Citations

Abstract ARID1A (BAF250a) is a component of the SWI/SNF chromatin modifying complex, plays an important tumour suppressor role, and is considered prognostic in several malignancies. However, in ovarian carcinomas there are contradictory reports on its relationship to outcome, immune response, and correlation with clinicopathological features. We assembled a series of 1623 endometriosis‐associated ovarian carcinomas, including 1078 endometrioid (ENOC) and 545 clear cell (CCOC) ovarian carcinomas, through combining resources of the Ovarian Tumor Tissue Analysis (OTTA) Consortium, the Canadian Ovarian Unified Experimental Resource (COEUR), local, and collaborative networks. Validated immunohistochemical surrogate assays for ARID1A mutations were applied to all samples. We investigated associations between ARID1A loss/mutation, clinical features, outcome, CD8 + tumour‐infiltrating lymphocytes (CD8 + TILs), and DNA mismatch repair deficiency (MMRd). ARID1A loss was observed in 42% of CCOCs and 25% of ENOCs. We found no associations between ARID1A loss and outcomes, stage, age, or CD8 + TIL status in CCOC. Similarly, we found no association with outcome or stage in endometrioid cases. In ENOC, ARID1A loss was more prevalent in younger patients ( p = 0.012) and was associated with MMRd ( p < 0.001) and the presence of CD8 + TILs ( p = 0.008). Consistent with MMRd being causative of ARID1A mutations, in a subset of ENOCs we also observed an association with ARID1A loss‐of‐function mutation as a result of small indels ( p = 0.035, versus single nucleotide variants). In ENOC, the association with ARID1A loss, CD8 + TILs, and age appears confounded by MMRd status. Although this observation does not explicitly rule out a role for ARID1A influence on CD8 + TIL infiltration in ENOC, given current knowledge regarding MMRd, it seems more likely that effects are dominated by the hypermutation phenotype. This large dataset with consistently applied biomarker assessment now provides a benchmark for the prevalence of ARID1A loss‐of‐function mutations in endometriosis‐associated ovarian cancers and brings clarity to the prognostic significance. © 2021 The Pathological Society of Great Britain and Ireland.

Abstract Background: There is suggestive evidence that inflammation is related to ovarian cancer survival. However, more research is needed to identify inflammation-related factors that are associated with ovarian cancer survival and to determine their combined effects. Methods: This analysis used pooled data on 8,147 women with invasive epithelial ovarian cancer from the Ovarian Cancer Association Consortium. The prediagnosis inflammation-related exposures of interest included alcohol use; aspirin use; other nonsteroidal anti-inflammatory drug use; body mass index; environmental tobacco smoke exposure; history of pelvic inflammatory disease, polycystic ovarian syndrome, and endometriosis; menopausal hormone therapy use; physical inactivity; smoking status; and talc use. Using Cox proportional hazards models, the relationship between each exposure and survival was assessed in 50% of the data. A weighted inflammation-related risk score (IRRS) was developed, and its association with survival was assessed using Cox proportional hazards models in the remaining 50% of the data. Results: There was a statistically significant trend of increasing risk of death per quartile of the IRRS [HR = 1.09; 95% confidence interval (CI), 1.03–1.14]. Women in the upper quartile of the IRRS had a 31% higher death rate compared with the lowest quartile (95% CI, 1.11–1.54). Conclusions: A higher prediagnosis IRRS was associated with an increased mortality risk after an ovarian cancer diagnosis. Further investigation is warranted to evaluate whether postdiagnosis exposures are also associated with survival. Impact: Given that pre- and postdiagnosis exposures are often correlated and many are modifiable, our study results can ultimately motivate the development of behavioral recommendations to enhance survival among patients with ovarian cancer.

Abstract Background: Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC. Methods: We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways. Results: Two approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P &lt; 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P &lt; 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P &lt; 10−4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P &lt; 10−6). Conclusions: DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways. Impact: This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

