400x.
67
human and mouse specific tags can be distinguished by annotation using human and mouse
genome databases, making it possible to exclude the influence of mouse gene expression in
xenograft tissues. In this study, non-annotated tags, and all the tags annotated with mouse genes,
were not included in further analysis, even though some of the tags were also annotated to
human genes. As could be expected, some known metastasis-associated genes, were found to be
differentially expressed in the two sublines, such as EZH2(11/1)(Varambally et al., 2002),
S100A4 (9/0) (Saleem et al., 2006), CCR7 (7/0) (Muller et al., 2001) and CCL20 (8/0) (Beider et
al., 2009). This indicates the validity of the approach used.
ASAP1, also known as DDEF1 and AMAP1, is an ADP ribosylation factor GTPaseactivating protein (ArfGAP). It was first identified on the basis of Arf GAP activity, and
separately, in screening of Src-binding proteins (Brown et al., 1998; King et al., 1999). ASAP1
was found to bind to Src, focal adhesion kinase (FAK) and phosphatidylinositol-4,5bisphosphate (PIP2) and to be involved in regulation of cell migration (Brown et al., 1998; Liu et
al., 2002; Liu et al., 2005; Randazzo et al., 2000). A role for ASAP1 in prostate cancer has not
previously been reported. The finding in the present study showed that the level of ASAP1
expression increased progressively in both human prostate xenografts and clinical specimens
going from benign to malignant to metastatic conditions. This phenomenon is consistent with
observations in breast cancer and uveal melanoma studies. Thus high levels of ASAP1
expression in invasive ductal carcinoma (IDC) have been reported, whereas the adjacent noncancerous mammary ductal epithelia showed very low expression levels (Ehlers et al., 2005;
Onodera et al., 2005). Furthermore, ASAP1 protein was significantly up-regulated in high-grade
uveal melanomas compared to low-grade tumors (Ehlers et al., 2005). However, these studies
did not investigate association of ASAP1 expression with clinicopathological factors and disease
68
outcome as was done in the present study. In the latter, the correlation of strong ASAP1
expression with both positive clinical stage of metastasis and PSA recurrence suggests that
increased ASAP1 expression is linked to aggressiveness and metastatic potential in primary
prostate cancers.
Several limitations in this study should be considered. Some associations of increased
ASAP1 expression with clinical parameters, that were inconclusive due to limited statistical
power, may attain statistical significance if the sample size is increased. For example, while there
was a trend that patients with strong ASAP1 expression had an increased probability of PSA
recurrence after surgery, only near statistical significance was observed using Kaplan-Meier
analysis and log-rank test (P=0.07). It should be noted that only 37 out of 66 cases of the patient
cohort have been followed up. Only 4 out of the 37 cases (10.8%) had PSA recurrence after a
median follow-up of 38 months. This recurrence rate is lower than other reported PSA
recurrence rates (about 20%) following radical prostatectomy (Hull et al., 2002; Khan et al.,
2005). Studies involving larger patient cohorts with longer follow-up will be helpful to clarify
whether strong ASAP1 expression in primary tumors is indicative of recurrence of the disease.
Gain of the 8q region has been reported as one of the most common chromosomal
alterations in prostate cancer tissue (Gudmundsson et al., 2007; Haiman et al., 2007; Kim et al.,
2007; Visakorpi et al., 1995; Yeager et al., 2007). It has also been observed in the highly
invasive PC-3 prostate cancer cell line (Porkka et al., 2004; Tsuchiya et al., 2002). Gain of the
8q region has also been reported to correlate with metastatic progression and poor prognosis of
prostate cancer (Ribeiro et al., 2006; van Dekken et al., 2003). As such, it is of major interest
that the ASAP1 gene has been mapped to chromosomal location 8q24.21. The finding in the
present study that copy number gain of the ASAP1 gene is likely a common event in primary
69
prostate cancer (57.9%) is similar to that observed for uveal melanoma, in which ASAP1 was
amplified in approximately 50% of uveal melanomas. The latter study also showed that ASAP1
overexpression correlated strongly with gain in 8q copy number. However, such a correlation
between increased ASAP1 expression and gain of ASAP1 was not observed in the present study.
On the other hand, amplification of ASAP1 leading to increased protein expression cannot be
excluded, since in our patient cohort highly increased ASAP1 protein expression was found in
the case in which ASAP1 was amplified. Since only one such case was observed, larger patient
cohorts should be examined for a relationship between ASAP1 amplification and increased
ASAP1 protein expression.
In summary, the findings in this study suggest that prostate cancer metastasis-associated
genes can be successfully identified by comparison of gene expression patterns of paired
metastatic and non-metastatic sublines derived from one patient‟s primary cancer tissue. The
results obtained with clinical specimens suggest that ASAP1 and its products may be involved in
prostate cancer progression and represent potential new biomarkers for identification of prostate
cancer patients at high risk of metastasis. Further functional studies will help to clarify the role of
ASAP1 in prostate cancer metastasis and may provide new insights into prostate cancer
progression.
70
Chapter 4
FUNCTIONAL VALIDATION OF ASAP1 AS A METASTASISASSOCIATED GENE IN PROSTATE CANCER
4.1.
INTRODUCTION
Tumor cells metastasize via a series of biological cascades. Tissue invasion is one of the
key steps in this complex process. Reorganization of the cytoskeleton as well as degradation of
the extracellular matrix is important for tumor cells in dissociating from the primary tumor,
invading adjacent tissue and subsequently metastasizing to distant sites (Bacac and Stamenkovic,
2008; Mareel et al., 2009; Yamaguchi et al., 2005).
Various studies have demonstrated that specific genes are involved in tissue invasion and
metastasis of prostate cancer cells (Clarke et al., 2009; Gopalkrishnan et al., 2001). In the
previous study (Chapter 3), a number of prostate cancer metastasis-associated genes were
identified by comparison of metastatic and non-metastatic prostate cancer sublines derived from
a patient‟s primary cancer specimen. The ASAP1 gene was particularly interesting due to its
elevated expression in malignant, especially metastatic tissues and gene amplification/copy
number gain in clinical cancer samples.
ASAP1 belongs to a family of ADP-ribosylation factors GTPase activating proteins
(ARF GAPs) with two splice variants ASAP1 (125kDa) and ASAP1b (120kDa) in human
(Onodera et al., 2005). Schematic representation of ASAP1 and ASAP1b was shown in Fig.4.1.
Part of this chapter will be submitted for publication. Dong Lin, Yuwei Wang, Fang Zhang et.al. ASAP1 is important
but not sufficient for prostate cancer invasion and metastasis. (In preparation).
71
Figure 4.1. Schematic representation of ASAP1 and ASAP1b proteins. Two splice variants, ASAP1 and
ASAP1b were reported in human. The 120kDa isoform, ASAP1b, is lack of 4 of 16 proline-rich sequences
rd
th
(3 to 6 , 57aa), which present in 125kDa isoform ASAP1. BAR: Bin–Amphiphysin–Rvs domain; PH:
Pleckstrin homology domain; Arf GAP: Arf GAP (ADP-ribosylation factors GTPase activating protein)
domain; ANK: Ankyrin repeats; PRD: Proline rich domain; SH3: SRC homology 3 domain.
72
ARFs represent a family of small G proteins that are involved in the regulation of membrane
trafficking and the actin cytoskeleton (D'Souza-Schorey and Chavrier, 2006). The activation of
ARFs is regulated by GTPase exchange factors (GEFs) and GAPs. The GEFs activate ARFs by
facilitating ARFs to release GDP and bind with GTP, and GAPs deactivate ARFs by stimulating
ARFs‟ GTPase activity, thus allowing for the hydrolysis of bound GTP to GDP. ASAP1 was
identified based on its ARF GAP activity and through its interaction with Src independently
(Brown et al., 1998; King et al., 1999). ASAP1 has been found to bind to and be phosphorylated
by Src and FAK (focal adhesion kinase) and associated with focal adhesion structure and
regulation of cell motility (Brown et al., 1998; Liu et al., 2002; Liu et al., 2005). Recently,
ASAP1 was thought to contribute to the cancer invasive and metastatic phenotype in uveal
melanoma and breast cancer (Ehlers et al., 2005; Onodera et al., 2005). In previous study
(Chapter 3), increased ASAP1 protein expression was correlated with prostate cancer metastasis
and poor PSA recurrence-free survival in xenograft model and clinical prostate cancer samples.
The findings suggest that ASAP1 may play a role in prostate cancer metastasis. To investigate
the role of ASAP1 in tissue invasion and metastasis of prostate cancer, ASAP1 protein
expression was (i) reduced by siRNA and lentivirus-mediated RNA interference and (ii)
overexpressed by lentivirus-mediated overexpression. Effects of the gene silencing or
overexpression were evaluated in vitro and in vivo, using cell-based assays such as wound
healing, matrigel invasion and orthotopical metastatic assays.
73
4.2.
MATERIALS AND METHODS
4.2.1. Materials and animals
Chemicals, stains, solvents and solutions were obtained from Sigma-Aldrich Canada Ltd,
Oakville, ON, unless otherwise indicated. Six- to eight-week old NOD-SCID mice were obtained
from the in-house breeding program of the BC Cancer Research Centre Animal Resource Centre,
BC Cancer Agency, Vancouver.
4.2.2. Cell cultures
The human prostate cancer cell lines, PC-3 and LNCaP, were obtained from the
American Type Culture Collection (Manassas, VA). Cells were maintained in RPMI-1640
medium (Stem Cell Technologies, Vancouver, BC), supplemented with 10% fetal bovine serum
(Gibco-BRL, Burlington, ON), penicillin (50 units/ml) and streptomycin (50 g/ml) (Stem Cell
Technologies) in a humidified atmosphere of 95% air and 5% CO2 at 37°C. Subculturing was
carried out using standard techniques, including trypsinization using 0.25% trypsin/1.0 mM
EDTA.
4.2.3. Small interfering RNA (siRNA) and cell transfection
siRNAs (Stealth™) targeting ASAP1 and negative control (scrambled) siRNAs were
purchased from Invitrogen. The ASAP1-targeting Stealth™ RNAis were: siRNA1, 5‟GACCAGAUCUCUGUCUCGGAGUUCA-3‟
UGAACUCCGAGACAGAGAUCUGGUC-3‟,
GGGCAAUAAGGAAUAUGGCAGUGAA-3‟
and
and
5‟-
siRNA2,
5‟-
and
5‟-
UUCACUGCCAUAUUCCUUAUUGCCC-3‟. Vehicle and scrambled siRNAs were used as
74
controls. The scrambled sequences were 5‟-GAUCGCAGAUGUUUCUCGCUCGACA-3‟ and
5‟-UGUCGAGCGAGAAACAUCUGCGAUC-3‟. To examine the effect of the siRNAs on
ASAP1 expression, PC-3 cells were plated in 6-well plates in antibiotic-free RPMI-1640. After
20 hours, the cells were transfected with 60 nmol/L siRNA in LipofectamineTM 2000 reagent
following the manufacturer‟s instructions. Briefly, a mixture of Lipofectamine TM 2000 and
siRNA in Opti-MEM (500 µl) was gently added to each well. After 8 hours, the transfection
mixture
was
removed
and
fresh
antibiotic-free
RPMI-1640
was
added.
Vehicle
(LipofectamineTM2000) and scrambled siRNA were applied in separate wells. Following 72
hours incubation, the PC-3 cells were harvested for western blot analysis, scratch wound healing
and matrigel invasion assays.
4.2.4. Generation of the lentiviral constructs
cDNAs for human ASAP1 were generously provided by Dr. Hisataka Sabe (Osaka
Bioscience Institute, Suita, Osaka, Japan). shRNA oligos targeting ASAP1 and negative control
oligos
were
purchased
from
Invitrogen.
shRNA
oligos
were:sh-ASAP1-1,
5‟-
TGCTGTTAAGTCTCGGAGTGCAGTTAGTTTTGGCCACTGACTGACTAACTGCACCGA
GACTTAA-3‟and5‟CCTGTTAAGTCTCGGTGCAGTTAGTCAGTCAGTGGCCAAAACTAACTGCACTCCGAG
ACTTAAC-3‟;
sh-ASAP1-2,
5‟-
TGCTGTTCTGAGGTAGTTTAGGAAGAGTTTTGGCCACTGACTGACTCTTCCTACTACC
and
TCAGAA-3‟
5‟-
CCTGTTCTGAGGTAGTAGGAAGAGTCAGTCAGTGGCCAAAACTCTTCCTAAACTACC
TCAGAAC-3‟;
sh-control,
75
5‟-
TGCTCGAGACCGAATTCTAGAGGGCCCGGTACCACTAGTTAATTAATCGATACTAGT
CTGCAGCTAGCGGCGCGCCTCTAGAGAATTCGGTCTCA-3‟
and
5‟-
CCTGTGAGACCGAATTCTCTAGAGGCGCGCCGCTAGCTGCAGACTAGTATCGATTAA
TTAACTAGTGGTACCGGGCCCTCTAGAATTCGGTCTCG-3‟.
