Rider, David N.

5077 Background: A standard of care (SOC) for the adjuvant treatment of ovarian and primary peritoneal cancer is a platinum-based intravenous (IV) chemotherapy doublet. Intraperitoneal (IP) chemotherapy is also a SOC, but the high incidence of grade 3/4 adverse events has limited its acceptance among clinicians. To identify genetic markers for completion of IP chemotherapy, we analyzed SNPs in four genes known to play a role in metabolism of platinum or taxane drugs. Methods: Patients diagnosed with primary or recurrent stage III or IV epithelial ovarian or primary peritoneal cancer who had primary or secondary debulking surgery at Mayo Clinic (Rochester, MN) between January 2007 and February 2009 followed by IP chemotherapy were included in this study. A cycle was defined as IV paclitaxel (135mg/m2) on day one, IP cisplatin (100mg/ m2) on day two, and IP paclitaxel (60mg/ m2) on day eight. With prior consent from the patient, peripheral blood was obtained before treatment for extraction of germline DNA. Using a custom Illumina BeadXpress 96-plex panel, SNPs in GSTM1 (N=7), ABCB1 (N=57), CYP3A4 (N=7), and CYP2C8 (N=25) were genotyped. The association between SNPs in these subsets of genes and completion of IP chemotherapy was analyzed using linear regression. Results: Thirty-seven patients were included in this study and 16 (43.2%) completed IP chemotherapy. Twenty-two out of the fifty-seven ABCB1 SNP’s were associated with the number of cycles (p<0.15). There were no significant associations for GSTM1, CYP3A4 and CYP2C8 SNP’s. The minor A allele at missense SNP rs2229109 in the ABCB1 gene was present in five (31.2%) who completed treatment and only one (4.8%) who did not (p<0.007). However, the later was due to catheter complication. There was no association between rs2229109 and overall or progression-free survival. Conclusions: Our findings suggest that SNP rs2229109 in ABCB1 gene is associated with completion of IP chemotherapy, and potentially, less toxicity from chemotherapy. Thus, these patients may be optimal candidates for IP chemotherapy. Further studies in a larger population are needed.

Abstract Abstract 1242 Background: While bivariate interactions between Factor V Leiden, prothrombin G20201A and hereditary deficiency of antithrombin, protein C and protein S compound VTE risk, whether other gene-gene interactions are associated with VTE is largely unknown. Objective: To test novel gene-gene interactions for an association with VTE. Methods: Genome-wide scan (Illumina 660Q [557,112 SNPs]) and candidate gene (12,551 SNPs in 764 genes within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways) genotypes from 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status) were merged and imputed to about 2.5 million SNPs with MACH using HapMap Phase 2 (60 CEU). We tested all pairwise SNP-SNP interactions using a 2-stage procedure (fast epistasis in the first stage and age, gender, MI/stroke status and state of residence adjusted analysis using logistic regression in the second stage). Results: The mean ± standard deviation case and control ages were 54.4 ± 16.2 and 55.6 ± 15.8 years, respectively and 51% were female. Among 2.299×10^12 pairwise interactions tested, 900 million reached a p-value<E-06 and were be tested in the second stage. Of these, 2417, 278 and 22 SNP-SNP interactions reached p-values ≤1E-9, 1E–10, and1E-11 respectively; 121 SNP-SNP interactions reached the Bonferroni statistical significance threshold (≤5.555659E-11). The gene-gene pairwise interactions with p-values≤1E-11 were: (1) chromosome 3 open reading frame 70 (C3orf70) – short-chain dehydrogenase/reductase (SDR family) member 4 (DHRS4), (2) 1-acylglycerol-3-phosphate O-acyltransferase 4 (AGPAT4) - NIMA (never in mitosis gene a)-related kinase 6 (NEK6), and (3) TatD DNase domain containing 2 (TATDN2) – WAS protein family, member 3 (WASF3). No gene function data are available for C3orf70. DHRS4 encodes for a 3-ketosteroid reductase important for active steroid hormone regulation, AGPAT4 is important for signal transduction and lipid biosynthesis, NEK6 encodes for Nek6 which downregulates p53-induced cancer cell senescence, TATDN2 encodes a deoxyribonuclease, WASF3 encodes for a member of the Wiskott-Aldrich syndrome protein family which are key regulators of signal transduction and cytoskeletal reorganization in hematopoietic cells. Conclusion: Pairwise gene-gene interaction analyses suggest potential associations between VTE and novel genes for future testing in replication studies. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