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 &lt; 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: DNA polymerase epsilon (POLE) is encoded by the POLE gene, and POLE-driven tumors are characterized by high mutational rates. POLE-driven tumors are relatively common in endometrial and colorectal cancer, and their presence is increasingly recognized in ovarian cancer (OC) of endometrioid type. POLE-driven cases possess an abundance of TCT>TAT and TCG>TTG somatic mutations characterized by mutational signature 10 from the Catalog of Somatic Mutations in Cancer (COSMIC). By quantifying the contribution of COSMIC mutational signature 10 in RNA sequencing (RNA-seq) we set out to identify POLE-driven tumors in a set of unselected Mayo Clinic OC. Methods: Mutational profiles were calculated using expressed single-nucleotide variants (eSNV) in the Mayo Clinic OC tumors (n=195), The Cancer Genome Atlas (TCGA) OC tumors (n=419), and the Genotype-Tissue Expression (GTEx) normal ovarian tissues (n=84). Non-negative Matrix Factorization (NMF) of the mutational profiles inferred the contribution per sample of four distinct mutational signatures, one of which corresponds to COSMIC mutational signature 10. Results: In the Mayo Clinic OC cohort we identified six tumors with a predicted contribution from COSMIC mutational signature 10 of over five mutations per megabase. These six cases harbored known POLE hotspot mutations (P286R, S297F, V411L, and A456P) and were of endometrioid histotype (P=5e-04). These six tumors were hypermutated with a higher tumor mutation load (mean, 54.02 mutations per megabase) compared to non-POLE endometrioid OC cases (mean, 7.69 mutations per megabase; P=5e-04), and had an early onset (average age of patients at onset, 48.33 years) when compared to non-POLE endometrioid OC cohort (average age at onset, 60.13 years; P=.008). Samples from TCGA and GTEx had a low COSMIC signature 10 contribution (median 0.16 mutations per megabase; maximum 1.78 mutations per megabase) and carried no POLE hotspot mutations.Conclusions: From the largest cohort of RNA-seq from endometrioid OC to date (n=53), we identified six hypermutated samples likely driven by POLE (frequency, 11%). Our result suggests the clinical need to screen for POLE driver mutations in endometrioid OC, which can guide enrollment in immunotherapy clinical trials.

Abstract Background: Next-generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in oncology clinical practice. However, the utility of genetic information in clinical decision-making process has not been examined extensively from a real-world, data-driven perspective. Through mining real-world data (RWD) from clinical notes, we could extract patients’ genetic information and further associate treatment decisions with genetic information.Methods: We proposed a real-world evidence (RWE) study framework that incorporates context-based natural language processing (NLP) methods and data quality examination before final association analysis. The framework was demonstrated in a Foundation-tested women cancer cohort (N=196). Upon retrieval of patients’ genetic information using NLP system, we assessed the completeness of genetic data captured in unstructured clinical notes according to a genetic data-model. We examined the distribution of different topics regarding BRCA1/2 throughout patients’ treatment process, and then analyzed the association between BRCA1/2 mutation status and the discussion/prescription of targeted therapy. Results: We identified seven topics in clinical context of genetic mentions including: Information, Evaluation, Insurance, Order, Negative, Positive, and Variants of unknown significance (VUS). Our rule-based system achieved a precision of 0.87, recall of 0.93 and F-measure of 0.91. Our machine learning system achieved a precision of 0.901, recall of 0.899 and F-measure of 0.9 for four-topic classification and a precision of 0.833, recall of 0.823 and F-measure of 0.82 for seven-topic classification. We found in result-containing sentences, capture of BRCA1/2 mutation information was 75%, but detailed variant information (e.g. variant types) is largely missing. Using cleaned RWD, significant associations were found between BRCA1/2 positive mutation and targeted therapies.Conclusions: In conclusion, we demonstrated a framework to generate RWE using RWD from different clinical sources. Rule-based NLP system achieved the best performance for resolving contextual variability when extracting RWD from unstructured clinical notes. Data quality issues such as incompleteness and discrepancies exist thus manual data cleaning is needed before further analysis can be performed. Finally, we were able to use cleaned RWD to evaluate real-world utility of genetic information to initiate a prescription of targeted therapy.

