1. health and fitness
2. disease
3. cancer

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A proteomic-bioinformatic integrated
approach for studying the effect of a peptide
drug candidate on ovarian Cancer
Maria Paola Costi
Department of Life Science
Unimore
Modena
6th Annual EUTROC Meeting
Hammersmith Hospital, London
Saturday 12th July 2014
SCIENTIFIC PROGRAMME
Session 1 - Chairs: Franca Esposito (University of Naples Federico II) / Mara Kyrgiou (Imperial College London)
9.00 – 9.10
Hani Gabra (Imperial College London)
Introduction
On behalf of the organising committee, we
would like to invite you to the 6th Annual
Ovarian Cancer
• Ovarian Cancer (OC) It is the most lethal of the gynecologic
malignancies
• Non specific symptoms that accompany the early disease 
OC diagnosis in advanced stage  therapeutic options are limited.
CAUSES OF FAILURE
FIRST LINE TREATMENT
 surgical cytoreduction +

OC diagnosis in advanced stage (FIGO
Stages IIB to IV)

Rapid occurrence of resistance to the
standard systemic therapies
chemotherapy (and/or radiotherapy)
Chemiotherapy Platinum (cisplatin)
/taxane (paclitaxel) combination
High initial response (≈ 70%)
High percentage of relapse after 6
months (> 90%)
Our aims are
1. to develop new drugs against resistant
ovarian cancer
2. to provide a new methodology for
fingerprint evaluation
of biomolecules changes in cells
3. to translate the concept to clinical samples
Development of new drugs against resistant
ovarian cancer
Fingerprint
design
Design &
chemistry
Recombinant
protein and
cell lines
evaluation
Selection
and
optimizations
Mass
spectrometry
identification
Fingerpint
validated,
biology studies
and mechanism
explored.
Thymidylate synthase and folate pathway
targeting
Targeting
Thymidylate synthase pathways
hTS
monomers
hTS dimer active/inactive
+
?
hTS
HN
O
N
2' deoxy-ribose
mRNA
O
O
dUMP
mTHF
CH3
HN
O
N
2' deoxy-ribose
dTMP
DNA
New strategies against resistant ovarian
cancer (ROC)
Antifolate peptides
Pemetrexed (AlimtaTM)
Binding at TS dimeric interface
Binding at TS active site
Under clinical evaluation for ROC
Proteomic evaluation of the
effect of peptides on:
OC cell lines
Primary tumor tissues
Cardinale D. et al.,PNAS, 2011, Pelà et al, J Med
Chem.2014
•PMX (AlimtaTM) is an antifolate that inhibits TS, DHFR,
GART and ATIC.
•14 clinical trials Pemetrexed phase II
•Proteomic evaluation of the effect of
PMX on:
OC cell lines
OC biopsies from a Phase II clinical trial
Can we approach the whole proteomic/tar
geted proteomic approach
for a wider view of lead/drugs effect?
Targeting the same target,
different mechanism of inhibition
Different cellular protein profile?
Need for a more integrated non
reductionistic approach
Study of the effect of antifolate peptides
in the cell lines through
Proteomic-bioinformatic approach
A2780
A2780/CP
IGROV1
Treated with LR,
LR-DGln4 and PMX
To define a Protein Profile: proteins expression could be
informative of the effect of peptides on OC cell lines.
Whole proteome analysis:
MS label free quantification
approach
Differential proteomic analysis:
Treated with LR peptide
VS Control
Bioinformatic studies
Of Differentially
Expressed Proteins
(Pathways modulated)
Protein Panel selection
for Western blot validation.
Western blot and Analysis of Data
Protein profile definition
Differential proteomic and
bioinformatic approach
NETWORK ANALYSIS OF DEPS
64 out of 160 DEPs resulted connected
using interrogation through:
- BioGrid, IntAct and Reactome
Up – regulated
Down – regulated
Up/Down – regulated
FOUR MAIN CLUSTER ARE
MODULATED BY LR
•Cluster a ribosomal proteins.
•Cluster b proteins of pyrimidine
ribonucleotide metabolic process,
proteins RNA-connected and
protein transport-connected.
•Cluster c ribonucleoproteins.
•Cluster d proteasome complex.
Up – regulated
Down – regulated
Up/Down – regulated
Functional neighbors
Folate Pathway Members connected to DEPs
Up–regulated
Down–regulated
Up/Down–regulated
Folate–related
PMX-related
Physical protein
interactions
Lecture protein
interactions
35 proteins from the original dataset and 14 folateassociated proteins
Proteins Panel Selection
4 proteins known to be directly
involved in the folate cycle
3 folate related protein neighbor to
proteins deregulated by LR treatment
3 differentially
expressed proteins
