Integration of a Cross-Ancestry Polygenic Model With Clinical Risk Factors Improves Breast Cancer Risk Stratification.

PURPOSE: To develop and validate a cross-ancestry integrated risk score (caIRS) that combines a cross-ancestry polygenic risk score (caPRS) with a clinical estimator for breast cancer (BC) risk. We hypothesized that the caIRS is a better predictor of BC risk than clinical risk factors across diverse ancestry groups. METHODS: We used diverse retrospective cohort data with longitudinal follow-up to develop a caPRS and integrate it with the Tyrer-Cuzick (T-C) clinical model. We tested the association between the caIRS and BC risk in two validation cohorts including > 130,000 women. We compared model discrimination for 5-year and remaining lifetime BC risk between the caIRS and T-C and assessed how the caIRS would affect screening in the clinic. RESULTS: The caIRS outperformed T-C alone for all populations tested in both validation cohorts and contributed significantly to risk prediction beyond T-C. The area under the receiver operating characteristic curve improved from 0.57 to 0.65, and the odds ratio per standard deviation increased from 1.35 (95% CI, 1.27 to 1.43) to 1.79 (95% CI, 1.70 to 1.88) in validation cohort 1 with similar improvements observed in validation cohort 2. We observed the largest gain in positive predictive value using the caIRS in Black/African American women across both validation cohorts, with an approximately two-fold increase and an equivalent negative predictive value as the T-C. In a multivariate, age-adjusted logistic regression model including both caIRS and T-C, caIRS remained significant, indicating that caIRS provides information over T-C alone. CONCLUSION: Adding a caPRS to the T-C model improves BC risk stratification for women of multiple ancestries, which could have implications for screening recommendations and prevention.

Comprehensive Breast Cancer Risk Assessment for CHEK2 and ATM Pathogenic Variant Carriers Incorporating a Polygenic Risk Score and the Tyrer-Cuzick Model.

PURPOSE: Breast cancer risks for CHEK2 and ATM pathogenic variant (PV) carriers are modified by an 86-single nucleotide polymorphism polygenic risk score (PRS) and individual clinical factors. Here, we describe comprehensive risk prediction models for women of European ancestry combining PV status, PRS, and individual clinical variables. MATERIALS AND METHODS: This study included deidentified clinical records from 358,095 women of European ancestry who received testing with a multigene panel (September 2013 to November 2019). Model development included CHEK2 PV carriers (n = 4,286), ATM PV carriers (n = 2,666), and women negative for other breast cancer risk gene PVs (n = 351,143). Odds ratios (ORs) were calculated using multivariable logistic regression with adjustment for familial cancer history. Risk estimates incorporating PV status, PRS, and Tyrer-Cuzick v7.02 were calculated using a Fixed-Stratified method that accounts for correlations between risk factors. Stratification of PV carriers into risk categories on the basis of remaining lifetime risk (RLR) was assessed in independent cohorts of PV carriers. RESULTS: ORs for association of PV status with breast cancer were 2.01 (95% CI, 1.88 to 2.16) and 1.83 (95% CI, 1.68 to 2.00) for CHEK2 and ATM PV carriers, respectively. ORs for PRS per one standard deviation were 1.51 (95% CI, 1.37 to 1.66) and 1.45 (95% CI, 1.30 to 1.64) in CHEK2 and ATM PV carriers, respectively. Using the combined model (PRS plus Tyrer-Cuzick plus PV status), RLR was low (≤ 20%) for 24.2% of CHEK2 PV carriers, medium (20%-50%) for 63.8%, and high (> 50%) for 12.0%. Among ATM PV carriers, RLR was low for 31.5% of patients, medium for 58.5%, and high for 9.7%. CONCLUSION: In CHEK2 and ATM PV carriers, risk assessment including PRS, Tyrer-Cuzick, and PV status has the potential for more precise direction of screening and prevention strategies.

Integrating Clinical and Polygenic Factors to Predict Breast Cancer Risk in Women Undergoing Genetic Testing.

