Table S1. Frequencies of gene locus amplifications across tumor types; Table S2. Effect of FGFR inhibitors on growth of RK3E expressing FGFR2 and FGFR3 fusion constructs and RT-4 bladder cancer cell line; Figure S1. Chemical structure of JNJ-42756493; Figure S2. Western Blot confirming the overexpression of HA-tagged FGFR2 fusion genes

Abstract Background Androgen receptor splice variant 7 (ARV7) is a ligand-independent transcription factor associated with resistance to androgen deprivation therapy. There are efforts in development to monitor ARV7 expression during the treatment of patients with prostate cancer. Methods We evaluated ARV7 expression in primary and metastatic prostate adenocarcinomas tissues utilizing automated RNAScope (Advanced Cell Diagnostics) ISH assay, Immunohistochemistry (IHC) and quantitative PCR (qPCR). The novel RNAscope ISH assay was used for direct chromogenic visualization of RNA transcripts and to confirm positivity as an orthogonal approach to validate IHC and quantitative qPCR assay findings. We screened a total of 44 CRPC FFPE tumor samples by IHC and a subset of 28 (excluding controls) with the ISH and qPCR assays. Samples for qPCR were enriched for tumor by macrodissection. RNAScope Scoring Criteria was used to score ISH expression and raw Ct values were normalized to the RPL19 housekeeping gene for qPCR. Thresholds for each assay was established by comparing the findings with the other 2 assays. The data was calculated as ARV7 (+) or ARV7 (-) based on thresholds and compared to the other 2 assays to establish assay performance statistics. Results The ISH screening of 28 CRPC tumors resulted in 16 tumors with some level of positivity and approximately 10 tumors with significant positivity. Of the 44 CRPC tumors stained by IHC, 16 tumors showed various levels of ARV7 nuclear positivity and 8 tumors with strong positivity. Conclusions The detection of ARV7 was achieved in three independent assays. The correlation of three orthogonal data sets were used to identify positive and negative tissues. ISH has the potential for greater sensitivity compared to traditional IHC. The development of automated RNAscope ISH assay allows for more samples to run in a standardized manner with minimal inter-operator variably and requires less hands on-time gives consistently reproducible results. Citation Format: Tanesha Cash-Mason, Jackson Wong, Martinez Martinez, Michael Sharp, Jayaprakash Karkera, John D. Alvarez, Gerald C. Chu, Shibu Thomas, Weiman Li, S. Ken Tian. Arv7 validation in castrate resistant prostate tumors utilizing Rnascope in situ hybridization assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5538.

Abstract Background: Though the techniques to interrogate the appearance of a biomarker in tissue sections have greatly advanced, there are limitations as to how representative an analysis of a tissue section is compared to the entire diseased tissue. Depending on the heterogeneous expression level of a biomarker, tissue sampling can result in different interpretations of the biomarker’s appearance, and hence could potentially lead to a false therapeutic intervention. Hypothesis: Digital image analysis has demonstrated tremendous value in quantifying many features related to biomarker distribution and expression in biological tissues. The information can be collected for various indications and biomarkers and a phenotypic signature can be established that describes a biomarker representation across indications. Moreover, the assessment of new samples can be compared to the established phenotypic signature and a confidence score applied in support to the determined endpoint. Approach: For a proof of concept, 6 prostate cancer samples were processed and a single section was collected after every 100microns. A total of 7 sections per sample were stained for the lymphocyte marker CD3, and the number of positive target cells were determined in the tumor and tumor microenvironment using tissue Image Analysis (tIA™). To assess how indicative the evaluation of a single tissue section would be for the entire tumor, the heterogeneity level was determined on the section level as well as by random grid analysis on each individual section. Both criteria were utilized to define an indication and biomarker specific confidence interval and heterogeneity score. Conclusion: The combination of IHC and tIA is a powerful tool to convert complex data into meaningful interpretations. tIA is also a capable tool to catalogue valuable information about the biomarker’s expression pattern across different disease stages and hence could be used to evaluate how representative a single biomarker evaluation is in the grand scheme. Ultimately, we demonstrated a technique that can be applied to any biomarker and would assist in guiding therapeutic decisions. Citation Format: Carsten Schnatwinkel, Daniel Rudmann, Famke Aeffner, Jasmeet Bajwa, Natalie Hutnick, Michael Sharp, Gerry Chu, JD Alvarez. Providing confidence around computational tissue analysis using heterogeneity assessments [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1710. doi:10.1158/1538-7445.AM2017-1710

