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Supplementary Tables - PDF file 193K, File contains Tables S1-S11

Supplementary Figure 1 - PDF file 44K, Figure S1, containing pedigrees for each of the 16 families sequenced for the study. Sixteen pages are included.

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.

Appendix 1: Additional Methods for Subtype Assignment Figure S1. Consistency check between published supervised classification vs. novel unsupervised clustering in TCGA Figure S2. Subclasses were computed by applying a consensus NMF clustering method which confirmed the presence of four stable clusters. Consensus matrices and sample correlation matrices are shown for k=2 to k=8 using the 1500 probe sets based on genes described by TCGA. Figure S3. Kaplan Meier analysis of progression free and overall survival for bevacizumab vs. standard treatment. Panel A: total study population. Panel B: patients at high risk for progression (suboptimally cytoreduced stage III and all stage IV patients) Supplemental Table 1. Results of progression-free survival restricted mean

Description of supplementary files - PDF file 44K, File contains description of supplementary files.

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.

Background Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease. Objective To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa. Design, setting, and participants A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls. Outcome measurements and statistical analysis Frequencies of genetic variants (singly or jointly in a gene) were compared between cases and controls. Results and limitations Eleven genes previously reported to be associated with PCa were detected (ATM, BRCA2, HOXB13, FAM111A, EMSY, HNF1B, KLK3, MSMB, PCAT1, PRSS3, and TERT), as well as an additional 10 novel genes (PABPC1, QK1, FAM114A1, MUC6, MYCBP2, RAPGEF4, RNASEH2B, ULK4, XPO7, and THAP3). Of these 10 novel genes, all but PABPC1 and ULK4 were primarily associated with the risk of aggressive PCa. Conclusions Our approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease. Patient summary Multiple genes are associated with prostate cancer (PCa) among men with a strong family history of this disease or among men with an aggressive form of PCa.

OBJECTIVE. This study is designed to identify genes and pathways that could promote metastasis to the bowel in high-grade serous ovarian cancer (OC) and evaluate their associations with clinical outcomes. METHODS. We performed RNA sequencing of OC primary tumors (PTs) and their corresponding bowel metastases (n = 21 discovery set; n = 18 replication set). Differentially expressed genes (DEGs) were those expressed at least 2-fold higher in bowel metastases (BMets) than PTs in at least 30% of patients (P < .05) with no increased expression in paired benign bowel tissue and were validated with quantitative reverse transcription PCR. Using an independent OC cohort (n = 333), associations between DEGs in PTs and surgical and clinical outcomes were performed. Immunohistochemistry and mouse xenograft studies were performed to confirm the role of LRRC15 in promoting metastasis. RESULTS. Among 27 DEGs in the discovery set, 21 were confirmed in the replication set: SFRP2, Col11A1, LRRC15, ADAM12, ADAMTS12, MFAP5, LUM, PLPP4, FAP, POSTN, GRP, MMP11, MMP13, C1QTNF3, EPYC, DIO2, KCNA1, NETO1, NTM, MYH13, and PVALB. Higher expression of more than half of the genes in the PT was associated with an increased requirement for bowel resection at primary surgery and an inability to achieve complete cytoreduction. Increased expression of LRRC15 in BMets was confirmed by immunohistochemistry and knockdown of LRRC15 significantly inhibited tumor progression in mice. CONCLUSIONS. We identified 21 genes that are overexpressed in bowel metastases among patients with OC. Our findings will help select potential molecular targets for the prevention and treatment of malignant bowel obstruction in OC.