For ASAP1 knockdown experiment, oligonucleotide pairs were inserted into the
pcDNA6.2™GW/EmGFP-miR vector (Invitrogen) and subcloned to pLC-EF1A-DEST
destination vector, which contains elongation factor 1 alpha (EF1A) promoter, to generate the
lentiviral expression clones, pLC-EF1A-control, pLC-EF1A-sh-ASAP1-1 and pLC-EF1A-shASAP1-2. For the overexpression experiment, ASAP1 and ASAP1b coding sequences were
cloned into pENTR2B vector (Invitrogen). KOZAC sequences were amplified by using primers
that incorporate an EcoRI site and a DraIII site and were ligated in upstream of ASAP1 and
ASAP1b coding sequence. Sequences of recombinant ASAP1 and ASAP1b were confirmed by
full length sequencing. The recombinant ASAP1 and ASAP1b were subcloned into pLG-ADEST destination vector, which expresses the gene of interest driven by the ARR2PB promoter
and also expresses eGFP driven by the ubiquitin-C promoter as a fluorescent marker, to generate
the androgen-regulated lentiviral expression vectors, pLG-PP-ASAP1 and pLG-PP-ASAP1b.
4.2.5. Virus production and transductions
One 10 cm dish was seeded with 4×106 293T cells (obtained from ATCC) from a nonconfluent culture plate in 10 ml DMEM (Invitrogen), supplemented with 10 % FBS (Invitrogen)
in antibiotic-free media. The following day, the cells were cotransfected by the calcium
phosphate precipitation method according to the manufacturer‟s instructions (Promega
Profection Mammalian Transfection System, Promega) with 10 µg lentiviral vector, 7.5 µg
76
pCMV Δ8.91, and 2.5 µg pVSV-G. 12 to 16 hours later, the cells were washed with 5 ml PBS
and 5 ml DMEM containing 10% FBS. The supernatant was collected after 24 and 48 hours and
filtered through a 0.45 µm filter (SE1M00300, Millipore) to remove debris. The supernatant
containing the virus was stored at 4ºC for a maximum of two days and then moved to –80ºC for
long term storage.
For lentiviral transduction, cells were seeded in 6-well plates at a density of 1×105 in 2 ml.
After 24 hours, the media was replaced with 0.5 ml virus stock mixed with 0.5 ml tissue culture
medium containing 8 μg/ml polybrene. The medium was changed 16 hours after infection and
the EGFP-positive cells were checked after 48 hours under a fluorescence microscope.
4.2.6. Western blotting
Cells growing on a 6-well plate were harvested by scraper and protein lysates were
prepared using modified RIPA buffer (1% NP-40, 0.5% sodium deoxycholic acid) supplemented
with a protease inhibitor cocktail (Roche, Basel, Switzerland). Total lysate protein was
determined using the BCA protein assay (Pierce, Rockford, IL). Typically, 5 µg of proteins were
separated by electrophoresis through 7.5% SDS polyacrylamide gels and transferred to PVDF
membranes (Immobilon-P, Millipore, Billerica, MA). Membranes were incubated with mouse
anti-ASAP1 monoclonal primary antibody (BD Biosciences, San Jose, CA) or rabbit anti-actin
polyclonal primary antibody (Sigma) for 1 hour at room temperature. After washing and
incubation with secondary antibodies, bands were visualized on autoradiography film by ECL
(SuperSignal West Femto Maximum Sensitivity Substrate, Pierce).
77
4.2.7. In vitro cell proliferation assay
Cells were seeded in 96-well plates (~1500 cells per well). Cell proliferation was
assessed by methylthiazolyldiphenyl-tetrazolium (MTT) assay every 24 hours. For the MTT
assay, 10 μl MTT (5 mg/ml in PBS) was added to each well containing 100 μl media for a 4-hour
incubation at 37 °C. 100 μl 20% SDS was added to each well to solubilize the dye. Absorbance
was determined at 570 nm using a plate reader. Experiments were performed in triplicate.
4.2.8. Scratch wound healing migration assay
PC-3 cells were seeded into 6-well culture plates using their regular maintenance
medium. After the cells reached confluence, the medium was removed and a plastic pipette tip
was drawn across the centre sections of the wells to produce clean ~1-mm-wide open areas
(wounds) in the monolayers. Photographs were taken immediately and after 24 hours of further
incubation at 37°C in RPMI-1640 medium with reduced serum content (0.1% FBS). Cellrecovered areas at 24 hours were measured to estimate the extent of cell migration. Data are
presented as percentages calculated by normalizing the values obtained for the control cells as
100%.
4.2.9. Matrigel invasion assays
Assays were performed using modified Boyden chambers consisting of 8 µm pore filter
inserts in 24-well plates (BD Biosciences, San Jose, CA). Cells in serum-free RPMI-1640
medium were plated (7.5x104/well) on Matrigel-coated and uncoated membranes of the upper
compartments and incubated at 37°C in a CO2 incubator, using RPMI-1640 containing 5% FBS
in the lower chambers as a chemoattractant. After 22 hours the inserts were pulled out and the
78
remaining, non-invading cells on the upper surface removed with a cotton swab. The cells on the
lower surface of the membrane were fixed in methanol, air-dried and stained with 0.1% crystal
violet for 10 minutes. The cells on each membrane were counted in five fields (at 200x
magnification) using a light microscope. Tumor cell invasion index was taken as the percentage
of the number of cells that had passed through the Matrigel-coated membranes relative to the
number of cells that had passed through the uncoated membranes. Data are presented as
percentages calculated by normalizing the values obtained for the untreated cells as 100%.
4.2.10. In vivo orthotopic metastatic assay
Cells were trypsinized from 10 cm dishes and resuspended with collagen at a
concentration of 3×106/100 μl. Collagen gel pellets containing cells (6×105/20 μl) were dropped
onto 10 cm dishes and incubated at 37°C for 30 minutes before grafting. The grafting procedure
is the same as described before (Wang et al., 2005b). In brief, two pellets were grafted into
anterior prostates of mice and, after 8 weeks, mice were killed for gross examination of lymph
nodes. In addition, lymph nodes, lungs, livers, kidneys, spleens and bone (femur) of the hosts
were fixed for examination of metastases using histological and immunohistochemical
techniques.
4.2.11. Histopathological and immunohistochemical staining
Preparation of paraffin-embedded tissue sections and immunohistochemical analyses
were carried out as previously described (see Chapter 2). Mouse monoclonal anti-Ki67 primary
antibody was obtained from Dako (Carpinteria, CA). Biotinylated anti-mouse secondary
antibody was obtained from Amersham International (Arlington Heights, IL). All tissue sections
79
were lightly counterstained with 5% (w/v) Harris hematoxylin. Control sections were processed
in parallel with mouse non-immune IgG (Dako) used at the same concentrations as the primary
antibody.
4.2.12. Statistical analysis
Data were presented as mean ± SD. Different values among groups were compared using
a two-tailed unpaired Student's t test. Statistical significance in this study was set as P≤0.05.
4.3.
RESULTS
4.3.1. Knockdown of ASAP1 protein by siRNA decreases PC-3 cell migration and
invasion
In vitro scratch wound-healing and cell invasion assays were used to examine the effect
of reduced ASAP1 protein expression on migration and tissue invasion of PC-3 cells. These
human prostate cancer cells, commonly used to represent advanced prostate cancer, were
employed since they are apparently more invasive and metastatic than, e.g., LNCaP cells
(Hoosein et al., 1991), and were found to express ASAP1 protein more highly than LNCaP cells
(Fig. 4.2A). Reduction of ASAP1 expression in PC-3 cells was obtained by transfection of the
cells with ASAP1-targeting siRNAs. As shown by Western blot analysis, ASAP1 protein
expression was markedly reduced 72 hours after transfection with siRNA 1 and 2, in contrast to
cells transfected with the vehicle (lipofectamineTM2000) or scramble siRNA (Fig. 4.2B). In the
wound-healing assays, the scramble siRNA-treated control cell cultures showed similar healed
wound areas as vehicle-treated cultures during a 24-hour period. In contrast, the cultures treated
80
Figure 4.2. Effects of siRNA-reduced ASAP1 protein expression on cell migration and matrigel
invasiveness of PC-3 cells. A. Western blot showing ASAP1 protein expression in PC-3 cells is higher
than that in LNCaP cells. B. Western blot showing reduction of ASAP1 protein content in PC-3 cells
transfected with either siRNA1 or 2, targeting the ASAP1 gene, in contrast to vector- and scrambletreated cells. C. Healed scratch wound areas in monolayers of siRNA-transfected PC-3 cells are
significantly smaller than those of vector-treated cultures 24 hours after scratching (P <0.01). D. siRNAinduced reduction of ASAP1 expression resulted in a markedly decrease of relative invasive ability in
siRNA-transfected PC-3 cells compared with vector-treated cultures (29.5±14.5%, 29.8±12.6%%,
respectively, P <0.01); data are expressed as mean ± SD.
81
with ASAP1-targeting siRNAs 1 and 2, showed significantly smaller healed wound areas
(49.2±13.7% and 49.9±17.6%, respectively) compared to vector-treated cultures (P < 0.01; Fig.
4.2C). In the cell invasion assay, reduction of ASAP1 expression by siRNA resulted in a
markedly decreased cell invasive ability (29.5±14.5% and 29.8±12.6% in siRNA1- and siRNA2treated cultures, respectively) compared to vector-treated cultures (Fig. 4.2D).
4.3.2. Effect of reduced ASAP1 expression on in vitro matrigel invasion and in
vivo metastatic ability of PC-3 cells stably transduced with shRNA
Stable ASAP1-knockdown PC-3 cells were generated by transducing PC-3 cells with
lentivirus carrying ASAP1-targeting shRNA sequences. Transduction efficiency was determined
by checking EmGFP-positive cells under a fluorescence microscope (Fig. 4.3A). Stable PC-3
cells that were transfected with a control viral vector (PC-3-sh-control) expressed similar levels
of endogenous ASAP1 protein as parental PC-3 cells. In contrast, cells that were transfected with
ASAP1-targeting viral vectors (PC-3-sh-ASAP1-1 and PC-3-sh-ASAP1-2) showed significantly
decreased ASAP1 expression (Fig. 4.3B). ASAP1 knockdown in single-cell clones of PC-3 cells
were confirmed and a pool of several single-cell clones was used in subsequent experiments to
avoid use of cells that had integrated non-functioning shRNA insertions. As shown by MTT
assay, ASAP1 stable knockdown did not affect PC-3 cell growth compared to PC-3-sh-control
and parental cells (Fig. 4.3C). In the cell invasion assay, PC-3-sh-control cells showed similar
invasive ability as parental PC-3 cells. The stable ASAP1-knockdown cells showed a markedly
lower invasive ability (59.0±11.9% and 41.4%±2.6 in PC-3-sh-ASAP1-1 and PC-3-sh-ASAP1-2
cells, respectively) compared to parental cells (Fig. 4.3D).
To study the effect of decreased ASAP1 expression on PC-3 cell metastasis in vivo,
82
Figure 4.3. Effects of stable ASAP1 knockdown on cell invasiveness of PC-3 cells. A. Expression of
EmGFP in lentivirus transfected (green) and parental PC-3 cells inspected under a fluorescence
microscope. B. Western blot showed markedly decreased expression level of ASAP1 protein in PC-3
cells transfected with ASAP1-targeting viral vectors (PC-3-sh-ASAP1-1/2) compared with parental or
vector control PC-3 cells. C. MTT assay showed the similar growth rate of parental, vector control and
stable ASAP1 knockdown PC-3 cells. D, Relative invasive ability of ASAP1 knockdown PC-3 cells is
markedly lower compared with vector control and parental PC-3 cells; data are expressed as mean ± SD.
83
NOD-SCID mice were randomly divided into two groups (ten mice per group), and collagen
pellets containing stable PC-3-sh-control and PC-3-sh-ASAP1-1 cells were grafted
orthotopically into the prostate of each mouse. After 8 weeks, mice grafted with PC-3-sh-control
cells had formed primary tumors in the prostate glands and metastatic tumors in local and distal
lymph nodes (Fig. 4.4 A). In addition, in 6 out of 10 mice, presence of metastases was identified
by histopathological examination in other organs such as lung and kidney (Fig. 4.4 C, E). In
contrast, the mice grafted with the PC-3-sh-ASAP1-1 cells had developed tumors that were
largely confined to the prostate gland, with some metastases found in local lymph nodes and
rarely in distal lymph nodes (Fig. 4.4B). The number of lymph node metastases in the mice of
the PC-3-sh-ASAP1-1 group was much lower than that in the control group (P<0.01, Table 4.1).