DEPs
Western Blot targeted approach and
panel validation
Differential
Proteomic
Analysis
Bioinformatics
analysis
10 proteins
selected
WESTERN BLOT
ANALYSIS
How can we translate the profile in a easy
read-out?
Peptide L-Barcode
A2780 peptide barcode
LR 0 1 2 3 4 5 6 7 8 9
PROTEIN CODE: 0=GART, 1=TRAP1, 2=DHFR, 3=HSP90AA1,
4=ATIC, 5=MGMT, 6=TS, 7=MTHFR, 8=EIF2S1, 9=SHMT1
LR treatment vs A2780 & IGROV1
2.0
A2780
IGROV1
treated with LR 5 μM (n=3)
1.5
1.0
0.5
0.0
EIF2S1
MTHFR
DHFR
HSP90AA1
ATIC
MGMT
TS
TRAP1
GART
SHMT1
-0.5
-1.0
A2780
LR 0 1 2 34 5 6 7 8 9
IGROV1
LR 0 1 2 34 5 6 7 89
LR effect in sensitive OC cell lines
Conserved
IGROV1 code:
peptide barcode
0 = GART
1 = TRAP1
2 = DHFR
3 = MGMT
4 = ATIC
5 = HSP90AA1
6 = TS
LR 0
1 2 34 5
LR 0
IGROV1/A2780
A2780 peptide
peptide
barcode
barcode
6 7 89
1 2 34 5
LR 0
6 XXX
1 2 34 5
CONSERVED
code
6 7 89
VARIABLE
code
4
LR-DGln
1.5
treatment vs A2780 &
IGROV1
A2780
IGROV1
treated with LR-DGln4 5 μM (n=3)
1.0
0.5
0.0
EIF2S1
MTHFR
DHFR
HSP90AA1
ATIC
MGMT
TS
TRAP1
GART
SHMT1
-0.5
-1.0
A2780 peptide barcode
LR-DGln4 0
1 2 34 5 6 7 8 9
IGROV1 peptide barcode
LR-DGln4
0 1 2 34 5 6 7 8 9
4
LR-DGln
peptide L-barcode
IGROV1 peptide barcode
IGROV1/A2780 peptide
A2780 peptide
barcodebarcode
DGln4 0 1 2 345 6 7 8 9 DGln4 0 1 2 345 6 7 8 9
SIMILAR CONSERVED CODES
LR 0 1 2 3 4 5 6 X X X
LR/LRDGln4 0 1 2 3 4 X X X X X
SUGGESTING
the
SAME MECHANISM OF ACTION
Cisplatin resistant/sensitive OC cell lines
A2780/CP peptide barcode
1.5
A2780/CP
A2780
treated with LR 5 μM (n=3)
1.0
0.5
0.0
EIF2S1
LR-DGln4 0
MTHFR
DHFR
HSP90AA1
ATIC
MGMT
TS
TRAP1
GART
SHMT1
1 2 3 45 6 7 8 9
-0.5
-1.0
A2780 peptide barcode
SIMILAR CONSERVED CODES
A2780/CP LR-DGln4 0 1 2 X 4 5 X X X X
A2780
LR-DGln4 0 1
2 3 45 67 8 9
LR-DGln4 0 1 2 3 4 X X X X X
SAME MECHANISM OF ACTION
Peptides L-barcode
LR/LR-DGln4 0 1 2 3 X 5 X X X X X
0 = GART
1 = TRAP1
2 = DHFR
5 = HSP90AA1
X variable
PTX barcode Vs
A2780 PTX barcode
PTX 0 1 2 3 4 5 6 7 8 9
DIFFERENTS BARCODES
DIFFERENT MECHANISM
OF ACTION
4
LR-DGln
barcode
A2780
A2780
PTX/peptide
peptide barcode
barcode
LR-DGln4 0 1 2 3 4 5 6
7 8 9
Statistical analysis of
the WB results
Heat map
PCA. Different clusters
for a different mechanism
Heatmap. Blue down expression,
red high expressing
F.Genovese, MPCosti et al. J.Proteom Research, submitted
What is the biological meaning of the
protemic signature identified?
Looking for a protein signature induced by LR….
OC A2780 CELLS
CONTROL vs LR-peptide
TREATED
..a proteomicsbioinformatics
combined approach led
to the identification of a
set of proteins regulated
upon treatment with LRderived peptides.
TRANSLATION OF THE PROTEOMIC RESULTS INTO BIOLOGICAL/MOLECULAR
EFFECTS ON OVARIAN CANCER CELLS!
DI-INACTIVE CONFORMATION
ACTIVE CONFORMATION
CK2 and other kinases
P
[DGln4] LR
Ubiquitin-proteasome
system
Ribosomal proteins,
RNA metabolism and
translational initiation
Stress-responsive pathways
P
TRANSLATIONAL
BLOCK
eIF2A phosphorylation
BINDING TO SEVERAL
CELLULAR mRNAs
(TRANSCRIPTION
FACTORS? RNA binding
proteins/TRANSLATIONAL
REPRESSORS? Stressresponsive proteins?)
TRAP1
VDAC1
HSP90
-Opening of mitochondrial transition pore (MTP)
-ROS increase
APOPTOTIC CELL DEATH
Conclusions
1.
The results confirm that our new methodology provides:
a) An approach to the discovery of molecular drug targets/off-targets which
could be part of a pharmacodynamic profile to monitor candidate drugs
activity since the very early phases of the drug development process.
b) Deregulations can be mainly assigned to the following processes or
functions:
• regulation of translational initiation,
• termination of RNA Pol-II transcription,
• transport,
• proteasome.
2.
different expression level changes observed consequently to our
peptides treatment in comparison with a folate antagonist currently used in
therapy, Pemetrexed, are in agreement with the hypothesized different
mechanism of action.
AIRC_DROC
Targeting Drug Resistance
in Ovarian Cancer
Filippo Genovese
Alessandra Gualandi
Chiara Marraccini
Silvia Pirondi
Leda Severi
Andrea Martello
Domenico D’Arca
ASSOCIAZIONE ITALIANA
PER LA RICERCA SUL CANCRO
Maria Rosaria Amoroso
Gaetano Marverti
Paul Perco
Michela Pelà
Remo Guerrini
Glauco Ponterini
Maria Paola Costi
Thank you.
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