Investigator

Paul D P Pharoah

Professor of Cancer Epidemiology · Cedars-Sinai Medical Center, Computational Biomedicine

PDPPaul D P Pharoah
Papers(12)
Measuring the accurac…Growth kinetics of hi…Cellular origins of m…Validation of the BOA…Rare germline genetic…Risk Factors for Ovar…Characterizing somati…Exome sequencing iden…Predicted Proteome As…Racial and ethnic dif…Expanding Our Underst…Population-based targ…
Collaborators(10)
Susan J RamusP. M. WebbJonathan TyrerStacey J. WinhamJames D. BrentonCatherine J. KennedyAntonis C. AntoniouMichael AnglesioUsha MenonFrancesmary Modugno
Institutions(9)
Cedars Sinai Medical …University of New Sou…QIMR Berghofer Medica…University Of Cambrid…Mayo Clinic RochesterWestmead Institute Fo…University of British…University College Lo…University Of Pittsbu…

Papers

Measuring the accuracy of electronic health record-based phenotyping in the All of Us Research Program to optimize statistical power for genetic association testing

Abstract Objective Accurate phenotyping is an essential task for researchers utilizing electronic health record (EHR)-linked biobank programs like the All of Us Research Program to study human genetics. However, little guidance is available on how to select an EHR-based phenotyping procedure that maximizes downstream statistical power. This study aims to estimate accuracy of three phenotype definitions of ovarian, female breast, and colorectal cancers in All of Us (v7 release) and determine which is most likely to optimize downstream statistical power for genetic association testing. Materials and Methods We used empirical carrier frequencies of deleterious variants in known risk genes to estimate the accuracy of each phenotype definition and compute statistical power after accounting for the probability of outcome misclassification. Results We found that the choice of phenotype definition can have a substantial impact on statistical power for association testing and that no approach was optimal across all tested diseases. The impact on power was particularly acute for rarer diseases and target risk alleles of moderate penetrance or low frequency. Additionally, our results suggest that the accuracy of higher-complexity phenotyping algorithms is inconsistent across Black and non-Hispanic White participants in All of Us, highlighting the potential for case ascertainment biases to impact downstream association testing. Discussion EHR-based phenotyping presents a bottleneck for maximizing power to detect novel risk alleles in All of Us, as well as a potential source of differential outcome misclassification that researchers should be aware of. We discuss the implications of this as well as potential mitigation strategies.

Validation of the BOADICEA model for epithelial tubo-ovarian cancer risk prediction in UK Biobank

Abstract Background The clinical validity of the multifactorial BOADICEA model for epithelial tubo-ovarian cancer (EOC) risk prediction has not been assessed in a large sample size or over a longer term. Methods We evaluated the model discrimination and calibration in the UK Biobank cohort comprising 199,429 women (733 incident EOCs) of European ancestry without previous cancer history. We predicted 10-year EOC risk incorporating data on questionnaire-based risk factors (QRFs), family history, a 36-SNP polygenic risk score and pathogenic variants (PV) in six EOC susceptibility genes (BRCA1, BRCA2, RAD51C, RAD51D, BRIP1 and PALB2). Results Discriminative ability was maximised under the multifactorial model that included all risk factors (AUC = 0.68, 95% CI: 0.66–0.70). This model was well calibrated in deciles of predicted risk with calibration slope=0.99 (95% CI: 0.98–1.01). Discriminative ability was similar in women younger or older than 60 years. The AUC was higher when analyses were restricted to PV carriers (0.76, 95% CI: 0.69–0.82). Using relative risk (RR) thresholds, the full model classified 97.7%, 1.7%, 0.4% and 0.2% women in the RR < 2.0, 2.0 ≤ RR < 2.9, 2.9 ≤ RR < 6.0 and RR ≥ 6.0 categories, respectively, identifying 9.1 of incident EOC among those with RR ≥ 2.0. Discussion BOADICEA, implemented in CanRisk (www.canrisk.org), provides valid 10-year EOC risks and can facilitate clinical decision-making in EOC risk management.

