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Background: IFN-γ, a cytokine that plays diverse roles in innate and adaptive immunity, has been shown to be essential in anti-tumor immune response. In vitro and in vivo studies have shown the synergistic effect of IFN-γ in combination with HER2-targeting monoclonal antibodies with or without taxane chemotherapy. We have conducted a phase 1 clinical trial of systemic IFN-γ in combination with trastuzumab, pertuzumab, and paclitaxel in HER2-positive metastatic breast cancer. Methods: Two dose levels (DL) of IFN-γ, 50 (DL1) and 75 mcg/m2 (DL2), were evaluated. IFN-γ was given as subcutaneous injection three times weekly starting on day 1 of therapy for 12 weeks. Paclitaxel was administered intravenously (IV) weekly at 80mg/m2 in combination with trastuzumab IV (8 mg/kg loading dose, then 6 mg/m2 q 21 days) and pertuzumab IV (840 mg loading dose, then 420 mg q 21 days). Eligible patients had measurable metastatic HER2-positive breast cancer, were candidates to receive paclitaxel chemotherapy, and had an ECOG PS 0-1. The primary objective of this study was to evaluate the safety and tolerability of the combination therapy during the 12 weeks of treatment and to determine the recommended phase II dose (RP2D). Dose-limiting toxicity (DLT) during cycle one was defined as follows: Non-hematologic or hematologic toxicities that are ≥ grade 3 and probably or definitely related to study therapy which lead to chemotherapy treatment delays > 14 days. Results: A total of nine patients (3 on DL1 and 6 on DL2) were enrolled between 2/2017 and 11/2017. No DLT was observed. For DL1, no serious adverse events (SAE) or significant adverse events (AE) were observed among 3 patients who completed 12 weeks of treatment. For DL2, two out of 6 patients had SAEs including grade 3 pneumonitis (at week 8; treatment was subsequently discontinued) and grade 3 non-neutropenic fever (at week 6), which were possibly related to study treatment. These toxicities, however, did not meet the protocol definition of DLT. Based on these findings suggesting an improved tolerability of DL1 (50 mcg/m2), DL1 was selected as the RP2D. The most frequently observed grade 1 and 2 AEs that were at least possibly related to IFN-γ were fatigue (45%) nausea (36%), myalgia (36%), and fever (27%) diarrhea (18%). No grade 4 AE was noted. Grade 3 AEs included diarrhea, nausea, pneumonitis, non-neutropenic fever. Three out of 9 patients achieved partial response and 6 patients had stable disease per RECIST criteria. Conclusion: IFN-γ in combination with trastuzumab, pertuzumab, and paclitaxel was well tolerated in patients with HER2-positive metastatic breast cancer. Updated results will be presented and the phase 2 neoadjuvant trial is ongoing to further assess the efficacy of this approach. Citation Format: Han HS, Khong H, Costa R, Loftus L, Goodridge D, Henry T, Soliman H, Ismail-Khan R, Fridley B, Czerniecki B. A phase I study of interferon-gamma (γ)plus weekly paclitaxel, trastuzumab and pertuzumab in patients with HER-2 positive breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-09-15.

Despite being immunogenic, high-grade serous ovarian carcinomas (HGSC), the most common histotype, generally are not responsive to immune checkpoint inhibitors. To understand potential reasons for this, we examined associations of tumor-infiltrating B cells and T cells, including sub-populations defined by expression of immune checkpoints and T cell exhaustion markers, with survival in three epidemiologic studies. Analyses included participants in the Nurses’ Health Study (NHS), NHSII, and New England Case-control study who were diagnosed with stage 1-3 HGSC for whom tumor tissue was obtained. B cells (CD19, CD20, CD138), T cells (CD3), and T cell subpopulations (CD3 co-localized with CD8, CD4, PD1, PDL1, LAG3, TIM3) were measured using multiplex immunofluorescence assays performed on tissue microarray slides containing 3 cores per case. For each participant, we summed counts of immune cells infiltrating the tumor and total tumor cells across cores. Counts of immune cell subpopulations were adjusted for the parent cell count using residuals from beta-binomial models. Hazard ratios (HR) and 95% confidence intervals (CI) for overall mortality according to presence/absence or quantiles of immune cells were calculated using Cox proportional hazards regression models adjusting for age at diagnosis, diagnosis year, stage, study, and total tumor cell count. Among 389 women with HGSC, presence vs. absence of CD19+ B cells was suggestively associated with lower mortality (HR 0.79, 95%CI:0.61-1.01); similar associations were observed for CD19-adjusted CD20+ B cells and CD138+ plasma cells (HRs 0.75-0.78, quintile 5 vs. 1).Higher total T cells was associated with improved survival (HR 0.67, 95%CI:0.45-0.99, quintile 5vs. 1). Similar reduced risks were observed with high levels of both CD19+ B cells and CD3+ T cells (HR 0.66) or high levels of one cell type (HRs 0.65-0.75) compared with low levels of both. For the two primary T cell subfractions, lower risk was observed with higher CD3-adjustedCD3+CD8+ cytotoxic T cells (HRs 0.68, 0.73, 0.69, 0.59 for quintiles 2-5 vs. 1), but notCD3+CD4+ helper T cells (HR 0.97, 95%CI: 0.72-1.31, tertile 3 vs. 1). T cells with immune checkpoint markers (PD1, PDL1) and/or markers of T-cell exhaustion (LAG3, TIM3) generally were not associated with mortality or tended to be associated with lower mortality risk, with a significant inverse association observed for CD3-adjusted CD3+PD1+TIM3- cells (HR 0.61,95%CI:0.41-0.92, quintile 5 vs. 1).Overall, higher levels of B cells and CD3+CD8+ T cells in tumor were associated with improved outcomes, consistent with other studies. Congruent with the apparent ineffectiveness of immune checkpoint inhibitors in ovarian cancer, our results do not support that T cells expressing immune checkpoint and/or T cell exhaustion markers are related to worse outcome among women with HGSC. Future analyses will consider multiple cell types simultaneously and the stroma compartment. Citation Format: Shelley S. Tworoger, Mary K. Townsend, Jose Conejo-Garcia, Brooke L. Fridley, Carlos Moran Segura, Daryoush Saeed-Vafa, Naoko Sasamoto, Kathryn L. Terry. Association of ovarian tumor immune profiles with overall survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5887.

New technologies, such as multiplex immunofluorescence microscopy (mIF), are being developed and used for the assessment and visualization of the tumor immune microenvironment (TIME). These assays produce not only an estimate of the abundance of immune cells in the TIME, but also their spatial locations; however, there are currently few approaches to analyze the spatial context of the TIME. Thus, we have developed a framework for the spatial analysis of the TIME using Ripley’s K, coupled with a permutation-based framework to estimate and measure the departure from complete spatial randomness as a measure of the interactions between immune cells. This approach was applied to mIF data collected on tissue microarrays (TMA) and intratumoral regions of interest (ROIs), defined as >90% tumor cells based on pancytokeratin expression and morphology, selected from whole tissue sections from high-grade serous ovarian carcinoma patients (HGSOC) in the African American Cancer Epidemiology Study (94 subjects on TMAs resulting in 263 tissue cores; 93 subjects with 260 ROIs; 27 subjects included in both TMA and ROIs). Cox proportional hazard models, adjusting for stage and age of diagnosis, were constructed to determine the association of abundance and spatial clustering of tumor-infiltrating lymphocytes (TILs; CD3+), cytotoxic T-cells (CD3+ CD8+), and regulatory T-cells (CD3+ FoxP3+) with overall survival. For all models, the referent group was women with no positive cells for the marker of interest. In the analysis of ROIs, HGSOC patients with high abundance and low spatial clustering of TILs (hazard ratio [HR] = 0.069, 95% confidence interval [CI] = 0.01-0.35) and cytotoxic T-cells (HR and CI not estimable as no deaths observed) had the best survival. This finding of better survival in patients with high abundance and low clustering of TILs and cytotoxic T-cells was replicated in the analysis of TMAs (HR = 0.51, 95% CI = 0.31-0.85 for TILs and HR = 0.11, 95% CI = 0.02-0.53 for cytotoxic T-cells). We also demonstrated the models with both abundance and spatial information was more informative than abundance alone (p < 0.01 for CD3+ and CD3+CD8+ in both ROIs and TMAs). High co-localization of regulatory T-cells and cytotoxic T-cells showed best overall survival on both ROI and TMAs (HR=0.49, 95% CI = 0.28-0.88 and HR = 0.42, 95% CI = 0.25-0.71, respectively). The model with spatial co-occurrence information was significantly better than the model with only abundance (p < 0.05). These findings underscore the prognostic importance of evaluating not only immune cell abundance but also the spatial contexture of the immune cells in the ovarian TIME. The use of our framework for spatial analysis of the TIME and immune cell clustering may be applicable in other cancers and provide a novel approach to identification of biomarkers for predicting patient outcomes. Citation Format: Alex C. Soupir, Christopher M. Wilson, Joellen M. Schildkraut, Lauren C. Peres, Brooke L. Fridley. Immune cell clustering in ovarian cancer tumors and its association with survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2541.

Subgroups of Hispanics/Latinos (HL) experience up to 30% higher colorectal cancer (CRC) mortality than non-Hispanic Whites. This disparity is not fully explained by socio-demographics or access to care, suggesting that biology plays a role. However, biological factors have been underexplored, in part due to a lack of diversity in available datasets. To address this limitation, we established the Latino Colorectal Cancer Consortium (LC3) and examined the association between genetic ancestry and somatic mutation frequencies in HL and in non-HL from Total Cancer Care (Moffitt Cancer Center). We hypothesized that ancestral haplotypes that vary across racial/ethnic populations contribute to differential somatic mutational profiles. We identified 321 primary CRC cases (34% HL (majority of Mexican and Puerto Rican origin), 63% non-HL, 3% unknown) and whole exome sequencing data. Somatic mutations were called from tumor/normal pairs using a bioinformatic pipeline including Burrows-Wheeler Aligner, the Genome Analysis Toolkit (GATK), MuTect, and Strelka. High quality mutation calls were filtered to exclude variants at ≥1% in 1000 Genomes. Inherited variants for ancestry analysis were called using GATK. Global proportions of African (AFR), Asian (ASN), European (EUR), and Indigenous American (IA) ancestry were estimated using ADMIXTURE with exome-wide SNPs overlapping 1000 Genomes. The associations between genetic ancestry and somatic mutation status in 38 genes commonly over-mutated in CRC were examined using compositional analysis in the context of logistic regression. Among HL, ancestry proportions were: AFR (mean: 0.15; range: 2 × 10−03-0.63), ASN (0.07; 0.02-0.92), EUR (0.56, 0.08-0.85) and IA (0.22, 3 × 10−03-0.64). Among non-HL, they were: AFR (0.03; 1 × 10−05-0.83), ASN (0.10; 0.01-0.70), EUR (0.85, 0.13-0.93) and IA (0.02, 2 × 10−03-0.65). Genetic ancestry was associated with the presence of any mutation in MSH3 (P=0.014), ACVR1B (P=0.016) or BRAF (P=0.016); or specifically, with the presence of any truncating mutation in TGFBR2 (P=0.018) or ACVR1B (P=0.024). Relative to EUR ancestry, individuals with higher IA ancestry had a lower probability of any BRAF mutation (OR (95% CI)=0.72 (0.55-0.94); P=0.015) and a higher probability of an APC truncating mutation (1.17 (1.00-1.36); P=0.053). In contrast, higher AFR ancestry (relative to EUR) was associated with increased odds of ACVR1B (OR (95% CI)=1.27 (1.02-1.58); P=0.033) or NRAS mutations (1.22 (1.00-1.47); P=0.047) and decreased odds of an FBXW7 mutation (0.87 (0.77-0.98); P=0.023). Our findings from the largest study of CRC somatic landscapes in HL provide early evidence of mutation frequency differences in driver genes associated with genetic ancestry. Our ongoing efforts to expand LC3 will inform the development of ancestry-tailored treatment strategies to benefit diverse populations. Citation Format: Marco Matejcic, Jamie K. Teer, Hannah J. Hoehn, Zhihua Chen, Diana B. Diaz, Nathalie Nguyen, Douglas Cress, Estrella Carballido, Jason Fleming, Domenico Coppola, Mariana C. Stern, Brooke L. Fridley, Jane C. Figueiredo, Stephanie L. Schmit. Genetic ancestry and somatic mutational frequencies in colorectal cancer: Findings from the Latino Colorectal Cancer Consortium [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1192.