Abstract Abstract 2295 Background: While interaction between Factor V Leiden and other VTE risk exposures compound VTE risk, whether other gene-environment interactions are associated with VTE is largely unknown. Objective: To test novel gene-environment interactions for an association with VTE. Methods: Genome-wide scan (Illumina 660Q [557,112 SNPs]) and candidate gene (12,551 SNPs in 764 genes within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways) genotypes from 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status) were merged and imputed to 2.5 million SNPs with MACH using HapMap Phase 2 (60 CEU). We tested pairwise interactions between these SNPS and each of 7 exposures (“stress” [defined as ever hospitalized, ever surgery, ever trauma, ever transfemoral procedure or ever leg paresis], ever surgery, ever neurosurgery, ever orthopedic surgery; and among women, ever pregnant, ≥3 pregnancies and ever oral contraceptives/hormone therapy), adjusted for age, gender, MI/stroke status and state of residence, using logistic regression. Results: The mean ± standard deviation case and control ages were 54.4 ± 16.2 and 55.6 ± 15.8 years, respectively and 51% were female. Among the 7 models, a significant interaction was found between stress and A2BP1 (rs735919, OR=0.2, p=2.8E-07), ever surgery and ABCG8 (rs6709904, OR=0.27, p=2.1E-07), orthopedic surgery and SLC24A3 (rs6081599, OR=0.53, p=2.8E-07), neurosurgery and TBC1D4 (rs17064485, OR=8.5, p=3.5E-07), every pregnant and MICALCL (rs11022321, OR=0.17, p=8.3E-07), >3 pregnancies and KLRB1 (rs2536929, OR=0.31, p=1.1E-07) and ever oral contraceptives/hormone therapy and LINGO2 (rs10969259, OR=2.02, p=4.9E-07). A2BP1 plays a role in RBC shape and size, ABCG8 is associated with severe hypercholesterolemia, SLC24A3 is important for intracellular calcium homeostasis, TBC1D4 participates in cell signaling in CD4+/CD45RO+ memory T-cells, MICALCL is an extracellular signal-regulated kinase 2-binding protein, KLRB1 regulates natural killer cell function, and LINGO2 encodes a leucine-rich repeat signaling protein. Our observed interaction of VTE risk factors with these genes to compound the risk of VTE requires replication in future studies. If confirmed, functional studies will be important to determine the roles of these gene products in the causal pathway to VTE. Conclusion: VTE risk factors and SNPs within several novel genes may interact to compound the risk of VTE. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

Abstract Abstract 480 Background: While interaction between Factor V Leiden and other VTE risk exposures (i.e., oral contraceptives, hormone therapy, pregnancy, cancer, minor trauma) compound VTE risk, whether other gene-environment interactions are associated with VTE is largely unknown. Objective: To test gene-environment interactions for an association with VTE. Methods: Cases (n=1488) were Mayo Clinic European-American patients of non-Hispanic ancestry with objectively-diagnosed VTE in the absence of active cancer, venous catheter or antiphospholipid antibodies. Controls (n=1439) were Mayo Clinic outpatients without VTE who were frequency-matched on case age, gender, race, MI/stroke status and state of residence. We selected candidate genes relevant to the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways, focusing on platelet, monocyte, neutrophil and endothelial cell agonists, receptors, ligands, signal transduction and adhesion molecules, granule contents and effectors; plasma proteases and inhibitors; matrix metalloproteases; inflammatory cytokines and receptors; estrogen, progesterone and androgen receptors; co-regulators and enzymes related to estrogen metabolism; important enzymes for catechol, homocysteine, thromboxane A2 and prostacyclin biosynthesis and metabolism; and HMG CoA reductase. For these genes (n=750), we selected all non-synonymous coding single nucleotide polymorphisms (SNPs) with minor allele frequency ≥0.5%; the remaining SNPs were selected using an LD tagging algorithm (Carlson et al. AJHG 2004); 479 ancestry-informative markers were also included (total n=13,241 SNPs). Leukocyte genomic DNA was genotyped using a custom Illumina Infinium iSelect platform, including appropriate controls. We tested all pairwise interactions between 12,483 SNPs (12296 autosomal, 187 chromosome X) that passed quality control and each of seven exposures (ever “stress”[defined as ever hospitalized, ever surgery, ever trauma, ever transfemoral procedure or ever leg paresis], ever surgery, ever neurosurgery, ever orthopedic surgery; and among women, ever pregnant, ≥3 