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

// Nicholas B. Larson 1 , Shannon K. McDonnell 1 , Zach Fogarty 1 , Melissa C. Larson 1 , John Cheville 2 , Shaun Riska 1 , Saurabh Baheti 1 , Alexandra M. Weber 3 , Asha A. Nair 1 , Liang Wang 4 , Daniel O’Brien 1 , Jaime Davila 1 , Daniel J. Schaid 1 and Stephen N. Thibodeau 5 1 Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA 2 Division of Anatomic Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA 3 Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA 4 Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA 5 Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA Correspondence to: Nicholas B. Larson, email: Larson.nicholas@mayo.edu Keywords: prostate cancer, genetic risk, expression quantitative trait loci, mediation Received: April 26, 2017 Accepted: July 29, 2017 Published: September 08, 2017 ABSTRACT Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis -acting associations due to study limitations. While trans -eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans -eQTL associations are mediated by cis -regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis -mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans -eQTL associations that were significantly mediated by cis -regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B , and target trans -genes with known HNF response elements ( MIA2 , SRC , SEMA6A , KIF12 ). We additionally identified evidence of cis -acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1 . The majority of these cis -mediator relationships demonstrated trans -eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Background Mutations in several genes predispose to colorectal cancer. Genetic testing for hereditary colorectal cancer syndromes was previously limited to single gene tests; thus, only a very limited number of genes were tested, and rarely those infrequently mutated in colorectal cancer. Next-generation sequencing technologies have made it possible to sequencing panels of genes known and suspected to influence colorectal cancer susceptibility. Methods Targeted sequencing of 36 known or putative CRC susceptibility genes was conducted for 1231 CRC cases from five subsets: (1) Familial Colorectal Cancer Type X (n = 153); (2) CRC unselected by tumor immunohistochemical or microsatellite stability testing (n = 548); (3) young onset (age

Prostate cancer (PrCa) is highly heritable; 284 variants have been identified to date that are associated with increased prostate cancer risk, yet few genes contributing to its development are known. Expression quantitative trait loci (eQTL) studies link variants with affected genes, helping to determine how these variants might regulate gene expression and may influence prostate cancer risk. In the current study, we performed eQTL analysis on 471 normal prostate epithelium samples and 249 PrCa-risk variants in 196 risk loci, utilizing RNA sequencing transcriptome data based on ENSEMBL gene definition and genome-wide variant data. We identified a total of 213 genes associated with known PrCa-risk variants, including 141 protein-coding genes, 16 lncRNAs, and 56 other non-coding RNA species with differential expression. Compared to our previous analysis, where RefSeq was used for gene annotation, we identified an additional 130 expressed genes associated with known PrCa-risk variants. We detected an eQTL signal for more than half (n = 102, 52%) of the 196 loci tested; 52 (51%) of which were a Group 1 signal, indicating high linkage disequilibrium (LD) between the peak eQTL variant and the PrCa-risk variant (r2>0.5) and may help explain how risk variants influence the development of prostate cancer.

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

e13535 Background: Pediatric patients (pts) receiving long-term vincristine treatment for acute lymphoblastic leukemia (ALL) who carry two variant alleles of CEP72 rs924607 experience more severe peripheral neuropathy (PN) at lower cumulative vincristine doses. The objective of this retrospective pharmacogenetic analysis was to determine if pts homozygous for rs924607 have increased PN risk when receiving short-term vincristine treatment for diffuse large B-cell lymphoma (DLBCL). Methods: Caucasian pts with DLBCL randomized to either of two vincristine-containing regimens (R-CHOP or DA-EPOCH-R) on the CALGB 50303 (Alliance) trial were genotyped for germline rs924607 via TaqMan. Vincristine was administered intravenously 1.4 mg/m2 (2 mg cap) on day 1 of each R-CHOP cycle (1.4 mg/m2/cycle) or 0.4 mg/m2/day (no cap) on days 1-4 of each DA-EPOCH-R cycle (1.6 mg/m2/cycle). Dosing was repeated every 21 days for 6 treatment cycles, for a maximum cumulative vincristine dose of 8.4 (R-CHOP) or 9.6 (DA-EPOCH-R) mg/m2 over 18 weeks. The primary analysis compared risk of NCI CTCAE grade 3 or higher PN in rs924607 homozygous variant pts versus wild-type allele carriers using multivariable Cox proportional hazards regression adjusted for treatment received (R-CHOP vs. DA-EPOCH-R), age (continuous), and sex (male vs. female). A secondary analysis was conducted only in pts assigned to the DA-EPOCH-R arm. Results: Of 307 pts included in the analysis, 32 (10.4%) experienced grade 3+ PN. PN occurrence was nominally lower in homozygous pts (5/59 = 8.5%) than wild-type carriers (27/248 = 10.9%). In the primary analysis, homozygous pts did not experience PN earlier in treatment (Hazard ratio (HR) = 1.04, (95% confidence interval: 0.39-2.75), one-sided p-value = 0.47). There was no significant difference between groups in dose-at-PN occurrence (homozygous (n = 5): 8.81 mg/m2 vs. wild-type carrier (n = 27):6.74 mg/m2, p > 0.05). The secondary analysis in pts on the DA-EPOCH-R arm (n = 147), in which the majority of PN events occurred (n = 27/32 = 84%), homozygous pts (n = 26) did not have significantly increased PN risk (HR = 1.30, p = 0.56). Conclusions: This retrospective analysis of the prospective CALGB 50303 trial did not find that pts homozygous for CEP72 rs924607 had increased PN risk during short-term vincristine treatment for DLBCL. Support: U10CA180821, U10CA180882, U24CA196171; https://acknowledgments.alliancefound.org . ClinicalTrials.gov Id: NCT00118209.