Introduction: Much of the information in electronic medical records (EMRs) required for the practice of clinical oncology is contained in unstructured text. While natural language processing (NLP) has been used to extract information from EMR text, accuracy is suboptimal. In late 2018 a powerful new deep-learning NLP algorithm was published: Bidirectional Encoder Representations from Transformers (BERT). BERT set new accuracy records and for the first time achieved human-level performance on several NLP benchmarks. Our goal was to train BERT to extract clinically relevant data from pathology reports with high accuracy. Procedures: Like many cancer centers nationwide, Moffitt Cancer Center employs Certified Tumor Registrars (CTRs) to collect and report data about cancer patients to state and federal agencies. The CTR extracted data are labels that identify, with high accuracy, important information in each pathology report. Consequently, we used this data to tune BERT to perform a question-and-answering (Q&A) task. Our system sought the answers to 2 predetermined questions in each pathology report: “What organ contains the tumor?”, and “What is the kind of tumor or carcinoma?” To achieve this, we matched surgical pathology reports created at Moffitt from January 1, 2007 onwards with structured data extracted by CTRs. The resulting dataset was randomly divided into training (80%) and testing (20%) subsets. After Q&A training, model performance was assessed using the test dataset. Two metrics were calculated for each question: a true-or-false indication of a perfect word-for-word match between the BERT-extracted data and CTR-extracted data; and, the F1 statistic. The latter produces a value between 0% and 100% indicating the degree of overlap between words in the BERT-extracted data and words in the CTR-extracted data. Results: The final dataset contained 14,143 pathology reports (11,520 for training, 2,623 for testing). This dataset included tumors from 228 organ sites involving 232 histological classifications. The three most common organ sites / histological classifications were: Prostate Gland / Adenocarcinoma (6.7%); Breast / Invasive Carcinoma (6.1%); and, Breast Overlapping Lesion / Invasive Carcinoma (5.9%). Our BERT-based Q&A system searched for answers to both questions in each test report. Thus, a total of 5,246 answers were generated. Of these, 4,667 (89%) were a perfect word-for-word match with the corresponding CTR extracted phrases. The mean F1 statistic between the BERT answers and the CTR extracted phrases was 92%. Conclusions: Future efforts will focus on improving performance via unsupervised training of the BERT language model using 484,000 Moffitt pathology reports. We will also extract additional data fields with CTR-matched ground truth labels. Ultimately new NLP transformer models could aid extraction of information from pathology reports and other EMR documents. This, in turn, could greatly facilitate personalized medicine. Citation Format: Ross Mitchell, Rachel Howard, Patricia Lewis, Katie Fellows, Jennie Jones, Phillip Reisman, Brooke Fridley, Dana Rollison. Deep learning for automatic extraction of tumor site and histology from unstructured pathology reports [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2101.

Background: IFN-γ, a cytokine that plays diverse roles in innate and adaptive immunity, has been shown to be essential in anti-tumor immune response. In vitro and in vivo studies have shown the synergistic effect of IFN-γ in combination with HER2-targeting monoclonal antibodies with or without taxane chemotherapy. We previously conducted a phase I trial of IFN-γ in combination with paclitaxel, trastuzumab and pertuzumab (IPTP) in metastatic HER2-positive breast cancer (HER2+BC) based on which we initiated a phase II neoadjuvant study with this combination. Methods: Early stage HER2+BC patients were eligible. Treatment included 12 weeks of weekly paclitaxel 80 mg/m2 IV, trastuzumab IV every 3 weeks x 4 (8 mg/kg loading dose, then 6 mg/m2) and pertuzumab IV every 3 weeks x 4 (840 mg loading dose, then 420 mg) in combination with IFN-γ 50 mcg/m2 subcutaneous injection three times weekly starting on day 1. The primary objective was to evaluate the pathologic complete response rate (pCR) in breast and nodes. This study had a planned interim analysis after 23 patients were evaluable for pCR based on a Simon's two stage design with 90% power and a type I error rate of 0.1. The final proportion of hormone receptor (HR) status among accrued patients will be used for comparison to historical control because pCR is expected to be lower for HR+HER2+BC compared to HR-HER2+BC subtype (25% vs 50% respectively). Here we are reporting the planned interim analysis results. Results: Twenty three patients were enrolled between 1/2018 and 7/2019. Most patients had clinical stage II/III (86%) and 43% were clinically and pathologically node positive. Nineteen out of 23 (82%) had HR+ and 3 had invasive lobular carcinoma. The pCR for all patients was 52% (12/23). The pCR for HR+HER2+ and HR-HER2+ BC subgroup was 57% (11/19) and 25% (1/4) respectively. Further evaluation using RCB (residual cancer burden) showed 12 pts RCB-0, 5 RCB-I, 5 RCB-II, and 1 RCB-III. Two SAE included pneumonitis/heart failure and hematochezia. The most frequently observed grade 1 and 2 AEs were fatigue (69%), diarrhea (59%), rash (41%) and nausea (41%). Grade 3 toxicities (4% or higher) included diarrhea (n=3) and no grade 4 AE was noted. Conclusion: The addition of IFN-γ to neoadjuvant chemotherapy using paclitaxel, trastuzumab and pertuzumab was well tolerated with manageable toxicities. This study evaluated de-escalated treatments only 12 weeks duration and the anthracycline-free regimen which was highly effective with pCR of 52%. The pCR for HR+HER2+BC subtype was 57% which compares favorably to the expected pCR of 25% with neoadjuvant chemotherapy alone in HR+HER2+ patients. This regimen met the criteria to proceed to the second stage of the phase II trial and appears promising especially in HR+HER2+BC. Updated results will be presented at the meeting including correlative studies. Citation Format: Hyo S. Han, Dawn Goodridge, Avan Armaghani, Ricardo Costa, Aixa Soyano Muller, Loretta Loftus, Hatem Soliman, Brooke Fridley, Laila Khazai, Aiana Cerezo, Jesse Hevia, Marilin Rosa, Hung Khong, Brian Czerniecki. A phase II neoadjuvant trial of Interferon-gamma plus weekly paclitaxel, trastuzumab and pertuzumab in patients with HER-2 positive breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT185.

Digital image-based scoring of immunohistochemistry (IHC) staining allows faster, more objective and potentially more reproducible quantification of area stained or cell counts compared to manual scoring. However, predictors of discrepancies between these two assessment methods are not well understood. We examined clinical and pathological characteristics associated with discordance between image-based and manual scoring using ovarian cancer tissue microarrays (TMA) across a range of IHC stains. We evaluated 2,159 TMA cores from 681 ovarian cancer cases stained by four tissue cytoplasmic stains quantified as percentage of the tumor area stained (POSTN, CXCL14, ADH1B, COL11A1) and two immune cell markers quantified by cell count of infiltrating immune cells (CD68, CD163). The TMA slides were scored manually using semi-quantitative scoring by gynecologic pathologists as well as digitally using image-based Definiens automated platform. We used generalized linear mixed models with individual patients and TMAs included as random effects and stain as fixed effect to examine predictors of discordance, defined as absolute difference of ≥1SD in z-scores between image-based and manual scoring, overall and by each stain. The multi-level model included characteristics of the TMA, core, and tumor factors as predictors. Overall, TMA construction by automated robotic system (vs manual), smaller core size or area, borderline (vs invasive tumors), and having no geographic necrosis in the tumor were significantly associated with greater discordance between image-based and manual scoring. Interestingly, all these factors, except geographic necrosis, were differentially associated with discordance across the stains (p-interaction Citation Format: Naoko Sasamoto, Mary Townsend, Farnoosh Abbas-Aghababazadeh, Kathryn L. Terry, Joseph O. Johnson, Jonathan L. Hecht, Brooke L. Fridley, Shelley S. Tworoger. Predictors of discordance between image-based and manual scoring of immunohistochemical stains in ovarian cancer tissue microarrays [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 34.

Genetic risk factors are important contributors to the development of colorectal cancer. Following the definition of a linkage signal at 9q22-31, we fine mapped this region in an independent collection of colon cancer families. We used a custom array of single-nucleotide polymorphisms (SNP) densely spaced across the candidate region, performing both single-SNP and moving-window association analyses to identify a colon neoplasia risk haplotype. Through this approach, we isolated the association effect to a five-SNP haplotype centered at 98.15 Mb on chromosome 9q. This haplotype is in strong linkage disequilibrium with the haplotype block containing HABP4 and may be a surrogate for the effect of this CD30 Ki-1 antigen. It is also in close proximity to GALNT12, also recently shown to be altered in colon tumors. We used a predictive modeling algorithm to show the contribution of this risk haplotype and surrounding candidate genes in distinguishing between colon cancer cases and healthy controls. The ability to replicate this finding, the strength of the haplotype association (odds ratio, 3.68), and the accuracy of our prediction model (∼60%) all strongly support the presence of a locus for familial colon cancer on chromosome 9q. Cancer Res; 70(13); 5409–18. ©2010 AACR.

Introduction: In females, X-chromosome inactivation (XCI) epigenetically silences transcription of one copy of the X chromosome. Which chromosome is silenced is randomly selected, and is tissue- and cell-specific. While some genes are known to escape XCI under normal conditions, aberrant XCI patterns are thought to occur in female-specific cancers, although the role of XCI in ovarian tumorigenesis and progression is largely unknown. The process of XCI is complex, and integration of gene expression, DNA methylation, and copy number data can inform the XCI status of individual genes and chromosome-wide XCI patterns for individual patients. Methods: We evaluated gene- and chromosome-level patterns of XCI by integrating RNA sequence, copy number alteration, genotype, and DNA methylation data to study XCI escape patterns in tumor samples from 99 ovarian cancer patients. We measured allele-specific expression (ASE) for 397 X-linked genes to identify the active alleles for each tumor. Combining ASE data with knowledge of copy number status, we used a Bayesian beta-binomial mixture model to estimate which genes escaped XCI for each patient, and validated our findings using DNA methylation data. To assess global XCI patterns, we performed cluster analyses on the ASE and methylation data, after adjusting for loss of heterozygosity. We examined the relationship between the clusters and clinical factors, including overall survival and time to recurrence. Results: DNA promoter methylation demonstrated inverse regional correlations with ASE. Cluster analyses using ASE and methylation data demonstrated evidence of two tumor clusters, representing normal XCI and global XCI dysregulation. The dysregulated XCI cluster (N=52) was associated with lower X-inactive specific transcript expression as expected (p Conclusions: We identified discrepant gene-level XCI tumor classifications compared to normal tissue and identified a group of patients with chromosome-wide XCI dysregulation associated with worse clinical prognosis. This provides evidence of the role of XCI in ovarian cancer and highlights the need to integrate multiple genomic data types to study XCI. Citation Format: Stacey J. Winham, Nicholas B. Larson, Sebastian M. Armasu, Zachary C. Fogarty, Melissa C. Larson, Kimberly R. Kalli, Kate Lawrenson, Simon Gayther, Brooke L. Fridley, Ellen L. Goode. Integrative analyses of gene expression, DNA methylation, genotype and copy number alterations characterize X-chromosome inactivation in ovarian cancer [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 2420. doi:10.1158/1538-7445.AM2017-2420

To reveal biologic mechanisms underlying clinical outcome of high-grade serous (HGS) epithelial ovarian carcinomas (EOC), we evaluated the association between tumor epigenetic changes and time to recurrence (TTR). We assessed methylation at approximately 450,000 genome-wide CpGs in tumors of 337 Mayo Clinic (Rochester, MN) patients. Semi-supervised clustering of discovery (n = 168) and validation (n = 169) sets was used to determine clinically relevant methylation classes. Clustering identified two methylation classes based on 60 informative CpGs, which differed in TTR in the validation set [R vs. L class, P = 2.9 × 10−3, HR = 0.52; 95% confidence interval (CI), 0.34–0.80]. Follow-up analyses considered genome-wide tumor mRNA expression (n = 104) and CD8 T-cell infiltration (n = 89) in patient subsets. Hypomethylation of CpGs located in 6p21.3 in the R class associated with cis upregulation of genes enriched in immune response processes (TAP1, PSMB8, PSMB9, HLA-DQB1, HLA-DQB2, HLA-DMA, and HLA-DOA), increased CD8 T-cell tumor infiltration (P = 7.6 × 10−5), and trans-regulation of genes in immune-related pathways (P = 1.6 × 10−32). This is the most comprehensive assessment of clinical outcomes with regard to epithelial ovarian carcinoma tumor methylation to date. Collectively, these results suggest that an epigenetically mediated immune response is a predictor of recurrence and, possibly, treatment response for HGS EOC. Cancer Res; 74(11); 3084–91. ©2014 AACR.

