Johnatty, Sharon E.

Objective: Studies on low-grade serous ovarian cancer (LGSC) are limited by a low number of cases. The aim of this study was to define the prognostic significance of age, stage, and CA-125 levels on survival in a multi-institutional cohort of women with pathologically confirmed LGSC. Methods: Women with LGSC were identified from the collaborative Ovarian Cancer Association Consortium (OCAC). Cases of newly diagnosed primary LGSC were included if peri-operative CA-125 levels were available. Age at diagnosis, FIGO stage, pre- and post-treatment CA-125 levels, residual disease, adjuvant chemotherapy, disease recurrence, and vital status were collected by the participating institutions. Progression-free (PFS) and overall survival (OS) were calculated. Multivariable (MVA) Cox proportional hazard models were used and hazard ratios (HR) calculated. Results: A total of 176 women with LGSC were included in this study; 82% had stage III/IV disease. The median PFS was 2.3 years and the median OS was 6.4 years. Age at diagnosis was not significantly associated with worse PFS (p = 0.23) or OS (p = 0.3) (HR per year: 0.99; 95%CI, 0.96–1.01 and 0.98; 95%CI 0.95–1.01). FIGO stage III/IV was independently associated with PFS (HR 4.26, 95%CI 1.43–12.73) and OS (HR 1.69, 95%CI 0.56–5.05). Elevated CA-125 (≥35 U/mL) at diagnosis was not significantly associated with worse PFS (p = 0.87) or OS (p = 0.78) in MVA. Elevated CA-125 (≥35 U/mL) after completion of primary treatment was independently associated with worse PFS (HR 2.81, 95%CI 1.36–5.81) and OS (HR 6.62, 95%CI 2.45–17.92). In the MVA, residual disease was independently associated with PFS (0.022), but not OS (0.85). Conclusion: Advanced LGSC was associated with poor long-term prognosis. FIGO stage and abnormal post-treatment CA-125 level are key prognostic factors inversely associated with PFS and OS. Highlights: 1. Through a multi-center collaborative effort, data from 176 women with low-grade serous ovarian cancer were analyzed. 2. Although low-grade serous ovarian cancer is often considered indolent, the progression-free and overall survival are poor. 3. Elevated post-treatment CA-125 levels are independently associated with poor survival.

Abstract Background: Many loci have been found to be associated with risk of epithelial ovarian cancer (EOC). However, although there is considerable variation in progression-free survival (PFS), no loci have been found to be associated with outcome at genome-wide levels of significance. Methods: We carried out a genome-wide association study (GWAS) of PFS in 2,352 women with EOC who had undergone cytoreductive surgery and standard carboplatin/paclitaxel chemotherapy. Results: We found seven SNPs at 12q24.33 associated with PFS (P < 5 × 10–8), the top SNP being rs10794418 (HR = 1.24; 95% CI, 1.15–1.34; P = 1.47 × 10–8). High expression of a nearby gene, ULK1, is associated with shorter PFS in EOC, and with poor prognosis in other cancers. SNP rs10794418 is also associated with expression of ULK1 in ovarian tumors, with the allele associated with shorter PFS being associated with higher expression, and chromatin interactions were detected between the ULK1 promoter and associated SNPs in serous and endometrioid EOC cell lines. ULK1 knockout ovarian cancer cell lines showed significantly increased sensitivity to carboplatin in vitro. Conclusions: The locus at 12q24.33 represents one of the first genome-wide significant loci for survival for any cancer. ULK1 is a plausible candidate for the target of this association. Impact: This finding provides insight into genetic markers associated with EOC outcome and potential treatment options. See related commentary by Peres and Monteiro, p. 1604

