Recessive Fanconi anemia (FA) phenotype is used in classification of BRCA1/FANCS, BRCA2/FANCD1 and PALB2/FANCN variants with respect to dominant hereditary breast-ovarian cancer syndrome. We assessed its utility by examining the spectrum of phenotypes observed in individuals biallelic for BRCA1, BRCA2 or PALB2 pathogenic variants, and exploring the relationship between cancer presentation and allele severity score based on variant molecular features. A data collection instrument comprising 158 Human Phenotype Ontology (HPO) terms was used to document clinical features for individuals with FA from published and/or prospectively collected (total n=172, 43 previously unpublished) phenotypic data. Unique FA-related variants (15 BRCA1, 123 BRCA2, 22 PALB2) were annotated for predicted molecular impact, location, observed splicing or functional impact, and potential in-frame splice rescue. Annotations were used to assign different permutations of allele severity scores, which were assessed for correlation with FA presentation features. The association of BRCA1 and BRCA2 allele severity score with magnitude of breast cancer risk in heterozygotes was evaluated using case-control analysis. Patient-detected features extended beyond the FA ORPHA:84 HPO list, including 84 terms related by hierarchy, and 94 novel terms. Genotype severity score was significantly associated with age at cancer diagnosis in BRCA2 FA individuals (p=1.8×10-8). A similar permutation approach revealed significant differences in magnitude of breast cancer risk according to BRCA1 and BRCA2 allele severity score in heterozygotes. Findings indicate potential to redefine the existing list of FA-related HPO terms, and to use an allele severity scoring approach to predict cancer risk in both FA patients and heterozygotes.

The recessive Fanconi anemia (FA) phenotype is used to classify BRCA1 (FANCS), BRCA2 (FANCD1), and PALB2 (FANCN) variants with respect to dominant hereditary breast-ovarian cancer syndrome. We assessed its utility by examining the phenotypic spectrum observed in individuals with bi-allelic BRCA1, BRCA2, or PALB2 pathogenic variants and exploring the relationship between cancer presentation and allele severity score based on variant molecular features. A data collection instrument comprising 158 Human Phenotype Ontology (HPO) terms was used to document clinical features for individuals with FA from published and/or prospectively collected sources (total n = 172, 43 previously unpublished). Distinct FA-related variants (15 BRCA1, 123 BRCA2, and 22 PALB2) were annotated for predicted molecular impact, location, observed splicing or functional impact, and potential in-frame splicing rescue and used to assign different permutations of allele severity scores, which were assessed for correlation with FA presentation features. The association of BRCA1 and BRCA2 allele severity score with the magnitude of breast cancer risk in heterozygotes was evaluated using case-control analysis. Clinical features extended beyond the HPO list, including 84 terms related by hierarchy and 94 additional terms. The BRCA2 genotype severity score was associated with age at cancer diagnosis in individuals with FA (p = 1.8 × 10-8). A similar permutation approach revealed significant differences in the magnitude of breast cancer risk according to the BRCA1 and BRCA2 allele severity score in heterozygotes. Our findings indicate the potential to redefine FA ORPHA:84 HPO terms and to use an allele severity scoring approach to predict cancer risk in individuals with bi-allelic or heterozygous BRCA1 or BRCA2 variants.

Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT , in HGSOC ( p = 3.9 × 10 −8 ). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC.

Supplementary Tables 1-7 from Assessment of Hepatocyte Growth Factor in Ovarian Cancer Mortality

Supplemental Table 1: Study Sites Information Supplemental Table 2: Sample Sizes by Study Site Supplemental Table 3: Candidate Gene Summary Supplemental Table 4: Candidate Gene GE Analyses top hits (p-value < 10-3) Supplemental Table 5: Candidate Gene BMI-GE Analyses top hits (p-value < 10-3) Supplemental Table 6: Sample Sizes by Low/High status across environmental factors. Supplemental Table 7: Sample Sizes by young adult BMI (Low/High) and Environmental (Low/High) status across 7 environmental factors.

Potential hormonal mechanism to motivate investigation of multi-factor obesity-hormone related risk factors - SNP interactions.

PDF - 149K, Supplemental Table 1. Participating invasive epithelial ovarian cancer studies. Supplementary Table 2. NF-κB genes studied. Supplemental Table 3. Association between clinical variables and overall survival.