We investigated the serum proteome of hormone-sensitive prostate cancer patients to determine candidate biomarkers associated with androgen deprivation therapy (ADT) efficacy.Serum proteomes generated using isobaric mass tags for relative and absolute quantitation were analyzed using reverse-phase liquid chromatography coupled to tandem mass spectrometry. The advanced hormone-sensitive prostate cancer cohorts studied were: (1) untreated "paired" pre-ADT and 4-month post-ADT hormone-sensitive patients (n = 15); (2) "early ADT failure" patients (n = 10) in whom ADT treatment failed within a short period of time; and (3) "late ADT failure" patients (n = 10) in whom ADT treatment failed after a prolonged response time. Differential abundance was assessed, and ingenuity pathway analysis (IPA) was used to identify interaction networks in selected candidates from these comparisons.Between "post-ADT" and combined "early" and "late" ADT failure groups 149 differentially detected candidates were observed, and between "early" and "late" ADT failure groups 98 candidates were observed; 47 candidates were common in both comparisons. IPA network enrichment analysis of the 47 candidates identified 3 interaction networks (P .01) including 17-β-estradiol, nuclear factor kappa-light-chain enhancer of activated B cells complex, and P38 mitogen-activated protein kinases as pathways with potential markers of response to ADT.A global proteomic analysis identified pathways with markers of ADT response, which will need validation in independent data sets.

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.

BACKGROUND Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa. METHODS Here, we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family). RESULTS Overall, 4,856 candidate gene SNVs were identified, including 1,052 missense and 10 nonsense variants. Twenty missense variants were shared by all three family members in each family in which they were observed. Additionally, 15 missense variants were shared by two of three family members and predicted to be deleterious by five different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and one nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa. CONCLUSIONS Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility. Prostate 74:1371–1378, 2014. © 2014 Wiley Periodicals, Inc.

Array comparative genomic hybridization (aCGH) technology is commonly used to estimate genome-wide copy-number variation and to evaluate associations between copy number and disease. Although aCGH technology is well developed and there are numerous algorithms available for estimating copy number, little attention has been paid to the important issue of the statistical experimental design. Herein, we review classical statistical experimental designs and discuss their relevance to aCGH technology as well as their importance for downstream statistical analyses. Furthermore, we provide experimental design guidance for various study objectives.

To evaluate whether germline variations in genes involved in sex steroid biosynthesis and metabolic pathways predict time to treatment failure for patients with advanced prostate cancer undergoing androgen deprivation therapy (ADT), because there are few known clinical predictors of response.In a cohort of 304 patients with advanced prostate cancer undergoing ADT, we genotyped 746 single-nucleotide polymorphisms (SNPs) from 72 genes from germline DNA (680 tagSNPs from 58 genes and 66 candidate SNPs from 20 genes [6 genes common in both]). Association with the primary end point of time to ADT failure was assessed using proportional hazards regression models at the gene level (for genes with tagging SNPs) and at the SNP level. False discovery rates (FDRs) of 0.10 or less were considered noteworthy to account for multiple testing.At the gene level, TRMT11 showed the strongest association with time to ADT failure (P.001; FDR=0.008). Two of 4 TRMT11 tagSNPs were associated with time to ADT failure. Median time to ADT failure for rs1268121 (AG) was 3.05 years for the AA, 4.27 years for the AG, and 6.22 years for the GG genotypes (P=.002), and for rs6900796 (GA), it was 2.42 years for the GG, 3.52 years for the AG, and 4.18 years for the AA genotypes (P.001). No other gene level or SNP level tests had an FDR of 0.10 or less.Genetic variation in TRMT11 was associated with time to ADT failure. Confirmation of these preliminary findings in an independent cohort is needed.