Rare germline genetic variation in PAX8 transcription factor binding sites and susceptibility to epithelial ovarian cancer

Abstract Common genetic variation throughout the genome and rare coding variants identified to date explain about half of the inherited genetic component of epithelial ovarian cancer risk. It is likely that rare variation in the noncoding genome will explain some of the unexplained heritability, but identifying such variants is challenging. The primary problem is a lack of statistical power to identify individual risk variants by association, as power is a function of sample size, effect size, and allele frequency. Power can be increased by using burden tests, which test for the association of carriers of any variant in a specified genomic region. This has the effect of increasing the putative effect allele frequency. PAX8 is a transcription factor that plays a critical role in tumor progression, migration, and invasion. Furthermore, regulatory elements proximal to target genes of PAX8 are enriched for common ovarian cancer risk variants. We hypothesized that rare variation in PAX8 binding sites is also associated with ovarian cancer risk but unlikely to be associated with risk of breast, colorectal, or endometrial cancer. We have used publicly available, whole-genome sequencing data from the UK 100,000 Genomes Project to evaluate the burden of rare variation in PAX8 binding sites across the genome. Data were available for 522 ovarian cancers, 2984 breast cancers, 2696 colorectal cancers, 836 endometrial cancers, and 2253 noncancer controls. Active binding sites were defined using data from multiple PAX8 and H3K27 chromatin immunoprecipitation sequencing experiments. We found no association between the burden of rare variation in PAX8 binding sites (defined in several ways) and risk of ovarian, breast, or endometrial cancer. An apparent association with colorectal cancer was likely to be a technical artifact as a similar association was also detected for rare variation in random regions of the genome. Despite the null result, this study provides a proof-of-principle for using burden testing to identify rare, noncoding germline genetic variation associated with disease. Larger sample sizes available from large-scale sequencing projects, together with improved understanding of the function of the noncoding genome, will increase the potential of similar studies in the future.

Risk Factors for Ovarian Cancer by BRCA Status: A Collaborative Case-Only Analysis

Abstract Background: Women with an inherited pathogenic variant in BRCA1 or BRCA2 have a greatly increased risk of developing ovarian cancer, but the importance of behavioral factors is less clear. We used a case-only design to compare the magnitude of associations with established reproductive, hormonal, and lifestyle risk factors between BRCA mutation carriers and noncarriers. Methods: We pooled data from five studies from the Ovarian Cancer Association Consortium including 637 BRCA carriers and 4,289 noncarriers. Covariate-adjusted generalized linear mixed models were used to estimate interaction risk ratios (IRR) and 95% confidence intervals (CI), with BRCA (carrier vs. noncarrier) as the response variable. Results: IRRs were above 1.0 for known protective factors including ever being pregnant (IRR = 1.29, 95% CI; 1.00–1.67) and ever using the oral contraceptive pill (1.30, 95% CI; 1.07–1.60), suggesting the protective effects of these factors may be reduced in carriers compared with noncarriers. Conversely, the IRRs for risk factors including endometriosis and menopausal hormone therapy were below 1.0, suggesting weaker positive associations among BRCA carriers. In contrast, associations with lifestyle factors including smoking, physical inactivity, body mass index, and aspirin use did not appear to differ by BRCA status. Conclusions: Our results suggest that associations with hormonal and reproductive factors are generally weaker for those with a pathogenic BRCA variant than those without, while associations with modifiable lifestyle factors are similar for carriers and noncarriers. Impact: Advice to maintain a healthy weight, be physically active, and refrain from smoking will therefore benefit BRCA carriers as well as noncarriers.

Characterizing somatic mutations in ovarian cancer germline risk regions

Abstract Epithelial ovarian cancer (EOC) genetics research has been focused on germline or somatic mutations independently. Emerging evidence suggests that the somatic mutational landscape can be shaped by the germline genetic background. In this study, we aim to unravel the role of somatic alterations within EOC germline susceptibility regions by incorporating functional annotations. We investigate somatic events, including mutational signatures, point mutations, copy number alterations, and transcription factor binding disruptions, within 33 EOC germline susceptibility regions. Our analysis identifies significant associations between candidate germline susceptibility genes and somatic mutational signatures known to be key risk factors for EOC, such as mismatch repair deficiency, age-related mutagenesis, and homologous recombination deficiency. In addition, we find somatic point mutations and copy number alterations are significantly enriched in histotype-specific active enhancers and promoters within EOC risk loci. Furthermore, we examine the impact of germline variants and somatic mutations on transcription factor binding sites, identifying cancer developmental transcription factor motifs frequently affected by both types of mutations. Overall, our study highlights the importance of integrating germline and somatic mutations with regulatory and epigenomic data to gain insights into the genetic basis of EOC.

Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility

Abstract Background: Predicting protein levels from genotypes for proteome-wide association studies (PWAS) may provide insight into the mechanisms underlying cancer susceptibility. Methods: We performed PWAS of breast, endometrial, ovarian, and prostate cancers and their subtypes in several large European-ancestry discovery consortia (effective sample size: 237,483 cases/317,006 controls) and tested the results for replication in an independent European-ancestry GWAS (31,969 cases/410,350 controls). We performed PWAS using the cancer GWAS summary statistics and two sets of plasma protein prediction models, followed by colocalization analysis. Results: Using Atherosclerosis Risk in Communities (ARIC) models, we identified 93 protein–cancer associations [false discovery rate (FDR) < 0.05]. We then performed a meta-analysis of the discovery and replication PWAS, resulting in 61 significant protein–cancer associations (FDR < 0.05). Ten of 15 protein–cancer pairs that could be tested using Trans-Omics for Precision Medicine (TOPMed) protein prediction models replicated with the same directions of effect in both cancer GWAS (P < 0.05). To further support our results, we applied Bayesian colocalization analysis and found colocalized SNPs for SERPINA3 protein levels and prostate cancer (posterior probability, PP = 0.65) and SNUPN protein levels and breast cancer (PP = 0.62). Conclusions: We used PWAS to identify potential biomarkers of hormone-related cancer risk. SNPs in SERPINA3 and SNUPN did not reach genome-wide significance for cancer in the original GWAS, highlighting the power of PWAS for novel locus discovery, with the added advantage of providing directions of protein effect. Impact: PWAS and colocalization are promising methods to identify potential molecular mechanisms underlying complex traits.

Racial and ethnic differences in epithelial ovarian cancer risk: an analysis from the Ovarian Cancer Association Consortium

Abstract Limited estimates exist on risk factors for epithelial ovarian cancer (EOC) in Asian, Hispanic, and Native Hawaiian/Pacific Islander women. Participants in this study included 1734 Asian (n = 785 case and 949 control participants), 266 Native Hawaiian/Pacific Islander (n = 99 case and 167 control participants), 1149 Hispanic (n = 505 case and 644 control participants), and 24 189 White (n = 9981 case and 14 208 control participants) from 11 studies in the Ovarian Cancer Association Consortium. Logistic regression models estimated odds ratios (ORs) and 95% CIs for risk associations by race and ethnicity. Heterogeneity in EOC risk associations by race and ethnicity (P ≤ .02) was observed for oral contraceptive (OC) use, parity, tubal ligation, and smoking. We observed inverse associations with EOC risk for OC use and parity across all groups; associations were strongest in Native Hawaiian/Pacific Islander and Asian women. The inverse association for tubal ligation with risk was most pronounced for Native Hawaiian/Pacific Islander participants (odds ratio (OR) = 0.25; 95% CI, 0.13-0.48) compared with Asian and White participants (OR = 0.68 [95% CI, 0.51-0.90] and OR = 0.78 [95% CI, 0.73-0.85], respectively). Differences in EOC risk factor associations were observed across racial and ethnic groups, which could be due, in part, to varying prevalence of EOC histotypes. Inclusion of greater diversity in future studies is essential to inform prevention strategies. This article is part of a Special Collection on Gynecological Cancers.