AbstractProblemPrevious studies identified circulating CD14+HLA‐DRlo/− monocytic cells as an immune suppressive subset in solid malignancies, such as prostate, renal cell carcinoma, and pancreatic cancer. Such monocytic cells have been implicated not only in tumour progression but also as a potential barrier for immunotherapy. This study examined the relationship between the frequency of circulating monocytic cells and epithelial ovarian cancer (EOC) progression pre‐ and post‐frontline chemotherapy, defined by disease stage, which is a leading prognostic factor for this malignancy.Method of studyIncident cases of 236 women with EOC were recruited and comprehensive flow cytometry was utilized to assess the frequency of peripheral blood CD33+CD11b+HLA‐DR−/lowCD14+CD15− monocytic cells, henceforth termed CD14+HLA‐DRlo/− monocytic cells, prior to and after completion of frontline chemotherapy. Multivariable odds ratios (OR) were used to estimate the association between CD14+HLA‐DRlo/− monocytic cell percentages and disease stage. Wilcoxon signed‐rank tests evaluated changes in these monocytic cell levels pre‐ and post‐chemotherapy in a patient subset (n = 70).ResultsPatients with elevated frequencies of circulating CD14+HLA‐DRlo/− monocytic cells at diagnosis were at 3.33‐fold greater odds of having advanced stage (III/IV) EOC (CI: 1.04‐10.64), with a significant trend in increasing CD14+HLA‐DRlo/−monocytic cell levels (P = .04). There was a 2.02% median decrease of these monocytic cells post‐chemotherapy among a subset of patients with advanced stage disease (P < .0001).ConclusionThese findings support the potential clinical relevance of CD14+HLA‐DRlo/−monocytic cells in EOC for prognosis and may indicate a non‐invasive biomarker to measure disease progression.

Abstract Background : Next- generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in oncology clinical practice. However, the utility of genetic information in clinical decision-making process has not been examined extensively from a real-world, data-driven perspective. Through mining real-world data (RWD) from clinical notes, we could extract patients’ genetic information and further associate treatment decisions with genetic information. Methods : We proposed a real-world evidence (RWE) study framework that incorporates context-based natural language processing (NLP) methods and data quality examination before final association analysis. The framework was demonstrated in a Foundation-tested women cancer cohort (N=196). Upon retrieval of patients’ genetic information using NLP system, we assessed the completeness of genetic data captured in unstructured clinical notes according to a genetic data-model. We examined the distribution of different topics regarding BRCA1/2 throughout patients’ treatment process, and then analyzed the association between BRCA1/2 mutation status and the discussion/prescription of targeted therapy . Results: We identified seven topics in clinical context of genetic mentions including: Information, Evaluation, Insurance, Order, Negative, Positive, and Variants of unknown significance (VUS) . O ur rule-based system achieved a precision of 0.87, recall of 0.93 and F- measure of 0.91. Our machine learning system achieved a precision of 0.901, recall of 0.899 and F- measure of 0.9 for four-topic classification and a precision of 0.833, recall of 0.823 and F- measure of 0.82 for seven-topic classification. We found in result-containing sentences, capture of BRCA1/2 mutation information was 75%, but detailed variant information (e.g. variant types) is largely missing. Using cleaned RWD, significant associations were found between BRCA1/2 positive mutation and targeted therapies. Conclusions : In conclusion, we demonstrated a framework to generate RWE using RWD from different clinical sources. Rule-based NLP system achieved the best performance for resolving contextual variability when extracting RWD from unstructured clinical notes . Data quality issues such as incompleteness and discrepancies exist thus manual data cleaning is needed before further analysis can be performed. Finally, we were able to use cleaned RWD to evaluate real-world utility of genetic information to initiate a prescription of targeted therapy.

Abstract Copy number alterations and loss of heterozygosity (LOH) are common in ovarian tumors, including those on the X chromosome. In females, one of the two copies of the X chromosome is transcriptionally silenced during embryonic development in the epigenetic process of X chromosome inactivation. Specifically, the long non-coding RNA XIST is expressed from the inactive X (Xi) and triggers chromosome-wide DNA methylation. In breast and ovarian cancer cell line studies, Xi deletion with concomitant duplication of the active X (Xa) has been observed. We sought to examine which copy of the X chromosome, Xi or Xa, was gained or lost in a set of primary ovarian tumors, using levels of XIST expression as a marker of X chromosome inactivation. To determine which copy of the X chromosome harbors the alterations, we compared local copy number and LOH in Xq13.2 to the levels of XIST expression in a set of N=134 primary tumors from Mayo Clinic ovarian cancer patients. Associations with XIST expression were examined using ANOVA, with copy number of two and absence of LOH as the reference level. Associations between expression of XIST and expression of other genes were examined with a mixed effects model, to account for the repeated observations across patients, after adjusting for local copy number and LOH. Associations with XIST expression and overall survival were performed with Cox regression. Additional analyses were performed in a subset of 24 patient tumors with X chromosome-wide alterations to simplify interpretation, including a visual examination of chromosome-wide DNA methylation patterns. Analyses were replicated in N=106 ovarian tumors from TCGA with X chromosome-wide alterations. Across N=134 ovarian tumors from Mayo Clinic, abnormal copy number (not equal to two) was associated with reduced XIST expression (p=0.0016). Levels of XIST expression were similar for tumors with one copy and tumors with three or more copies. Similarly, levels of XIST expression were also lower for tumors with LOH (p=5.2E-5). Reduced XIST expression was also associated with poorer survival, after adjusting for age (p=0.02). Results were consistent in the subset of tumors with whole chromosome alterations (pCN=0.0013, pLOH=0.0019). For these tumors, when LOH was present, XIST expression was low and the DNA methylation distribution is bi-modal, suggesting that the inactive X was lost and the active X was gained. Furthermore, after adjusting for copy number and LOH, XIST expression was weakly positively correlated with the median expression of other genes (R2=0.04, p=0.026). In N=106 TCGA tumors with whole X chromosome alterations, XIST expression was also reduced in tumors with abnormal copy number (p=0.006) and with LOH (p=1.5E-10). Taken together, because XIST is expressed from Xi and not Xa, associations of reduced XIST expression with abnormal copy number and presence of LOH suggest that Xi is frequently lost and Xa is gained in ovarian tumors, consistent with cell line studies. These results should be further validated in larger sample sets and examined for association with clinical outcome. Citation Format: Yilin Song, Bryan M. McCauley, Melissa C. Larson, Sebastian M. Armasu, Kate Lawrenson, Ellen L. Goode, Nicholas B. Larson, Stacey J. Winham. Evidence of decreased X chromosome inactivation in primary ovarian tumors [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 2452.

