Antibody Validation: How Do We Determine Specificity? Nicole E. Barnhardt, Michael Gerdes, Melinda Larsen, Fiona Ginty, Zhengyu Pang, Tom Treynor, Ali Can, Musodiq Bello, Anirban Bhaduri, Sanjay Bhatikar, Xiaodong Tao, Sean Dinn, Michael Montalto Abstract Lit search and ID Commercial Vendors for antibody Antibody specificity reflects the ability of an antibody to distinguish between two different epitopes. Their precise ability to discriminate between varying epitopes can and does vary from one supplier to the next. With new molecular targets being identified for improved diagnosis and treatment of disease, the need for validated antibodies grows. In choosing an antibody for research, literature citations, target applications, and supplier reliability play critical roles. Equally important, are the tests performed to evaluate the specificity of the antibody for one’s research application. This poster will outline the internal validation process that the Molecular Pathology Project at GE Global Research Center applies to each new target of interest. For each target, three carefully chosen antibodies are ordered. Selected antibodies for one target are tested via fluorescent immunohistochemistry (IHC) simultaneously using positive and negative human tissue control slides. Staining is evaluated using an internal image analysis GUI to determine which of the three antibodies stains with highest signal to noise ratio. Equally strong staining can result in taking more than one antibody to the next level of validation. Once staining is confirmed, diseased and normal human tissue of interest are subsequently tested via fluorescent IHC in tissue microarrays (TMAs). When possible, commercially available peptide or recombinant protein is combined with the antibody prior to incubation with tissue. If the antibody of choice can be blocked successfully via peptide or recombinant protein, antibody specificity is considered valid and no further testing is done. When peptides and recombinant proteins are not available, we continue testing specificity with siRNA knockdowns in human cell lines. Several cell lines are screened based on published literature citing their target expression. Using chamber slides, several cell lines can be stained via immunocytochemistry concurrently to determine antigen expression, again using fluorescent detection methods. Once a cell line is identified, the cells are expanded and the appropriate siRNA knockdown experiment is performed using AMAXA transfection technology. Knockdown confirmation is obtained via immunocytochemistry with the antibody in question. Using this approach, we are able to select highly specific antibodies base on IHC performance and use these antibodies for additional studies. •Lack of strict validation for commercial sale of antibodies Criteria Scoring Method Comments Agrees with supporting literature 0=no reports 1=staining in cells 3=staining in tissue Keep copies of papers for each target on shared drive for easy access at weekly meetings. Most publications will be for brown stain, try to find IF examples as well. Highest Primary-secondary staining intensity in positive controls compared to similar antibodies 0=no signal 1=weak staining 2=medium 3=strong Signal should be quantified automatically with standard protocol using infrastructure. AB with highest signal intensity, and highest specificity score proceeds to direct conjugation. High specificity 0= non-specific 1= specific with background 2= specific and clean This needs to be done visually, but agreed upon at weekly meetings. 0= no or <50% knockdown 1= >50% knockdown and no staining Minimum number of cells in the knockdown needs to be identified 0=no signal 1=weak staining 2=medium 3=strong Comparison of signal intensity with primary secondary result will be required for benchmarking. 0= non-specific 1= specific with background 2= specific and clean Specificity profiles should be similar to what was found for primary secondary Order 3 antibodies for each target 0 0 Stain Positive Control Tissue 1 2 Fluorescence + Stain, + Pep + Stain, - Pep No Stain (-) Direct Conjugation NO GO siRNA knockdown (KD) < 50% No Go No positive staining in siRNA knockdown Staining Assessment (-) may need Amp (+) Consistent staining profiles of direct conjugate in relevant TMAs Determine level of Amp NO GO Figure1. Flow chart for antibody validation Figure 2. This table summarizes the qualitative and quantitative antibody validation criteria. 