Pedigrees collected for linkage studies are a valuable resource that could be used to estimate genetic relative risks (RRs) for genetic variants recently discovered in case-control genome wide association studies. To estimate RRs from highly ascertained pedigrees, a pedigree "retrospective likelihood" can be used, which adjusts for ascertainment by conditioning on the phenotypes of pedigree members. We explore a variety of approaches to compute the retrospective likelihood, and illustrate a Newton-Raphson method that is computationally efficient particularly for single nucleotide polymorphisms (SNPs) modeled as log-additive effect of alleles on the RR. We also illustrate, by simulations, that a naïve "composite likelihood" method that can lead to biased RR estimates, mainly by not conditioning on the ascertainment process-or as we propose-the disease status of all pedigree members. Applications of the retrospective likelihood to pedigrees collected for a prostate cancer linkage study and recently reported risk-SNPs illustrate the utility of our methods, with results showing that the RRs estimated from the highly ascertained pedigrees are consistent with odds ratios estimated in case-control studies. We also evaluate the potential impact of residual correlations of disease risk among family members due to shared unmeasured risk factors (genetic or environmental) by allowing for a random baseline risk parameter. When modeling only the affected family members in our data, there was little evidence for heterogeneity in baseline risks across families.

Multiple studies have identified loci associated with the risk of developing prostate cancer but the associated genes are not well studied. Here we create a normal prostate tissue-specific eQTL data set and apply this data set to previously identified prostate cancer (PrCa)-risk SNPs in an effort to identify candidate target genes. The eQTL data set is constructed by the genotyping and RNA sequencing of 471 samples. We focus on 146 PrCa-risk SNPs, including all SNPs in linkage disequilibrium with each risk SNP, resulting in 100 unique risk intervals. We analyse cis-acting associations where the transcript is located within 2 Mb (±1 Mb) of the risk SNP interval. Of all SNP–gene combinations tested, 41.7% of SNPs demonstrate a significant eQTL signal after adjustment for sample histology and 14 expression principal component covariates. Of the 100 PrCa-risk intervals, 51 have a significant eQTL signal and these are associated with 88 genes. This study provides a rich resource to study biological mechanisms underlying genetic risk to PrCa., Single nucleotide polymorphisms—SNPs—have been identified for prostate cancer but whether these SNPs alter the expression of genes is largely unknown. In this study, the authors search for genes located within 2 Mb of the SNPs and identify SNPs that influence gene expression, so called expression quantitative trait loci.

The identification of cis-acting regulatory variation in primary tissues has the potential to elucidate the genetic basis of complex traits and further our understanding of transcriptomic diversity across cell types. Expression quantitative trait locus (eQTL) association analysis using RNA sequencing (RNA-seq) data can improve upon the detection of cis-acting regulatory variation by leveraging allele-specific expression (ASE) patterns in association analysis. Here, we present a comprehensive evaluation of cis-acting eQTLs by analyzing RNA-seq gene-expression data and genome-wide high-density genotypes from 471 samples of normal primary prostate tissue. Using statistical models that integrate ASE information, we identified extensive cis-eQTLs across the prostate transcriptome and found that approximately 70% of expressed genes corresponded to a significant eQTL at a gene-level false-discovery rate of 0.05. Overall, cis-eQTLs were heavily concentrated near the transcription start and stop sites of affected genes, and effects were negatively correlated with distance. We identified multiple instances of cis-acting co-regulation by using phased genotype data and discovered 233 SNPs as the most strongly associated eQTLs for more than one gene. We also noted significant enrichment (25/50, p = 2E−5) of previously reported prostate cancer risk SNPs in prostate eQTLs. Our results illustrate the benefit of assessing ASE data in cis-eQTL analyses by showing better reproducibility of prior eQTL findings than of eQTL mapping based on total expression alone. Altogether, our analysis provides extensive functional context of thousands of SNPs in prostate tissue, and these results will be of critical value in guiding studies examining disease of the human prostate.

Author details Department of Experimental Pathology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA. Henry Ford Health System, Detroit, MI 48202, USA. Cancer Preventive Material Development Research Center (CPMRC), College of Oriental Medicine, Kyunghee University, Seoul 130-701, Republic of Korea. Department of Anesthesiology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. Department of Cardiovascular Disease, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. Department of Obstetrics and Gynecology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. Metabolon, Inc, Durham, NC 27713, USA. Department of Cancer Biology, University of Kansas Medical Center, Kansas City, KN 66160, USA.

Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa.Here, we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family).Overall, 4,856 candidate gene SNVs were identified, including 1,052 missense and 10 nonsense variants. Twenty missense variants were shared by all three family members in each family in which they were observed. Additionally, 15 missense variants were shared by two of three family members and predicted to be deleterious by five different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and one nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa.Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility.

Background Loss of the endosulfatase HSulf-1 is common in ovarian cancer, upregulates heparin binding growth factor signaling and potentiates tumorigenesis and angiogenesis. However, metabolic differences between isogenic cells with and without HSulf-1 have not been characterized upon HSulf-1 suppression in vitro. Since growth factor signaling is closely tied to metabolic alterations, we determined the extent to which HSulf-1 loss affects cancer cell metabolism. Results Ingenuity pathway analysis of gene expression in HSulf-1 shRNA-silenced cells (Sh1 and Sh2 cells) compared to non-targeted control shRNA cells (NTC cells) and subsequent Kyoto Encyclopedia of Genes and Genomics (KEGG) database analysis showed altered metabolic pathways with changes in the lipid metabolism as one of the major pathways altered inSh1 and 2 cells. Untargeted global metabolomic profiling in these isogenic cell lines identified approximately 338 metabolites using GC/MS and LC/MS/MS platforms. Knockdown of HSulf-1 in OV202 cells induced significant changes in 156 metabolites associated with several metabolic pathways including amino acid, lipids, and nucleotides. Loss of HSulf-1 promoted overall fatty acid synthesis leading to enhance the metabolite levels of long chain, branched, and essential fatty acids along with sphingolipids. Furthermore, HSulf-1 loss induced the expression of lipogenic genes including FASN, SREBF1, PPARγ, and PLA2G3 stimulated lipid droplet accumulation. Conversely, re-expression of HSulf-1 in Sh1 cells reduced the lipid droplet formation. Additionally, HSulf-1 also enhanced CPT1A and fatty acid oxidation and augmented the protein expression of key lipolytic enzymes such as MAGL, DAGLA, HSL, and ASCL1. Overall, these findings suggest that loss of HSulf-1 by concomitantly enhancing fatty acid synthesis and oxidation confers a lipogenic phenotype leading to the metabolic alterations associated with the progression of ovarian cancer. Conclusions Taken together, these findings demonstrate that loss of HSulf-1 potentially contributes to the metabolic alterations associated with the progression of ovarian pathogenesis, specifically impacting the lipogenic phenotype of ovarian cancer cells that can be therapeutically targeted.

Although farnesyltransferase inhibitors have shown promising activity in relapsed lymphoma and sporadic activity in acute myelogenous leukemia, their mechanism of cytotoxicity is incompletely understood, making development of predictive biomarkers difficult. In the present study, we examined the action of tipifarnib in human acute myelogenous leukemia cell lines and clinical samples. In contrast to the Ras/MEK/ERK pathway-mediated Bim upregulation that is responsible for tipifarnib-induced killing of malignant lymphoid cells, inhibition of Rheb-induced mTOR signaling followed by dose-dependent upregulation of Bax and Puma occurred in acute myelogenous leukemia cell lines undergoing tipifarnib-induced apoptosis. Similar Bax and Puma upregulation occurred in serial bone marrow samples harvested from a subset of acute myelogenous leukemia patients during tipifarnib treatment. Expression of FTI-resistant Rheb M184L, like knockdown of Bax or Puma, diminished tipifarnib-induced killing. Further analysis demonstrated that increased Bax and Puma levels reflect protein stabilization rather than increased gene expression. In U937 cells selected for tipifarnib resistance, neither inhibition of signaling downstream of Rheb nor Bax and Puma stabilization occurred. Collectively, these results not only identify a pathway downstream from Rheb that contributes to tipifarnib cytotoxicity in human acute myelogenous leukemia cells, but also demonstrate that FTI-induced killing of lymphoid versus myeloid cells reflects distinct biochemical mechanisms downstream of different farnesylated substrates. (ClinicalTrials.gov identifier NCT00602771).

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.