Abstract Background: The precise mechanism by which the immune system is adversely affected in cancer patients remains poorly understood, but the accumulation of immunosuppressive/protumorigenic myeloid-derived suppressor cells (MDSCs) is thought to be a prominent mechanism contributing to immunologic tolerance of malignant cells in epithelial ovarian cancer (EOC). To this end, we hypothesized genetic variation in MDSC pathway genes would be associated with survival after EOC diagnoses. Methods: We measured the hazard of death due to EOC within 10 years of diagnosis, overall and by invasive subtype, attributable to SNPs in 24 genes relevant in the MDSC pathway in 10,751 women diagnosed with invasive EOC. Versatile Gene-based Association Study and the admixture likelihood method were used to test gene and pathway associations with survival. Results: We did not identify individual SNPs that were significantly associated with survival after correction for multiple testing (P < 3.5 × 10−5), nor did we identify significant associations between the MDSC pathway overall, or the 24 individual genes and EOC survival. Conclusions: In this well-powered analysis, we observed no evidence that inherited variations in MDSC-associated SNPs, individual genes, or the collective genetic pathway contributed to EOC survival outcomes. Impact: Common inherited variation in genes relevant to MDSCs was not associated with survival in women diagnosed with invasive EOC. Cancer Epidemiol Biomarkers Prev; 26(3); 420–4. ©2016 AACR.

Abstract Purpose: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. Experimental Design: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. Results: Five SNPs were significantly associated (P ≤ 1.0 × 10−5) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10−6). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤6 × 10−3). Conclusions: We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies. Clin Cancer Res; 21(23); 5264–76. ©2015 AACR.

Abstract Primary and acquired chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that heritable polymorphisms might be associated with clinical outcome. Through the Ovarian Cancer Association Consortium, we have collected detailed clinical data from a large number of ovarian cancer patients. We have conducted association analyses of progression-free survival (PFS) and overall survival (OS) for 2,901 European women with ovarian carcinoma for ∼8 million imputed SNPs with minor allele frequency ≥ 0.02 and good imputation quality (imputation r2 ≥ 0.3) from the iCOGS experiment (Pharoah et al Nat Genet. 2013). Cox regression models adjusted for known prognostic factors were used to assess the log-additive effects of SNPs on PFS and OS in 2,825 patients who underwent cytoreductive surgery and received any chemotherapy (‘all chemo’) and in the subset of 1,098 patients who underwent cytoreductive surgery followed by ≥ 4 cycles of carboplatin AUC 5 or 6 and paclitaxel 175 or 135 mg/m2 intravenously (‘standard chemo’). We identified five SNPs at four loci that were significantly associated with outcome (p ≤ 10-7) in at least one of four analyses (Table). Analysis of expression data for genes within a 1Mb region flanking each lead SNP indicates significant associations between nearby genes and ovarian cancer survival. Of particular interest is the heat shock protein crystalline αB (CRYAB) at 11q23.1. We have also identified significant associations with KIAA1598 and RAVER2. Further analysis of these loci in a larger genotyped sample is necessary to definitively identify SNP(s) associated with outcome. Our study adds to the growing evidence that genetic variants are associated with ovarian cancer prognosis. Table: SNPs associated with ovarian cancer outcome and gene expression Overall Survival (P)*Progression-Free Survival (P)*Lead SNPChromosome LocusImputation R²Expression AnalysisAll chemoStandard chemoAll chemoStandard chemors1429768671p31.30.742.14E-0512.69E-044.68E-055.11E-073.64E-09rs559375217q32.30.600.198.58E-082.32E-052.80E-031.85E-03rs7885346210q26.110.602.23E-0724.57E-036.57E-081.65E-016.85E-03rs1089121911q23.10.841.53E-0531.51E-059.50E-081.50E-042.32E-04rs3579103211q23.10.811.53E-0531.66E-055.88E-086.46E-051.87E-04*P-values are adjusted for known confounders of ovarian cancer outcomes; FIGO stage, grade, histology, residual disease, and additionally for age at diagnosis for OS.1 RAVER2; 2 KIAA1598; 3 CRYAB Citation Format: Sharon E. Johnatty, Jonathan Tyrer, Jonathan Beesley, Bo Gao, Yi Lu, Stuart MacGregor, Anna deFazio, Paul Pharoah, Ellen Goode, Georgia Chenevix-Trench. Identification of genetic loci associated with ovarian cancer prognosis. [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 3286. doi:10.1158/1538-7445.AM2014-3286