In addition, no apparent metastatic foci were found in any of the other organs examined (Fig.
4.4D, F).
4.3.3. Effect of ASAP1 overexpression on invasiveness of LNCaP cells
LNCaP cells were transfected with lentivirus carrying full coding sequences of ASAP1 or
ASAP1b to generate cells that stably overexpressed ASAP1 or ASAP1b protein. Transduction
efficiency was determined by checking GFP-positive cells under a fluorescence microscope (Fig.
4.5A). LNCaP cells stably transfected with control vectors (LNCaP-lv-control), did not show
detectable endogenous ASAP1 expression, similar to parental LNCaP cells. In contrast, cells
transfected with ASAP1 expression vectors (LNCaP-lv-ASAP1 and LNCaP-lv-ASAP1b)
showed overexpression of ASAP1 at a level similar to that of PC-3 cells (Fig. 4.5B). As shown
by MTT assay, ASAP1 or ASAP1b stable overexpression did not affect LNCaP cell growth
compared to LNCaP-lv-control and parental cells (Fig. 4.5C). In the cell invasion assay,
84
Figure 4.4. Effects of stable ASAP1-knockdown on metastatic activity of PC-3 cells in NOD-SCID mice.
PC-3-sh-control and PC-3-sh-ASAP1-1 were grafted into ventral prostates of NOD-SCID mice (orthotopic
site). After 8 weeks, large, hardened lymph nodes were observed in the mice carrying PC-3-sh-control
cells in local and distal lymph nodes (A, arrows); the metastasis in distal organ, e.g. lung, and containing
proliferative cancer cells, were identified by H&E staining and IHC staining using specific, anti-human ki67
antibody (C, E, arrows). In contrast, mice bearing ASAP1-knockdown tumors showed a much lower
number of enlarged, metastases-containing lymph nodes (B, arrow and Table 4.2); no apparent
metastatic foci were found in distal organs, e.g. lung (D, F).
85
Table 4.1. Decreased metastasis of PC-3 cells in vivo by reduction of ASAP1 expression
Group
volume of primary
tumor (mm3)
number of lymph
node>2mm
PC-3-sh-control
1175.1±269.5
75 (n=10) *
PC-3-sh-ASAP1-1
1564.5±384.2
38 (n=8) +
*
p value
Metastases were found in lumbar, renal, liver, pancreatic and omentum lymph nodes.
+ Metastases were found in lumbar and renal lymph nodes only.
86
<0.01
Figure 4.5. Effects of stable ASAP1 protein overexpression on cell invasiveness of LNCaP cells. A.
Expression of GFP in lentivirus transfected (green) and parental LNCaP cells inspected under a
fluorescence microscope. B. Western blot showing ASAP1 protein overexpressed in LNCaP cells
transfected with lentivirus carrying either ASAP1 (125 kDa) or ASAP1b (120 kDa) coding sequence
compared with parental LNCaP cells and PC-3 cells. C. MTT assay showed the similar growth rate of
parental, vector control and ASAP1 or ASAP1b stably overexpressed LNCaP cells. D. Relative invasive
ability of ASAP1 overexpressed LNCaP cells is similar to those of vector control or parental LNCaP cells;
data are expressed as mean ± SD.
87
LNCaP-lv-ASAP1 and LNCaP-lv-ASAP1b cells did not show significantly increased invasive
ability compared with LNCaP-lv-control and parental cells (Fig. 4.5D).
4.4.
DISCUSSION
Tissue invasion and metastasis are two major hallmarks of malignancy (Hanahan and
Weinberg, 2000). As previously found, there is a good correlation between elevated ASAP1
protein expression and prostate cancer metastasis in clinical samples. In the present study,
suppression of ASAP1 protein expression by ASAP1-targeting siRNAs and lentiviral vectors
markedly reduced cell migration of PC-3 cells, their tissue invasive ability in vitro and their
metastasis in vivo. Based on a literature survey, this is the first time that a role for ASAP1 in
prostate cancer has been reported. The results obtained are consistent with findings by Onodera
and colleagues that a lowering of ASAP1 protein levels reduced migration and tissue invasion of
breast cancer cells in vitro (Onodera et al., 2005). In contrast, another group has reported that
reduction of ASAP1 expression had no effect on migration or tissue invasion of cultured breast
cancer cells using the same cell lines (Inoue et al., 2008). At present, it is not clear what the
explanations are for the discrepancy between the observations of the two groups, but it may be
speculated that it is based on subtle differences in experimental conditions, in particular
differences in the siRNA sequences used. In the present study, the two siRNA and two shRNA
sequences targeted different regions of ASAP1 mRNA. The marked reduction of tissue invasion
by all four different sequences, compared to control/scramble sequences, supports the notion that
the suppression of tissue invasion by PC-3 prostate cancer cells was not due to off-target effects,
but rather a result of specific reduction of ASAP1 protein expression.
88
Tissue invasion in vitro has been linked to the formation and function of specialized
cellular structures, i.e. invadopodia (Buccione et al., 2009; Stylli et al., 2008). They are
responsible for focal degradation of underlying substrate. These proteolytically active plasma
membrane protrusions are considered to be important for tissue invasion and metastasis in the
majority of studies performed with cancer cell lines (Artym et al., 2006; Kelly et al., 1998;
Mueller et al., 1999). It was recently reported that PC-3 cells also use invadopodia for tissue
invasion; their formation is coordinated with localization of MMP-9 and focal degradation of the
cellular matrix during the invasion process (Desai et al., 2008). Consistent with a function in
tissue invasion, ASAP1 protein was found in invadopodia of breast cancer cells and in analogous
structures (podosomes) in src-transformed fibroblasts, and shown to be required for the
formation of the structures (Bharti et al., 2007; Onodera et al., 2005). Together, these findings
suggest that ASAP1 may control PC-3 tissue invasion via regulation of the formation and
function of invadopodia.
Two splice variants of ASAP1 have been identified in human, ASAP1 and ASAP1b; the
only structural difference between ASAP1 and ASAP1b is that the latter lacks the 3rd to 6th
proline-rich sequences. It has been reported that ASAP1 or both variants function in tissue
invasion by forming a trimeric protein complex with cortactin through its proline-rich sequences
and paxillin through its SH3 domain in breast cancer (Bharti et al., 2007; Hashimoto et al., 2006;
Onodera et al., 2005). It is not unlikely that a complex of ASAP1 and cortactin also plays a role
in tissue invasion of prostate cancer cells. However, in the present study, overexpression of
neither ASAP1 nor ASAP1b led to significant increases in tissue invasion of poorly invasive
LNCaP cells. Interestingly, it was observed that paxillin protein expression in LNCaP cells is
much lower than that in PC-3 cells (Posadas et al., 2009), while cortactin was found to be present
89
in both PC-3 and LNCaP cells at about the same level. This suggests that the LNCaP cells are
deficient in certain molecules, other than ASAP1, that are required for tissue invasion. In
addition, it has been reported that tissue invasion is dependent on extracellular matrix (ECM)
degradation activity of matrix metalloprotease (MMP) associated with invadopodia. MT1-MMP,
a membrane-type MMP molecule, is considered as a master regulator of invadopodia activity and
protease-mediated tissue invasion of a number of cell lines (Clark et al., 2007; Nakahara et al.,
1997). In prostate cancer cells, MT1-MMP protein and mRNA were expressed in PC-3 cells. In
contrast, LNCaP cells showed no detectable MT1-MMP protein expression and only very low
levels of MT1-MMP mRNA expression (Jung et al., 2003; Nagakawa et al., 2000). This suggests
that while ASAP1 is likely an important factor in prostate cancer invasion and metastasis, its
overexpression is in hindsight not likely to lead to increased tissue invasiveness if other
metastasis-related proteins are absent. In view of this, the overexpression of ASAP1 or/and cooverexpression of its related proteins in cell lines with different genetic background may be
helpful to clarify its role in cancer invasion and metastasis. In addition, the androgen regulated
lentiviral vector overexpressing ASAP1, driven by the probasin promoter, provides a useful tool
for prostate-conditional overexpression of ASAP1 in the mouse. Prostate-specific overexpression
of ASAP1 in established transgenic/knockout mouse models, such as prostate-conditional PTEN
knockout mice, may provide a better understanding of the role of ASAP1 in prostate cancer
invasion and metastasis.
In summary, the findings in this study suggest that ASAP1 plays a role in prostate cancer
invasion and metastasis and may be used as a therapeutic target for prostate cancer metastasis.
Overexpression of ASAP1 may be required, but is not sufficient to enhance cell invasion and
metastasis in prostate cancer. Further studies on the role of ASAP1 in invadopodia and its
90
synergistic effect with other related and binding proteins will provide a better understanding of
the molecular mechanisms of ASAP1 controlling tissue invasion and metastasis in prostate
cancer.
91
Chapter 5
SUMMARY AND SPECULATIONS
Understanding the cellular and molecular mechanisms underlying prostate cancer
metastasis is important for development of predictive markers and identification of new
therapeutic targets. Proper strategy and access to clinically relevant models are essential to
achieve this goal. To circumvent problems arising from tumor heterogeneity, one of the major
hurdles in metastasis research, a number of cancer sublines with different metastatic abilities
were developed from one patient‟s primary cancer tissue. Chromosomal aberrations in a
metastatic subline were used to identify the presence of cells with metastatic potential in the
primary tumor; the results indicate that metastatic ability of a tumor can be associated with a
small cancer subpopulation and not necessarily predominant subpopulation. By differential gene
expression analysis of metastatic and non-metastatic sublines a novel prostate cancer metastasisassociated gene, ASAP1, was identified. Analyses using experimental and clinical samples
indicated that ASAP1 has a significant role in prostate cancer invasion and metastasis.
Tumor heterogeneity is a major hurdle for identification of metastasis-associated genes
via comparative analysis of clinical primary and metastatic prostate cancer tissues. To
circumvent this problem, a number of sublines from one patient‟s primary prostate cancer
specimen were developed as described in Chapter 2 aimed at generating relatively pure
metastatic and non-metastatic sublines. The use of subrenal capsule grafting methodology
minimized loss of cancer subpopulations as suggested by very high engraftment rates (>90%)
92
and in view of superior nutrient supply at the graft site used. The significant differences in
growth rate and karyotype of the sublines are consistent with the widely accepted heterogeneous
nature of prostate cancers. Importantly, the sublines showed marked differences in local tissue
invasiveness and metastatic ability as indicated by an in vivo metastatic assay. This provides
functional evidence of the presence in human primary prostate cancers of subpopulations with
different metastatic potential.
It is still controversial whether metastatic potential of primary tumors is associated with a
minority or with the bulk of the cancer cells. Using chromosomal aberrations that were unique
for a metastatic subline as a marker, it was found that metastatic potential was associated with
only a small number of cancer cells in the primary prostate cancer tissue. This suggests that
metastatic potential of primary tumors can be associated with a minority of cells rather than with
the bulk of the tumor as suggested by the clonal selection hypothesis.
Comparing sublines with different metastatic potential derived from the same patient‟s
multifocal primary tumor tissue appears to form a good strategy for identifying predictive
metastatic markers. However, the matched tumor tissue lines (LTL-220M, LTL-220N and LTL221N) derived from only one patient‟s primary tumor likely do not fully represent the disease.
Some genetic alterations observed in the metastatic subline (LTL-220M) may not be functionally
linked to prostate cancer metastasis in the general population. For example, the particular marker
used in this study, e.g. PTEN, was selected only because it is localized in the 10q region. It likely
is only useful for indicating subgroups of cancer cells for the particular patient, and not suitable
as a general marker for prostate cancer metastasis, since gain, rather than loss of PTEN, is
usually observed in this process. Studies based on more paired patient-derived metastatic and
non-metastatic cancer sublines are likely to provide a better coverage of the various cancer
93
subpopulations in heterogeneous clinical specimens. Common metastatic signatures in multiple
metastatic tumor sublines should provide good candidates for predictive metastatic markers.
The paired metastatic and non-metastatic sublines generated in this study are (1)
established from one patient‟s primary tumor tissue using the same micro-environment (subrenal
capsule); (2) quite clinically relevant as they are derived from cancer tissues rather than from
cultured cells and as the establishment procedure was carried out in vivo under optimal
nutritional conditions. In view of this, it is likely that genes, found to be differentially expressed
in the sublines, will include some with critical roles in metastasis. Further analysis of DNA
alterations and differential RNA expressions in matched sublines may lead to identification of
suitable markers to identify metastatic potential in primary tumors, essential for better prediction
of prostate cancer progression and disease management.