Meeting abstracts The state of the immune system is reflected, in part, by the cell populations present in individual tissues which reflect the tumor microenvironment (TME). Several studies have suggested that understanding the TME constituents is useful for predicting drug response outcomes.

Abstract Mesothelin is a 40 kDa secreted glycoprotein expressed in normal mesothelial cells and over-expressed in several histological types of tumors. Detection of mesothelin by immunohistochemistry (IHC) may assist in the diagnosis of mesothelioma. Mesotheliomas are positive for mesothelin staining, but carcinomas of the lung may also be positive for this marker. Mesothelin positivity in adenocarcinoma of the lung reportedly ranges from 22% to 71% of cases depending upon the specific subtype. Mesothelin positivity in squamous cell carcinomas (SCC) of lung is reported to be 16% in non-keratinizing and 31% in keratinizing subtypes. We performed mesothelin IHC on a cohort of 50 lung carcinoma samples (16 adenocarcinomas and 34 SCC). Mesothelin expression was observed in 10 out of 16 (62.5%) lung adenocarcinoma samples, of which 8 showed greater than 10% of tumor cells with positive membrane staining of any intensity. Mesothelin expression was observed in 19 out of 34 (55.9%) lung SCC samples, of which only 3 samples showed greater than 10% of tumor cells with positive membrane staining of any intensity. These findings are in concordance with previous reports which show a higher prevalence of mesothelin protein expression in lung adenocarcinoma than in lung SCC. To correlate RNA expression with protein expression, we performed gene expression profiling on a subcohort of these lung cancer specimens. Out of 50 lung carcinoma samples, 28 samples (10 adenocarcinomas and 18 SCCs) provided adequate RNA yield for gene expression profiling for mesothelin. A total mean relative gene expression (mRGE) value of 13.64 with a standard deviation (SD) of ±3.71 was obtained for the adenocarcinoma samples and a mRGE value of 14.78 with a SD of 2.64 was obtained for the SCC samples. We next arbitrarily assigned samples with greater than 10% mesothelin stained cells as “positive” and the remainder as “negative”. Six negative adenocarcinoma samples yielded a mRGE value of 12.98 with a SD of ±3.84, and four positive adenocarcinoma samples yielded a mRGE value of 14.63 with SD of ±3.82. Sixteen negative SCC samples resulted in a mRGE 14.63 with SD of ± 2.75 and two positive SCC samples yielded a mRGE of 15.98 with a SD of ±1.37. There was no apparent correlation between mRGE values and IHC positivity. We also correlated gene expression with p53 mutation status. Sixteen wild type samples, composed of equal number of adenocarcinoma and SSC had a total mRGE of 14.29 with SD of ±3.32. Seven samples with p53 mutations had a total mRGE of 16.09 with SD ±1.93. These data indicate that mesothelin gene expression is not associated with p53 mutation status. Future studies with an increased number of samples may yield significant associations between protein expression, gene expression and mutation status. Citation Format: Jackson Wong, Dana Gaffney, Michael Sharp, Brenda Hertzog, Jayaprakash Karkera, Suso Platero, John Alvarez. Profiling mesothelin protein expression by immunohistochemistry and gene expression in adenocarcinoma and squamous cell carcinoma of lung. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4666. doi:10.1158/1538-7445.AM2014-4666