Background: Little transcriptomic research has compared epithelial ovarian cancer (EOC) histological subtypes. We set out to characterize the transcriptomes of high-grade serous carcinomas (HGSC) and endometrioid carcinomas (EC), which make up around 70% and 20% of EOC tumors, respectively, and have some histopathological similarities. Methods: Fresh frozen tumors from EOC patients seen at the Mayo Clinic (30 EC and 62 HGSC) were used. 1ug RNA riboZero was used for library preparation using the Illumina TruSeq kit and sequenced on a HiSeq 2000 machine. Reads were aligned using TopHat2 followed by quantification of abundances using RSEM and differential expression analysis with edgeR. We analyzed transcriptomes, conducted pathway analyses, and summarized key candidate gene sets. Expressed SNVs (eSNVs) from the RNA-seq data were determined using GATK and RVboost. Results: The analysis found 699 genes with FDR < 1×10-5 for differential expression between HGSC and EC, with most genes being up-regulated in EC. The top most associated genes were TPH1, MAP2K6, KLK2, ADAM23, TESC and TRAF3IP2 (p Discussion: Using one of the largest sets of identically processed fresh-frozen EOC tumors, some patterns emerged among the numerous EC v HGSC transcriptomic differences. TPH1, up-expressed in EC, is regulated by SOX4 which was also up-regulated in EC. Two sets of genes related to Kallikreins serine proteases were differentially expressed, including KLK2 which is known to regulate EGFR and pro-inflammatory cytokines and is regulated by MYC. Lastly, TRAF3IP2 encodes for a protein involved in regulating cytokines through members of the NFKB pathway. Conclusions: These findings suggest important biological insights into one of the rarer EOC histologies and may aid in the development of targeted treatment options. Research is on-going to incorporate additional features (e.g., DNA methylation, copy number) into a “systems biology” framework to better understand the molecular differences between EOC histologies. Citation Format: Brooke L. Fridley, Junqiang Dai, Rama Raghavan, Chen Wang, Pengcheng Lu, Stacey Winham, Madalene Earp, Kate Lawrenson, Simon A. Gayther, Kimberly R. Kalli, Ellen L. Goode. Transcriptome characterization of high grade serous and endometrioid epithelial ovarian cancer tumors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1833.

The importance of inflammation pathways to the development of many human cancers prompted us to examine the associations between single-nucleotide polymorphisms (SNP) in inflammation-related genes and risk of ovarian cancer. In a multisite case–control study, we genotyped SNPs in a large panel of inflammatory genes in 930 epithelial ovarian cancer cases and 1,037 controls using a custom array and analyzed by logistic regression. SNPs with P < 0.10 were evaluated among 3,143 cases and 2,102 controls from the Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI) post-GWAS collaboration. Combined analysis revealed association with SNPs rs17561 and rs4848300 in the interleukin gene IL1A which varied by histologic subtype (Pheterogeneity = 0.03). For example, IL1A rs17561, which correlates with numerous inflammatory phenotypes, was associated with decreased risk of clear cell, mucinous, and endometrioid subtype, but not with the most common serous subtype. Genotype at rs1864414 in the arachidonate 5-lipoxygenase ALOX5 was also associated with decreased risk. Thus, inherited variation in IL1A and ALOX5 seems to affect ovarian cancer risk which, for IL1A, is limited to rarer subtypes. Given the importance of inflammation in tumorigenesis and growing evidence of subtype-specific features in ovarian cancer, functional investigations will be important to help clarify the importance of inherited variation related to inflammation in ovarian carcinogenesis. Cancer Res; 72(5); 1064–9. ©2012 AACR.

Two cytidine analogues, gemcitabine (dFdC) and 1-β-d-arabinofuranosylcytosine (AraC), show significant therapeutic effect in a variety of cancers. However, response to these drugs varies widely. Evidence from tumor biopsy samples shows that expression levels for genes involved in the cytidine transport, metabolism, and bioactivation pathway contribute to this variation in response. In the present study, we set out to test the hypothesis that variation in gene expression both within and outside of this “pathway” might influence sensitivity to gemcitabine and AraC. Specifically, Affymetrix U133 Plus 2.0 GeneChip and cytotoxicity assays were performed to obtain basal mRNA expression and IC50 values for both drugs in 197 ethnically defined Human Variation Panel lymphoblastoid cell lines. Genes with a high degree of association with IC50 values were involved mainly in cell death, cancer, cell cycle, and nucleic acid metabolism pathways. We validated selected significant genes by performing real-time quantitative reverse transcription-PCR and selected two representative candidates, NT5C3 (within the pathway) and FKBP5 (outside of the pathway), for functional validation. Those studies showed that down-regulation of NT5C3 and FKBP5 altered tumor cell sensitivity to both drugs. Our results suggest that cell-based model system studies, when combined with complementary functional characterization, may help to identify biomarkers for response to chemotherapy with these cytidine analogues. [Cancer Res 2008;68(17):7050–8]

Many germline genetic variants have been found to be associated with susceptibility to epithelial ovarian cancer (EOC), but currently few associations have been identified for EOC outcomes such as overall survival. In the absence of evidence for common germline markers, it is possible that rare variants not captured in GWAS arrays may be associated with overall survival. We hypothesize that rare variants, either individually or combined across a gene, may be associated with overall survival in EOC. We utilized data from two genotyping projects of the Ovarian Cancer Association Consortium (OCAC) that used commercial exome-based arrays. The primary sample, genotyped on the Affymetrix Axiom Exome Array at 227,892 standard and custom variants, consisted of 14 independent EOC studies (4293 cases; 2257 deaths). The secondary sample, genotyped on the Illumina Infinium HumanExome BeadChip at 114,620 variants, consisted of six additional EOC studies (1744 cases; 1027 deaths). Both sets were analyzed using Cox proportional hazards regression to determine the association of each variant with overall survival time. Meta-analysis was conducted across samples at 73,203 overlapping variants. Gene-level tests of over 18,000 genes were also conducted using burden tests and Sequencing Kernel Association Tests (SKAT) adapted for Cox proportional hazards models. Gene-level tests were conducted separately for the primary and secondary cases and then were meta-analyzed. Models were adjusted for age, site, and three principle components. Six individual variants had meta-analysis p-values < 1.0E-4, five of which were rare (MAF < 0.003). Common variant rs8170 (MAF = 0.2) in BABAM1 encoding BRISC and BRCA1 A complex member 1 - previously reported to be associated with EOC risk_showed evidence of association with overall survival (Pmeta = 1.5E-5) and consistent estimates of effect size across both samples (HR1 = 1.18, HR2 = 1.19). In imputed genotype data from over 18,000 subjects from OCAC genotyped on the COGS array, this association reaches genome-wide significance (HR = 1.15, P = 4.7E-9). Five genes had gene-level meta-analysis p-values < 1.0E-4, including top ranked ATG2B (p = 1.1E-6), an autophagy gene important for apoptosis; zinc finger protein PEG3 (p = 1.8E-5), playing a role in autophagy and down-regulated in EOC; helicase-like transcription factor HLTF (p = 1.9E-5), involved in post-replication DNA repair; mitochondrial fission regulator 1-like gene FAM54B (p = 3.1E-5); and T-cell surface glycoprotein CD1E (p = 8.8E-5). With over 6000 EOC cases in the primary and secondary samples, this is the largest genome-wide assessment of rare variant genetic associations with EOC overall survival. Variant rs8170 in BABAM1, a necessary component of the BRCA1 complex, is associated with overall survival. Single variant and gene-level analyses provide complementary approaches, suggesting additional candidates that warrant follow-up study. Citation Format: Stacey J. Winham, Brooke L. Fridley, Melissa C. Larson, Zachary Fogarty, Andrew Berchuck, Yian Ann Chen, Hui-Yi Lin, Georgia Chenevix-Trench, Jenny Permuth-Wey, Thomas A. Sellers, Ailith Pirie, Ellen L. Goode, Ovarian Cancer Association Consortium. Investigation of exome variants associated with overall survival in ovarian cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4636. doi:10.1158/1538-7445.AM2015-4636

Cyclophosphamide (Cy) a DNA alkylating agent, is commonly used for treatment of several malignancies such as breast cancer and lymphoma. It is also widely used in conditioning regimens for bone marrow transplantation. Cy is a prodrug requiring activation to 4-hydroxycyclophosphamide by hepatic cytochrome P450 enzymes. 4-hydroxy-Cy non-enzymatically converts to active phosphoramide mustard (PM), which produces inter and intra-strand DNA crosslinks causing DNA breaks and hence the cytotoxicity. Although of great clinical utility the dose limiting side effects of Cy as myelosuppression, nephrotoxicity, cardiotoxicity, neurotoxicity and bladder toxicity posses clinical challenge. Genetic polymorphisms in P450 enzymes especially CYP2B6 as well as phase II drug metabolizing enzymes has been shown to partially explain the inter-patient variation in response in some studies however role of pharmacodynamics players is still not clear. Thus, we designed the present study to identify genes predictive of phosphoramide mustard response. We utilized EBV transformed lymphoblast cell lines (LCLs) that are part of International HapMap project as the model system and treated these with PM to by pass the CYP mediated activation of Cy. Since most of the Cy metabolizing genes (CYPs) are expressed in liver but not as much in LCLs, use of PM instead of Cy in the present study enriched our ability to identify genes of relevance to the pharmacodynamic significance. Briefly we treated LCLs with six different concentrations of PM (100, 50, 20, 10, 1, and 0.1 μM), due to stability issues PM was prepared fresh for each experiment. Cell viability was determined 48 hr post drug treatment by MTT assays. Genome-wide gene expression and genotype data was obtained from publically available source and was evaluated for association with PM cellular sensitivity. Top 100 SNPs (p< 2×10-5) mapped to 10 genes of biological significance including CREBBP, DPP10, HYAL3, XRCC1, SNAPC3, CCDC21, PSIP1, RASSF1, and SALL4 CREBBP (CREB binding protein) is a major transcriptional regulator for both estrogen dependent breast cancer signaling and Lymphotoxin b receptor signaling pathways. CREBBP has an intrinsic histone acetyltransferase activity that acts as a scaffold to stabilize additional protein interactions with the transcription complex. Gene-expression association analysis identified 34 genes significantly associated with PM cytotoxicity including EIF4E2, MMP16, MUC6, NDUFA2, NDUFA9 and SDHB. Identification of SNPs in XRCC1 further confirmed the impact of altered DNA damage repair/response pathway in compromising PM response. Our results identified genetic markers of pharmacodynamic significance to Cy response thus opening up opportunities for clinical validation of these in patients receiving Cy and moving a step closer to personalized medicine. Citation Format: Lata Chauhan, Brooke L. Fridley, Alice Wang, Jatinder Kaur Lamba. Identification of markers predictive of phosphoramide mustard (PM) cellular sensitivity in lymphoblast cell lines. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5495. doi:10.1158/1538-7445.AM2015-5495