In Chapter 3, ASAP1 was identified as a novel prostate cancer metastasis-associated gene
by comparison of gene expressions of the metastatic PCa1-met and non-metastatic PCa2 sublines
that had been derived from another patient‟s primary prostate cancer. The level of ASAP1
protein expression significantly increased progressively in both clinical specimens going from
benign to malignant to metastatic conditions. This phenomenon is consistent with observations in
breast cancer and uveal melanoma studies. Notably, the same expression pattern is also observed
in subrenal capsule xenografts of benign, non-metastatic and metastatic cancer tissues, which
provides evidence that this experimental system is relevant to the clinical situation. The
correlation of strong ASAP1 expression in primary tumors with metastasis and PSA recurrence
suggests that increased ASAP1 expression is linked to aggressiveness and metastatic potential of
primary prostate cancers.
94
It should be noted that only 37 out of 66 cases of the patient cohort have been followed
up and that only 4 out of the 37 cases (10.8%) had PSA recurrence in this study which is lower
than other reported PSA recurrence rates following radical prostatectomy. Although there is a
significant association of high ASAP1 expression with metastasis and poor outcome, studies
involving larger patient cohorts with longer follow-up will be necessary to establish whether
strong ASAP1 expression in primary tumors can be used as a predictive metastatic marker.
Gain of the 8q region has been reported as one of the most common chromosomal
alterations in prostate cancer tissue. It has also been reported to correlate with metastatic
progression and poor prognosis of the disease. As such, it is of major interest that the ASAP1
gene has been mapped to chromosomal location 8q24.21. The results of the present study
indicate that copy number gain of the ASAP1 gene is likely a common event in primary prostate
cancer (57.9%), but a significant correlation between increased ASAP1 protein expression and
gain of ASAP1 copy number was not observed. Similarly, copy number gain of the gene has not
been found for breast cancers highly expressing ASAP1 (Onodera et al., 2005). On the other
hand, gain of chromosome 8q correlated strongly with expression of ASAP1 mRNA and protein
in uveal melanoma (Ehlers et al., 2005). Thus, the genetic alteration and the mechanisms
involved in ASAP1 overexpression may be different for various types of cancer. The
transcriptional and post-transcriptional regulation of ASAP1 expression is not clear. Recently, it
has been reported that 5‟-UTR of ASAP1 mRNA exhibits an internal ribosomal entry site (IRES)
activity in differentiated monocytes but not in breast cancer cells with elevated ASAP1 protein
levels (Miyata et al., 2008). Studies on IRES-dependent ASAP1 expression in prostate cancer
will be helpful to clarify the mechanisms of increased ASAP1 expression in prostate cancer.
95
Tissue invasion and metastasis are two major hallmarks of malignancy. The role of
ASAP1 in prostate cancer tissue invasion and metastasis was further investigated by in vitro and
in vivo functional assays as described in Chapter 4. Suppression of ASAP1 protein expression by
ASAP1-targeting siRNAs and lentiviral vectors markedly reduced cell migration of PC-3 cells,
their tissue invasive ability in vitro and their metastasis in vivo. This suggests that ASAP1 plays
a role in prostate cancer cell invasion and metastasis and may be used as a therapeutic target for
prostate cancer metastasis. Based on a literature survey, this is the first time that a role for
ASAP1 in prostate cancer has been reported.
ASAP1 was originally reported as an ArfGAP to exhibit efficient GTPase-activating
protein (GAP) activities against Arf1 and Arf5, but very weak activity against Arf6 (Brown et
al., 1998; Furman et al., 2002). ASAP1 was recently implicated in tissue invasion and was
reported to be important for the assembly and function of invadopodia, dynamic actin-based
structures essential in the degradation and penetration of the extracellular matrix by metastatic
cancer cells. Both Arf1 and Arf6 activities have been reported to be involved in invadopodia
function (Furman et al., 2002; Hashimoto et al., 2004). The GAP activity of ASAP1 against Arfs
might regulate the secretory processes mediating transport of matrix proteases to the sites of
invadopodia. On the other hand, there is evidence that ASAP1, independent of its GAP activity,
may be involved in the formation and function of invadopodia and tumor invasion. It has been
reported that ASAP1 can form a complex with paxillin and cortactin, key components of
invadopodia in breast cancer. Furthermore, knockdown of ASAP1 or disruption of the complex
inhibited the formation of invadopodia, or related structures called podosomes, and invasion of
cells through matrigel (Bharti et al., 2007; Onodera et al., 2005). Importantly, GAP activity of
ASAP1 appears to be dispensable for invadopodia and podosomes formation; the
96
phosphorylation of ASPA1 by src and intact SH3 domain may be required for the formation of
podosomes (Bharti et al., 2007). ASAP1 can be recruited by GTP-Arf6 to sites of GTP-Arf6
activation (plasma membrane and cytoplasmic vesicles) and colocalizes with Arf6 at
invadopodia without immediate hydrolysis of Arf6 (Hashimoto et al., 2005; Onodera et al.,
2005). Recently the GEP100, a GEF of Arf6, was linked to epidermal growth factor receptor
(EGFR) signaling-regulated breast cancer invasion (Morishige et al., 2008). These studies
suggest that ASAP1 could act as an effector of GTP-Arf6 and play a role in invadopodia
formation and cancer invasion as a scaffold/adaptor protein.
A recent study by another group has demonstrated that invadopodia are associated with
tissue invasion by matrix degradation in prostate cancer (Desai et al., 2008). For future studies, it
is important to clarify the precise molecular mechanisms involved in ASAP1-mediated
invadopodia formation and function in prostate cancer. Further studies on the interaction of
ASAP1 and its related proteins, such as Arf1 and Arf6, their coordination in prostate cancer
invasion and regulation of upstream signaling, may lead to a better appreciation of the role of
ASAP1 in tissue invasion and metastasis of prostate cancer. Studies focusing on ASAP1 and
related proteins in clinical prostate cancer samples should provide a better understanding of their
roles in prostate cancer invasion and metastasis.
The finding that ASAP1 has a role in prostate cancer metastasis suggests that the
approach used to identify metastasis-associated genes by comparison of gene expressions of
paired metastatic and non-metastatic sublines derived from the same patient‟s primary cancer
tissue is valid. Cancer progression, including metastasis, is thought to involve multiple genetic
and epigenetic changes. The metastasis cascade is apparently not controlled by a single gene, but
rather by a set of genes. In this study, only differentially expressed genes in cancer cells, i.e.
97
human genes rather than those of the host, i.e. mouse genes, were analyzed and only the ASAP1
gene was further studied after SAGE analysis. In fact, a set of differentially expressed human
genes, linked to prostate cancer metastasis, has recently been identified in our laboratory. Further
analysis of differentially expressed mouse genes will likely be valuable for a better
understanding of epithelial-stromal interactions in prostate cancer metastasis. Together, the
studies may lead to a better insight into the mechanisms underlying prostate cancer metastasis
and provide novel predictive metastatic markers and therapeutic targets for the disease.
98
REFERENCES
AJCC 6th edition (2002) and UICC 6th edition.
Canadian Cancer Society/National Cancer Institute of Canada. Canadian Cancer
Statistics http://www.cancer.ca
King R.J.B. (2000). Cancer Biology, 2nd Edition, Pearson Education Limited, England.
Pierce G.B. (1998). The Biogical Basis of Cancer. MKinnell, Parchment, Perantoni and
Pierce (eds). Cambridge university Press, New York, USA. .
Public Health Agency of Canada. Cancer Surveillance Online http://dsol-smed.phacaspc.gc.ca/dsol-smed/cancer.
Abate-Shen C, Banach-Petrosky WA, Sun X, Economides KD, Desai N, Gregg JP et al
(2003). Nkx3.1; Pten mutant mice develop invasive prostate adenocarcinoma and
lymph node metastases. Cancer Res 63: 3886-90.
Arora R, Koch MO, Eble JN, Ulbright TM, Li L, Cheng L (2004). Heterogeneity of
Gleason grade in multifocal adenocarcinoma of the prostate. Cancer 100: 2362-6.
Artym VV, Zhang Y, Seillier-Moiseiwitsch F, Yamada KM, Mueller SC (2006). Dynamic
interactions of cortactin and membrane type 1 matrix metalloproteinase at invadopodia:
defining the stages of invadopodia formation and function. Cancer Res 66: 3034-43.
Arya M, Patel HR, McGurk C, Tatoud R, Klocker H, Masters J et al (2004). The
importance of the CXCL12-CXCR4 chemokine ligand-receptor interaction in prostate
cancer metastasis. J Exp Ther Oncol 4: 291-303.
Autzen P, Robson CN, Bjartell A, Malcolm AJ, Johnson MI, Neal DE et al (1998). Bone
morphogenetic protein 6 in skeletal metastases from prostate cancer and other common
human malignancies. Br J Cancer 78: 1219-23.
Bacac M, Stamenkovic I (2008). Metastatic cancer cell. Annu Rev Pathol 3: 221-47.
Bachmann IM, Halvorsen OJ, Collett K, Stefansson IM, Straume O, Haukaas SA et al
(2006). EZH2 expression is associated with high proliferation rate and aggressive tumor
subgroups in cutaneous melanoma and cancers of the endometrium, prostate, and
breast. J Clin Oncol 24: 268-73.
Bandyopadhyay S, Zhan R, Chaudhuri A, Watabe M, Pai SK, Hirota S et al (2006).
Interaction of KAI1 on tumor cells with DARC on vascular endothelium leads to
metastasis suppression. Nat Med 12: 933-8.
99
Baricos WH, Reed JC, Cortez SL (2003). Extracellular matrix degradation by cultured
mesangial cells: mediators and modulators. Exp Biol Med (Maywood) 228: 1018-22.
Barry M, Perner S, Demichelis F, Rubin MA (2007). TMPRSS2-ERG fusion
heterogeneity in multifocal prostate cancer: clinical and biologic implications. Urology
70: 630-3.
Bayani J, Squire JA (2004). Preparation of cytogenetic specimens from tissue samples.
Curr Protoc Cell Biol Chapter 22: Unit 22 2.
Beider K, Abraham M, Begin M, Wald H, Weiss ID, Wald O et al (2009). Interaction
between CXCR4 and CCL20 pathways regulates tumor growth. PLoS One 4: e5125.
Bellezza I, Aisa MC, Palazzo R, Costanzi E, Mearini E, Minelli A (2005). Extracellular
matrix degrading enzymes at the prostasome surface. Prostate Cancer Prostatic Dis 8:
344-8.
Bentley H, Hamdy FC, Hart KA, Seid JM, Williams JL, Johnstone D et al (1992).
Expression of bone morphogenetic proteins in human prostatic adenocarcinoma and
benign prostatic hyperplasia. Br J Cancer 66: 1159-63.
Bernards R, Weinberg RA (2002). A progression puzzle. Nature 418: 823.
Bharti S, Inoue H, Bharti K, Hirsch DS, Nie Z, Yoon HY et al (2007). Src-dependent
phosphorylation of ASAP1 regulates podosomes. Mol Cell Biol 27: 8271-83.
Bhowmick NA, Moses HL (2005). Tumor-stroma interactions. Curr Opin Genet Dev 15:
97-101.
Birkedal-Hansen H, Moore WG, Bodden MK, Windsor LJ, Birkedal-Hansen B, DeCarlo
A et al (1993). Matrix metalloproteinases: a review. Crit Rev Oral Biol Med 4: 197-250.
Bogenrieder T, Herlyn M (2003). Axis of evil: molecular mechanisms of cancer
metastasis. Oncogene 22: 6524-36.
Bostwick DG, Ramnani D, Qian J (2000). Prostatic intraepithelial neoplasia: animal
models 2000. Prostate 43: 286-94.
Bostwick DG, Shan A, Qian J, Darson M, Maihle NJ, Jenkins RB et al (1998).
Independent origin of multiple foci of prostatic intraepithelial neoplasia: comparison with
matched foci of prostate carcinoma. Cancer 83: 1995-2002.
Brown MT, Andrade J, Radhakrishna H, Donaldson JG, Cooper JA, Randazzo PA
(1998). ASAP1, a phospholipid-dependent arf GTPase-activating protein that associates
with and is phosphorylated by Src. Mol Cell Biol 18: 7038-51.
100
Bryant RJ, Cross NA, Eaton CL, Hamdy FC, Cunliffe VT (2007). EZH2 promotes
proliferation and invasiveness of prostate cancer cells. Prostate 67: 547-56.
Bryden AA, Hoyland JA, Freemont AJ, Clarke NW, Schembri Wismayer D, George NJ
(2002). E-cadherin and beta-catenin are down-regulated in prostatic bone metastases.
BJU Int 89: 400-3.
Buccione R, Caldieri G, Ayala I (2009). Invadopodia: specialized tumor cell structures
for the focal degradation of the extracellular matrix. Cancer Metastasis Rev 28: 137-49.
Buccione R, Orth JD, McNiven MA (2004). Foot and mouth: podosomes, invadopodia
and circular dorsal ruffles. Nat Rev Mol Cell Biol 5: 647-57.