Supplementary Figures 1-4 from Assessment of Hepatocyte Growth Factor in Ovarian Cancer Mortality

Supplementary Figures 1-5, Tables 1-8. Supplementary Figure 1: Overview of the analytic approach. Supplementary Figure 2: QQ plots of SNPs with MAF ≥0.02 and imputation r2 ≥0.9 associated with Overall Survival in A. Supplementary Figure 3: ‘All OCAC’ histology-adjusted analysis. Supplementary Figure 4: Forest plots of promising SNPs. Supplementary Figure 5: KM-Plotter graphs of significant associations with outcome. Supplementary Table 1: All studies (OCAC & TCGA) eligible for analyses according to first-line chemotherapy. Supplementary Table 2: Description of individual OCAC studies included in the secondary 'all OCAC' analysis. Supplementary Table 3a: Overall Survival estimates for selected SNPs (MAF ≥0.02) comparing iCOGS imputed (r2 ≥0.3) and iPLEX genotyped samples. Supplementary Table 3b: Progression-free Survival estimates for selected SNPs (MAF ≥0.02) comparing iCOGS imputed (r2 ≥0.3) and iPLEX genotyped samples. Supplementary Table 4: SNPs with imputation r2 ≥0.9, EAF ≥0.02 and p ≤ 1E-05 for at least one of four outcomes analyzed in cases selected according to first-line chemotherapy. Supplementary Table 5: Meta-analysis of largest possible sample (TCGA, non-overlapping iCOGS and iplex genotyped) for selected promising SNPs analyzed in cases selected according to first-line chemotherapy. Supplementary Table 6: Significant association between protein-coding genes within 1Mb of promising SNPs and ovarian cancer outcomes. Supplementary Table 7: SNPs with imputation r-sq≥0.9 and p ≤ 1E-05 for Overall Survival in histology-adj 'all OCAC' analysis. Supplementary Table 8: iCOGS estimates for SNPs previously identified to be associated with response to chemotherapy as reported in the aNHGRI GWAS catalog.

Supplemental Table S1: Number of invasive EOC patients by study site. Supplemental Table S2: Results of Set 1 single variant analysis, for variants with P<5.0E-5. Analysis was adjusted for age, stage, grade, histology, site and PCs, and includes all variants genotyped in Set 1 (including variants non-overlapping with Set 2). Supplemental Table S3: Results of Set 1 gene-level analysis with P<1.0E-4 based on the burden test. Analysis was adjusted for age, stage, grade, histology, site and PCs. CMAF=combined (sum) minor allele frequency across all variants in the gene.

Background:Women with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC. Methods:We performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan-Meier survival curves. Results:Of the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients' median age overall was 54 years. Of the 659 patients with International Federation of Obstetrics and Gynecology stage data, 156 (23.7%) had stage I disease, 64 (9.7%) had stage II, 395 (59.9%) had stage III, and 44 (6.7%) had stage IV. Of the 377 patients with surgical data, 200 (53.0%) had no visible residual disease. Of the 361 patients with chemotherapy data, 330 (91.4%) received first-line platinum-based chemotherapy. The median follow-up duration was 5.0 years. The median progression-free survival and overall survival were 43.2 months and 110.4 months, respectively. Multivariate analysis indicated a statistically significant impact of stage and residual disease on progression-free survival and overall survival. Platinum-based chemotherapy was not associated with a survival advantage. Conclusion:This multicentre analysis indicates that complete surgical cytoreduction to no visible residual disease has the most impact on improved survival in LGSC. This finding could immediately inform and change practice.

PDF file - 157K, Supplemental Table 1. Regulatory T cell genes included in this study (N=25). Supplemental Table 2. Regulatory T cell SNPs included in this study. Supplemental Table 3. Participating invasive epithelial ovarian cancer studies. Supplemental Table 4. Association between clinical variables and overall survival.

Abstract Background: While numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC). Methods: The primary patient set (Set 1) included 14 independent EOC studies (4,293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1,744 patients) and 114,620 variants. Because power to detect rare variants individually is reduced, gene-level tests were conducted. Sets were analyzed separately at individual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped). Results: No individual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta = 1.1E−6, HRSet1 = 1.17, HRSet2 = 1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta = 1.1E−6; Pcorrected = 0.01). Conclusions: Common variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed. Impact: This study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study. Cancer Epidemiol Biomarkers Prev; 25(3); 446–54. ©2016 AACR.