Expanding Our Understanding of Ovarian Cancer Risk: The Role of Incomplete Pregnancies

Abstract Background Parity is associated with decreased risk of invasive ovarian cancer; however, the relationship between incomplete pregnancies and invasive ovarian cancer risk is unclear. This relationship was examined using 15 case-control studies from the Ovarian Cancer Association Consortium (OCAC). Histotype-specific associations, which have not been examined previously with large sample sizes, were also evaluated. Methods A pooled analysis of 10 470 invasive epithelial ovarian cancer cases and 16 942 controls was conducted. Odds ratios (ORs) and 95% confidence intervals (CIs) for the association between incomplete pregnancies and invasive epithelial ovarian cancer were estimated using logistic regression. All models were conditioned on OCAC study, race and ethnicity, age, and education level and adjusted for number of complete pregnancies, oral contraceptive use, and history of breastfeeding. The same approach was used for histotype-specific analyses. Results Ever having an incomplete pregnancy was associated with a 16% reduction in ovarian cancer risk (OR = 0.84, 95% CI = 0.79 to 0.89). There was a trend of decreasing risk with increasing number of incomplete pregnancies (2-sided Ptrend < .001). An inverse association was observed for all major histotypes; it was strongest for clear cell ovarian cancer. Conclusions Incomplete pregnancies are associated with a reduced risk of invasive epithelial ovarian cancer. Pregnancy, including incomplete pregnancy, was associated with a greater reduction in risk of clear cell ovarian cancer, but the result was broadly consistent across histotypes. Future work should focus on understanding the mechanisms underlying this reduced risk.

Population-based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high-grade serous ovarian cancer

Purpose The known epithelial ovarian cancer (EOC) susceptibility genes account for less than 50% of the heritable risk of ovarian cancer suggesting that other susceptibility genes exist. The aim of this study was to evaluate the contribution to ovarian cancer susceptibility of rare deleterious germline variants in a set of candidate genes. Methods We sequenced the coding region of 54 candidate genes in 6385 invasive EOC cases and 6115 controls of broad European ancestry. Genes with an increased frequency of putative deleterious variants in cases versus controls were further examined in an independent set of 14 135 EOC cases and 28 655 controls from the Ovarian Cancer Association Consortium and the UK Biobank. For each gene, we estimated the EOC risks and evaluated associations between germline variant status and clinical characteristics. Results The ORs associated for high-grade serous ovarian cancer were 3.01 for PALB2 (95% CI 1.59 to 5.68; p=0.00068), 1.99 for POLK (95% CI 1.15 to 3.43; p=0.014) and 4.07 for SLX4 (95% CI 1.34 to 12.4; p=0.013). Deleterious mutations in FBXO10 were associated with a reduced risk of disease (OR 0.27, 95% CI 0.07 to 1.00, p=0.049). However, based on the Bayes false discovery probability, only the association for PALB2 in high-grade serous ovarian cancer is likely to represent a true positive. Conclusions We have found strong evidence that carriers of PALB2 deleterious mutations are at increased risk of high-grade serous ovarian cancer. Whether the magnitude of risk is sufficiently high to warrant the inclusion of PALB2 in cancer gene panels for ovarian cancer risk testing is unclear; much larger sample sizes will be needed to provide sufficiently precise estimates for clinical counselling.

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE)

Abstract Purpose: Gene expression–based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. Experimental Design: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. Results: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. Conclusions: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications. See related commentary by McMullen et al., p. 5271

Ovarian and Breast Cancer Risks Associated With Pathogenic Variants in RAD51C and RAD51D

Abstract Background The purpose of this study was to estimate precise age-specific tubo-ovarian carcinoma (TOC) and breast cancer (BC) risks for carriers of pathogenic variants in RAD51C and RAD51D. Methods We analyzed data from 6178 families, 125 with pathogenic variants in RAD51C, and 6690 families, 60 with pathogenic variants in RAD51D. TOC and BC relative and cumulative risks were estimated using complex segregation analysis to model the cancer inheritance patterns in families while adjusting for the mode of ascertainment of each family. All statistical tests were two-sided. Results Pathogenic variants in both RAD51C and RAD51D were associated with TOC (RAD51C: relative risk [RR] = 7.55, 95% confidence interval [CI] = 5.60 to 10.19; P = 5 × 10-40; RAD51D: RR = 7.60, 95% CI = 5.61 to 10.30; P = 5 × 10-39) and BC (RAD51C: RR = 1.99, 95% CI = 1.39 to 2.85; P = 1.55 × 10-4; RAD51D: RR = 1.83, 95% CI = 1.24 to 2.72; P = .002). For both RAD51C and RAD51D, there was a suggestion that the TOC relative risks increased with age until around age 60 years and decreased thereafter. The estimated cumulative risks of developing TOC to age 80 years were 11% (95% CI = 6% to 21%) for RAD51C and 13% (95% CI = 7% to 23%) for RAD51D pathogenic variant carriers. The estimated cumulative risks of developing BC to 80 years were 21% (95% CI = 15% to 29%) for RAD51C and 20% (95% CI = 14% to 28%) for RAD51D pathogenic variant carriers. Both TOC and BC risks for RAD51C and RAD51D pathogenic variant carriers varied by cancer family history and could be as high as 32–36% for TOC, for carriers with two first-degree relatives diagnosed with TOC, or 44–46% for BC, for carriers with two first-degree relatives diagnosed with BC. Conclusions These estimates will facilitate the genetic counseling of RAD51C and RAD51D pathogenic variant carriers and justify the incorporation of RAD51C and RAD51D into cancer risk prediction models.