Background: Epithelial ovarian cancer (EOC) is composed of five major histologic types: 1) high-grade serous carcinoma (HGSC), accounting for most cases (∼70%); and the rarer 2) clear cell, 3) endometrioid, 4) mucinous, and 5) low- grade serous carcinoma (LGSC). As EOC risk factors are histology specific, as are the site of precursor lesions, accurate subtyping is critical to understanding EOC prognostic factors and etiology. Our aim was to compare two currently employed histology assignment strategies using gene expression, DNA methylation, and clinical outcome data Methods: Histology assignment based on: a) pathologist, and b) an integrated pathologist and IHC prediction algorithm (pathIHC) (using ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1 staining patterns), was compared for tumors of all histologies at the Mayo Clinic, Rochester. The 500 most variable probes from Illumina Methylation450 BeadChips (N = 259) and Agilent 4×44K expression arrays (N = 245) were used to perform unsupervised hierarchical clustering. Fisher's Exact test was used to test the association of clusters with histology. Cox proportional hazards regression analysis was used to test the association of clusters and histology with time to progression (TTP) and time to death (TTD). Results: Eighty-two percent of tumors were concordant between histology assignment strategies. Clustering based on methylation data produced two distinct clusters. PathIHC produced more homogenous clusters (p-value = 2.8×10-16) than pathology alone (p = 1.3×10-9). Cluster M1, characterized by high levels of methylation across almost all probes, was enriched for the rarer EOC subtypes; cluster M2, characterized by moderate levels of methylation across 50%-75% of probes, was predominantly HGSC. These patterns were observed irrespective of histology assignment strategy; however, when using histology by pathologist, cluster M2 had more endometrioid and LGSC tumors interspersed with HGSC tumors. Clustering based on expression data also produced two clusters. PathIHC produced slightly more homogenous clusters (p = 9.0×10-11, pathology alone, p = 2.3×10-10). Cluster E1 was enriched for the rarer EOC subtypes; cluster E2 was primarily serous lineage tumours (HGSC and LGSC), particularly when using histology by pathIHC. Considering only clinical outcomes, histologies by pathology were more significantly different in terms of TTP (p = 1.1×10-6) and TTD (p = 1.7×10-3) than histologies by pathIHC (TTP, p = 5.4×10-6; TTD, p = 5.7×10-3). Conclusions: Histology by pathIHC produced more homogeneous clusters in both the methylation and expression data; thus, molecular data supports this strategy. Differences in clinical outcomes (TTP and TTD) between histology groups were more pronounced when using assignment by pathologist; thus, clinical data supports this strategy. Citation Format: M A. Earp, S J. Winham, S M. Armasu, B L. Fridley, M C. Larson, Z C. Fogarty, K R. Kalli, C Wang, G L. Keeney, J M. Cunningham, S Ramus, M Kobel, E L. Goode. Comparison of pathology versus IHC-based ovarian carcinoma histology assignment using gene expression, DNA methylation, and clinical outcome data. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4246. doi:10.1158/1538-7445.AM2015-4246

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer death among women in the United States (5% of cancer deaths). The standard treatment for patients with advanced EOC is initial debulking surgery followed by carboplatin-paclitaxel combination chemotherapy. Unfortunately, even with modern chemotherapy, most patients relapse and die with the five-year overall survival around 45%. In addition, those patients that initially respond to taxane-platinum therapy eventually develop platinum-resistant tumors and relapse. Thus, finding novel therapeutics for treating EOC is essential. One approach that has been used widely in cancer drug discovery is Connectivity Mapping (CMAP) using gene expression data and drug phenotype data assessed on cancer cell lines (CCL) (i.e. “sensitive” or “resistant” based on dose-response drug data). However, recent publications have highlighted some issues with the use of these standard CCL sets that are often used in these drug screening studies. Therefore, instead of CMAP analysis based on gene expression signatures developed on drug response data collected on a small set of EOC cell lines, we took a novel CMAP approach based on information collected on EOC patients and clinical endpoints. That is, we determined the gene expression signature (e.g., set of genes) that were associated with time to recurrence in data collected on EOC patients within TCGA (n = 518) and a Mayo Clinic study (n = 474). The set of genes associated with time to recurrence (with and without adjustment for additional clinical covariates) was completed separately for TCGA and Mayo Clinic studies, restricting all analyses to EOC tumor of high-grade serous histology. Each of these 4 sets of genes, where genes with hazard ratios (HR) > 1 coded as “positively” associated and genes with HR < 1 coded as “negatively” associated with the phenotype, were inputted into CMAP software (Broad Institute) to determine a set of drugs for which our signature “matches” the “reference” signature. The drugs that overlapped between the CMAP analyses on the two studies were carried forward for validation studies involving drug screens on a set of 10 EOC cell lines. Of the 11 drugs carried forward, we a priori hypothesized that 5 of these drugs would kill EOC cells (mitoxantrone, podophyllotoxin, wortmannin, doxorubicin, and 17-AAG), for which all 5 showed an ability to kill EOC cells in vitro (cell lines were treated using serial dilutions of the drugs (20-0 μM) for 72 h followed by measuring cell viability using the CellTiter-Blue assay). Further research is on-going to understand the functional mechanism by which these candidate drugs might treat EOC and to apply this bioinformatics approach to other cancer drug screening studies. Note: This abstract was not presented at the meeting. Citation Format: Brooke L. Fridley, Rama Raghavan, Gottfried E. Konecny, Chen Wang, Ellen L. Goode, Harsh B. Pathak, Stephen Hyter. A bioinformatics approach to drug discovery: patient based connectivity mapping. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4853. doi:10.1158/1538-7445.AM2015-4853

Background: We investigated the role of multifactor interactions and epithelial ovarian cancer (EOC) risk using data collected within the Collaborative Oncological Gene-environment Study and the Ovarian Cancer Association Consortium containing 18,000 EOC cases and 26,000 controls. To date, researchers have identified 18 EOC susceptibility loci. However, it has been estimated that many more common variant loci exist; we hypothesized that some of the unexplained variation is due to gene-environment interactions. Similar to breast and endometrial cancers, many EOC risk factors relate to estrogen exposure, and increased levels of estrogen has been associated with obesity in post-menopausal women. Therefore, we hypothesized that gene-environment interactions dealing with hormone-related risk factors could differ between obese and non-obese women. Methods: We considered multifactor interactions between single nucleotide polymorphisms (SNPs) and six hormone-related factors: oral contraceptive use; parity; endometriosis; tubal ligation; hormone replacement therapy (HRT); and estrogen use; and assessed whether these GE interactions differed between obese and non-obese women. The SNPs included in this analysis included the top associated markers within the 18 confirmed risk loci, as well as, 36,811 SNPs that lie within 84 candidate gene regions related to hormone biosynthesis & metabolism and insulin-like growth factors. For the candidate SNP analyses, we assessed multifactor interactions across environmental factors using logistic regression models including age, study site, and population substructure. For the candidate gene analyses, a two-stage screening and testing procedure was utilized. All analyses were completed including: (1) all histologies; and (2) only serous histology. Results: For the 18 known EOC risk loci, no hormone-related risk factors showed statistically significant interaction at a threshold of 10-4. In contrast, the two-stage analysis of the candidate genes found several significant gene-environment-environment effects, after adjusting for multiple testing. For analysis of all cases, the SNPs in the following candidate genes showed a multifactor interaction with a hormone-related risk factor and obesity: IGFBP5 (HRT, rs729597, p = 1.3×10-13), CGA (HRT, rs58124219, p = 1.0×10-5), and SSTR1 (parity, rs77266093, p = 1.1×10-5). Similarly, the serous histology analyses detected a multifactor interaction with HRT, obesity and IGFBP5 (rs729597, p = 8.8×10-5). Additionally, serous only analyses also detected an interaction involving ESR1 (tubal ligation, Chr6:152246911(indel), p = 8.0×10-6). Conclusions: In a very large case-control collection, assessment of multifactor gene-environment interaction is feasible, and, here, suggest that the relationship between SNPs in candidate genes and hormone-related risk factors in EOC susceptibility may vary. Citation Format: Joseph Usset, Brooke Fridley, Ellen Goode, Joellen Schildkraut, Paul Pharoah. Assessment of multifactor gene-environment interactions and ovarian cancer risk: SNPs, obesity, and hormone-related risk factors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4684. doi:10.1158/1538-7445.AM2015-4684

Background: To provide a systematic analysis of formalin fixation artifacts on Illumina sequencing libraries and results, we generated two complementary sequencing libraries (target enrichment sequencing and whole exome sequencing) from 11 pairs of matched formalin-fixed paraffin-embedded (FFPE) and fresh-frozen (FF) tumor samples and two pairs of matched FFPE and FF germline samples. We also generated whole genome sequencing data from a single pair of FF/FFPE tumor samples. Results: The results indicate minimal variations in library fragment size, coverage, and PCR duplicates within FF/FFPE paired samples that are less than 1 year old; whereas, a large variation in these parameters were observed in FF/FFPE pairs in samples that are approximately 2 years old. No significant increase in global mismatch rates and C•G>T•A substitutions were observed in FFPE samples from the former group; whereas, a discernible increase in mismatch rates and C•G>T•A substitutions were observed in FFPE samples from the latter group. However, over 99.7% and 99.5% of concordant calls were observed between matched FF and FFPE pairs at reference and non-reference positions within the targeted regions, respectively. Although an increased rate of global mismatches and C•G>T•A substitutions were observed in some FFPE samples, discordant rates were low (T•A substitutions are comparable in non-reference positions in paired FF and FFPE samples. Conclusions: We developed upfront quality assessment and library preparation method that use low input DNA from FFPE samples to perform next-generation sequencing. The results from our studies indicate the suitability of FFPE samples in sequencing studies. Citation Format: Sarah Munchel, Yen Hoang, Yue Zhao, Joseph Cottrell, Brandy Klotzle, Andrew Godwin, Janelle Noel, Brooke Fridley, Peter Beyerlein, Jian-Bing Fan, Marina Bibikova, Jeremy R. Chien. Targeted or whole genome sequencing of formalin-fixed tissue samples. [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 4281. doi:10.1158/1538-7445.AM2014-4281

An ovarian cancer Genome Wide Association Study (GWAS) identified 9p22.2 as a novel susceptibility locus with the most statistically significant single nucleotide polymorphisms (SNPs) located in an intergenic region near the Basonuclin 2 (BNC2) gene, which codes for a putative transcription regulator containing three pairs of zinc finger (ZF) domains. The minor alleles are protective in terms of ovarian cancer susceptibility. However, the molecular mechanisms by which these SNPs modify susceptibility remain largely unknown. The significant SNPs in the 9p22.2 locus lie in non-coding regions and therefore are hypothesized to affect the activity of regulatory elements and modify the expression of a target gene(s). In order to test this hypothesis we conducted fine mapping for the locus which delimited a ∼74kb region containing SNPs with a p-value less than 10-8. FAIRE-Seq and ChIP-Seq experiments for histone markers conducted in immortalized ovarian surface epithelial cells (IOSE) and fallopian tube epithelial cells (IFTE) were used to prioritize functional SNP candidates which overlap with regulatory elements. Luciferase assays tested the ability of these regulatory elements to activate transcription. Chromosome conformation capture (3C) experiments demonstrate a physical interaction between the BNC2 promoter and candidate regulatory elements containing risk-associated SNPs. Methylation Quantification at Trait Loci (mQTL) revealed an association between decreased methylation at the BNC2 promoter and the protective minor alleles. Expression analysis shows decreased expression of BNC2 in cancer versus normal tissue implicating tumor suppressor function of BNC2. Therefore the protective minor allele likely increases expression of BNC2 which in turn contains tumor suppressing properties that decrease ovarian cancer risk. BNC2 protein is in complex with transcriptional regulatory proteins, in particular the NURD complex components. Moreover, BNC2 acts as a transcriptional repressor in in vitro transfection assays indicating that it functions in transcriptional repression. We then used protein binding microarrays and CHIP-Seq experiments to identify its putative DNA binding motifs and its downstream target genes. Analysis of this data suggests that BNC2 functions in a regulatory transcription network that impacts on genes implicated in ovarian cancer with enrichment for genes in the TGF-beta response pathway. Citation Format: Melissa A. Buckley, Howard C. Shen, Gustavo A. Mendoza-Fandino, Nicholas T. Woods, Anxhela Gjyshi, Juliet French, Kate Lawrenson, Honglin Song, Jonathan Tyrer, Renato S. Carvalho, Alexandra Valle, Ann Chen, Sean Yoder, Gregory Bloom, Ya-Yu Tsai, Ally Yang, Timothy R. Hughes, Xiaotao Qu, Mine Cicek, Melissa Larson, Ellen Goode, Brooke Fridley, Susan Ramus, Georgia Chenevix-Trench, Paul Pharoah, Thomas A. Sellers, Simon Gayther, Alvaro N.A. Monteiro, Ovarian Cancer Association Consortium. Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition. [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 3285. doi:10.1158/1538-7445.AM2014-3285

Background: Lung carcinoma is the most common malignancy worldwide, and the leading cause of cancer deaths. Histologically, majority of lung cancers are non-small cell carcinomas (NSCLC). The 5-year relative survival of patients with metastatic NSCLC remains dismal at Citation Format: Jatinder Kaur Lamba, Brooke L. Fridley, Taraswi M. Ghosh, Qing Yu, Gaurav Mehta, Pankaj Gupta. Genetic variation in platinating agent and taxane pathway genes as predictors of outcome and toxicity in advanced non-small cell lung cancer. [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 5554. doi:10.1158/1538-7445.AM2014-5554