pregnancies and ever oral contraceptives/hormone therapy), adjusted for age, gender, MI/stroke status and state of residence, using logistic regression. False discovery rates (q-value) were calculated to estimate the expected fraction of false positive associations due to multiple statistical tests. Results: The mean ± SD case and control ages were 55.3 ± 16.4 and 56.5 ± 15.9 years, respectively, and 51% were female. Analysis of ancestry-informative markers revealed no evidence of population stratification. Among the seven models, a significant interaction (q≤0.05) was found between ever surgery and two genes located on chromosome 1: USF1 (rs2516840, OR=2.1, p=2.0E-06; q=0.02), and F11R (rs790055 & rs790056; OR∼2.29, p∼4E-06; q=0.02); the two F11R SNPs are in complete linkage dysequilibrium (LD), and the USF1 SNP is in moderate LD with the F11R SNPs (r2∼0.6). USF1 encodes for upstream transcription factor 1 which regulates many genes involved in lipid and glucose homeostasis. F11R encodes for the platelet F11 receptor (JAM [junctional adhesion molecule], a cell adhesion molecule important for platelet adhesion to cytokine-stimulated endothelial cells. Conclusion: Interaction between surgery and SNPs within USF1 and F11R are associated with significantly increased risks for VTE. These potential associations require confirmation in future replication studies. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 150 Background: While bivariate interactions between Factor V Leiden, prothrombin G20201A and hereditary deficiency of antithrombin, protein C and protein S compound VTE risk, whether other gene-gene interactions are associated with VTE is largely unknown. Objective: To test gene-gene interactions for an association with VTE. Methods: Cases (n=1004) were Mayo Clinic European-American patients of non-Hispanic ancestry with objectively-diagnosed VTE in the absence of active cancer, venous catheter or antiphospholipid antibodies. Controls (n=1066) were Mayo Clinic outpatients without VTE who were frequency-matched on case age, gender, race, MI/stroke status and state of residence. We selected candidate genes relevant to the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways, focusing on platelet, monocyte, neutrophil and endothelial cell agonists, receptors, ligands, signal transduction and adhesion molecules, granule contents and effectors; plasma proteases and inhibitors; matrix metalloproteases; inflammatory cytokines and receptors; estrogen, progesterone and androgen receptors; co-regulators and enzymes related to estrogen metabolism; important enzymes for catechol, homocysteine, thromboxane A2 and prostacyclin biosynthesis and metabolism; and HMG CoA reductase. For these genes (n=780), we selected all non-synonymous coding single nucleotide polymorphisms (SNPs) with minor allele frequency ≥0.5%; the remaining SNPs were selected using an LD tagging algorithm (Carlson et al. AJHG 2004); 558 ancestry-informative markers were also included (total n=13,237 SNPs). Leukocyte genomic DNA was genotyped using a custom Illumina Infinium iSelect chemistry and platform, including appropriate controls. For these analyses, all pairwise SNP-SNP interactions for 12,313 SNPs were tested using logistic regression. In addition, we tested all Factor V Leiden -, prothrombin G20210A - and ABO non-O blood group - SNP interactions. Results: The mean ± SD case and control ages were 55.3 ± 16.4 and 56.5 ± 15.9 years, respectively, and 51% were female. Analysis of ancestry-informative markers gave no evidence of population stratification. Among almost 76 million pairwise interactions tested, 504, 44 and 8 SNP-SNP interactions reached p-values ≤ 1E-5, 1E-6, and 1E-7 respectively; none reached the Bonferroni statistical significance threshold (≤ 6.6E-10). The gene-gene pairwise interactions with p-values ≤ 1E-7 included: Leptin receptor - Estrogen receptor 1, α1 Antichymotrypsin - β2 glycoprotein 1, CRADD(caspace) - B1 Bradykinin receptor, ILF10 - Prolactin receptor and GFRA2(TGFβ neurotrophic factor receptor) - Bactericidal permeability-increasing protein. Gene-gene pairwise interactions with the lowest p-value for Factor V Leiden -, prothrombin G20210A - and ABO non-group O - were Protein kinase C beta (2.1E-5), von Willebrand Factor (7.6E-4) and Phospholipase C gamma-2 (6.7E-4), respectively. Conclusion: Pairwise gene-gene interaction analyses suggest potential associations between VTE and novel genes and gene pathways. These potential associations require confirmation in future replication studies. Disclosures: No relevant conflicts of interest to declare.

