Riska, Shaun M.

104 Background: Currently there are no serum predictive markers of response to AA. We used a proteomic based analytic approach to identify candidates. Methods: Serum from three non-localized prostate cancer cohorts was analyzed. The first included15 paired untreated hormone-sensitive “pre-AA” and 3-month “post-AA” specimens; the second included 10 “early AA failure” (median time to AA failure:11 months) and the third included 10 “late AA failure” specimens (median time to AA failure: 95 months). Proteomic analysis was performed with isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS). Differentially expressed candidate proteins were identified by comparisons of (i) paired pre/post-AA proteomes and (ii) post-AA proteome with the combined AA failure cohorts at a False Discovery Rate of 0.2. ELISA assays were used to verify candidate markers in a second stored aliquot of first cohort specimens. This cohort was followed for AA failure. Association of post-AA ELISA levels of candidate markers with time to AA failure was performed using Cox proportional hazards regression, summarized as relative risk (RR) for AA failure. Results: Median PSA in pre/post-AA first cohort were 3.15 ng/ml and 0.29 ng/ml. Median PSA in the second and third cohorts were 27.3 and 4.3 ng/ml. Between post-AA and AA failure cohorts, 149 proteins were differentially expressed. Between early and late AA failure 98 proteins were differentially expressed; 47 proteins were common in both comparisons. ELISA assays verified expression levels of 2/47 proteins in the first cohort; zinc alpha-2 macroglobulin (ZAG), and Neuropilin-2 (NPL2). Median change in ZAG decreased by 2073.5 ng/ml (post versus pre-AA) while median change in NPL2 levels increased by 2.9 ng/ml. After a median follow-up of 43 months from the post-AA time-point, 4/15 first cohort subjects had failed AA. The RR of AA failure for ZAG levels below the median change was 3.8 (95% CI: 0.4-37) and 3.0 (95% CI: 0.3-29) for NPL2. Conclusions: A global proteomic analysis identified ZAG and NPL2 as candidate serum predictive markers of AA response which needs further validation.

Abstract Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer. Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed. Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34–0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44–1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27–0.74), P = 0.0015]. Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794–801. ©2017 AACR.

Objectives To evaluate the prognostic significance of germline variation in candidate genes in patients with castration‐resistant prostate cancer (CRPC). Methods Germline DNA was extracted from peripheral blood mononuclear cells of patients with CRPC enrolled in a clinically annotated registry. Fourteen candidate genes implicated in either initiation or progression of prostate cancer were tagged using single nucleotide polymorphisms (SNPs) from HapMap with a minor allele frequency of >5%. The primary endpoint was overall survival (OS), defined as time from development of CRPC to death. Principal component analysis was used for gene levels tests of significance. For SNP‐level results the per allele hazard ratios (HRs) and 95% confidence intervals (CIs) under the additive allele model were estimated using Cox regression, adjusted for age at CRPC and Gleason score (GS). Results A total of 240 patients with CRPC were genotyped (14 genes; 84 SNPs). The median (range) age of the cohort was 69 (43–93) years. The GS distribution was 55% with GS ≥8, 32% with GS = 7 and 13% with GS <7 or unknown. The median (interquartile range) time from castration resistance to death for the cohort was 2.67 (1.6–4.07) years (144 deaths). At the gene level, a single gene, JAK2 was associated with OS ( P < 0.01), and 11 of 18 JAK2 SNPs were individually associated with OS after adjustment for age and GS. A multivariate model consisting of age, GS, rs2149556 (HR 0.67; 95% CI 0.38–1.18) and rs4372063 (HR 2.17; 95% CI 1.25–3.76) was constructed to predict survival in patients with CRPC (concordance of 0.69, P < 3.2 × 10 −9 ). Conclusions Germline variation in the JAK2 gene was associated with survival in patients with CRPC and warrants further validation as a potential prognostic biomarker.

Abstract Colorectal cancer (CRC) is estimated to be the third most common cancer in both men and women in the US in 2012, accounting for over 50,000 deaths. Familial CRC accounts for approximately 30% of all CRC, yet only 5% of familial CRCs can be attributed to mutations in known hereditary colon cancer (HCC) genes. Many families with a strong family history of CRC do not have mutations in known CRC genes. Finding the genes underpinning CRC in these families may improve screening for disease and allow the development of more targeted therapeutics. We completed targeted sequencing of over 2,000 genes and miRNAs in 1,500 cases of CRC from the Colon Cancer Family Registry (CCFR) in an effort to identify rare variants associated with CRC risk and to identify mutations in known CRC genes missed by conventional sequencing. Several categories of genes were included: 18 known HCC genes; 18 candidate HCC genes; 185 genes in previously reported CRC linkage peaks; 1,423 miRNAs; and 363 genes identified through whole exome sequencing of 40 affected cases in 16 families with hereditary CRC (n=2,007 total genes sequenced). Genomic DNA samples were indexed, then libraries were made using Agilent's SureSelect Targeted Enrichment kit. Samples were pooled (96 samples/pool), then each pool of samples was run on five lanes on an Illumina HiSeq2000 (average of 19.2 samples/lane). GenomeGPS, an in-house developed workflow, was used for read alignment, variant calling, and annotation. In early analyses of the first 161 cases, the mean number of mapped reads exceeded 20 million per sample and over 90% of the target region exceeded 40x coverage. A total of 26,484 SNPs were identified and passed quality filtering. Sequencing identified known mutations in MMR genes in positive control cases as well as mutations in HCC genes in previously untested cases. Analysis is currently on-going on the remaining samples and we will report results on the full set of 1500 cases at the meeting. Citation Format: Melissa S. DeRycke, Shanaka R. Gunawardena, Sumit Middha, Shannon K. McDonnell, Shaun M. Riska, Zachary C. Fogarty, Bruce W. Eckloff, Daniel J. Schaid, Ellen L. Goode, Stephen N. Thibodeau. Targeted sequencing to identify rare variants in colorectal cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2548. doi:10.1158/1538-7445.AM2013-2548

Abstract Background: Colorectal cancer (CRC) in densely affected families without Lynch Syndrome may be due to mutations in undiscovered genetic loci. Familial linkage analyses have yielded disparate results; the use of exome sequencing in coding regions may identify novel segregating variants. Methods: We completed exome sequencing on 40 affected cases from 16 multicase pedigrees to identify novel loci. Variants shared among all sequenced cases within each family were identified and filtered to exclude common variants and single-nucleotide variants (SNV) predicted to be benign. Results: We identified 32 nonsense or splice-site SNVs, 375 missense SNVs, 1,394 synonymous or noncoding SNVs, and 50 indels in the 16 families. Of particular interest are two validated and replicated missense variants in CENPE and KIF23, which are both located within previously reported CRC linkage regions, on chromosomes 1 and 15, respectively. Conclusions: Whole-exome sequencing identified DNA variants in multiple genes. Additional sequencing of these genes in additional samples will further elucidate the role of variants in these regions in CRC susceptibility. Impact: Exome sequencing of familial CRC cases can identify novel rare variants that may influence disease risk. Cancer Epidemiol Biomarkers Prev; 22(7); 1239–51. ©2013 AACR.