Abstract Background: The molecular apocrine (MA) subtype of breast cancer is identified by gene expression profiling. MA tumors are estrogen receptor (ER) negative and progesterone receptor (PR) negative, but still express estrogen responsive genes. The androgen receptor (AR) pathway may be driving growth in these tumors because androgen responsive genes are expressed in tumors with the MA gene signature. The MA gene signature is identified in approximately 10% of triple negative breast cancer (TNBC) and may predict patients with tumors responsive to agents that inhibit the AR pathway. AR protein expression, measured by immunohistochemistry (IHC), may be a surrogate for the MA gene signature, but to date, a careful comparison of gene expression profiles and AR protein expression has not been conducted. In this study, cohorts of TNBCs were assessed for the MA gene signature and these results were compared with AR IHC expression and with a novel gene expression assay that may predict tumors with the MA gene signature. Methods: Formalin fixed, paraffin-embedded (FFPE) TNBC samples were commercially obtained. ER, PR and HER2 status of these samples was confirmed by IHC. AR expression was detected by IHC using two different antibody clones. Both staining intensity and percent positive cells were recorded for each sample. Gene expression data was collected from a cohort of TNBC FFPE samples using cDNA-mediated Annealing, Selection, extension, and Ligation (DASL) technology. A 2-gene classifier of the MA gene expression signature was derived by interrogating publically available gene expression data from ER-negative breast cancers. A reverse-transcriptase polymerase chain reaction (RT-PCR) assay to detect the 2-gene classifier was developed. Cell lines predicted to have the MA gene signature by the 2-gene assay were tested for sensitivity to R-1881 in vitro. Results: Using computational approaches and publically available datasets, we confirmed the validity of the MA gene signature and estimated the prevalence to be between 12% and 37% in ER-negative breast tumors. The 2-gene classifier was 100% specific in determining MA tumors in a training set using gene expression data as a standard. In a validation set, the 2-gene assay was 66% correlative with AR IHC positivity when the IHC cut-off was set at 10% positive tumor cells. Cell lines predicted to express the MA gene signature by the 2-gene classifier proliferated in response to androgen. This effect was blocked by Flutamide. Conclusions: These results indicate that AR IHC using a 10% cut-off may not completely correlate with the MA gene signature. Further refinement of AR IHC scoring criteria may produce greater specificity. Cell proliferation data suggests the 2-gene assay can predict tumors that will proliferate in response to androgen. Work is ongoing to determine the correlation between the 2-gene assay results, AR IHC and DASL gene expression data to fully understand the predictability of this assay. Understanding this correlation may allow use of simple clinical assays to accurately select patients responsive to agents that block AR signaling. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P5-01-09.

Abstract NSCLC is the cancer with highest death rate; it is typically diagnosed at a late stage and has limited therapeutic options. FGFR signaling is a potential oncogenic driver in many cancers, including NSCLC. In this study we evaluated the copy number variations (CNVs) of FGFR1 and FGFR2 by dual color FISH in specimens from 139 NSCLC patients (78 SCC, 46 ADC, 15 other). CNVs were observed for both FGF receptors. However, FGFR1 was more frequently affected by CNV than FGFR2 (45% vs. 17%). Only a small fraction of patients exhibited CNV of both receptors. In general, the level of gene amplification was higher for FGFR1 as compared with FGFR2. Interestingly, FGFR2 CNV exhibited a high degree of intra-tumor heterogeneity. FGFR1 gene dose elevations were observed due to gene locus amplification (27%) as well as polysomy of chromosome 8 (17%). The degree of gene locus amplification was classified from low (gene ratio 1.5 – 2.5) to high (>4.5). An analysis of the two most common histologies (i.e. Squamous Cell Carcinoma (SCC) and Adenocarcinoma (ADC)) indicated that gene locus amplifications were more frequent in SCC (38%) as compared with ADC (7%), while polysomy of chromosome 8 was observed at similar rates (18-19%). Lack of FGFR1 rearrangements was confirmed using a break-apart FISH probe. FGFR2 gene dose elevations show gene locus amplifications and polysomy of chromosome 10. Locus amplifications of FGFR2 were observed in 11% of SCC, but were not found in ADC. Similar rates for polysomy of FGFR1were observed in SCC (7%) and ADC (5%). Overall, gene dose elevation of FGFR1 and FGFR2 were found more frequently in SCC. Of higher relevance is the fraction of patients with gene dose elevation due to gene locus amplification. Approximately 40% of the SCC patients possess gene locus amplification of at least one of the two probed FGF-receptors. However, only ∼9% of the SCC patients have both loci amplified. In conclusion here we present for the first time evidence for a potential genetic addiction of NSCLC, specifically on FGFR1 gene locus amplification. Therefore targeting FGFR in combination with proper patient stratification, may be an attractive opportunity to develop improved clinical options for treatment of NSCLC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4177. doi:10.1158/1538-7445.AM2011-4177