3a 3b 2. cells + media No AMAXA 3. cells + nucleofector sol'n +siRNA No AMAXA 4. cells + nucleofector sol'n Program 3e recombinant protein 3c 3f 3d LV Sigma LV + Pep Vendors Criteria #counts:187936 Avg. Threshold: 169 Avg. Threshold: 169 Avg. Threshold: 169 6d1 6e 6e1 6f 6f1 6e2 6f2 p53 Vision Biosystems p53 Sigma 3g 3h HT29 +EGFRsiRINA+EGFR HT29 +EGFRsiRINA+EGFR #cells:62 #cells:83 #cells:117 #counts:24058 #counts:42895 #counts:24058 Avg. Threshold: 169 Avg. Threshold: 169 Avg. Threshold: 169 %Knockdown: 53 %Knockdown: 37 %Knockdown: 75 LV VB S Literature 3 3 2 Signal Intensity 3 1 2 High Specificity 3 1 2 siRNA knockdown 1 N/A N/A Direct Conjugation N/A N/A N/A TMA's N/A N/A N/A Figure 5. These images summarize the confirmation of the EGFR siRNA knockdown. Images 6a, 6b, and 6c are three representative images from the HT29 cells from the control samples (samples 1, 2, 3 respectively). Images 6d, 6e, and 6f are three representative images from three siRNA knockdown samples (12, 11, 8 respectively). Nucleus counter images and thresholded images are to the right of each image (6a1, 6b1, 6c1, 6d1, 6e1, 6f1, 6a2, 6b2, 6c2, 6d2, 6e2, and 6f2), with the corresponding histograms and threshold data below. The average threshold for all images was used in the analysis. Cell counts, #counts within the signal range, threshold are listed below each group of images. For the siRNA images, the knockdown efficiency is also included below the images. Sample #8, in which 5ug of EGFR duplex #1 was transfected, gave the highest trasfection efficiency. 3j Figure 3. IHC fluorescent staining for p53 on breast carcinoma tissue. Images 3a, 3c and 3d illustrate the 3 different commercial p53 antibodies staining results. Image 3b illustrates the result from the blocking experiment. Images 3e-h, show screenshots of the histograms and thresholding from the image analysis. Graph 3i highlights the results from the image analysis, Lab Vision having the highest signal intensity. Table 3j illustrates the criteria scores for each of these antibodies. EGFR: 1020 Fluorescent IHC + Peptide Block 4a Discussion The process of antibody validation is complex, and specificity testing is just one aspect of the process. Here we’ve outlined our approach for identifying the best commercial antibody to use for our further studies. Using both a qualitative and a quantitative approach ensures that we have chosen an antibody based on multiple criteria. Literature searches are important for identifying how an antibody may stain as well as obtaining antibody references. Standard primary-secondary IHC with fluorescent detection on positive control tissue gives us a reference for signal intensity as well as an indication of localization. Peptide or protein neutralization aids in determining specificity, but when not available, using siRNA serves as a back-up. By using ImageJ for analysis, we aim to eliminate bias from our decision and attempt to apply a standardization to the entire process. EGFR: Antibody Evaluation on Tissue 4b Signal Intensity 300 Signal 200 100 0 Santa Cruz + Peptide Lab Visions 4e SC LV Sigma Antibody Vendors 4d 4c SC+Pep 4f 4i Criteria S SC LV Literature 1 1 1 Signal Intensity 3 0 0 High specificity 3 0 0 siRNA KD 3 N/A N/A Direct Conjugate N/A N/A N/A TMA N/A N/A N/A Sigma Santa Cruz 4g Figure 4. IHC fluorescent staining for EGFR on positive control human placenta tissue, using three different commercial antibodies (4b,4c,4d) and one peptide for blocking (4a). Images 4e-h, show screenshots of the histograms and thresholding from the image analysis. Graph 4i highlights the results from the image analysis, Sigma having the highest signal intensity. Table 4j illustrates the criteria scores for each of these antibodies. 