Bunt SK, Yang L, Sinha P, Clements VK, Leips J, Ostrand-Rosenberg S (2007).
Reduced inflammation in the tumor microenvironment delays the accumulation of
myeloid-derived suppressor cells and limits tumor progression. Cancer Res 67: 1001926.
Bussemakers MJ, Van Bokhoven A, Tomita K, Jansen CF, Schalken JA (2000).
Complex cadherin expression in human prostate cancer cells. Int J Cancer 85: 446-50.
Carver BS, Pandolfi PP (2006). Mouse modeling in oncologic preclinical and
translational research. Clin Cancer Res 12: 5305-11.
Cavalcanti-Adam EA, Volberg T, Micoulet A, Kessler H, Geiger B, Spatz JP (2007). Cell
spreading and focal adhesion dynamics are regulated by spacing of integrin ligands.
Biophys J 92: 2964-74.
Chambers AF, Groom AC, MacDonald IC (2002). Dissemination and growth of cancer
cells in metastatic sites. Nat Rev Cancer 2: 563-72.
Chay CH, Cooper CR, Gendernalik JD, Dhanasekaran SM, Chinnaiyan AM, Rubin MA
et al (2002). A functional thrombin receptor (PAR1) is expressed on bone-derived
prostate cancer cell lines. Urology 60: 760-5.
Chellaiah M, Kizer N, Silva M, Alvarez U, Kwiatkowski D, Hruska KA (2000). Gelsolin
deficiency blocks podosome assembly and produces increased bone mass and
strength. J Cell Biol 148: 665-78.
Chellaiah MA (2005). Regulation of actin ring formation by rho GTPases in osteoclasts.
J Biol Chem 280: 32930-43.
101
Chen CT, Gan Y, Au JL, Wientjes MG (1998). Androgen-dependent and -independent
human prostate xenograft tumors as models for drug activity evaluation. Cancer Res
58: 2777-83.
Chen WT (1989). Proteolytic activity of specialized surface protrusions formed at rosette
contact sites of transformed cells. J Exp Zool 251: 167-85.
Chen WT, Wang JY (1999). Specialized surface protrusions of invasive cells,
invadopodia and lamellipodia, have differential MT1-MMP, MMP-2, and TIMP-2
localization. Ann N Y Acad Sci 878: 361-71.
Chen Z, Fan Z, McNeal JE, Nolley R, Caldwell MC, Mahadevappa M et al (2003).
Hepsin and maspin are inversely expressed in laser capture microdissectioned prostate
cancer. J Urol 169: 1316-9.
Chen Z, Trotman LC, Shaffer D, Lin HK, Dotan ZA, Niki M et al (2005). Crucial role of
p53-dependent cellular senescence in suppression of Pten-deficient tumorigenesis.
Nature 436: 725-30.
Cheng L, Song SY, Pretlow TG, Abdul-Karim FW, Kung HJ, Dawson DV et al (1998).
Evidence of independent origin of multiple tumors from patients with prostate cancer. J
Natl Cancer Inst 90: 233-7.
Chung LW, Baseman A, Assikis V, Zhau HE (2005). Molecular insights into prostate
cancer progression: the missing link of tumor microenvironment. J Urol 173: 10-20.
Chung LW, Huang WC, Sung SY, Wu D, Odero-Marah V, Nomura T et al (2006).
Stromal-epithelial interaction in prostate cancer progression. Clin Genitourin Cancer 5:
162-70.
Clark ES, Whigham AS, Yarbrough WG, Weaver AM (2007). Cortactin is an essential
regulator of matrix metalloproteinase secretion and extracellular matrix degradation in
invadopodia. Cancer Res 67: 4227-35.
Clarke NW, Hart CA, Brown MD (2009). Molecular mechanisms of metastasis in
prostate cancer. Asian J Androl 11: 57-67.
Coffey DS (1993). Prostate cancer. An overview of an increasing dilemma. Cancer 71:
880-6.
Cooke DB, Quarmby VE, Mickey DD, Isaacs JT, French FS (1988). Oncogene
expression in prostate cancer: Dunning R3327 rat dorsal prostatic adenocarcinoma
system. Prostate 13: 263-72.
102
Cooper CR, Chay CH, Pienta KJ (2002). The role of alpha(v)beta(3) in prostate cancer
progression. Neoplasia 4: 191-4.
Coussens LM, Tinkle CL, Hanahan D, Werb Z (2000). MMP-9 supplied by bone
marrow-derived cells contributes to skin carcinogenesis. Cell 103: 481-90.
Cunha GR, Chung LW (1981). Stromal-epithelial interactions--I. Induction of prostatic
phenotype in urothelium of testicular feminized (Tfm/y) mice. J Steroid Biochem 14:
1317-24.
Cunha GR, Donjacour AA, Cooke PS, Mee S, Bigsby RM, Higgins SJ et al (1987). The
endocrinology and developmental biology of the prostate. Endocr Rev 8: 338-62.
Cutz JC, Guan J, Bayani J, Yoshimoto M, Xue H, Sutcliffe M et al (2006). Establishment
in severe combined immunodeficiency mice of subrenal capsule xenografts and
transplantable tumor lines from a variety of primary human lung cancers: potential
models for studying tumor progression-related changes. Clin Cancer Res 12: 4043-54.
D'Souza-Schorey C, Chavrier P (2006). ARF proteins: roles in membrane traffic and
beyond. Nat Rev Mol Cell Biol 7: 347-58.
Damber JE, Aus G (2008). Prostate cancer. Lancet 371: 1710-21.
Day ML, Zhao X, Vallorosi CJ, Putzi M, Powell CT, Lin C et al (1999). E-cadherin
mediates aggregation-dependent survival of prostate and mammary epithelial cells
through the retinoblastoma cell cycle control pathway. J Biol Chem 274: 9656-64.
Deryugina EI, Ratnikov B, Monosov E, Postnova TI, DiScipio R, Smith JW et al (2001).
MT1-MMP initiates activation of pro-MMP-2 and integrin alphavbeta3 promotes
maturation of MMP-2 in breast carcinoma cells. Exp Cell Res 263: 209-23.
Desai B, Ma T, Chellaiah MA (2008). Invadopodia and matrix degradation, a new
property of prostate cancer cells during migration and invasion. J Biol Chem 283:
13856-66.
Deutsch E, Maggiorella L, Eschwege P, Bourhis J, Soria JC, Abdulkarim B (2004).
Environmental, genetic, and molecular features of prostate cancer. Lancet Oncol 5:
303-13.
Dhanasekaran SM, Barrette TR, Ghosh D, Shah R, Varambally S, Kurachi K et al
(2001). Delineation of prognostic biomarkers in prostate cancer. Nature 412: 822-6.
Dhodapkar MV, Steinman RM, Krasovsky J, Munz C, Bhardwaj N (2001). Antigenspecific inhibition of effector T cell function in humans after injection of immature
dendritic cells. J Exp Med 193: 233-8.
103
Di Cristofano A, Pesce B, Cordon-Cardo C, Pandolfi PP (1998). Pten is essential for
embryonic development and tumour suppression. Nat Genet 19: 348-55.
Dong JT (2006). Prevalent mutations in prostate cancer. J Cell Biochem 97: 433-47.
Dong JT, Lamb PW, Rinker-Schaeffer CW, Vukanovic J, Ichikawa T, Isaacs JT et al
(1995). KAI1, a metastasis suppressor gene for prostate cancer on human chromosome
11p11.2. Science 268: 884-6.
Dong JT, Suzuki H, Pin SS, Bova GS, Schalken JA, Isaacs WB et al (1996). Downregulation of the KAI1 metastasis suppressor gene during the progression of human
prostatic cancer infrequently involves gene mutation or allelic loss. Cancer Res 56:
4387-90.
Dong X, Guan J, English JC, Flint J, Yee J, Evans K et al (2010). Patient-Derived First
Generation Xenografts of Non-Small Cell Lung Cancers: Promising Tools for Predicting
Drug Responses for Personalized Chemotherapy. Clin Cancer Res 16: 10.
Dong Z, Bonfil RD, Chinni S, Deng X, Trindade Filho JC, Bernardo M et al (2005).
Matrix metalloproteinase activity and osteoclasts in experimental prostate cancer bone
metastasis tissue. Am J Pathol 166: 1173-86.
Ebisawa T, Tada K, Kitajima I, Tojo K, Sampath TK, Kawabata M et al (1999).
Characterization of bone morphogenetic protein-6 signaling pathways in osteoblast
differentiation. J Cell Sci 112 ( Pt 20): 3519-27.
Edlund M, Miyamoto T, Sikes RA, Ogle R, Laurie GW, Farach-Carson MC et al (2001).
Integrin expression and usage by prostate cancer cell lines on laminin substrata. Cell
Growth Differ 12: 99-107.
Edwards SM, Eeles RA (2004). Unravelling the genetics of prostate cancer. Am J Med
Genet C Semin Med Genet 129C: 65-73.
Ehlers JP, Worley L, Onken MD, Harbour JW (2005). DDEF1 is located in an amplified
region of chromosome 8q and is overexpressed in uveal melanoma. Clin Cancer Res
11: 3609-13.
Ernst T, Hergenhahn M, Kenzelmann M, Cohen CD, Bonrouhi M, Weninger A et al
(2002). Decrease and gain of gene expression are equally discriminatory markers for
prostate carcinoma: a gene expression analysis on total and microdissected prostate
tissue. Am J Pathol 160: 2169-80.
104
Fernandez PL, Farre X, Nadal A, Fernandez E, Peiro N, Sloane BF et al (2001).
Expression of cathepsins B and S in the progression of prostate carcinoma. Int J
Cancer 95: 51-5.
Festuccia C, Dolo V, Guerra F, Violini S, Muzi P, Pavan A et al (1998). Plasminogen
activator system modulates invasive capacity and proliferation in prostatic tumor cells.
Clin Exp Metastasis 16: 513-28.
Fichtner I, Rolff J, Soong R, Hoffmann J, Hammer S, Sommer A et al (2008).
Establishment of patient-derived non-small cell lung cancer xenografts as models for
the identification of predictive biomarkers. Clin Cancer Res 14: 6456-68.
Fidler IJ (2002a). Critical determinants of metastasis. Semin Cancer Biol 12: 89-96.
Fidler IJ (2002b). The organ microenvironment and cancer metastasis. Differentiation
70: 498-505.
Fidler IJ (2003). The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis
revisited. Nat Rev Cancer 3: 453-8.
Fidler IJ, Kripke ML (1977). Metastasis results from preexisting variant cells within a
malignant tumor. Science 197: 893-5.
Fidler IJ, Talmadge JE (1986). Evidence that intravenously derived murine pulmonary
melanoma metastases can originate from the expansion of a single tumor cell. Cancer
Res 46: 5167-71.
Fizazi K, Yang J, Peleg S, Sikes CR, Kreimann EL, Daliani D et al (2003). Prostate
cancer cells-osteoblast interaction shifts expression of growth/survival-related genes in
prostate cancer and reduces expression of osteoprotegerin in osteoblasts. Clin Cancer
Res 9: 2587-97.
Foley R, Hollywood D, Lawler M (2004). Molecular pathology of prostate cancer: the key
to identifying new biomarkers of disease. Endocr Relat Cancer 11: 477-88.
Fong CJ, Sherwood ER, Sutkowski DM, Abu-Jawdeh GM, Yokoo H, Bauer KD et al
(1991). Reconstituted basement membrane promotes morphological and functional
differentiation of primary human prostatic epithelial cells. Prostate 19: 221-35.
Foty RA, Steinberg MS (2004). Cadherin-mediated cell-cell adhesion and tissue
segregation in relation to malignancy. Int J Dev Biol 48: 397-409.
Freeman MR, Bagli DJ, Lamb CC, Guthrie PD, Uchida T, Slavin RE et al (1994).
Culture of a prostatic cell line in basement membrane gels results in an enhancement of
105
malignant properties and constitutive alterations in gene expression. J Cell Physiol 158:
325-36.
Furman C, Short SM, Subramanian RR, Zetter BR, Roberts TM (2002). DEF-1/ASAP1
is a GTPase-activating protein (GAP) for ARF1 that enhances cell motility through a
GAP-dependent mechanism. J Biol Chem 277: 7962-9.
Geiger B, Bershadsky A, Pankov R, Yamada KM (2001). Transmembrane crosstalk
between the extracellular matrix--cytoskeleton crosstalk. Nat Rev Mol Cell Biol 2: 793805.
Gimona M, Buccione R (2006). Adhesions that mediate invasion. Int J Biochem Cell Biol
38: 1875-92.
Gleason DF, Mellinger GT (2002). Prediction of prognosis for prostatic adenocarcinoma
by combined histological grading and clinical staging. 1974. J Urol 167: 953-8;
discussion 959.