Both genetic and epigenetic factors influence the development and progression of epithelial ovarian cancer (EOC). However, there is an incomplete understanding of the interrelationship between these factors and whether they interact to impact disease risk. Given that the development of ovarian cancer is complex, we aimed to identify DNA methylation marks that are candidates for mediating ovarian cancer genetic risk. We used 214 cases and 214 age-matched controls from the Mayo Clinic Ovarian Cancer Study. Pretreatment, blood-derived DNA was profiled for genome-wide methylation (Illumina Infinium HumanMethylation27 BeadArray) and single nucleotide polymorphisms (SNPs, Illumina Infinium HD Human610-Quad BeadArray). We employed a three-step filtering procedure, followed by the Causal Inference Test (CIT), to distinguish CpG sites that mediate genetic risk, from those that are consequential or independently acted on by genotype. Controlling for the estimated distribution of immune cells and other key covariates, we identified 1,993 out of 25,926 (7.7%) CpGs that were significantly differentially methylated between cases and controls (FDR, q < 0.05). The relationship between methylation and case-control status among these 1,993 CpGs was found to be highly consistent with the results of an independent study. Implementation of the CIT test revealed 13 CpG/SNP pairs, comprising 13 unique CpGs and 17 unique SNPs, which represent potential methylation-mediated relationships between genotype and EOC risk. These findings provide additional insight into EOC etiology and may serve as novel biomarkers for EOC susceptibility. Citation Format: Devin C. Koestler, Prabhakar Chalise, Mine S. Cicek, Julie M. Cunningham, Sebastian Armasu, Melissa C. Larson, Jeremy Chien, Matthew Block, Kimberly R. Kalli, Thomas A. Sellers, Ellen L. Goode, Brooke L. Fridley. Integrative genomic analysis identifies epigenetic marks that mediate genetic risk for epithelial ovarian cancer. [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 260. doi:10.1158/1538-7445.AM2014-260

Tumor infiltrating regulatory T cells (Tregs) appear to play a role in survival in a number of solid tumors, including ovarian cancer. We assessed genetic variation via tag SNPs (N=749) in 25 Treg associated genes (CD28, CTLA4, FOXP3, IDO1, IL10, IL10RA, IL15, 1L17RA, IL23A, IL23R, IL2RA, IL6, IL6R, IL8, LGALS1, LGALS9, MAP3K8, STAT5A, STAT5B, TGFB1, TGFB2, TGFB3, TGFBR1, TGRBR2, and TGFBR3) in relation to ovarian cancer survival. SNPs were selected based on r2 ≥ 0.8, MAF ≥ 0.05, 5 kb upstream and downstream from the gene. We had SNP and outcome data for ovarian cancer from 10,084 combined ovarian cancer cases, including 5,248 high grade serous, 1,452 endometrioid, 661 mucinous, and 795 clear cell cases of European descent across multiple studies from the Ovarian Cancer Association Consortium (OCAC). Cox proportional hazards regression modeling was used to estimate per-allele hazard ratios (HRs) and 95% confidence intervals (CIs) for associations with overall survival, adjusting for age at diagnosis, population substructure PCs, study site, histology (for the all case analysis), tumor stage, tumor grade and oral contraceptive use. The strongest associations were found for endometrioid histologic subtype and IL2RA SNPs (maximum r2=0.67) rs11256497 [HR=1.42, 95% CI: 1.22-1.64; p=5.7 x 10−6], rs791587 [HR=1.36, 95% CI: 1.17-1.57; p=6.2 x 10−5], rs2476491 [HR=1.40, 95% CI: 1.19-1.64; p=5.6 x 10−5], and rs10795763 [HR=1.35, 95% CI: 1.17-1.57; p=7.9 x 10−5], as well as clear cell ovarian cancer and CTLA4 SNP rs231775 [HR=0.67, 95% CI: 0.54-0.82; p=9.3 x 10−5]. No other associations were observed at p Citation Format: Bridget Charbonneau, Keith Knutson, Robert A. Vierkant, Julie M. Cunningham, Zachary C. Fogarty, Kimberly R. Kalli, Matthew J. Maurer, Ann L. Oberg, Brooke L. Fridley, Claudia C. Preston, Paul D.P. Pharoah, Susan J. Ramus, Catherine M. Phelan, Kunle Odunsi, Kirsten Moysich, Ellen L. Goode. Polymorphisms in regulatory T cell related genes and ovarian cancer survival. [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 4844. doi:10.1158/1538-7445.AM2013-4844

BACKGROUND Metformin, a widely used anti-diabetic drug, is being considered as a highly promising agent for treatment and prevention of many types of cancer, including breast cancer. Although the exact mechanism of action of metformin is unknown, it is thought that metformin is an AMPK activator. To better individualize metformin therapy and explore additional underlying molecular mechanism associated with metformin action, we conducted a metformin pharmacogenomic study using 266 genomic data-enriched lymphoblastoid cell lines (LCLs). METHODS Genome-wide microarray data were generated for all LCLs, including 1.3 million SNPs, 485K DNA methylation probes and 54K mRNA expression probe sets. Metformin cytotoxicity assay was performed using MTS assay. Genome-wide association (GWA) analyses and integrated analyses using all the genomic data and metformin cytotoxicity (IC50 value) were performed to identify top candidate genes for functional validation in breast cancer cell lines, MDA-MB 231 and Hs578T, using siRNA screening approach. Further mechanistic study was performed to investigate the role of candidates in regulation of AMPK activity. RESULTS GWA analyses in LCLs identified 198 mRNA expression probe sets and 210 DNA methylation probes associated with metformin IC50 with p-value CONCLUSIONS GWAS using a genomic data-enriched LCL model system, together with functional validation in breast cancer cell lines, could help us to identify novel genetic and epigenetic biomarkers involved in metformin response and help us to better understand the mechanisms of metformin in cancer treatment. Citation Format: Nifang Niu, Xianglin Tan, Brooke L. Fridley, Daniel J. Schaid, Ryan P. Abo, Anthony Batzler, Erin E. Carlson, Gregory Jenkins, Sebastian Moran, Holger Andrea Heyn, Manel Esteller Badosa, Liewei Wang. Metformin pharmacogenomics: A genome-wide associate study to identify genetic and epigenetic biomarkers involved in metformin response. [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 2271. doi:10.1158/1538-7445.AM2013-2271

The FKBP5 gene encodes the FKBP51 immunophilin, a negative regulator of AKT. Variability in level of FKBP5 expression is a major factor contributing to variation in response to several classes of chemotherapeutic agents including gemcitabine, first line treatment for pancreatic cancer. Genetic variation of FKBP5 could influence its expression, function, and, ultimately, treatment response of pancreatic cancer. We set out to comprehensively study the role of genetic variation in FKBP5 identified by Next Generation DNA resequencing in response to gemcitabine treatment of pancreatic cancer by utilizing both tumor and germline DNA samples from 43 pancreatic cancer patients, including 19 paired tumor-normal samples. Genotype-phenotype association studies with overall survival (in tumor only) as well as with FKBP5 gene expression were performed using the same samples in which Next Generation DNA resequencing had been performed, followed by functional genomic studies of top selected single nucleotide polymorphisms (SNPs). In-depth resequencing identified 404 FKBP5 SNPs in both normal and tumor DNA patient samples. SNPs with the smallest p-values for association with FKBP5 survival or expression were subjected to functional genomic studies. Electromobility shift assay (EMSA) showed that the rs73748206 “T” allele altered DNA-protein binding patterns, consistent with a significantly increased reporter gene activity. The effect of rs73748206 was also confirmed by mRNA expression studies using lymphoblastoid cell lines (LCL) derived from the same patients from whom DNA used for resequencing had been obtained. This comprehensive FKBP5 resequencing study provides insight into the role of inheritance in variation in response to gemcitabine therapy of pancreatic cancer. Citation Format: Katarzyna A. Ellsworth, Bruce W. Eckloff, Liang Li, Irene Moon, Brooke L. Fridley, Greg D. Jenkins, Erin Carlson, Abra Brisbin, Ryan Abo, William Bamlet, Gloria Petersen, Eric D. Wieben, Liewei Wang. Contribution of FKBP5 genetic variation to gemcitabine treatment and survival in pancreatic 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 2209. doi:10.1158/1538-7445.AM2013-2209

Population stratification in case-control studies can result from differences in ancestral make-up between cases and controls due to sampling variation. Ancestry is therefore routinely estimated and controlled for in these studies. Although less common, it is also possible for ancestry to truly be associated to the disease of interest. Controlling for ancestry can then compromise the power to detect variants that underlie both ancestry and disease. Using data from a multi-center case-control study of epithelial ovarian cancer (OC) among women of European-American ethnicity in which case-control samples were drawn from four geographically distinct North-American sites, we developed a three-step method to investigate whether the stratification observed across the four sites is due to chance or to a non-spurious association between European ancestry and OC. First, we collapsed genome-wide data into two principal components (PCs) that represent the major axes of European ancestral variation, which correspond to north-south and to west-east geographical clines. Next, we determined the discriminant function based on these two PCs that best separates cases and controls for each individual study site and we used the largest angle between the four discriminant function vectors as a measure of similarity ranging from 0 degrees, where all four vectors are exactly the same, to 180 degrees where two of the vectors face exactly opposite directions. If stratification is due to sampling, it is unlikely that the four sites will present similar discriminant functions by chance alone. We then gauged significance of similarity by permuting the case control status across individuals within each site and recalculating the maximum angle between the discriminant function vectors, thus obtaining a null distribution for the statistic. We found that all four sites present the greatest separation between cases and controls on the west-east axis of ancestral variation, with a higher proportion of ovarian cancer cases presenting western ancestry. The largest angle between the four discriminant function vectors observed was of 36.5 degrees. Permutation testing showed this level of similarity between the functions to have a p-value < 0.01 and suggests that OC risk is somehow tied to European ancestry. It remains to be seen whether shared culture or other exposures such as parity or oral contraceptive use explain this connection or whether genetic variants underlie it and are potentially being missed due to routine ancestry control in association testing. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1678. doi:1538-7445.AM2012-1678

Background Ovarian cancer is the fifth most common cause of cancer death in women in the US; approximately 15,000 women will die from this disease in 2011 (ACS, 2011). The 5 year survival rate for stage IV disease is only 18%. Only a handful of independent significant prognostic factors are known, including tumor stage at surgery, size of residual tumor at the end of primary surgery, and age at diagnosis. Understanding how the variation of cytosine methylation in the context of cytosine-guanine dinucleotides (CpGs) affects complex disease etiology and survival is the current focus of many ongoing research studies. We conducted an epigenome-wide study of methylation in ovarian cancer cases to evaluate whether variation in methylation of CpG sites in genomic DNA may be associated with ovarian cancer survival. Methods Subjects included cases from an ongoing case-control study. The Mayo Clinic Ovarian Cancer Study is a clinic-based study that recruits ovarian cancer cases within 12 months of diagnosis. Pre-treatment, germline DNA from lymphocytes from 137 cases was bisulfite-modified, amplified and genotyped on the Illumina 450K methylation chip and included in these analyses. Quality control (QC) analyses include the elimination of all methylation probes with a single nucleotide polymorphism (SNP) or insertion/deletion (in/del) at the same location; removal of non-specific probes; and estimation of bisulfite conversion rates using embedded control probes. Planned analyses include assessment of clinical covariates (age, stage, extent of surgical debulking, grade, presence of ascites) to determine which are associated with overall survival in our data. Additional analyses will assess the age- and multi-variate-adjusted association of each methylation probe with overall survival using Cox proportional hazards regression models with each methylation probe modeled as a continuous variable. Data will be summarized using Manhattan plots. These analyses will be repeated using ‘time to recurrence’ as the outcome variable, with recurrence defined as time to ovarian cancer recurrence/progression or death. Results Bioinformatics analyses suggest that 36,659 probes were located at the site of a SNP or in/del and should be removed from future analyses. Another 448 probes had a detection rate of p< 0.01 and 6630 probes had signals for the negative control samples; all were removed from analyses. A total of 43,802 probes were removed. In addition, ten cases were excluded due to either poor bisulfite conversion (N=9) or extremely low raw methylation values across all probes (N=1). This leaves a total of 127 cases for analyses. Results from planned analyses will be presented, including estimation of the association of methylation probes with both overall survival and time to recurrence. Conclusions Data to be presented will describe whether there is any evidence that methylation of genomic DNA in ovarian cancer cases is associated with outcome of ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5008. doi:1538-7445.AM2012-5008