313 Background: We evaluated variation in candidate genes implicated in either initiation or progression of prostate cancer with survival in CRPC stage. Methods: Germline DNA was extracted from peripheral blood mononuclear cells of CRPC patients enrolled in a clinically annotated registry. Fourteen candidate genes were tagged using single nucleotide polymorphisms (SNPs) from HapMap with 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 (HR) and 95% confidence intervals (CI) under the additive allele model using Cox regression adjusted for age at CRCP and Gleason score (GS) were used. Results: Two hundred and forty five CRPC patients who met the criteria of having adequate DNA were genotyped (14 genes, 84 SNPs). The median age of the cohort was 69 years (range 43-93). The GS distribution was 55% with GS≥8, 32% with GS = 7 and 13% with GS < 7 or unknown. Median time from castration resistance to death for the cohort was 2.67 years (IQ range: 1.6-4.07, 144 deaths). At the gene level JAK2 was detected to be associated with OS. Six of 18 JAK2 SNPs were associated with OS after adjustment for age and GS as well as pruning of SNPs in high linkage disequilibrium with each other (see table). In our multivariate model including age, GS, rs2149556, and rs4372063, the adjusted HRs for rs2149556 and rs4372063 were 0.67 (95% CI 0.38-1.18) and 2.17 (95% CI 1.25-3.76), respectively. The protective effect of rs2149556 appears after adjusting for the presence of minor alleles for rs4372063 in this dataset. Conclusions: Germline variation in the JAK2gene is associated with survival in CRPC stage and warrants further validation as a potential prognostic biomarker. [Table: see text]

Changes in miRNA expression are a common feature in colon cancer. Those changes occurring in the transition from normal to adenoma and from adenoma to carcinoma, however, have not been well defined. Additionally, miRNA changes among tumor subgroups of colon cancer have also not been adequately evaluated. In this study, we examined the global miRNA expression in 315 samples that included 52 normal colonic mucosa, 41 tubulovillous adenomas, 158 adenocarcinomas with proficient DNA mismatch repair (pMMR) selected for stage and age of onset, and 64 adenocarcinomas with defective DNA mismatch repair (dMMR) selected for sporadic (n = 53) and inherited colon cancer (n = 11). Sporadic dMMR tumors all had MLH1 inactivation due to promoter hypermethylation. Unsupervised PCA and cluster analysis demonstrated that normal colon tissue, adenomas, pMMR carcinomas and dMMR carcinomas were all clearly discernable. The majority of miRNAs that were differentially expressed between normal and polyp were also differentially expressed with a similar magnitude in the comparison of normal to both the pMMR and dMMR tumor groups, suggesting a stepwise progression for transformation from normal colon to carcinoma. Among the miRNAs demonstrating the largest fold up- or down-regulated changes (≥4), four novel (miR-31, miR-1, miR-9 and miR-99a) and two previously reported (miR-137 and miR-135b) miRNAs were identified in the normal/adenoma comparison. All but one of these (miR-99a) demonstrated similar expression differences in the two normal/carcinoma comparisons, suggesting that these early tumor changes are important in both the pMMR- and dMMR-derived cancers. The comparison between pMMR and dMMR tumors identified four miRNAs (miR-31, miR-552, miR-592 and miR-224) with statistically significant expression differences (≥2-fold change).

International audience; Multiple genome-wide scans for hereditary prostate cancer (HPC) have identified susceptibility loci on nearly every chromosome. However, few results have been replicated with statistical significance. One exception is chromosome 22q, for which five independent linkage studies yielded strong evidence for a susceptibility locus in HPC families. Previously, we refined this region to a 2.53 Mb interval, using recombination mapping in 42 linked pedigrees. We now refine this locus to a 15 kb interval, spanning Apolipoprotein L3 (APOL3), using family-based association analyses of 150 total prostate cancer (PC) cases from two independent family collections with 506 unrelated population controls. Analysis of the two independent sets of PC cases highlighted single nucleotide polymorphisms (SNPs) within the APOL3 locus showing the strongest associations with HPC risk, with the most robust results observed when all 150 cases were combined. Analysis of 15 tagSNPs across the 5' end of the locus identified six SNPs with P-values < or =2 × 10(-4). The two independent sets of HPC cases highlight the same 15 kb interval at the 5' end of the APOL3 gene and provide strong evidence that SNPs within this 15 kb interval, or in strong linkage disequilibrium with it, contribute to HPC risk. Further analyses of this locus in an independent population-based, case-control study revealed an association between an SNP within the APOL3 locus and PC risk, which was not confirmed in the Cancer Genetic Markers of Susceptibility data set. This study further characterizes the 22q locus in HPC risk and suggests that the role of this region in sporadic PC warrants additional studies.