Patients with hormone refractory prostate cancer (HRPC) have very few clinical options. A bottle neck in development of new therapies is the poor understanding of the molecular basis of hormone independency. A pathway thought to be important in this progression is FGFR. Amplification of FGFR1 has been observed in breast cancer and has led to the hypothesis that it is involved in Tamoxifen resistance (Turner et al., 2010). Here we evaluated the copy number variations (CNV) of the gene loci of FGFR1 (8p12) and FGFR2 (10q26) by dual color FISH in FFPE tissue of recurrent PC patients (n=28), non-recurrent PC patients (n=15), PC patients undergoing palliative RPE (n=15), patients with benign prostate hyperplasia (n=17) and tumor free tissue samples (n=12). We analyzed CNV between different clinical patient subgroups. Two types of CNV for the gene loci of FGFR1 and FGFR2 were observed. Either the gene dose of the target gene locus occurred to be amplified or the gene dose was elevated due to polysomy of the respective chromosome. Furthermore patients with CNV of FGFR1 or FGFR2 exhibited in 40-50% intra tumor heterogeneity by presenting normal cells and cells with CNV. FGFR1 gene dose elevations (either due to gene locus amplification or polysomy of chromosome 8) were observed in 7% (1/15) of patients without recurrence but in 49% (17/35) of the patients with recurrence. Also, in patients undergoing palliative RPE 75% (12/16) of the patients exhibited FGFR1 gene dose elevation. In the case of FGFR2, gene dose elevations (gene locus amplification or polysomy of chromosome 10) were observed in none of the patients without recurrence but in 13% of the patients with recurrence and in 20% of patients undergoing palliative RPE. In the control groups such variations were not found. Interestingly, the gene dose variations differed in the prostate cancer patients depending on their hormone sensitivity. 47% (7/15) of hormone refractory patients and 30% (6/20) of the hormone sensitive patients showed elevated FGFR1 gene dose, for FGFR2, 30% and 20% of the respective subgroups were affected. In summary we conclude that this is first evidence that CNV of FGFR1 and FGFR2 might have implications for hormone resistance in PC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3211. doi:10.1158/1538-7445.AM2011-3211

Fibroblast growth factor receptors (FGFRs) are widely expressed in multiple organ systems and are involved in growth and angiogenesis. Mutations, translocations and amplifications in FGFR genes have been observed in several types of cancer. The purpose of this study was to identify biomarkers that may predict sensitivity and may change upon FGFR inhibition. 240 tumor cell lines from different types of cancer were treated with a small molecule FGFR inhibitor and IC50 values were calculated. Mutations, amplifications, deletions, gene expression analysis, and network analysis were used to find biomarkers that were sensitive or resistant to the inhibitor. Xenografts were used to identify pharmacodynamics biomarkers. Tumors from cancer patients were analyzed for FGFR gene amplifications using Fluorescent in situ hybridization. FGFR1 mRNA overexpression and FGFR2 amplification were identified as sensitive biomarkers while Kras mutation was associated with resistance. Multiple sensitive cell lines (n = 2–4) were found in cells derived from breast, lung, gastric, kidney, lymphoma, sarcoma, melanoma, and endometrial cancer. No sensitive cell lines were found in colorectal, pancreatic, leukemia, myeloma, or ovarian cancer. In human breast cancer cell lines, amplifications were found for FGFR1 (23%), FGFR2 (11%), and FGFR4 (16%). Of the 26 breast cancer cell lines analyzed for FGFR1 amplification, 5 had moderate amplification (4–10 copies) and 1 was highly amplified (>10 copies). In non-small cell lung cancer cell lines, amplifications were found for FGFR1 (37%) and FGFR2 (20%). In xenografts, pS6 and pMAPK levels changed upon compound treatment. FGFR1 and FGFR2 amplifications were also found in prostate (15% and 15%, respectively) tumors from patients. This study identified biomarkers for an FGFR small molecule inhibitor. These results may provide a rationale for patient selection and patient dosing when using a FGFR inhibitor. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr C12.