Ovarian cancer is the leading cause of death in gynecologic malignancies in the United States with most patients presenting with late stage disease; patients receive the same treatment regardless of histology or tumor characteristics. The mismatch repair (MMR) molecular pathway is well-defined and known to be involved in up to 20% of ovarian cancers; however, association of deficient v proficient MMR status (dMMR v pMMR status) with risk factors and outcome is not well understood. We are conducting extensive molecular testing of the MMR genes MLH1, MSH2, MSH3, MSH6, and PMS2 on Mayo Clinic invasive epithelial ovarian cancer cases. First, the prevalence of dMMR tumors will be estimated in ovarian cancer cases (n=496) based on loss of expression of MLH1, MSH2, MSH3, MSH6, and PMS2 determined by immunohistochemistry staining of primary antibodies using negative and positive controls. Staining of tissue microarrays (TMAs) is complete; triplicate cores will be scored independently for presence or loss of protein expression by a board-certified pathologist. Second, for those dMMR cases, the possible cause of MMR deficiency will be evaluated considering germline and somatic mutations. The loss of expression of each protein will be characterized as germline if a deleterious mutation is present in peripheral blood or somatic if the pathogenic mutation is only present in tumor tissue. In cases with MLH1 loss somatic hypermethylation will also be considered. Analysis of germline mutation data will include all 496 cases and somatic mutations data will include a subset of cases tested with frozen tumor DNA (n=292) using Fluidigm access array targeted resequencing. Third, the clinical features of dMMR disease will be compared to those of pMMR; in particular, age at diagnosis, histopathology, and disease outcome. Among cases in this analysis, the majority have high-grade serous disease with a mean age at diagnosis of 61 years, about half had recurrence or progression (n=243) of which two-thirds (n=167) are deceased. Finally, known and suspected ovarian cancer risk factors (family history, smoking, body mass index, parity, use of hormone therapy, and genetic variation in susceptibility loci at 2q31, 3q25, 8q24, 9p22, 17q21, and 19p13) will be analyzed by MMR phenotype. Risk factor questionnaire data is available on 462 cases (93%), as well as 737 population controls with germline genome-wide genotype data. About half of the cases (n=231) report a 1st or 2nd degree family member with breast or ovarian cancer. Given the limited knowledge about ovarian cancer etiology and the poor prognosis of advanced disease, it is very important to study risk factors with this molecular subtype. The ovarian cancer dMMR phenotype may have distinct clinicopathological features that could guide risk stratification and be useful in diagnostics and therapeutics. This is the largest study characterizing MMR in an ovarian cancer population to date. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2619. doi:1538-7445.AM2012-2619

Mi(cro)RNAs are short non-coding RNA molecules that play a key role in carcinogenesis by regulating tumor suppressors and oncogenes. Published data has implicated miRNAs in ovarian cancer (OC) development and progression, and we hypothesize that single nucleotide polymorphisms (SNPs) in sites of miRNA: messenger RNA (mRNA) binding may influence OC risk by altering expression levels of targeted mRNAs. To evaluate associations between SNPs in miRNA binding sites and OC risk, we used bioinformatics tools and public databases to identify miRNA binding SNPs relevant to ovarian cancer. We then evaluated the frequency of approximately 1,100 SNPs in ∼20,000 epithelial OC cases and 20,000 controls represented in the international Collaborative Oncological Gene-environment Study. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) between genotypes and case status, with adjustment for the first five principal components representing European ancestry. Log-additive genetic models were applied to each SNP, modeling the number of copies of the minor allele. Subgroup analysis was conducted for serous adenocarcinomas, the most predominant histologic subtype of epithelial OC. Preliminary analysis of 11,215 invasive epithelial OCs and 15,910 controls included four SNPs with PT SNP predicted to reside in a highly conserved miRNA binding site of BTBD3 (BTB POZ domain containing 3), a transcription factor suggested to be involved in cell proliferation, cancer progression, and response to platinum-based chemotherapy. rs6104808 was associated with a decreased risk of OC overall (OR (95% CI): 0.42 (0.28-0.62), P=1.26 x 10−5)), and the association was stronger among cases with serous adenocarcinoma (OR (95% CI): 0.30 (0.17-0.50), P=9.89 x 10−6)). This represents the largest, most comprehensive epidemiologic study to date to evaluate associations between miRNA binding site SNPs and OC susceptibility. Although based on a preliminary analysis, these data suggest a significant role and putative biological mechanism for common germline variants in miRNA binding sites leading to cancer development. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2927. doi:1538-7445.AM2012-2927

DNA copy number variations (CNVs) are a significant and ubiquitous source of human genetic variation. However, the influence of CNVs on cancer susceptibility remains poorly understood. Out of 83 genome-wide association studies (GWAS) on cancer to date, only a few studies found significant associations on germline CNVs and cancer. Here we analyzed data from our ongoing two-stage GWAS of four North American case-control studies to test the hypothesis that CNVs in germline DNA from peripheral blood lymphocytes may serve as risk factors for epithelial ovarian cancer (EOC). To reduce disease heterogeneity, we focused on the subset of cases with serous histology. The analysis was therefore based on 942 serous ovarian cancer patients and 1,682 healthy controls who were genotyped using the Illumina 610K quad array. Subjects with extreme noise and genomic waviness in log R ratio (LR) were excluded prior to segmentation; principal component analysis was performed to adjust for batch effects. CNV segmentation was performed on LR data from 22 autosomes using circular binary segmentation embedded in the Copy Number Analysis Module from Golden Helix SNP Variation Suite version 7. Copy number segment covariates were discretized based on the thresholds that signify a transition between copy number states (deletion/no deletion; duplication/no duplication) after the segmentation. Unconditional logistic regression on a log-additive model was used to evaluate the association between copy number states and serous EOC risk after adjusting for study sites. By comparing single marker copy number states at 388,958 SNPs on 22 autosomes, we observed a total of 134 SNPs significantly associated with risk of serous EOC with a p value below 10−6. Associations with deletion polymorphisms were observed on chromosomes 7, 8, 14, and 18 when controlling for false discovery rate at 1%; no duplication polymorphisms were significant. We observed a large deletion at chromosome 14 that occurred in 8.9% of cases but in only 3.9% of controls, with a p value of 5.59×10−8 (Odds Ratio (OR): 2.56, 95% confidence interval (CI): 1.82-3.60). Another common deletion on chromosome 7 occurred in 8.8% of cases and only 4.3% of controls (p=3.83×10−6; OR: 2.23, 95% CI: 1.60-3.10). Two additional regions on chromosomes 8 and 18 with deletion events less than 5% were also identified. Women who harbored the deletion on chromosome 8 were at lower risk of developing serous ovarian cancer (p=4.83×10−8; OR: 0.04, 95% CI: 0.01-0.30). Women who carried the deletion on chromosome 18 had an increased risk for serous EOC (p=9.04×10−7; OR: 7.26, 95% CI: 2.94-17.97). Further validation of these four regions using independent data sets is currently underway. In summary, this is the largest reported genome-wide study of CNVs and serous EOC risk. These preliminary results suggested that germline CNVs may play an important role in ovarian cancer susceptibility. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1649. doi:1538-7445.AM2012-1649

As pathways of the immune system play an important role in multiple malignancies, we assessed the association between single-nucleotide polymorphisms (SNPs) in inflammation-related genes and risk of ovarian cancer in a multi-site case-control study. Using a custom array, we genotyped 930 epithelial ovarian cancer cases and 1,037 controls for SNPs in ALOX12, ALOX15, ALOX5, CCL11, CCL2, CCL3, CCR3, CRP, CXCL16, IL10, IL15RA, IL18, IL1A, IL1B, IL1RN, IL4R, IL6, IL6R, IL7R, IL8RA, IL8RB, IL9, NOS3, PTGS1, PTGS2, TLR2, and TNF. After analysis by logistic regression, SNPs with p Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2603. doi:1538-7445.AM2012-2603

Epithelial ovarian cancer (EOC) is the 6th most commonly diagnosed cancer among women in the world, accounting for 4% of all female cancers. On a worldwide basis, an estimated 204,000 new cases are diagnosed and 125,000 women die of EOC annually, with 5-year survival rate at 45%. Metastasis and its complications are the usual cause of EOC-related deaths. Thus, factors related to tumor aggressiveness, response to therapy, and the underlying health state of the patient often predict survival. Candidate gene and genome-wide association studies (GWAS) for survival from EOC have discovered only a few the genetic variants, accounting for only a small proportion of the heritability. One explanation for the missing heritability is that the common analysis approach _ assessing the effect of each single nucleotide polymorphism (SNP) individually _ is not well suited to the detection of small effects of multiple SNPs. Gene set analysis (GSA) overcomes this limitation by assessing the overall evidence of association of a phenotype with all measured variation in a set of genes or pathway. Therefore, we conducted a GSA using data from an EOC GWAS, using the Illumina 610-quad SNP array, to determine novel gene sets (GSs) associated with overall survival (OS) from EOC (N cases = 1057, N deaths = 495). All subjects were non-Hispanic, non-Jewish Caucasians, with sample and SNP call rates >95%. Subjects with ambiguous gender, unresolved identical genotypes, and less than 80% European ancestry were also excluded. SNPs were mapped to genes within 20 kb, with genes then mapped to GSs defined by the following: KEGG, Gene Ontology (biological, cellular, molecular) and PharmGKB. GSA was completed in which the association of each gene with OS was assessed using a principal component gene-level test (adjusting for study site, age and population sub-structure based on the first eigenvector from EigenStrat), followed by the aggregation of the gene-level p-values using the Gamma method with a soft truncation threshold of 0.15. Empirical p-values were determined using permutation methods. Of the 2,573 GSs assessed, 30 GSs had a p-value < 0.01. The top GSs were related to: mismatch repair (p = 3.0E-4), platelet formation (p=0.001), leukocyte adhesive activation (p=0.002), antigen processing and presentation of endogenous antigens (p = 0.002) or peptide antigens (p = 0.002), platinum pathway (p = 0.003), aging and lifespan (p = 0.004, p = 0.007), immune system development (p = 0.004) and somatic diversification (p=0.007). These results illustrate the usefulness of GSA for the development of novel hypotheses that can be followed-up with additional clinical or functional studies. Moreover, application of GSA to survival from EOC allowed the detection of significant GSs (and the corresponding genes/SNPs within these GSs) that impact OS that were not detected by assessing each SNP individually, where the smallest p-value from single SNP analysis of the GWAS for OS was 1.3E-05. 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 2738. doi:10.1158/1538-7445.AM2011-2738

The etiology of ovarian cancer is poorly understood but there is clearly a heritable component. Efforts to identify susceptibility alleles rarely consider interactions among alleles or their joint effects because it quickly becomes computationally intractable. In this study, we sought to identify multi-SNP effects jointly with a pathway-based analysis (GSEA-SNP) of 1,952 EOC cases and 2,042 frequency-matched controls genotyped with the Illumina 610K array. All subjects were self-reported non-Hispanic non-Jewish Caucasians, with SNP and sample call rates > 95%. Subjects with ambiguous gender, unresolved identical genotypes and < 80% European ancestry were excluded. SNPs with MAF < 1% were excluded. Missing genotypes were inferred using Mach based on the HapMap CEU population. SNPs not within introns were annotated to genes within 100 bp. We retrieved the following databases of gene sets (GSs) from a compiled database, MsigDB: human chromosome and cytogenetic band, chemical and genetic perturbations, canonical pathways, microRNA binding targets, transcription factor targets (TFT), cancer gene neighborhood (CGN), Cancer modules and Gene Ontology. The GSEA-SNP approach calculates and rank orders the trend statistic for association between each SNP and EOC risk. The Enrichment Score (ES) estimates the overrepresentation of top-ranked SNPs for each GS; the statistical significance was estimated using 10,000 permutations. The ES was normalized according to the size of GS to yield Normalized Enrichment Score (NES). The false discovery (FDR) rate was estimated using NES to adjust for multiple hypothesis testing. A total of 5181 gene-sets were included in the analysis. When controlling the FDR at 15%, 14 of the GSs were highly enriched with association signals, including two chromosomal regions, 8q13 (p = 0.0055, FDR = 0.15) and 6p24 (p = 0.0012, FDR = 0.08). BIOCARTA_LYM_PATHWAY, a pathway related to cell adhesion and diapedesis of lymphocytes, was also significant (p = 0.0002, FDR = 0.12). A TFT GS, composed of genes with promoter regions around transcription start sites containing the motif GGCNRNWCTTYS, was associated with risk (p = 0.0004, FDR = 0.08). Currently, no known transcription factors bind to this computationally predicted motif. Molecular function of double stranded RNA binding was also enriched (p = 0.005, FDR = 0.10). The remaining enriched sets were CGN sets, for which the neighborhoods around the cancer genes were originally defined using correlation of gene expression from 4 large data sets of various cancer types. The enriched CGN included: CD48 (p = 0.011), CD53 (p = 0.009), CD97 (p = 0.011), INPP5D (p = 0.010), PTPN6 (p = 0.008), VAV1 (p = 0.011), ITGAL (p = 0.012), PTPRC (p = 0.012), and STAT6 (p = 0.010). In summary, these analyses detected biologically plausible GSs related to etiology of EOC, highlighting SNPs in core enrichment groups that were not identified using individual SNP tests. 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 4729. doi:10.1158/1538-7445.AM2011-4729