Abstract A majority of patients with high-grade serous ovarian cancer (HGSC) develop progressive disease following primary treatment, with a five-year survival rate of approximately 40%, and less than 10% survive more than 10 years. Profound genomic instability, treatment with DNA-damaging drugs, and a large tumor burden promote the development of acquired resistance in a large proportion of patients, including multiple convergent resistant events within individuals. Despite the propensity of HGSC to develop drug resistance, a small proportion of patients with advanced disease at diagnosis become long-term survivors. These exceptional patients include those who had suboptimal surgical clearance, and therefore were not cured surgically, and others who have had no evidence of disease recurrence following initial surgery and adjuvant chemotherapy. Our study, which is part of the international collaborative Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG), seeks to identify molecular, immunologic, and epidemiologic factors that influence long-term survival in HGSC. This presentation describes our genomic and immunologic analysis of exceptional survival of this deadly disease. Patient characteristics and clinical histories were evaluated to identify patients diagnosed with advanced stage (Stage IIIC/IV) and histopathologically confirmed HGSC with greater than 10-year overall survival. Whole-genome sequencing (WGS) was performed on primary tumors (median 78x coverage) and germline samples (median 39x coverage) of 55 long-term survivors. Primary tumor samples were also characterized by RNA sequencing, DNA methylation profiling, and immunohistochemistry. Thirty-eight (69%) of long-term surviving patients had residual disease following surgery, suggestive of highly chemosensitive disease. Most patients (41, 75%) were alive at last follow-up and 26 (47%) were progression free. Somatic mutation burden was higher in primary tumors of long-term survivors relative to controls. Genome-wide mutational signatures were predominantly Signature 3 (associated with homologous recombination deficiency), Signature 1 (age related), and Signatures 5, 8, and 16 (unknown etiology). Inactivation of the tumor suppressor RB1 by structural rearrangements or homozygous deletion was frequent in long-term survivors, with 33% of tumors showing associated loss of RB1 protein expression by immunohistochemistry compared to 13% of unselected HGSC controls (n=207; P = 0.001). In an independent HGSC cohort (n=847), RB1 protein loss was associated with prolonged survival (HR: 0.75, P &lt; 0.001) compared to patients with RB1-positive tumors. Furthermore, co-occurrence of germline mutations in BRCA1 or BRCA2 and RB1 loss was associated with a significantly longer overall survival compared to patients with retained RB1 protein expression and no germline BRCA mutation (HR: 0.44, P &lt; 0.001). Multiplexed immunohistochemical analysis with immune cell panels demonstrated distinct associations with long-term survivors. This study delineates the full landscape of genomic alterations in HGSC of long-term survivors. Our findings indicate that specific mutations are associated with enhanced host immune responses and long-term survival. Citation Format: Dale Garsed, Ahwan Pandey, Sian Fereday, Kathryn Alsop, Maartje Wouters, Flurina Saner, Catherine Kennedy, Celeste Pearce, Malcolm Pike, Susan Ramus, Martin Kobel, Anna deFazio, Ellen Goode, Brad Nelson, David Bowtell. Molecular analysis of exceptional response in high-grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr IA05.