Abstract 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

Abstract Background: Invasive ovarian cancer is a significant cause of gynecologic cancer mortality. Methods: We examined whether this mortality was associated with inherited variation in approximately 170 candidate genes/regions [993 single-nucleotide polymorphisms (SNPs)] in a multistage analysis based initially on 312 Mayo Clinic cases (172 deaths). Additional analyses used The Cancer Genome Atlas (TCGA; 127 cases, 62 deaths). For the most compelling gene, we immunostained Mayo Clinic tissue microarrays (TMA, 326 cases) and conducted consortium-based SNP replication analysis (2,560 cases, 1,046 deaths). Results: The strongest initial mortality association was in HGF (hepatocyte growth factor) at rs1800793 (HR = 1.7, 95% CI = 1.3–2.2, P = 2.0 × 10−5) and with overall variation in HGF (gene-level test, P = 3.7 × 10−4). Analysis of TCGA data revealed consistent associations [e.g., rs5745709 (r2 = 0.96 with rs1800793): TCGA HR = 2.4, CI = 1.4–4.1, P = 2.2 × 10−3; Mayo Clinic + TCGA HR = 1.6, CI = 1.3–1.9, P = 7.0 × 10−5] and suggested genotype correlation with reduced HGF mRNA levels (P = 0.01). In Mayo Clinic TMAs, protein levels of HGF, its receptor MET (C-MET), and phospho-MET were not associated with genotype and did not serve as an intermediate phenotype; however, phospho-MET was associated with reduced mortality (P = 0.01) likely due to higher expression in early-stage disease. In eight additional ovarian cancer case series, HGF rs5745709 was not associated with mortality (HR = 1.0, CI = 0.9–1.1, P = 0.87). Conclusions: We conclude that although HGF signaling is critical to migration, invasion, and apoptosis, it is unlikely that HGF genetic variation plays a major role in ovarian cancer mortality. Furthermore, any minor role is not related to genetically-determined expression. Impact: Our study shows the utility of multiple data types and multiple data sets in observational studies. Cancer Epidemiol Biomarkers Prev; 20(8); 1638–48. ©2011 AACR.

Abstract Purpose: Cell-based approaches were used to identify genetic markers predictive of patients' risk for poor response prior to chemotherapy. Experimental Design: We conducted genome-wide association studies (GWAS) to identify single-nucleotide polymorphisms (SNP) associated with cellular sensitivity to carboplatin through their effects on mRNA expression using International HapMap lymphoblastoid cell lines (LCL) and replicated them in additional LCLs. SNPs passing both stages of the cell-based study were tested for association with progression-free survival (PFS) in patients. Phase 1 validation was based on 377 ovarian cancer patients receiving at least four cycles of carboplatin and paclitaxel from the Australian Ovarian Cancer Study (AOCS). Positive associations were then assessed in phase 2 validation analysis of 1,326 patients from the Ovarian Cancer Association Consortium and The Cancer Genome Atlas. Results: In the initial GWAS, 342 SNPs were associated with carboplatin-induced cytotoxicity, of which 18 unique SNPs were retained after assessing their association with gene expression. One SNP (rs1649942) was replicated in an independent LCL set (Bonferroni adjusted P < 0.05). It was found to be significantly associated with decreased PFS in phase 1 AOCS patients (Pper-allele = 2 × 10−2), with a stronger effect in the subset of women with optimally debulked tumors (Pper-allele = 4 × 10−3). rs1649942 was also associated with poorer overall survival in women with optimally debulked tumors (Pper-allele = 9 × 10−3). However, this SNP was not significant in phase 2 validation analysis with patients from numerous cohorts. Conclusion: This study shows the potential of cell-based, genome-wide approaches to identify germline predictors of treatment outcome and highlights the need for extensive validation in patients to assess their clinical effect. Clin Cancer Res; 17(16); 5490–500. ©2011 AACR.