Ovarian carcinoma is a significant cause of cancer mortality in women in the United States. Increasing evidence has demonstrated that differential methylation status in lymphocyte DNA may be linked to risk of carcinogenesis. We are investigating the differential DNA methylation in germline DNA obtained from pre-treatment ovarian cancer cases (n=256) and individually-age matched controls (n=274) using the Illumina Infinium Human Methylation 27K BeadChip. We are first studying methylation and the common moderate-risk alleles for ovarian cancer on chromosomes 2q31, 3q25, 8q24, 9p22, 17q21, and 19p13. Within each locus, we correlated single nucleotide polymorphism (SNP) genotypes with methylation values at relevant nearby CpG sites. Preliminary results are available on the first set of 84 cases and 90 controls. At 2q31, cases with TG or TT genotype at rs2072590 were hypomethylated at HOXD1 (a homeobox transcription factor) compared to cases with GG genotype (mean beta TG/TT=0.08, GG=0.09, p=0.034); and at 17q21, cases with AG or GG genotype at rs9303542 were hypomethylated at SKAP1 (a T-cell adaptor protein) compared to cases with AA genotype (mean beta AG/GG=0.14, AA=0.16, p=0.045). At these two loci, similar trends were seen among controls. Logistic regression adjusted for age and methylation chip was then used to assess the association between SNP genotype and ovarian cancer risk, with and without inclusion of the relevant methylation value. At HOXD1 rs2072590, the per-allele ovarian cancer risk of 1.34 attenuated to 1.25 with inclusion of the HOXD1 methylation value as a covariate, suggesting that the disease association may be mediated in part through methylation. Though based on preliminary data, results are consistent with a role for inherited variation on germline methylation at HOXD1 and SKAP1. Analysis of methylation on additional genotyped cases and controls is underway. Finally, because, trans effects may also exist, we are assessing relationships between genotype and methylation at other loci throughout the genome. Such correlative molecular studies have the potential to help elucidate mechanisms underlying associations from genome-wide association studies. 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 5616. doi:10.1158/1538-7445.AM2011-5616

We performed a multi-stage genome-wide association study (GWAS) for drug response in ovarian cancer. We selected 313 chemotherapy treated patients from the Australian Ovarian Cancer Study (AOCS). Patients were treated with paclitaxel/carboplatin and the trait of interest was Progression Free Survival (PFS). We maximized power for a fixed genotyping budget by genotyping individuals from the tails of the distribution: 94 with good survival and 94 with poor survival, taking into account extent of residual disease following surgery. Patients were genotyped on Illumina HumanOmni1-Quad arrays (1140419 loci).Two further cohorts with measures of PFS and whole genome data available; 134 ovarian patients from the Mayo clinic (genotyped on Illumina HumanHap 610 arrays, 620901 loci) and 68 patients from The Cancer Genome Atlas ovarian cancer set (genotyped on Illumina Human1M arrays, 1199187 loci) were meta-analyzed with the AOCS set (stage 1). We have imputed all the stage 1 samples with reference of the 1000 Genome data to allow more direct comparison of SNPs not common to all of the arrays used (up to 6 million SNPs with good imputation quality). Based on the chemotherapy treatment received by each patient, we assigned the patients into primary and secondary analysis, with primary analysis using a more strictly defined treatment subgroup. We followed up the stage 1 findings by genotyping 26 SNPs in more than 3,000 samples collected from 8 study sites of Ovarian Cancer Association Consortium (OCAC). These 26 SNPs were mainly genotyped SNPs, chosen from 23 distinct regions showing the strongest association with chemotherapy response from either primary or secondary analysis. 2 SNPs showed nominal significance in the replication sample (chr 12: rs1861932, chr 22: rs708444). We are currently genotyping more regions to seek replication of the initial findings. In summary, we sought to identify genes that underlie individual differences in chemoresistance. In the future, typing variations in these genes will be important for personalizing drug regimes for patients. 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 4679. doi:10.1158/1538-7445.AM2011-4679

Background. The hepatocyte growth factor (HGF) signaling pathway regulates key cellular functions related to tumor invasion and metastasis including cell motility, cell proliferation, and morphogenesis. We previously found that minor alleles at a single-nucleotide polymorphism (SNP; rs5745709) in the gene encoding the cytokine HGF was associated with poorer overall survival in women with invasive epithelial ovarian cancer (EOC) enrolled at Mayo Clinic (MAY) and The Cancer Genome Atlas (TCGA) (HR 1.6, 95% CI 1.3-1.9, p=8.9×10−5). In addition, we found that that genotype correlated with HGF expression in ovarian cancer tissue from TCGA women, suggesting that genetically-regulated expression of HGF may play a role in post-diagnosis survival. To further examine this possibility, we evaluated intensity of antibody immunostaining for HGF, MET (HGF's transmembrane tyrosine kinase receptor), and phospho-MET (pMET; MET's activated form) in tumor cells using tissue microarrays (TMAs) created from genotyped primary peritoneal and EOC cases, and correlated these expression levels with overall survival and HGF SNP genotypes. Methods. Participants were 326 white non-Hispanic women over 20 years of age with histologically-confirmed invasive EOC diagnosed between 1998 and 2009. All cases were enrolled at MAY within one year of diagnosis. Five μm sections of TMAs including three 0.6 mm cores per case were immunostained with HGF, MET, and pMET primary antibodies. Staining levels were classified according to combinations of staining extent and intensity as negative (< 10% cells stained), weak, moderate, or strong. The maximal expression value recorded over the multiple cores for each case was used. Cox proportional hazards regression was used to examine associations of overall survival with HGF, MET and pMET expression levels, adjusted for relevant clinical variables. Associations between expression levels and HGF SNP rs5745709 genotypes were examined using linear regression models. Results. HGF and MET expression were not associated with overall survival in our series of EOC cases (p=0.48 and 0.90, respectively). pMET expression was associated with survival, but in the opposite direction of that hypothesized (HR 0.77, 95% CI 0.39-1.52 for moderate expression; HR 0.55, 95% CI 0.27-1.10 for strong expression; each referent to negative/weak, p=0.01). Expression levels were not significantly associated with HGF rs5745709 genotypes (p=0.80 for HGF expression, p=0.89 for MET, p=0.41 for pMET). Conclusion. HGF expression levels were not associated with overall survival or with HGF SNP genotypes that correlated with survival in a previous study. Functional studies such as this one are crucial as a follow-up to discovery-based studies in order to assess biologic plausibility of observed results. 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 893. doi:10.1158/1538-7445.AM2011-893

As the leading cause of mortality among gynecologic cancers, it is critical to increase understanding of ovarian cancer pathogenesis, which remains largely unknown. Several xenobiotic metabolizing enzymes are responsible for processing and inactivating carcinogens that could initiate ovarian carcinogenesis. Here, we hypothesize that single-nucleotide polymorphisms (SNPs) in genes encoding xenobiotic metabolizing enzymes may be associated with differential risk of ovarian cancer. Cases with epithelial ovarian cancer (N=930) and controls (N=1,037), frequency-matched on age and geographic residence, were enrolled at Mayo Clinic and Duke University, and genotyped at 163 tagSNPs in EPHX1, SULT1E1, ADH5, ADH4, ADH6, ADH1A, ADH1B, ADH1C, NQO2, NAT1, NAT2, GSTP1, CYP19A1, CYP1A1, CYP1A2, and NQO1 using an Illumina GoldenGate™ BeadArray array. Logistic regression was used to estimate odds ratios (ORs) and adjust for population structure and other potential confounders, including oral contraceptive use, parity, and family history. SNP-specific statistical analyses identified several noteworthy results including an association with increased risk of ovarian cancer with a SNP (rs2917666) in NAD(P)H dehydrogenase, quinone 1 (NQO1) (per-allele OR 1.16, 95% confidence interval (CI) 1.01-1.33, p=0.04). The SNP rs1051740 in epoxide hydrolase 1, microsomal (xenobiotic) (EPHX1) was suggestive of increased risk of invasive serous disease (TT v CT OR 0.85, 95% CI 0.66-1.09, TT v CC 1.29, 95% CI 0.89-1.88, p=0.09). In an effort to replicate these observations, a subset of 11 SNPs with a p-value < 0.10 were then genotyped in 727 invasive cancer cases and 1,065 controls from an Australian ovarian cancer study using a Sequenom iPlex assay. Results of combined analyses confirmed an association between EPHX1 rs1051740 and increased invasive serous ovarian cancer risk (TT v CT OR 0.99, 95% CI 0.77-1.29, TT v CC OR 1.61, 95% CI 1.23-2.11, p=0.001; recessive OR 1.61, 95% CI 1.25-2.09, p=0.001). This gene is involved in the activation and detoxification of tobacco-derived carcinogens, and smoking has been associated with the mucinous histologic subtype of ovarian cancer. Analyses by histological subtype and gene-environment interaction analyses considering genotype in conjunction with tobacco use and alcohol intake are underway. Due to the important role of EPHX1 in metabolizing pro-carcinogens and the observed association between rs1051740 and risk of invasive serous disease, an examination of this SNP in a larger ovarian cancer consortium is warranted. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 914.

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC Introduction: Alterations in components of the stromal tissue that underlie the epithelium can initiate, promote or inhibit epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) are stromal genes with reduced expression in serous ovarian cancer. We hypothesized that single nucleotide polymorphisms (SNPs) in these genes may influence susceptibility to serous ovarian cancer. Methods: To test this hypothesis, we compared genotype frequencies of 11 tagSNPs in DCN and LUM between 397 Caucasian cases with primary serous ovarian cancer and 920 Caucasian controls in two studies conducted at Mayo Clinic and Duke University (discovery set). Associations were evaluated further in a third Caucasian population of 436 cases and 1,098 controls in Australia (replication set). TagSNPs were selected from unrelated Caucasian samples within HapMap based on the following criteria: (i) minor allele frequency ≥ 0.05, (ii) pairwise linkage disequilibrium (LD) of r2 ≥ 0.8, and (iii) location within, and 5kb upstream and downstream of, each gene region. Genotyping was performed using the Illumina GoldenGate™ assay and associations between SNPs and serous cancer were evaluated using unconditional logistic regression to estimate per allele odds ratios (OR) and 95% confidence intervals (95%CI). Untyped genotypes for DCN rs13312816 in the discovery set, and for DCN rs3138165 and LUM rs17018765 in the replication set, were imputed using the MACH software. Results: In the discovery set, we observed inverse associations between DCN rs3138165 (OR=0.7; 95%CI=0.5-1.0), DCN rs13312816 (OR=0.7; 95%CI=0.5-1.0), DCN [rs516115][1] (OR=0.8; 95%CI=0.7-1.0) and LUM rs17018765 (OR=0.7; 95%CI=0.5-1.0) and risk of serous ovarian cancers (all Ptrend=0.06). Associations were confirmed in the replication set for DCN rs3138165 (OR=0.6; 95%CI=0.4-0.9; Ptrend=0.009), DCN rs13312816 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.01) and LUM rs17018765 (OR=0.6; 95%CI=0.4-0.9; Ptrend=0.008), but not for DCN [rs516115][1] (Ptrend=0.20). To increase statistical power, data from the discovery and replication sets were combined (833 cases and 2,013 controls) following confirmation of no statistical heterogeneity in the ORs between study sites. In the combined sample, associations were strengthened for DCN rs3138165 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.002), DCN rs13312816 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.002), DCN [rs516115][1] (OR=0.9; 95%CI=0.8-1.0; Ptrend=0.03) and LUM rs17018765 (OR=0.6; 95%CI=0.5-0.8; Ptrend=0.001). All four SNPs were in the same LD block on chromosome 12, suggesting that serous ovarian cancer susceptibility may be driven by a single, correlated variant in the region. Conclusion: The findings of this study suggest that genetic variation in DCN and LUM may influence susceptibility to serous ovarian cancer and contribute to the mounting evidence that supports the role of the stroma in epithelial ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2854. [1]: /lookup/external-ref?link_type=GEN&access_num=rs516115&atom=%2Fcanres%2F70%2F8_Supplement%2F2854.atom

Background: We previously identified a panel of genes associated with outcome of ovarian cancer. The purpose of the current study was to assess whether variants in these genes correlated with ovarian cancer risk. Methods and Findings: Women with and without invasive ovarian cancer (749 cases, 1,041 controls) were genotyped at 136 single nucleotide polymorphisms (SNPs) within 13 candidate genes. Risk was estimated for each SNP and for overall variation within each gene. At the gene-level, variation within MSL1 (male-specific lethal-1 homolog) was associated with risk of serous cancer (p=0.03); haplotypes within PRPF31 (PRP31 pre-mRNA processing factor 31 homolog) were associated with risk of invasive disease (p=0.03). MSL1 rs7211770 was associated with decreased risk of serous disease (OR 0.81, 95% CI 0.66-0.98; p=0.03). SNPs in MFSD7, BTN3A3, ZNF200, PTPRS, and CCND1A were inversely associated with risk (p Conclusions: Tumor studies can reveal novel genes worthy of follow-up for cancer susceptibility. Here, we found that inherited markers in the gene encoding MSL1, part of a complex that modifies the histone H4, may decrease risk of invasive serous ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4718.