1. Blow N. : The Generation Game. Nature 447:741-744 (2007) 2. Hoos A., Urist M.J., Stojadinovic, A., Mastorides S., Dudas M.E., Leung, D.H.Y., Kuo, D., Brennan M.F., Lewis J.J. , Cordon-Cardo C. : Validation of Tissue Microarrays for Immunohistochemical Profiling of Cancer specimens Using the Example of Human Fibroblastic Tumors. American Journal of Pathology, Vol. 158, No. 4 (2001) 3. Rodrigues N. R., Rowan A. , Smith M.E.F. , Kerr I.B.,Bodmer W.F., Gannon J.V., Lane D.P.: p53 Mutations in Colorectal Cancer. Proc. Natl. Acad. Sci., 87:7555-7559, (1990) 4. Bonsing B.A., Corver W.E.,Gorsira M.C.B., van Vliet M., Oud P.S, Cornelisse C.J.,Fleuren G.J.: Specificity of Seven Monoclonal Antibodies Against p53 Evaluated With Western Blotting, Immunohistochemistry, Confocal Laser Scanning Microscopy, and Flow Cytometry. Cytometry 28:11–24 (1997) 5. Rimm D. : What Brown Cannot Do For You. Nature Biotechnology Vol. 24 No. 8 (2006) 6. Scartozzi M., Bearzi I., Berardi R., Mandolesi A., Fabris G.,Cascinu S.: Epidermal Growth Factor Receptor (EGFR) Status in Primary Colorectal Tumors Does Not Correlate With EGFR Expression in Related Metastatic Sites: Implications for Treatment With EGFR-Targeted Monoclonal Antibodies. Journal of Clinical Oncology, Vol. 22 No. 23 (2004) EGFR: Antibody Evaluation on Cells EGFR: 1020 Fluorescent ICC Program 8. cells + nucleofector sol'n + GFP 4uL + 1 siRNA (a) 5ug Program 9. cells + nucleofector sol'n + GFP 4uL + 2 siRNA (b) 0.5ug Program 100 10. cells + nucleofector sol'n + GFP 4uL + 2 siRNA (b) 3ug Program 0 5b 5a References 4h 4j 7. cells + nucleofector sol'n + GFP 4uL + 1 siRNA (a) 3ug After knockdown, cells were aliquoted into chamber slides and left in the incubator for the recommended 48 hours. GFP was used to monitor transfection progress and cells were imaged on a fluorescent Nikon inverted microscope, both 24 hours and then 48 hours after transfection. After 48 hours, cells were washed with PBS and fixed with 70% methanol as described as above. These slides were then stained using a standard ICC protocol, counterstained with DAPI, and imaged on the Zeiss microscope as described before. Representative images were selected from the control samples and analysis was averaged for these images. Select images from the siRNA samples were chosen and imaged individually to asses which sample gave optimal knockdown results. Image analysis was performed using MacBiophotonics ImageJ free software. Histograms and thresholding were performed exactly as described before. To assess the knockdown efficiency, both signal and number of cells had to be calculated. Using the nucleus counter under the particle analysis, the number of cells was calculated for each image. The ratio of bin counts within the signal range to number of cells for both controls and knock down samples was calculated. The ratio of the two was then subtracted from 1 to obtain the transfection efficiency. VB 3i Program Program #counts:322534 6d2 Signal 0 6. cells + nucleofector sol'n + GFP 4uL + 1 siRNA (a) 0.5ug 12. cells + nucleofector sol'n + GFP 4uL + 3 siRNA 3ug #counts:309878 6d 500 Program Program #cells:183 HT29 +EGFRsiRINA+EGFR 1000 5. cells + nucleofector sol'n + GFP 4uL=2ug 11. cells + nucleofector sol'n + GFP 4uL + 2 siRNA (b) 5ug #cells:310 1500 p53 Lab Vision No AMAXA HT29 +EGFR #cells:503 p53 Antibody Comparison p53 Lab Vision + 1. cells + media HT29 +EGFR 6c2 1020 Fluorescent IHC + Peptide Block •No easy way to discriminate between commercial antibodies For each of these targets of interest, commercial antibodies were chosen based on testing on tissue with IHC, literature citations, species reactivity, peptide availability, and vendor reliability. In each case, control tissue, antibodies, and peptides (when available) were ordered together prior to the initial staining. For p53, antibodies were selected from Lab Vision (MS-738-P0), Vision Biosystems ( NCL-p53-1801), and Sigma (P6874). The recombinant protein for blocking p53 was selected from Lab Vision (RP-9332-PABX) as well as the positive control slides (MS-738-PCS) which are breast carcinoma. For EGFR, antibodies were selected from Lab Vision (MS-378-P), Sigma (A204), and Santa Cruz (sc-03). The peptide for blocking was ordered from Santa Cruz (sc-03P), and the positive control slides, human placenta, were purchased from Lab Vision (MS-378-PCS). All slides were stained using a standard IHC protocol. Epitope retrieval was performed using both citrate buffer and tris-EDTA, one following the other in that order. Primary antibodies were diluted using highest concentration