Background Colon cancer arises from the accumulation of multiple genetic and epigenetic alterations to normal colonic tissue. microRNAs (miRNAs) are small, non-coding regulatory RNAs that post-transcriptionally regulate gene expression. Differential miRNA expression in cancer versus normal tissue is a common event and may be pivotal for tumor onset and progression. Methods To identify miRNAs that are differentially expressed in tumors and tumor subtypes, we carried out highly sensitive expression profiling of 735 miRNAs on samples obtained from a statistically powerful set of tumors (n = 80) and normal colon tissue (n = 28) and validated a subset of this data by qRT-PCR. Results Tumor specimens showed highly significant and large fold change differential expression of the levels of 39 miRNAs including miR-135b, miR-96, miR-182, miR-183, miR-1, and miR-133a, relative to normal colon tissue. Significant differences were also seen in 6 miRNAs including miR-31 and miR-592, in the direct comparison of tumors that were deficient or proficient for mismatch repair. Examination of the genomic regions containing differentially expressed miRNAs revealed that they were also differentially methylated in colon cancer at a far greater rate than would be expected by chance. A network of interactions between these miRNAs and genes associated with colon cancer provided evidence for the role of these miRNAs as oncogenes by attenuation of tumor suppressor genes. Conclusion Colon tumors show differential expression of miRNAs depending on mismatch repair status. miRNA expression in colon tumors has an epigenetic component and altered expression that may reflect a reversion to regulatory programs characteristic of undifferentiated proliferative developmental states.

209 Background: Predictive markers of response to AA are not known. In a prior study, we found that 8 single nucleotide polymorphisms (SNPs) from 4 candidate hormone-related genes (JAK2, TRMT11, NKX3-1 and HSD17B12) were associated with response to AA in HSPC in a North American cohort of 519 subjects. We attempt to replicate these findings in a cohort of Portuguese patients. Methods: The Portuguese cohort consisted of 308 HSPC patients, and the primary endpoint was time to AA failure, defined as time from initiating continuous AA to two serial PSA increases over the nadir, initiation of chemotherapy for progressive disease, or clinical or imaging based progression, whichever came first. For each SNP, we calculated hazard ratios (HRs) and 95% confidence intervals (CI) for time to AA failure using a recessive model with adjustment for Gleason score (GS). Results: The median age of the Portuguese cohort was 69 years (range 43, 85). The GS distribution was 35% subjects with GS≥8; 35% with GS=7 and 30% with GS

255 Background: In a prior study, we found that 8 single nucleotide polymorphisms (SNPs) from 4 candidate hormone-related genes (JAK2, TRMT11, NKX3-1 and HSD17B12) were associated with overall survival (OS) in CRPC stage in a North American cohort of 519 subjects. We attempt to replicate these findings in an independent cohort of Portuguese patients. Methods: A hundred and forty CRPC stage patients in the new cohort were genotyped fort he candidate SNPs. The primary endpoint was overall survival (OS), defined as time from development of CRPC to death. For SNP level results we estimated hazard ratios (HR) and 95% confidence intervals (CI) under the dominant allele model using Cox regression and adjusted for age and Gleason score (GS). Results: The median age of the Portuguese cohort was 69 years (range 53-84). The GS distribution was 48% subjects with GS≥8; 35% with GS=7 and 17% with GSG; MAF = 0.16) in the TRMT11gene was associated with OS after adjustment for age and GS: (dominant model p=0.05, HR=0.56; 95 CI=0.31-1.00). No other SNP was observed to have statistical significance with OS (Table 1). Conclusions: Variation in the TRMT11 gene is significantly associated with overall survival in patients with CRPC and warrants further validation as a potential prognostic biomarker. [Table: see text]

5509 Background: ICON7 demonstrated that the addition of bevacizumab to carboplatin and paclitaxel improves progression free survival (PFS), but not overall survival (OS) in first-line treatment of...