Abstract Individuals from pancreatic cancer families are at increased risk, not only of pancreatic cancer, but also of melanoma, breast, ovarian, and colon cancers. While some of the increased risk may be due to mutations in high-penetrance genes (i.e., BRCA2, PALB2, ATM, p16/CDKN2A or DNA mismatch repair genes), common genetic variants may also be involved. In a high-risk population of cases with either a family history of pancreatic cancer or early-onset pancreatic cancer (diagnosis before the age of 50 years), we examined the role of genetic variants previously associated with risk of pancreatic, breast, ovarian, or prostate cancer. We genotyped 985 cases (79 early-onset cases, 906 cases with a family history of pancreatic cancer) and 877 controls for 215,389 SNPs using the iSelect Collaborative Oncological Gene-Environment Study (iCOGS) array with custom content. Logistic regression was performed using a log-linear additive model. We replicated several previously reported pancreatic cancer susceptibility loci, including recently identified variants on 2p13.3 and 7p13 (2p13.3, rs1486134: OR = 1.36; 95% CI, 1.13–1.63; P = 9.29 × 10−4; 7p13, rs17688601: OR = 0.76; 95% CI, 0.63–0.93; P = 6.59 × 10−3). For the replicated loci, the magnitude of association observed in these high-risk patients was similar to that observed in studies of unselected patients. In addition to the established pancreatic cancer loci, we also found suggestive evidence of association (P &lt; 5 × 10−5) to pancreatic cancer for SNPs at HDAC9 (7p21.1) and COL6A2 (21q22.3). Even in high-risk populations, common variants influence pancreatic cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 25(7); 1185–91. ©2016 AACR.

Abstract Introduction: Peripheral blood leukocyte (PBL) telomere length is associated with colon cancer (CC) risk, but the relationship of PBL telomere length to survival in CC patients receiving chemotherapy is unknown. Methods: We measured relative telomere length (RTL) by qPCR of PBL DNA from 2,748 cases (53% male, 85% white, median age 58 yrs) in the North American Phase III Intergroup Trial N0147 that compared disease-free survival (DFS) among completely resected Stage III CC treated with mFOLFOX6 +/- cetuximab. Tumor markers were assessed, and 12% were BRAF mutant; 35% Kras mutant, and 12% deficient mismatch repair (dMMR). Linear and non-linear prognostic associations of PBL RTL to the primary endpoint of DFS were assessed by Cox models. Optimal categories of RTL were developed using cumulative martingale residual plots, designated from shortest to longest RTL (Table 1). Results: Never smokers had longer PBL RTL (p = 0.0006) than past or current smokers. Those with diabetes mellitus (DM) had longer PBL RTL than those without DM (p = 0.0165). PBL RTL was not associated with any tumor markers (MMR status; p = 0.7174; BRAF mutant vs wild-type (wt); p =0.4039; Kras mutant vs wt; p= 0.1149). PBL RTL was significantly associated with DFS in a non-linear form (p = 0.0389). Cases in the longer RTL category had more favorable DFS than those with shorter or longest RTL, (Table), which remained after adjusting for age, sex , T/N stage, grade, tumor markers, and treatment (p = 0.0230). We observed no significant interaction (p = 0.1490) between RTL categories and treatment. Conclusion: We observed a non-linear association between RTL and DFS in stage III CC, suggesting that an optimal range telomere length can influence tumor behavior in CC patients. Future studies of telomere maintenance mechanisms may help to explain the association of RTL with improved DFS. RTL is associated with smoking and DM in CC cases but further studies are needed to determine if either tobacco use or DM affect survival from CC by modulating PBL telomere length. Citation Format: Nivedita Basu, Ruth A. Johnson, Qian Shi, Garth D. Nelson, Julie M. Cunningham, Richard M. Goldberg, Frank A. Sinicrope, Daniel J. Sargent, Steven R. Alberts, Gloria M. Petersen, Stephen N. Thibodeau, Halcyon G. Skinner, Kristin Litzelman, Songwon Seo, Russell J. Vanderboom, Ronald E. Gangnon, Corinne D. Engelman, David N. Rider, Lisa A. Boardman. Telomeres and survival in stage III colon cancers: Findings from NCCTG N0147 (Alliance) study. [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 5102. doi:10.1158/1538-7445.AM2014-5102