Comprehensive epithelial tubo-ovarian cancer risk prediction model incorporating genetic and epidemiological risk factors

Background Epithelial tubo-ovarian cancer (EOC) has high mortality partly due to late diagnosis. Prevention is available but may be associated with adverse effects. A multifactorial risk model based on known genetic and epidemiological risk factors (RFs) for EOC can help identify women at higher risk who could benefit from targeted screening and prevention. Methods We developed a multifactorial EOC risk model for women of European ancestry incorporating the effects of pathogenic variants (PVs) in BRCA1 , BRCA2 , RAD51C , RAD51D and BRIP1 , a Polygenic Risk Score (PRS) of arbitrary size, the effects of RFs and explicit family history (FH) using a synthetic model approach. The PRS, PV and RFs were assumed to act multiplicatively. Results Based on a currently available PRS for EOC that explains 5% of the EOC polygenic variance, the estimated lifetime risks under the multifactorial model in the general population vary from 0.5% to 4.6% for the first to 99th percentiles of the EOC risk distribution. The corresponding range for women with an affected first-degree relative is 1.9%–10.3%. Based on the combined risk distribution, 33% of RAD51D PV carriers are expected to have a lifetime EOC risk of less than 10%. RFs provided the widest distribution, followed by the PRS. In an independent partial model validation, absolute and relative 5-year risks were well calibrated in quintiles of predicted risk. Conclusion This multifactorial risk model can facilitate stratification, in particular among women with FH of cancer and/or moderate-risk and high-risk PVs. The model is available via the CanRisk Tool ( www.canrisk.org ).

Identification of a Locus Near ULK1 Associated With Progression-Free Survival in Ovarian Cancer

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

Enhancing the BOADICEA cancer risk prediction model to incorporate new data on RAD51C , RAD51D , BARD1 updates to tumour pathology and cancer incidence

Background BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) for breast cancer and the epithelial tubo-ovarian cancer (EOC) models included in the CanRisk tool ( www.canrisk.org ) provide future cancer risks based on pathogenic variants in cancer-susceptibility genes, polygenic risk scores, breast density, questionnaire-based risk factors and family history. Here, we extend the models to include the effects of pathogenic variants in recently established breast cancer and EOC susceptibility genes, up-to-date age-specific pathology distributions and continuous risk factors. Methods BOADICEA was extended to further incorporate the associations of pathogenic variants in BARD1 , RAD51C and RAD51D with breast cancer risk. The EOC model was extended to include the association of PALB2 pathogenic variants with EOC risk. Age-specific distributions of oestrogen-receptor-negative and triple-negative breast cancer status for pathogenic variant carriers in these genes and CHEK2 and ATM were also incorporated. A novel method to include continuous risk factors was developed, exemplified by including adult height as continuous. Results BARD1 , RAD51C and RAD51D explain 0.31% of the breast cancer polygenic variance. When incorporated into the multifactorial model, 34%–44% of these carriers would be reclassified to the near-population and 15%–22% to the high-risk categories based on the UK National Institute for Health and Care Excellence guidelines. Under the EOC multifactorial model, 62%, 35% and 3% of PALB2 carriers have lifetime EOC risks of <5%, 5%–10% and >10%, respectively. Including height as continuous, increased the breast cancer relative risk variance from 0.002 to 0.010. Conclusions These extensions will allow for better personalised risks for BARD1 , RAD51C , RAD51D and PALB2 pathogenic variant carriers and more informed choices on screening, prevention, risk factor modification or other risk-reducing options.