Mitochondria have been implicated in carcinogenesis because of their central role in apoptosis, free radical production, and cellular energy metabolism. Although studies have identified somatic mitochondrial DNA mutations in ovarian cancers, little attention has been directed to the possible role of germline mitochondrial variants in mitochondrial dysfunction and subsequent ovarian cancer development. Through an ongoing epithelial ovarian cancer genome-wide association study of 1,856 invasive cases (59% with serous carcinomas) and 1,912 controls (frequency-matched on age, race, and study site), we genotyped 138 SNPs tagging variation in the maternally-inherited mitochondrial genome (mtDNA) to evaluate the hypothesis that single nucleotide polymorphisms (SNPs) in mtDNA are associated with ovarian cancer risk. All subjects were non-Hispanic, non-Jewish Caucasians, and were genotyped with the Illumina 610-quad Beadchip. Samples and SNPs with call rates less than 95% were excluded. Subjects with ambiguous gender, unresolved identical genotypes, and less than 80% European ancestry were excluded. For each SNP, logistic regression was used to estimate odds ratios (OR) and corresponding 95% confidence intervals (CI) between carriers of the minor versus major maternally-inherited allele and case status. Subgroup analysis was conducted to estimate allele-specific risks between serous-only cases and controls. Haplotype analysis was performed for regions containing statistically significant SNPs (p Two rare SNPs, C16329T in the displacement loop gene (MT-D-loop) (OR: 6.72, 95%CI: 1.5-29.8, p=0.004; minor allele frequency (MAF)=0.001) and C15905T in the tRNA threonine gene (MT-TT) (OR: 1.60, 95%CI: 1.1-2.3, p=0.009; MAF=0.027), were associated with increased ovarian cancer risk; whereas T6777C in the cytochrome c oxidase subunit 1 gene (MT-CO1) (OR: 0.68, 95%CI: 0.51-0.91, p=0.009; MAF=0.063) was associated with decreased risk. All three SNPs remained statistically significant after adjustment for multiple comparisons within the mitochondrial SNPs using permutation testing. C16329T and T6777C were also significantly associated among cases with serous histology, with ORs (95% CIs) of 6.13 (1.2-29.6) and 0.61 (0.43-0.87), respectively. Haplotype analysis for each of the three regions investigated revealed significant haplotype-disease associations; however, findings suggest that the respective associations were driven by the most significant SNP(s) listed above. This is the first large-scale epidemiologic study to provide evidence that SNPs in mitochondrial genes may be novel risk factors for ovarian cancer. Future investigation of additional mitochondrial variants (i.e. nuclear-encoded mitochondrial proteins) is necessary to more comprehensively investigate this association. Furthermore, replication of the most promising SNPs in a larger population is warranted to validate these findings. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2835.

Background Taxane, a class of common anticancer agent, is widely used to treat many cancers. Among the taxanes, paclitaxel and docetaxel are the most commonly used agents. The mechanism of action for taxane drugs is through stabilizing microtubules by enhancing tubulin assembly and against depolymerization, thereby disrupting the dynamics of the microtubule. Large inter-individual variation has been observed in response to taxane treatment. Therefore, in the present study, we conducted a genome-wide association (GWA) study to identify genetic polymorphisms that might contribute to variation in response to taxanes drugs using the “Human Variation Panel” lymphoblastoid cell line (LCL) model system that consists of 287 ethnically defined cell lines. Method Genome-wide SNP and basal gene expression data were obtained for 287 LCLs using Illumina HumanHap 550K, 510S BeadChips, Affymetix SNP Array 6.0 and Affymetrix U133 plus 2.0 GeneChip. Cytotoxicity assay was also performed in the same cell lines for both paclitaxel and docetaxel. Candidate genes were selected based on an integrated analysis of genome-wide SNPs, expression array data and IC50 values (a cytotoxicity phenotype indicating the drug concentration required for 50% inhibition of maximal cell growth) for paclitaxel and docetaxel. SiRNA screening was performed to functionally validate those top candidates, followed by MTS assay in a breast cancer cell line, MDA-MB231. Results Of the 54,000 probe sets considered, 390 probe sets, representing 272 unique annotated genes, were found to be associated with docetaxel cytotoxicity (IC50 value) with p value Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2599.

Using data from patients with invasive epithelial ovarian cancer, we sought to examine whether overall survival was associated with common inherited variation in candidate genes and genomic regions including those involved in angiogenesis, mitosis, and regions of interest from genome-wide association and expression studies. We conducted a two-stage analysis based on Mayo Clinic patients with replication of peak results in the Cancer Genome Atlas (TCGA). Ovarian cancer patients (N=312) seen at the Mayo Clinic diagnosed from 1999 to 2006 with median follow-up of 3.7 years (range, 0.1 − 9.5 years) and 172 observed deaths were analyzed at 993 single nucleotide polymorphisms (SNPs) in 179 genes. For all patients and for serous patients only (N=192 with 129 observed deaths), Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for each SNP, adjusted for other prognostic factors. Twenty-nine SNPs in ten genes revealed p < 0.01 among all cases or among serous cases only, including 21 independent SNP at r2=0.9; analyses within four genes (HGF, PLG, PRKACB, and DCTN5) yielded p < 0.001. The strongest result was in HGF at rs1800793 (all cases: HR 1.7, 95% CI 1.3 − 2.2, p-trend 1.9 E-5; serous cases: HR 1.6, 95% CI 1.2 − 2.2, p-trend 1.8 E-3). A correlated SNP rs2214825 also showed association (r2=0.76; all cases: HR 1.4, 95% CI 1.1 − 1.8, p-trend 3.3 E-3; serous cases: HR 1.4, 95% CI 1.0 − 1.9, p-trend 0.03), and PCA gene-level tests of the HGF locus were also significantly associated with survival (all cases, p=3.7 E-4; serous cases, p=0.01). Among all cases, differential survival was also associated with DCTN5 rs12447304 (HR 1.8, 95% CI 1.3-2.6; p=7.1 E-4), and among serous cases, with PLG rs783173 (HR 1.6, 95% CI 1.2 − 2.0, p = 8.1 E-4) and PRKACB rs1402694 (HR 1.7, 95% CI 1.3 − 2.2, p=3.2 E-4). We then examined SNPs in the most suggestive gene, HGF, using data from TCGA which had genotyped four overlapping HGF SNPs in 350 invasive cases (188 deaths). Covariate-adjusted TCGA analysis at rs2214825 revealed consistent results (HR 1.7, 95% CI 1.3-2.2, p=1.4 E-4) as did analyses of three other HGF SNPs (HR range 1.3 to 1.5, p range 3.4 E-3 to 0.049); correlation between SNP genotypes and HGF expression was also observed (p=1.4 E-3, rs2214825, probe 210997_at). While this is the first report of SNPs in HGF, it has long been known that the HGF signaling pathway, activated by HGF ligation of c-MET, plays a key role ovarian cancer cell growth, migration, and invasion. c-MET is overexpressed in 40%-60% of ovarian tumors, and high overexpression is associated with lower overall survival. In addition, HGF has been shown to enhance the response of ovarian cancer cells to low doses of paclitaxel and cisplatin by activating the intrinsic apoptotic pathway, leading to cancer cell death. These results now suggest that inherited differences in HGF among women with invasive disease may play a role in survival, holding potential clues for tailored avenues of treatment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 897.

Background Radiation therapy is used to treat half of the all cancer patients. Response to radiation therapy varies widely, in terms of both response and toxicity related events. Previous studies suggested almost 80% of the variation in normal tissue response to radiation treatment was likely to be due to genetic factors. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers that might help predict radiation response using a the “Human Variation Panel” lymphoblastoid cell lines (LCLs) that consists 287 ethnically defined cell lines. Method Basal gene expression level, 1.3 million genome-wide SNP data were obtained for 287 human LCLs using Affymetrix U133 plus 2.0 GeneChip, Illumina HumanHap 550K, 510S BeadChips and Affymetix SNP Array 6.0. Radiation cytotoxicity assay was also performed to obtain the area under radiation dose response curve (AUC), a summary measure for cytotoxicity for the same cell lines. Functional validation of candidate genes, selected based on the integrated analysis of SNP, expression and AUC data, was performed in multiple cancer cell lines using specific siRNAs followed by MTS and colony formation assays. Results 27 loci, containing at least 2 SNPs of p values Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3602.

Recent GWAS have identified and confirmed associations between several SNPs in the gene desert located on chromosome 8q24 with risk of cancers of the breast, prostate, glioma, bladder and colorectum. Evidence supporting an association with ovarian cancer is limited and inconsistent. Here we evaluate preliminary results in the 8q24 region from stage I of an ongoing invasive epithelial ovarian cancer GWAS among 1864 cases (1096 serous cases) and 1912 controls. All subjects were self-reported non-Hispanic non-Jewish Caucasian, and were genotyped with the Illumina 610quad Chip. Samples and SNPs with call rates less than 95% were excluded (9.6% and 9.9%, respectively) as well as 128 subjects with ambiguous gender, unresolved identical genotypes and less than 80% European ancestry were also excluded. Our most significant hit in the region was rs6651252 located at 8q24.21 with p = 0.000125 for all ovarian cancer, and 1.02*10−5 for serous cases only. This region is located approximately 849 kb downstream of the previous 8q24.21 findings on other cancers, and was not in linkage disequilibrium with any of the haplotype blocks reported previously. We further examined the block structure of this region with eight genotyped SNPs located within 129.61 to 129.64 MB (rs10088218, rs1516973, rs1516975, rs16903097, rs10098821, rs6651252, rs1561928, and rs1561927) and performed haplotype analysis to evaluate the association with ovarian cancer risk. One haplotype (AAGCAGGG, estimated frequency=0.11) was significantly associated with decreased ovarian cancer risk with an odds ratio of 0.67 (all cases, 95% CI: 0.78-0.91, p=0.0026, empirical p= 0.0020). This region contains no known genes, but it is located upstream and overlaps with a known copy number variation (CNV) reported by Redon et al. (2006). Previous published literature on array CGH and CNV results from TCGA (The Cancer Genome Atlas) also indicate that the 8q24.21 region is associated with frequent gains/amplification in ovarian tumors. Combined analysis of SNPs and CNV identified in this region is underway to elucidate the joint effect of these two types of genetic variation on ovarian cancer risk. Our result indicates a novel locus on 8q24.21 is associated with epithelial ovarian cancer susceptibility. Haplotype analysis reveals one specific haplotype that is associated with decreased ovarian cancer risk compared to the most common haplotype. Given previous 8q24 findings from other cancers and evidence from publicly available resources, fine-mapping and resequencing of this region is warranted. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4724.