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.

Hereditary endometrial cancer (EC) is most commonly attributed to pathogenic variants in mismatch repair genes. Evidence supports the existence of additional genetic risk factors in the context of multiple cancer diagnoses and/or family history of EC. EC patients (n = 5292) referred for diagnostic multigene cancer panel testing were annotated for presence of a pathogenic gene variant; personal history of prior, concurrent, or subsequent cancer of another type; reported family history of Lynch syndrome or EC. The Pearson chi(2) test was used to assess differences in gene variant prevalence between case sub-groups defined by personal and/or family history of cancer/s, using cases with no family history of Lynch/EC as reference. Another cancer diagnosis was reported for 55% of EC cases. EC cases with a prior and reported family history of Lynch cancer were enriched for variants in MLH1 (p = 3.5 x 10(-7)), MSH2 (p = 3.1 x 10(-7)), and PMS2 (p = .02). Consistent with expectations for a breast cancer gene also predisposing to EC, the variant frequency was increased in EC patients with prior BC and family history of EC for BRCA1 (p = 1.7 x 10(-5)) and PALB2 (p = .0002). Strategic case-case analyses to address cohort ascertainment bias have provided a rationale to direct future studies of candidate hereditary EC genes.

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.

Leiomyomas, adenomyosis, and endometriosis are reported to be risk factors for endometrial carcinoma (EC), and adenomyosis and endometriosis also for ovarian carcinoma (OC). We aimed to describe the prevalence of these conditions in EC patients with or without an OC diagnosis, and to investigate their relationship with EC risk and prognostic factors in these patients. We evaluated the co-existence of these three conditions in 1399 EC patients, and compared the prevalence of epidemiological risk factors and tumor prognostic features in patients with each condition versus not. Prevalence of conditions was also assessed in the subset of patients with prior/concurrent OC. The observed coexistence of leiomyomas, adenomyosis and endometriosis significantly deviated from that expected (P = 1.2 × 10−8). Patients were more likely to: report a younger age at menarche (PTrend = 0.004) if they had leiomyomas; have used oral contraceptives (P = 6.6 × 10−5) or had ≥2 full-term pregnancies (PTrend = 2.0 × 10−9) if they had adenomyosis; be diagnosed with EC at younger age (P = 5.0 × 10−11) if they had endometriosis. Patients with prior/concurrent OC were more likely to be diagnosed at younger age (P = 5.0 × 10−5), have endometriosis (P = 9.9 × 10−7), and present with higher stage EC (PTrend = 6.6 × 10−5). These findings justify further consideration of these gynecologic conditions as independent risk and prognostic factors for EC.

ObjectiveMedical research studies often rely on the manual collection of data from scanned typewritten clinical records, which can be laborious, time consuming and error prone because of the need to review individual clinical records. We aimed to use text mining to assist with the extraction of clinical features from complex text-based scanned pathology records for medical research studies.DesignText mining performance was measured by extracting and annotating three distinct pathological features from scanned photocopies of endometrial carcinoma clinical pathology reports, and comparing results to manually abstracted terms. Inclusion and exclusion keyword trigger terms to capture leiomyomas, endometriosis and adenomyosis were provided based on expert knowledge. Terms were expanded with character variations based on common optical character recognition (OCR) error patterns as well as negation phrases found in sample reports. The approach was evaluated on an unseen test set of 1293 scanned pathology reports originating from laboratories across Australia.SettingScanned typewritten pathology reports for women aged 18–79 years with newly diagnosed endometrial cancer (2005–2007) in Australia.ResultsHigh concordance with final abstracted codes was observed for identifying the presence of three pathology features (94%–98% F-measure). The approach was more consistent and reliable than manual abstractions, identifying 3%–14% additional feature instances.ConclusionKeyword trigger-based automation with OCR error correction and negation handling proved not only to be rapid and convenient, but also providing consistent and reliable data abstractions from scanned clinical records. In conjunction with manual review, it can assist in the generation of high-quality data abstractions for medical research studies.