Abstract Background: CCL2 is a potent chemoattractant for tumor-associated macrophages, which promotes tumor growth and metastasis. The CCL2/CCR2 interaction plays a key role in promoting tumor inflammation, angiogenesis, proliferation and metastasis. Ovarian tumors and tumor lines secrete CCL2, however, very little is known about the expression of CCR2 and macrophage markers in ovarian tumors. Using a Yale University ovarian cancer tissue microarray cohort with associated outcome data, we analyzed the expression of CCL2, CCR2, and macrophage markers CD68, iNOS (M1 marker) and Arginase-1 (M2 marker) using fluorescence immunohistochemistry methods. Methods: The Yale YTMA18-2 Ovarian Cancer tissue microarray cohort consists of 239 stage I–IV ovarian tumors of all major histological subtypes and also included 12 normal gynecologic tissue samples for comparison purposes. The expression levels were assessed using Automated QUantitative Analysis (AQUA® technology, HistoRx Inc.) and were correlated with clinical outcome. CCR2 and CCL2 were measured within pan-cytokeratin defined cytoplasmic regions, and CD68, iNOS and Arginase-1 were measured within the entire sample regions. These biomarkers were analyzed for relationships with each other by Spearman Rho analysis and unsupervised hierarchical clustering, and for association with outcome by Cox univariate analysis and Kaplan-Meier analysis. Punch cores from the tumor sample utilized in the ovarian cancer tissue microarray cohort were also analyzed for genotyping five SNPs in the CCL2 promoter region. Results: There was no significant difference in CCL2, CCR2, CD68, iNOS (M1 marker) and Arginase-1 (M2 marker) expression by age group, stage or major histology grouping (all p>0.05). When looking at all tumor tissues, there was a significant difference in patient outcome (10 year and full time period, p = 0.028 and p = 0.047, respectively) based on separation by CCL2 cluster-based expression groupings. High CCL2 expression patients have a worse outcome, with a 1.9 fold higher risk of death at 5 years than other patients in categorical Cox univariate analysis. Although there was no correlation between CCR2 and CCL2, Kaplan-Meier analysis of unsupervised cluster groupings based on both markers identified a subset of ovarian cancer patients with high expression of CCL2 and intermediate/high expression of CCR2 that have the poorest survival compared with other groupings. Additionally, ovarian tumor tissues expressed 3.5-fold higher level of CCL2 and 1.2 -fold higher levels of CCR2 (mean AQUA scores, respectively) compared to normal samples (p< .0001). There were no significant differences in patient outcome by CD68, iNOS (M1 marker) and Arginase-1 (M2 marker)cluster groupings. There was a statistically significant difference in patient outcome by Kaplan-Meier analysis between two SNPs but no correlation with CCL2 expression was observed. Conclusion: Taken together, these data suggest that there is a subset of ovarian cancer patients with elevated CCL2 protein expression levels associated with poor outcome. This is the first study to show a link between high CCL2 protein expression levels and poor survival in ovarian cancer. Thus, additional exploration of CCL2 expression levels as a predictive biomarker in ovarian cancer is warranted. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):C19.