5082 Background: We evaluated the association of germ-line variation in 10 candidate genes important in prostate cancer biology (NKX3-1, JAK2, SLCO2B1, STAT3, CYP19A1, HSD17B4, TRMT11, PRMT3, HSD17B12, NCOA4) with failure of AA in advanced prostate cancer patients. Methods: Patients (N=619) were enrolled for genotyping at the time of AA failure. Candidate genes were selected from the literature and previous pilot studies in smaller cohorts which had identified variation in TRMT11 and HSD17B12 to be associated with AA failure. Genes were tagged using single nucleotide polymorphisms (SNPs) from HapMap with minor allele frequency of >5% and r2≥0.8. DNA was extracted from peripheral blood and genotyped using Illumina Veracode platform. The primary endpoint was time to failure on AA, defined as time from initiating continuous AA to two serial PSA increases over the nadir or clinical or imaging based progression, whichever came first. Principal component analysis was used for gene-levels tests. Association with the primary endpoint was assessed using proportional hazards regression models at the gene-level and at the SNP level. For SNP level results we estimated per allele (ordinal model) hazard ratios (HR) and 95% confidence intervals (CI) using Cox regression, adjusted for Gleason score (GS). Results: We successfully genotyped 60 SNPs (from 10 genes) in 519 subjects. The median age of the cohort was 71 years (range 43, 92). The GS distribution was 51% subjects with GS≥8; 33% with GS=7 and 17% with GS

75 Background: We investigated the association of germline variation in ten candidate genes important in prostate cancer biology (NKX3-1, JAK2, SLCO2B1, STAT3, CYP19A1, HSD17B4, TRMT11, PRMT3, HSD17B12, NCOA4) with overall survival (OS) in a cohort of metastatic CRPC stage patients. Methods: Patients (N=497) were enrolled at the time of androgen deprivation therapy failure for D2 stage prostate cancer. Candidate genes were selected from the literature and pilot studies. Genes were tagged using SNPs from HapMap with minor allele frequency (MAF) of >5% and r2≥0.8. DNA was extracted from peripheral blood and genotyped using Illumina Veracode platform. The primary endpoint was OS, defined as time from development of CRPC to death. Principle components analysis was used for gene-levels tests. To account for multiple testing we calculated the false discovery rate (FDR). For SNP level results we estimated per allele (ordinal model) hazard ratios (HR) and 95% confidence intervals (CI) using Cox regression and adjusted for age and Gleason score (GS). Results: We successfully genotyped 60 SNPs (from 10 genes) in 497 Caucasian subjects. The median age of the CRPC cohort was 71 years (range 43,93). The GS distribution was 51% subjects with GS≥8; 32% with GS7 and 17% with GSC; MAF = 0.22) and rs7005368 (dominant model p=0.05, HR=1.38, 95CI=1.0-1.92; G>A; MAF=0.07). Both SNPs are in Hardy Weinberg Equilibrium and in complete LD (D'=1), although r2 is low (r2=0.025) due to different allele frequencies. Conclusions: Variation in the homeobox NKX-1 gene, a prostate specific tumor suppressor gene involved in prostate development and carcinogenesis is significantly associated with OS in CRPC after accounting for age and GS. Further validation is needed to develop these as prognostic biomarkers.

11 Background: Currently there are no serum markers of response to AA. We performed a proteome based analysis of serum from prostate cancer patients, followed by mapping of candidate markers to networks based on known molecular interactions in Ingenuity Knowledge Base (IKB). Methods: Isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS) was performed in serum of 3 non-localized prostate cancer cohorts. The first cohort included 15 paired untreated hormone-sensitive “pre AA” and 3-month “post AA” specimens; the second included 10 “early AA failure” (median failure time: 11 months) and the third included 10 “late AA failure” specimens (median failure time: 95 months). 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. To facilitate biological interpretation of multiple candidates identified in the comparisons, IPA was used. Candidate markers implicated in IPA networks with statistical significance were pursued in a second, independent patient cohort for association with time to AA failure using univariate Cox regression analysis. Results: Median PSA for pre/post AA first cohort were 3.15 and 0.29 ng/ml. Median PSA for 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. Network enrichment analysis of the 47 proteins by IPA identified four interaction networks (p

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.

Background Expression level of many genes shows abundant natural variation in human populations. The variations in gene expression are believed to contribute to phenotypic differences. Emerging evidence has shown that microRNAs (miRNAs) are one of the key regulators of gene expression. However, past studies have focused on the miRNA target genes and used loss- or gain-of-function approach that may not reflect natural association between miRNA and mRNAs. Methodology/Principal Findings To examine miRNA regulatory effect on global gene expression under endogenous condition, we performed pair-wise correlation coefficient analysis on expression levels of 366 miRNAs and 14,174 messenger RNAs (mRNAs) in 90 immortalized lymphoblastoid cell lines, and observed significant correlations between the two species of RNA transcripts. We identified a total of 7,207 significantly correlated miRNA-mRNA pairs (false discovery rate q