Abstract Background: We investigated the association of germline genetic variation in hormone biosynthesis and metabolism genes with prostate cancer specific mortality in a cohort of advanced prostate cancer patients. Methods: We genotyped 852 single nucleotide polymorphisms (SNPs) from 97 genes in a cohort of 267 advanced prostate cancer patients at the time of progression to castration recurrence (CRPC) during on-going androgen ablation. Tagging SNPs with minor allele frequency (MAF) of &gt;5% and r2 ≥0.8 were selected from HapMap, NIEHS and Seattle SNP databases. Medical records were queried for cause of death. The primary endpoint of time to prostate cancer specific mortality (PCSM), was pre-defined as time from development of CRPC to death from prostate cancer progression. Principle components analysis was used for gene-levels tests, and to account for multiple testing, we calculated the false discovery rate (FDR). For SNP level results, Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using cox regression. Results: The median age of the cohort was 72 years at CRPC. 43% had a Gleason score (GS)=8-10, 33% a GS=7, and 24% a GS&lt;7. After a median follow up of 1.8 years (IQ range: 0.8-3.3 years), 139 patients died, of which 107 were due to prostate cancer progression. In unadjusted gene level analyses, UGT1A7 (p=0.0059; FDR=0.19), UGT1A10 (p=0.0017; FDR=0.17) and UGT1A3 (p=0.0037; FDR=0.18) were associated with PCSM. After adjusting for age and GS, SNPs strongly associated with PCSM are listed in the Table. Conclusions: Variation in UGT genes involved in hormone metabolism yield prognostic information in CRPC. Further validation is needed to develop these as prognostic biomarkers. 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 4174. doi:10.1158/1538-7445.AM2011-4174

Abstract Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that affect prognosis are not known. The nuclear factor-κB (NF-κB) transcription factor family plays an important role in many immune and inflammatory responses, including the response to cancer. We studied common inherited variation in 210 genes in the NF-κB family in 10,084 patients with invasive EOC (5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous) from the Ovarian Cancer Association Consortium. Associations between genotype and overall survival were assessed using Cox regression for all patients and by major histology, adjusting for known prognostic factors and correcting for multiple testing (threshold for statistical significance, P &lt; 2.5 × 10−5). Results were statistically significant when assessed for patients of a single histology. Key associations were with caspase recruitment domain family, member 11 (CARD11) rs41324349 in patients with mucinous EOC [HR, 1.82; 95% confidence interval (CI), 1.41–2.35; P = 4.13 × 10−6] and tumor necrosis factor receptor superfamily, member 13B (TNFRSF13B) rs7501462 in patients with endometrioid EOC (HR, 0.68; 95% CI, 0.56–0.82; P = 2.33 × 10−5). Other associations of note included TNF receptor–associated factor 2 (TRAF2) rs17250239 in patients with high-grade serous EOC (HR, 0.84; 95% CI, 0.77–0.92; P = 6.49 × 10−5) and phospholipase C, gamma 1 (PLCG1) rs11696662 in patients with clear cell EOC (HR, 0.43; 95% CI, 0.26–0.73; P = 4.56 × 10−4). These associations highlight the potential importance of genes associated with host inflammation and immunity in modulating clinical outcomes in distinct EOC histologies. Cancer Epidemiol Biomarkers Prev; 23(7); 1421–7. ©2014 AACR.