Gleave M, Hsieh JT, Gao CA, von Eschenbach AC, Chung LW (1991). Acceleration of
human prostate cancer growth in vivo by factors produced by prostate and bone
fibroblasts. Cancer Res 51: 3753-61.
Glinsky GV, Glinskii AB, Stephenson AJ, Hoffman RM, Gerald WL (2004). Gene
expression profiling predicts clinical outcome of prostate cancer. J Clin Invest 113: 91323.
Gopalkrishnan RV, Kang DC, Fisher PB (2001). Molecular markers and determinants of
prostate cancer metastasis. J Cell Physiol 189: 245-56.
Gray IC, Stewart LM, Phillips SM, Hamilton JA, Gray NE, Watson GJ et al (1998).
Mutation and expression analysis of the putative prostate tumour-suppressor gene
PTEN. Br J Cancer 78: 1296-300.
Greenberg NM, DeMayo F, Finegold MJ, Medina D, Tilley WD, Aspinall JO et al (1995).
Prostate cancer in a transgenic mouse. Proc Natl Acad Sci U S A 92: 3439-43.
Greenlee RT, Murray T, Bolden S, Wingo PA (2000). Cancer statistics, 2000. CA
Cancer J Clin 50: 7-33.
Gudmundsson J, Sulem P, Manolescu A, Amundadottir LT, Gudbjartsson D, Helgason
A et al (2007). Genome-wide association study identifies a second prostate cancer
susceptibility variant at 8q24. Nat Genet 39: 631-7.
Gupta GP, Massague J (2006). Cancer metastasis: building a framework. Cell 127:
679-95.
106
Gupta S, Hussain T, MacLennan GT, Fu P, Patel J, Mukhtar H (2003). Differential
expression of S100A2 and S100A4 during progression of human prostate
adenocarcinoma. J Clin Oncol 21: 106-12.
Gutman S, Kessler LG (2006). The US Food and Drug Administration perspective on
cancer biomarker development. Nat Rev Cancer 6: 565-71.
Haiman CA, Patterson N, Freedman ML, Myers SR, Pike MC, Waliszewska A et al
(2007). Multiple regions within 8q24 independently affect risk for prostate cancer. Nat
Genet 39: 638-44.
Hanahan D, Weinberg RA (2000). The hallmarks of cancer. Cell 100: 57-70.
Hashimoto S, Hashimoto A, Yamada A, Onodera Y, Sabe H (2005). Assays and
properties of the ArfGAPs, AMAP1 and AMAP2, in Arf6 function. Methods Enzymol 404:
216-31.
Hashimoto S, Hirose M, Hashimoto A, Morishige M, Yamada A, Hosaka H et al (2006).
Targeting AMAP1 and cortactin binding bearing an atypical src homology 3/proline
interface for prevention of breast cancer invasion and metastasis. Proc Natl Acad Sci U
S A 103: 7036-41.
Hashimoto S, Onodera Y, Hashimoto A, Tanaka M, Hamaguchi M, Yamada A et al
(2004). Requirement for Arf6 in breast cancer invasive activities. Proc Natl Acad Sci U S
A 101: 6647-52.
Hoosein NM, Boyd DD, Hollas WJ, Mazar A, Henkin J, Chung LW (1991). Involvement
of urokinase and its receptor in the invasiveness of human prostatic carcinoma cell
lines. Cancer Commun 3: 255-64.
Hull GW, Rabbani F, Abbas F, Wheeler TM, Kattan MW, Scardino PT (2002). Cancer
control with radical prostatectomy alone in 1,000 consecutive patients. J Urol 167: 52834.
Ichikawa T, Ichikawa Y, Isaacs JT (1991a). Genetic factors and metastatic potential of
prostatic cancer. Cancer Surv 11: 35-42.
Ichikawa T, Ichikawa Y, Isaacs JT (1991b). Genetic factors and suppression of
metastatic ability of prostatic cancer. Cancer Res 51: 3788-92.
Inoue H, Ha VL, Prekeris R, Randazzo PA (2008). Arf GTPase-activating protein
ASAP1 interacts with Rab11 effector FIP3 and regulates pericentrosomal localization of
transferrin receptor-positive recycling endosome. Mol Biol Cell 19: 4224-37.
107
Isaacs JT (1982). Hormonally responsive versus unresponsive progression of prostatic
cancer to antiandrogen therapy as studied with the Dunning R-3327-AT and -G rat
adenocarcinomas. Cancer Res 42: 5010-4.
Isaacs JT (2005). New strategies for the medical treatment of prostate cancer. BJU Int
96 Suppl 2: 35-40.
Jemal A, Ward E, Hao Y, Thun M (2005). Trends in the leading causes of death in the
United States, 1970-2002. Jama 294: 1255-9.
Ji H, Houghton AM, Mariani TJ, Perera S, Kim CB, Padera R et al (2006). K-ras
activation generates an inflammatory response in lung tumors. Oncogene 25: 2105-12.
Johnson JI, Decker S, Zaharevitz D, Rubinstein LV, Venditti JM, Schepartz S et al
(2001). Relationships between drug activity in NCI preclinical in vitro and in vivo models
and early clinical trials. Br J Cancer 84: 1424-31.
Johnson JR, Hammond WG, Benfield JR, Tesluk H (1995). Successful
xenotransplantation of human lung cancer correlates with the metastatic phenotype.
Ann Thorac Surg 60: 32-6; discussion 36-7.
Jung M, Romer A, Keyszer G, Lein M, Kristiansen G, Schnorr D et al (2003). mRNA
expression of the five membrane-type matrix metalloproteinases MT1-MT5 in human
prostatic cell lines and their down-regulation in human malignant prostatic tissue.
Prostate 55: 89-98.
Junior JP, Srougi M, Borra PM, Dall' Oglio MF, Ribeiro-Filho LA, Leite KR (2008). Ecadherin and beta-catenin Loss of Expression Related to Bone Metastasis in Prostate
Cancer. Appl Immunohistochem Mol Morphol.
Kaplan-Lefko PJ, Chen TM, Ittmann MM, Barrios RJ, Ayala GE, Huss WJ et al (2003).
Pathobiology of autochthonous prostate cancer in a pre-clinical transgenic mouse
model. Prostate 55: 219-37.
Keller ET, Zhang J, Cooper CR, Smith PC, McCauley LK, Pienta KJ et al (2001).
Prostate carcinoma skeletal metastases: cross-talk between tumor and bone. Cancer
Metastasis Rev 20: 333-49.
Kelly T, Yan Y, Osborne RL, Athota AB, Rozypal TL, Colclasure JC et al (1998).
Proteolysis of extracellular matrix by invadopodia facilitates human breast cancer cell
invasion and is mediated by matrix metalloproteinases. Clin Exp Metastasis 16: 501-12.
Khan FA, Kaisary AV, Boustead GB, Gillatt DA, Winkler MH (2005). PSA recurrence
following radical prostatectomy is comparable for all age groups in the UK. Prostate
Cancer Prostatic Dis 8: 158-62.
108
Kim HL, Vander Griend DJ, Yang X, Benson DA, Dubauskas Z, Yoshida BA et al
(2001). Mitogen-activated protein kinase kinase 4 metastasis suppressor gene
expression is inversely related to histological pattern in advancing human prostatic
cancers. Cancer Res 61: 2833-7.
Kim JH, Dhanasekaran SM, Mehra R, Tomlins SA, Gu W, Yu J et al (2007). Integrative
analysis of genomic aberrations associated with prostate cancer progression. Cancer
Res 67: 8229-39.
King FJ, Hu E, Harris DF, Sarraf P, Spiegelman BM, Roberts TM (1999). DEF-1, a
novel Src SH3 binding protein that promotes adipogenesis in fibroblastic cell lines. Mol
Cell Biol 19: 2330-7.
Klein KA, Reiter RE, Redula J, Moradi H, Zhu XL, Brothman AR et al (1997).
Progression of metastatic human prostate cancer to androgen independence in
immunodeficient SCID mice. Nat Med 3: 402-8.
Klezovitch O, Chevillet J, Mirosevich J, Roberts RL, Matusik RJ, Vasioukhin V (2004).
Hepsin promotes prostate cancer progression and metastasis. Cancer Cell 6: 185-95.
Koblinski JE, Ahram M, Sloane BF (2000). Unraveling the role of proteases in cancer.
Clin Chim Acta 291: 113-35.
Kumar AA, Nelson Fausto, Richard Mitchell (2007). Robbins basic pathology, edited by
Vinay Kumar. Philadelphia, PA : Saunders/Elsevier.
Lah TT, Kos J (1998). Cysteine proteinases in cancer progression and their clinical
relevance for prognosis. Biol Chem 379: 125-30.
Landers KA, Burger MJ, Tebay MA, Purdie DM, Scells B, Samaratunga H et al (2005).
Use of multiple biomarkers for a molecular diagnosis of prostate cancer. Int J Cancer
114: 950-6.
Lee CH, Xue H, Sutcliffe M, Gout PW, Huntsman DG, Miller DM et al (2005).
Establishment of subrenal capsule xenografts of primary human ovarian tumors in SCID
mice: potential models. Gynecol Oncol 96: 48-55.
Li J, Yen C, Liaw D, Podsypanina K, Bose S, Wang SI et al (1997). PTEN, a putative
protein tyrosine phosphatase gene mutated in human brain, breast, and prostate
cancer. Science 275: 1943-7.
Li L, Yang G, Ebara S, Satoh T, Nasu Y, Timme TL et al (2001). Caveolin-1 mediates
testosterone-stimulated survival/clonal growth and promotes metastatic activities in
prostate cancer cells. Cancer Res 61: 4386-92.
109
Liao CP, Zhong C, Saribekyan G, Bading J, Park R, Conti PS et al (2007). Mouse
models of prostate adenocarcinoma with the capacity to monitor spontaneous
carcinogenesis by bioluminescence or fluorescence. Cancer Res 67: 7525-33.
Lichtinghagen R, Musholt PB, Lein M, Romer A, Rudolph B, Kristiansen G et al (2002).
Different mRNA and protein expression of matrix metalloproteinases 2 and 9 and tissue
inhibitor of metalloproteinases 1 in benign and malignant prostate tissue. Eur Urol 42:
398-406.
Lin D, Watahiki A, Bayani J, Zhang F, Liu L, Ling V et al (2008). ASAP1, a gene at
8q24, is associated with prostate cancer metastasis. Cancer Res 68: 4352-9.
Linder S (2007). The matrix corroded: podosomes and invadopodia in extracellular
matrix degradation. Trends Cell Biol 17: 107-17.
Linder S, Aepfelbacher M (2003). Podosomes: adhesion hot-spots of invasive cells.
Trends Cell Biol 13: 376-85.
Liotta LA (1986). Tumor invasion and metastases--role of the extracellular matrix:
Rhoads Memorial Award lecture. Cancer Res 46: 1-7.
Liu Y, Loijens JC, Martin KH, Karginov AV, Parsons JT (2002). The association of
ASAP1, an ADP ribosylation factor-GTPase activating protein, with focal adhesion
kinase contributes to the process of focal adhesion assembly. Mol Biol Cell 13: 214756.
Liu Y, Yerushalmi GM, Grigera PR, Parsons JT (2005). Mislocalization or reduced
expression of Arf GTPase-activating protein ASAP1 inhibits cell spreading and
migration by influencing Arf1 GTPase cycling. J Biol Chem 280: 8884-92.
Lorenz M, Yamaguchi H, Wang Y, Singer RH, Condeelis J (2004). Imaging sites of Nwasp activity in lamellipodia and invadopodia of carcinoma cells. Curr Biol 14: 697-703.
Mareel M, Oliveira MJ, Madani I (2009). Cancer invasion and metastasis: interacting
ecosystems. Virchows Arch 454: 599-622.
Marreiros A, Dudgeon K, Dao V, Grimm MO, Czolij R, Crossley M et al (2005). KAI1
promoter activity is dependent on p53, junB and AP2: evidence for a possible
mechanism underlying loss of KAI1 expression in cancer cells. Oncogene 24: 637-49.
Masuda H, Fukabori Y, Nakano K, Takezawa Y, T CS, Yamanaka H (2003). Increased
expression of bone morphogenetic protein-7 in bone metastatic prostate cancer.
Prostate 54: 268-74.
110
Mattern J, Jager S, Sonka J, Wayss K, Volm M (1985). Growth of human bronchial
carcinomas in nude mice. Br J Cancer 51: 195-200.
McCabe NP, Angwafo FF, 3rd, Zaher A, Selman SH, Kouinche A, Jankun J (2000).
Expression of soluble urokinase plasminogen activator receptor may be related to
outcome in prostate cancer patients. Oncol Rep 7: 879-82.