recommended by manufacturers protocol and then incubated according to manufacturers protocol. To test antibody specificity, the recombinant protein or peptide was incubated with the antibody from the corresponding vendor at an excess of 200 micromolar at room temperature for 2 hours prior to primary antibody incubation. All slides were blocked in serum of secondary antibodies’ host species. Slides were then incubated with secondary antibodies, which were Cyanine 3 conjugates from Jackson Immunology Laboratories (715166-150, 711-166-152, 713-166-147), in the dark, humidified, 1:200 for 45minutes. For each target, one slide was treated with only secondary antibody as a negative control. Slides were then counterstained with DAPI for nuclear detection. All imaging was done using a Zeiss AxioImage Z1 microscope with a Hammamatsu ORCA CCD Camera (fluorescent filter sets are ZeroShift from Semrock). Both p53 and EGFR images were taken at 20X (0.8na). For both Dapi and Cy3 channels, optimal exposure time was set using an automated measurement system by the Zeiss microscope. To the best of our ability, Dapi exposure times were almost identical (between 7-10ms). For Cy3, if different exposure times are necessary, a normalization for signal intensity is later applied so that the images are equally weighted. Images were then analyzed using MacBiophotonics ImageJ free software. For each image, a threshold was set to indicate which pixels represented positive staining. For some images, it was necessary to set both an upper and lower threshold limit in order to eliminate saturated pixels and background. Histograms data was copied into an excel spreadsheet along with the screenshots of each histogram, thresholding data, and thresholded image. For each target, the thresholds were averaged before calculating the signal intensity. Bin numbers were then multiplied by the number of counts in each bin, to obtain the total number of pixels in each bin. Signal intensity was then calculated by dividing the sum of the pixels by the sum of the counts within the thresholded range for each image. Signal intensities were then plotted in GraphPad Prism4 for comparison. Since no peptide or recombinant protein was available for the EGFR antibody from Sigma specificity was confirmed with an siRNA knockdown. Prior to selecting a cell line for knockdown, four cell lines known to express EGFR were purchased from ATCC (A431, MDA-MB-231, HT29, and HT1080). These cell lines were all grown according to manufacturers protocol. To assess EGFR expression, cells were transferred to cell culture chamber slides. Twenty-four to forty-eight hours later, when cells were approximately 90%-100% confluent, they were washed three times for five minutes each with sterile PBS. Following the last PBS rinse, cells were fixed for 10 minutes with cold 70% methanol. Chambers were then removed and slides were stained using a standard ICC protocol. These slides were also counterstained with DAPI and imaged using the Zeiss AxioImage Z1 microscope as above. From these results, one cell line was selected to use for the EGFR siRNA knockdown. The siRNA for the knockdown experiment was purchased from Invitrogen (12938-076). HT29 cells were knocked down using an optimized AMAXA protocol and AMAXA nucleofector technology. Samples and conditions were as follows: 6c1 6b2 6a2 HT29 +EGFR 6c 6b1 6b (-) •Multiple antibodies for same target with varying quality, specificity, clones and applications Methods 6a1 6a > 50% KD Highest signal intensity for direct conjugate for a given dilution Use in Multiplex EGFR: siRNA Knockdown EGFR Antibody Signal in Cell Lines 300 Signal 200 HT29 EGFR) A431 EGFR 5c HT1080 EGFR 5e 5f 5g 5h HT29 HT1080 A431 MDA-MB-231 Cell Line 5d MDA-MB-231 EGFR Figure 5. IHC fluorescent staining for EGFR on positive control human cell lines (5a-d). Images 5e-h, show screenshots of the histograms and thresholding from the image analysis. Measurement of signal intensity indicates that any of these cell lines could be used for siRNA knockdown, since each cell line expresses EGFR at relatively the same level. For Research Use Only © 2014 General Electric Company ― All rights reserved. GE and the GE Monogram are trademarks of General Electric Company. December 2014 JB26540US