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes

Abstract Purpose: To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes. Experimental Design: We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival. Results: We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy. Conclusions: Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838

Concurrent RB1 Loss and BRCA Deficiency Predicts Enhanced Immunologic Response and Long-term Survival in Tubo-ovarian High-grade Serous Carcinoma

Abstract Purpose: The purpose of this study was to evaluate RB1 expression and survival across ovarian carcinoma histotypes and how co-occurrence of BRCA1 or BRCA2 (BRCA) alterations and RB1 loss influences survival in tubo-ovarian high-grade serous carcinoma (HGSC). Experimental Design: RB1 protein expression was classified by immunohistochemistry in ovarian carcinomas of 7,436 patients from the Ovarian Tumor Tissue Analysis consortium. We examined RB1 expression and germline BRCA status in a subset of 1,134 HGSC, and related genotype to overall survival (OS), tumor-infiltrating CD8+ lymphocytes, and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cells with and without BRCA1 alterations to model co-loss with treatment response. We performed whole-genome and transcriptome data analyses on 126 patients with primary HGSC to characterize tumors with concurrent BRCA deficiency and RB1 loss. Results: RB1 loss was associated with longer OS in HGSC but with poorer prognosis in endometrioid ovarian carcinoma. Patients with HGSC harboring both RB1 loss and pathogenic germline BRCA variants had superior OS compared with patients with either alteration alone, and their median OS was three times longer than those without pathogenic BRCA variants and retained RB1 expression (9.3 vs. 3.1 years). Enhanced sensitivity to cisplatin and paclitaxel was seen in BRCA1-altered cells with RB1 knockout. Combined RB1 loss and BRCA deficiency correlated with transcriptional markers of enhanced IFN response, cell-cycle deregulation, and reduced epithelial–mesenchymal transition. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1. Conclusions: Co-occurrence of RB1 loss and BRCA deficiency was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

GWAS meta-analysis identifies five susceptibility loci for endometrial cancer

Endometrial cancer is the most common gynaecological cancer in high-income countries. In addition to environmental risk factors, genetic predisposition contributes towards endometrial cancer development but is still incompletely defined. Building on genome-wide association studies (GWASs) by the Endometrial Cancer Association Consortium, we conducted a GWAS meta-analysis of 17,278 endometrial cancer cases and 289,180 controls, incorporating biobank samples from the UK, Finland, Estonia and Japan. GWAS analysis identified five additional risk loci (3p25.2, 3q25.2, 6q22.31, 12q21.2, and 17q24.2). Corresponding gene-based analyses supported findings for three of the five loci, at NAV3 (12q21.2), PPARG (3p25.2), and BPTF (17q24.2), as well as two additional candidate risk regions at ATF7IP2 (16p13.2-p13.13) and RPP21 (6p22.1). Validation genotyping in further independent case-control series replicated the most significant locus at 12q21.2 and corroborated risk variants located intronic to NAV3, the gene for Neuron Navigator 3. Downregulation of NAV3 in endometrial cell lines accelerated cell division and wound healing capacity whereas NAV3 overexpression reduced cell survival and increased cell death, indicating that NAV3 acts as a tumour suppressor in endometrial cells. Our large study extends the number of genome-wide significant risk loci identified for endometrial carcinoma by about one-third and proposes a role of NAV3 as a tumour suppressor in this common cancer. This study was mainly supported by funding from the Wilhelm Sander Foundation, Germany, and the National Health and Medical Research Council (NHMRC) of Australia. A complete list of funding organisations is provided in the acknowledgements.

38Works
22Papers
206Collaborators
1Trials
Genetic Predisposition to DiseaseBreast NeoplasmsOvarian NeoplasmsColorectal NeoplasmsCarcinoma, Ovarian EpithelialNeoplasmsPrognosisBiomarkers, Tumor

Positions

2022–

Professor of Cancer Epidemiology

Cedars-Sinai Medical Center · Computational Biomedicine

2012–

Professor of Cancer Epidemiology

University of Cambridge · Public Health and Primary Care

Education

2000

PhD

University of Cambridge · Oncology

1986

BM, BCh

University of Oxford · School of Clinical Medicine