McNeal JE (1984). Anatomy of the prostate and morphogenesis of BPH, in New
Approaches to the Study of Benign Prostatic Hyperplasia (Kimball, F. A., ed.), Alan R.
Liss, New York, pp. 27–43.
McNeal JE (1988). Normal histology of the prostate. Am J Surg Pathol 12: 619-33.
McNeal JE (1998). Anatomy and normal histology of the human
Saunders Company, Philadelphia, USA.
prostate. W.B.
Mehra R, Han B, Tomlins SA, Wang L, Menon A, Wasco MJ et al (2007). Heterogeneity
of TMPRSS2 gene rearrangements in multifocal prostate adenocarcinoma: molecular
evidence for an independent group of diseases. Cancer Res 67: 7991-5.
Merk J, Rolff J, Becker M, Leschber G, Fichtner I (2009). Patient-derived xenografts of
non-small-cell lung cancer: a pre-clinical model to evaluate adjuvant chemotherapy?
Eur J Cardiothorac Surg 36: 454-9.
Minagawa H, Yamashita T, Honda M, Tabuse Y, Kamijo K, Tsugita A et al (2008).
Comparative analysis of proteome and transcriptome in human hepatocellular
carcinoma using 2D-DIGE and SAGE. Protein J 27: 409-19.
Miyake H, Hara I, Eto H (2003). Prediction of the extent of prostate cancer by the
combined use of systematic biopsy and serum level of cathepsin D. Int J Urol 10: 196200.
Miyake H, Hara I, Yamanaka K, Arakawa S, Kamidono S (1999a). Elevation of
urokinase-type plasminogen activator and its receptor densities as new predictors of
disease progression and prognosis in men with prostate cancer. Int J Oncol 14: 535-41.
Miyake H, Hara I, Yamanaka K, Gohji K, Arakawa S, Kamidono S (1999b). Elevation of
serum levels of urokinase-type plasminogen activator and its receptor is associated with
disease progression and prognosis in patients with prostate cancer. Prostate 39: 123-9.
Miyata M, Raven JF, Baltzis D, Koromilas AE, Sabe H (2008). IRES-mediated
translational control of AMAP1 expression during differentiation of monocyte U937 cells.
Cell Cycle 7: 3273-81.
111
Mizutani K, Miki H, He H, Maruta H, Takenawa T (2002). Essential role of neural
Wiskott-Aldrich syndrome protein in podosome formation and degradation of
extracellular matrix in src-transformed fibroblasts. Cancer Res 62: 669-74.
Mogal AP, van der Meer R, Crooke PS, Abdulkadir SA (2007). Haploinsufficient
prostate tumor suppression by Nkx3.1: a role for chromatin accessibility in dosagesensitive gene regulation. J Biol Chem 282: 25790-800.
Monsky WL, Lin CY, Aoyama A, Kelly T, Akiyama SK, Mueller SC et al (1994). A
potential marker protease of invasiveness, seprase, is localized on invadopodia of
human malignant melanoma cells. Cancer Res 54: 5702-10.
Moreau V, Tatin F, Varon C, Anies G, Savona-Baron C, Genot E (2006). Cdc42-driven
podosome formation in endothelial cells. Eur J Cell Biol 85: 319-25.
Morishige M, Hashimoto S, Ogawa E, Toda Y, Kotani H, Hirose M et al (2008). GEP100
links epidermal growth factor receptor signalling to Arf6 activation to induce breast
cancer invasion. Nat Cell Biol 10: 85-92.
Morris DS, Tomlins SA, Rhodes DR, Mehra R, Shah RB, Chinnaiyan AM (2007).
Integrating biomedical knowledge to model pathways of prostate cancer progression.
Cell Cycle 6: 1177-87.
Mousses S, Bubendorf L, Wagner U, Hostetter G, Kononen J, Cornelison R et al (2002).
Clinical validation of candidate genes associated with prostate cancer progression in the
CWR22 model system using tissue microarrays. Cancer Res 62: 1256-60.
Mueller SC, Ghersi G, Akiyama SK, Sang QX, Howard L, Pineiro-Sanchez M et al
(1999). A novel protease-docking function of integrin at invadopodia. J Biol Chem 274:
24947-52.
Muller A, Homey B, Soto H, Ge N, Catron D, Buchanan ME et al (2001). Involvement of
chemokine receptors in breast cancer metastasis. Nature 410: 50-6.
Murant SJ, Handley J, Stower M, Reid N, Cussenot O, Maitland NJ (1997). Coordinated changes in expression of cell adhesion molecules in prostate cancer. Eur J
Cancer 33: 263-71.
Murant SJ, Rolley N, Phillips SM, Stower M, Maitland NJ (2000). Allelic imbalance
within the E-cadherin gene is an infrequent event in prostate carcinogenesis. Genes
Chromosomes Cancer 27: 104-9.
Nagakawa O, Murakami K, Yamaura T, Fujiuchi Y, Murata J, Fuse H et al (2000).
Expression of membrane-type 1 matrix metalloproteinase (MT1-MMP) on prostate
cancer cell lines. Cancer Lett 155: 173-9.
112
Nakahara H, Howard L, Thompson EW, Sato H, Seiki M, Yeh Y et al (1997).
Transmembrane/cytoplasmic
domain-mediated
membrane
type
1-matrix
metalloprotease docking to invadopodia is required for cell invasion. Proc Natl Acad Sci
U S A 94: 7959-64.
Navone NM, Logothetis CJ, von Eschenbach AC, Troncoso P (1998). Model systems of
prostate cancer: uses and limitations. Cancer Metastasis Rev 17: 361-71.
Nelson JB, Carducci MA (2000). The role of endothelin-1 and endothelin receptor
antagonists in prostate cancer. BJU Int 85 Suppl 2: 45-8.
Nelson WG, De Marzo AM, Isaacs WB (2003). Prostate cancer. N Engl J Med 349: 36681.
Nemeth JA, Yousif R, Herzog M, Che M, Upadhyay J, Shekarriz B et al (2002). Matrix
metalloproteinase activity, bone matrix turnover, and tumor cell proliferation in prostate
cancer bone metastasis. J Natl Cancer Inst 94: 17-25.
Nguyen DX, Massague J (2007). Genetic determinants of cancer metastasis. Nat Rev
Genet 8: 341-52.
Noble RL (1977). The development of prostatic adenocarcinoma in Nb rats following
prolonged sex hormone administration. Cancer Res 37: 1929-33.
Ohl F, Jung M, Xu C, Stephan C, Rabien A, Burkhardt M et al (2005). Gene expression
studies in prostate cancer tissue: which reference gene should be selected for
normalization? J Mol Med 83: 1014-24.
Onodera Y, Hashimoto S, Hashimoto A, Morishige M, Mazaki Y, Yamada A et al (2005).
Expression of AMAP1, an ArfGAP, provides novel targets to inhibit breast cancer
invasive activities. Embo J 24: 963-73.
Ory S, Destaing O, Jurdic P (2002). Microtubule dynamics differentially regulates Rho
and Rac activity and triggers Rho-independent stress fiber formation in macrophage
polykaryons. Eur J Cell Biol 81: 351-62.
Ozawa M, Baribault H, Kemler R (1989). The cytoplasmic domain of the cell adhesion
molecule uvomorulin associates with three independent proteins structurally related in
different species. Embo J 8: 1711-7.
Paris PL, Weinberg V, Simko J, Andaya A, Albo G, Rubin MA et al (2005). Preliminary
evaluation of prostate cancer metastatic risk biomarkers. Int J Biol Markers 20: 141-5.
113
Perez-Soler R, Kemp B, Wu QP, Mao L, Gomez J, Zeleniuch-Jacquotte A et al (2000).
Response and determinants of sensitivity to paclitaxel in human non-small cell lung
cancer tumors heterotransplanted in nude mice. Clin Cancer Res 6: 4932-8.
Peters DG, Kudla DM, Deloia JA, Chu TJ, Fairfull L, Edwards RP et al (2005).
Comparative gene expression analysis of ovarian carcinoma and normal ovarian
epithelium by serial analysis of gene expression. Cancer Epidemiol Biomarkers Prev
14: 1717-23.
Podsypanina K, Ellenson LH, Nemes A, Gu J, Tamura M, Yamada KM et al (1999).
Mutation of Pten/Mmac1 in mice causes neoplasia in multiple organ systems. Proc Natl
Acad Sci U S A 96: 1563-8.
Pollard M (1973). Spontaneous prostate adenocarcinomas in aged germfree Wistar
rats. J Natl Cancer Inst 51: 1235-41.
Pollard M, Luckert PH, Schmidt MA (1982). Induction of prostate adenocarcinomas in
Lobund Wistar rats by testosterone. Prostate 3: 563-8.
Pontes-Junior J, Reis ST, Dall'oglio M, Neves de Oliveira LC, Cury J, Carvalho PA et al
(2009). Evaluation of the expression of integrins and cell adhesion molecules through
tissue microarray in lymph node metastases of prostate cancer. J Carcinog 8: 3.
Pontes Junior DM, Pepe VL, Osorio-de-Castro CG, Massena EP, Portela MC, Miranda
Mdo C et al (2008). [Definition of priority medicines for monitoring laboratory quality in
Brazil: the interface between health surveillance and the National Drug Policy]. Cad
Saude Publica 24: 2081-90.
Porkka KP, Tammela TL, Vessella RL, Visakorpi T (2004). RAD21 and KIAA0196 at
8q24 are amplified and overexpressed in prostate cancer. Genes Chromosomes
Cancer 39: 1-10.
Posadas EM, Al-Ahmadie H, Robinson VL, Jagadeeswaran R, Otto K, Kasza KE et al
(2009). FYN is overexpressed in human prostate cancer. BJU Int 103: 171-7.
Pretlow TG, Delmoro CM, Dilley GG, Spadafora CG, Pretlow TP (1991).
Transplantation of human prostatic carcinoma into nude mice in Matrigel. Cancer Res
51: 3814-7.
Ramaswamy S, Ross KN, Lander ES, Golub TR (2003). A molecular signature of
metastasis in primary solid tumors. Nat Genet 33: 49-54.
Randazzo PA, Andrade J, Miura K, Brown MT, Long YQ, Stauffer S et al (2000). The
Arf GTPase-activating protein ASAP1 regulates the actin cytoskeleton. Proc Natl Acad
Sci U S A 97: 4011-6.
114
Rembrink K, Romijn JC, van der Kwast TH, Rubben H, Schroder FH (1997). Orthotopic
implantation of human prostate cancer cell lines: a clinically relevant animal model for
metastatic prostate cancer. Prostate 31: 168-74.
Ribeiro FR, Jeronimo C, Henrique R, Fonseca D, Oliveira J, Lothe RA et al (2006). 8q
gain is an independent predictor of poor survival in diagnostic needle biopsies from
prostate cancer suspects. Clin Cancer Res 12: 3961-70.
Roy-Burman P, Wu H, Powell WC, Hagenkord J, Cohen MB (2004). Genetically defined
mouse models that mimic natural aspects of human prostate cancer development.
Endocr Relat Cancer 11: 225-54.
Ruijter ET, Miller GJ, van de Kaa CA, van Bokhoven A, Bussemakers MJ, Debruyne FM
et al (1999). Molecular analysis of multifocal prostate cancer lesions. J Pathol 188: 2717.
Ruijter ET, van de Kaa CA, Schalken JA, Debruyne FM, Ruiter DJ (1996). Histological
grade heterogeneity in multifocal prostate cancer. Biological and clinical implications. J
Pathol 180: 295-9.
Saha S, Sparks AB, Rago C, Akmaev V, Wang CJ, Vogelstein B et al (2002). Using the
transcriptome to annotate the genome. Nat Biotechnol 20: 508-12.
Saleem M, Kweon MH, Johnson JJ, Adhami VM, Elcheva I, Khan N et al (2006).
S100A4 accelerates tumorigenesis and invasion of human prostate cancer through the
transcriptional regulation of matrix metalloproteinase 9. Proc Natl Acad Sci U S A 103:
14825-30.
Sanda MG, Restifo NP, Walsh JC, Kawakami Y, Nelson WG, Pardoll DM et al (1995).
Molecular characterization of defective antigen processing in human prostate cancer. J
Natl Cancer Inst 87: 280-5.
Saramaki OR, Tammela TL, Martikainen PM, Vessella RL, Visakorpi T (2006). The
gene for polycomb group protein enhancer of zeste homolog 2 (EZH2) is amplified in
late-stage prostate cancer. Genes Chromosomes Cancer 45: 639-45.
Schmelz M, Cress AE, Scott KM, Burger F, Cui H, Sallam K et al (2002). Different
phenotypes in human prostate cancer: alpha6 or alpha3 integrin in cell-extracellular
adhesion sites. Neoplasia 4: 243-54.
Scholz CC, Berger DP, Winterhalter BR, Henss H, Fiebig HH (1990). Correlation of drug
response in patients and in the clonogenic assay with solid human tumour xenografts.
Eur J Cancer 26: 901-5.
115
Shain SA, McCullough B, Segaloff A (1975). Spontaneous adenocarcinomas of the
ventral prostate of aged A X C rats. J Natl Cancer Inst 55: 177-80.
Sharpless NE, Depinho RA (2006). The mighty mouse: genetically engineered mouse
models in cancer drug development. Nat Rev Drug Discov 5: 741-54.
Shen MM, Abate-Shen C (2007). Pten inactivation and the emergence of androgenindependent prostate cancer. Cancer Res 67: 6535-8.
Sigmund CD (1993). Major approaches for generating and analyzing transgenic mice.
An overview. Hypertension 22: 599-607.
Sinha AA, Quast BJ, Wilson MJ, Fernandes ET, Reddy PK, Ewing SL et al (2001). Ratio
of cathepsin B to stefin A identifies heterogeneity within Gleason histologic scores for
human prostate cancer. Prostate 48: 274-84.
Sridhar SC, Miranti CK (2006). Tetraspanin KAI1/CD82 suppresses invasion by
inhibiting integrin-dependent crosstalk with c-Met receptor and Src kinases. Oncogene
25: 2367-78.
Stamey TA, Warrington JA, Caldwell MC, Chen Z, Fan Z, Mahadevappa M et al (2001).
Molecular genetic profiling of Gleason grade 4/5 prostate cancers compared to benign
prostatic hyperplasia. J Urol 166: 2171-7.
Stephan C, Yousef GM, Scorilas A, Jung K, Jung M, Kristiansen G et al (2004). Hepsin
is highly over expressed in and a new candidate for a prognostic indicator in prostate
cancer. J Urol 171: 187-91.
Stylli SS, Kaye AH, Lock P (2008). Invadopodia: at the cutting edge of tumour invasion.
J Clin Neurosci 15: 725-37.
Sun YX, Wang J, Shelburne CE, Lopatin DE, Chinnaiyan AM, Rubin MA et al (2003).
Expression of CXCR4 and CXCL12 (SDF-1) in human prostate cancers (PCa) in vivo. J
Cell Biochem 89: 462-73.
Tahir SA, Yang G, Ebara S, Timme TL, Satoh T, Li L et al (2001). Secreted caveolin-1
stimulates cell survival/clonal growth and contributes to metastasis in androgeninsensitive prostate cancer. Cancer Res 61: 3882-5.
Tanaka S, Takahashi N, Udagawa N, Murakami H, Nakamura I, Kurokawa T et al
(1995). Possible involvement of focal adhesion kinase, p125FAK, in osteoclastic bone
resorption. J Cell Biochem 58: 424-35.
116
Thalmann GN, Sikes RA, Wu TT, Degeorges A, Chang SM, Ozen M et al (2000).
LNCaP progression model of human prostate cancer: androgen-independence and
osseous metastasis. Prostate 44: 91-103 Jul 1;44(2).
Thompson TC (1998). Metastasis-related genes in prostate cancer: the role of caveolin1. Cancer Metastasis Rev 17: 439-42.
Thompson TC, Park SH, Timme TL, Ren C, Eastham JA, Donehower LA et al (1995).
Loss of p53 function leads to metastasis in ras+myc-initiated mouse prostate cancer.
Oncogene 10: 869-79.
Thompson TC, Southgate J, Kitchener G, Land H (1989). Multistage carcinogenesis
induced by ras and myc oncogenes in a reconstituted organ. Cell 56: 917-30.
Tran NL, Nagle RB, Cress AE, Heimark RL (1999). N-Cadherin expression in human
prostate carcinoma cell lines. An epithelial-mesenchymal transformation mediating
adhesion withStromal cells. Am J Pathol 155: 787-98.
Trikha M, Nakada MT (2002). Platelets and cancer: implications for antiangiogenic
therapy. Semin Thromb Hemost 28: 39-44.
Tripathi M, Nandana S, Yamashita H, Ganesan R, Kirchhofer D, Quaranta V (2008).
Laminin-332 is a substrate for hepsin, a protease associated with prostate cancer
progression. J Biol Chem 283: 30576-84.
Tsuchiya N, Kondo Y, Takahashi A, Pawar H, Qian J, Sato K et al (2002). Mapping and
gene expression profile of the minimally overrepresented 8q24 region in prostate
cancer. Am J Pathol 160: 1799-806.
Umbas R, Schalken JA, Aalders TW, Carter BS, Karthaus HF, Schaafsma HE et al
(1992). Expression of the cellular adhesion molecule E-cadherin is reduced or absent in
high-grade prostate cancer. Cancer Res 52: 5104-9.
Untergasser G, Koch HB, Menssen A, Hermeking H (2002). Characterization of
epithelial senescence by serial analysis of gene expression: identification of genes
potentially involved in prostate cancer. Cancer Res 62: 6255-62.
Vafa A, Zhang Y, Sikes RA, Marengo SR (1998). Overexpression of p185erbB2/neu in
the NbE prostatic epithelial cell line increases cellular spreading and the expression of
integrin alpha6beta1. Int J Oncol 13: 1191-7.
van Dekken H, Alers JC, Damen IA, Vissers KJ, Krijtenburg PJ, Hoedemaeker RF et al
(2003). Genetic evaluation of localized prostate cancer in a cohort of forty patients: gain
of distal 8q discriminates between progressors and nonprogressors. Lab Invest 83: 78996.
117
Van Veldhuizen PJ, Sadasivan R, Cherian R, Wyatt A (1996). Urokinase-type
plasminogen activator expression in human prostate carcinomas. Am J Med Sci 312: 811.
van Weerden WM, de Ridder CM, Verdaasdonk CL, Romijn JC, van der Kwast TH,
Schroder FH et al (1996). Development of seven new human prostate tumor xenograft
models and their histopathological characterization. Am J Pathol 149: 1055-62.
Vander Griend DJ, Kocherginsky M, Hickson JA, Stadler WM, Lin A, Rinker-Schaeffer
CW (2005). Suppression of metastatic colonization by the context-dependent activation
of the c-Jun NH2-terminal kinase kinases JNKK1/MKK4 and MKK7. Cancer Res 65:
10984-91.
Varambally S, Dhanasekaran SM, Zhou M, Barrette TR, Kumar-Sinha C, Sanda MG et
al (2002). The polycomb group protein EZH2 is involved in progression of prostate
cancer. Nature 419: 624-9.
Varambally S, Yu J, Laxman B, Rhodes DR, Mehra R, Tomlins SA et al (2005).
Integrative genomic and proteomic analysis of prostate cancer reveals signatures of
metastatic progression. Cancer Cell 8: 393-406.
Velculescu VE, Kinzler KW (2007). Gene expression analysis goes digital. Nat
Biotechnol 25: 878-80.
Velculescu VE, Zhang L, Vogelstein B, Kinzler KW (1995). Serial analysis of gene
expression. Science 270: 484-7.
Visakorpi T, Kallioniemi AH, Syvanen AC, Hyytinen ER, Karhu R, Tammela T et al
(1995). Genetic changes in primary and recurrent prostate cancer by comparative
genomic hybridization. Cancer Res 55: 342-7.
Voskoglou-Nomikos T, Pater JL, Seymour L (2003). Clinical predictive value of the in
vitro cell line, human xenograft, and mouse allograft preclinical cancer models. Clin
Cancer Res 9: 4227-39.
Waghray A, Feroze F, Schober MS, Yao F, Wood C, Puravs E et al (2001).
Identification of androgen-regulated genes in the prostate cancer cell line LNCaP by
serial analysis of gene expression and proteomic analysis. Proteomics 1: 1327-38.
Wang S, Gao J, Lei Q, Rozengurt N, Pritchard C, Jiao J et al (2003). Prostate-specific
deletion of the murine Pten tumor suppressor gene leads to metastatic prostate cancer.
Cancer Cell 4: 209-21.
118
Wang Y, Revelo MP, Sudilovsky D, Cao M, Chen WG, Goetz L et al (2005a).
Development and characterization of efficient xenograft models for benign and
malignant human prostate tissue. Prostate 64: 149-59.
Wang Y, Xue H, Cutz JC, Bayani J, Mawji NR, Chen WG et al (2005b). An orthotopic
metastatic prostate cancer model in SCID mice via grafting of a transplantable human
prostate tumor line. Lab Invest 85: 1392-404.
Ware JL (1994). Prostate cancer progression. Implications of histopathology. Am J
Pathol 145: 983-93.
Waters DJ, Sakr WA, Hayden DW, Lang CM, McKinney L, Murphy GP et al (1998).
Workgroup 4: spontaneous prostate carcinoma in dogs and nonhuman primates.
Prostate 36: 64-7.
Weeraratna AT, Becker D, Carr KM, Duray PH, Rosenblatt KP, Yang S et al (2004).
Generation and analysis of melanoma SAGE libraries: SAGE advice on the melanoma
transcriptome. Oncogene 23: 2264-74.
Whang YE, Wu X, Suzuki H, Reiter RE, Tran C, Vessella RL et al (1998). Inactivation of
the tumor suppressor PTEN/MMAC1 in advanced human prostate cancer through loss
of expression. Proc Natl Acad Sci U S A 95: 5246-50.
Williams TM, Hassan GS, Li J, Cohen AW, Medina F, Frank PG et al (2005). Caveolin-1
promotes tumor progression in an autochthonous mouse model of prostate cancer:
genetic ablation of Cav-1 delays advanced prostate tumor development in tramp mice. J
Biol Chem 280: 25134-45.
Wise AM, Stamey TA, McNeal JE, Clayton JL (2002). Morphologic and clinical
significance of multifocal prostate cancers in radical prostatectomy specimens. Urology
60: 264-9.
Wong SY, Hynes RO (2006). Lymphatic or hematogenous dissemination: how does a
metastatic tumor cell decide? Cell Cycle 5: 812-7.
Wood M, Fudge K, Mohler JL, Frost AR, Garcia F, Wang M et al (1997). In situ
hybridization studies of metalloproteinases 2 and 9 and TIMP-1 and TIMP-2 expression
in human prostate cancer. Clin Exp Metastasis 15: 246-58.
Wyckoff JB, Wang Y, Lin EY, Li JF, Goswami S, Stanley ER et al (2007). Direct
visualization of macrophage-assisted tumor cell intravasation in mammary tumors.
Cancer Res 67: 2649-56.
119
Xing RH, Rabbani SA (1999). Regulation of urokinase production by androgens in
human prostate cancer cells: effect on tumor growth and metastases in vivo.
Endocrinology 140: 4056-64.
Yamaguchi H, Wyckoff J, Condeelis J (2005). Cell migration in tumors. Curr Opin Cell
Biol 17: 559-64.
Yang G, Truong LD, Timme TL, Ren C, Wheeler TM, Park SH et al (1998). Elevated
expression of caveolin is associated with prostate and breast cancer. Clin Cancer Res
4: 1873-80.
Yang J, Weinberg RA (2008). Epithelial-mesenchymal transition: at the crossroads of
development and tumor metastasis. Dev Cell 14: 818-29.
Yeager M, Orr N, Hayes RB, Jacobs KB, Kraft P, Wacholder S et al (2007). Genomewide association study of prostate cancer identifies a second risk locus at 8q24. Nat
Genet 39: 645-9.
Yu P, Fu YX (2006). Tumor-infiltrating T lymphocytes: friends or foes? Lab Invest 86:
231-45.
Zheng DQ, Woodard AS, Fornaro M, Tallini G, Languino LR (1999). Prostatic carcinoma
cell migration via alpha(v)beta3 integrin is modulated by a focal adhesion kinase
pathway. Cancer Res 59: 1655-64.
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ANIMAL CARE CERTIFICATE
Application Number: A06-1460
Investigator or Course Director: Yuzhuo Wang
Department: Cancer Genetics & Development (BCCA)
Animals:
Mice SCID 643
Start Date:
September 1, 2006
Approval
Date:
December 22, 2006
Funding Sources:
Funding
Agency:
Cancer Research Society
Funding Title:
Molecular Signatures for Predicting Metastatic Potential of Primary Human
Prostate Cancers: Applications of a New Cancer Modeling System
Unfunded title:
Molecular Signatures for Predicting Metastatic Potential of Primary Human
Prostate Cancers: Applications of a New Cancer Modeling System
The Animal Care Committee has examined and approved the use of animals for the above experimental
project.
This certificate is valid for one year from the above start or approval date (whichever is later) provided
there is no change in the experimental procedures. Annual review is required by the CCAC and some
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granting agencies.
A copy of this certificate must be displayed in your animal facility.
Office of Research Services and Administration
102, 6190 Agronomy Road, Vancouver, BC V6T 1Z3
Phone: 604-827-5111 Fax: 604-822-5093
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