PURPOSE: Screening and prevention decisions for women at increased risk of developing breast cancer depend on genetic and clinical factors to estimate risk and select appropriate interventions. Integration of polygenic risk into clinical breast cancer risk estimators can improve discrimination. However, correlated genetic effects must be incorporated carefully to avoid overestimation of risk. MATERIALS AND METHODS: A novel Fixed-Stratified method was developed that accounts for confounding when adding a new factor to an established risk model. A combined risk score (CRS) of an 86-single-nucleotide polymorphism polygenic risk score and the Tyrer-Cuzick v7.02 clinical risk estimator was generated with attenuation for confounding by family history. Calibration and discriminatory accuracy of the CRS were evaluated in two independent validation cohorts of women of European ancestry (N = 1,615 and N = 518). Discrimination for remaining lifetime risk was examined by age-adjusted logistic regression. Risk stratification with a 20% risk threshold was compared between CRS and Tyrer-Cuzick in an independent clinical cohort (N = 32,576). RESULTS: Simulation studies confirmed that the Fixed-Stratified method produced accurate risk estimation across patients with different family history. In both validation studies, CRS and Tyrer-Cuzick were significantly associated with breast cancer. In an analysis with both CRS and Tyrer-Cuzick as predictors of breast cancer, CRS added significant discrimination independent of that captured by Tyrer-Cuzick (P < 10-11 in validation 1; P < 10-7 in validation 2). In an independent cohort, 18% of women shifted breast cancer risk categories from their Tyrer-Cuzick-based risk compared with risk estimates by CRS. CONCLUSION: Integrating clinical and polygenic factors into a risk model offers more effective risk stratification and supports a personalized genomic approach to breast cancer screening and prevention.

Clinical significance of homologous recombination deficiency score testing in endometrial Cancer.

BACKGROUND: Homologous recombination deficiency (HRD) score is related to chemotherapy response in some cancers, but its role in endometrial cancer in not known. We determined frequency and clinical significance of alterations in the HR pathway in endometrial cancer. METHODS: 253 endometrioid endometrial adenocarcinoma (EEA) samples from two independent cohorts (discovery and replication) were tested for HRD score using the Myriad HRD assay, microsatellite instability (MSI) and tumor mutation burden (TMB) using a next generation sequencing assay. HRD scores were also generated on endometrial cancer cell lines and in vivo response to olaparib was assessed. RESULTS: ROC curves were employed to determine optimal cutoffs of HRD in relation to survival impact in endometrial cancer and a cutoff of HRD ≥ 4 was suggested for DFS using the discovery cohort. Patients from two independent cohorts with HRD score ≥ 4 trended toward worse survival as compared to those with HRD score < 4. Both cohorts were further separated into four groups according to molecular subtypes (TMB positive; MSI positive; HRD positive; all others). When grouped by molecular subtype, there was a significant difference between groups using an HRD ≥4 cutoff in the initial (p = 0.0024) and replication (p = 0.042) cohorts. The Hec1a model (HRD score = 19) was highly sensitive to olaparib in in vitro and in vivo experiments. CONCLUSIONS: High HRD score was associated with worse DFS in our patient cohort. These findings suggest that HRD score may have clinical utility in patients with advanced or recurrent endometrial cancer.

Development and Validation of a Clinical Polygenic Risk Score to Predict Breast Cancer Risk.

PURPOSE: Women with a family history of breast cancer are frequently referred for hereditary cancer genetic testing, yet < 10% are found to have pathogenic variants in known breast cancer susceptibility genes. Large-scale genotyping studies have identified common variants (primarily single-nucleotide polymorphisms [SNPs]) with individually modest breast cancer risk that, in aggregate, account for considerable breast cancer susceptibility. Here, we describe the development and empirical validation of an SNP-based polygenic breast cancer risk score. METHODS: A panel of 94 SNPs was examined for association with breast cancer in women of European ancestry undergoing hereditary cancer genetic testing and negative for pathogenic variants in breast cancer susceptibility genes. Candidate polygenic risk scores (PRSs) as predictors of personal breast cancer history were developed through multivariable logistic regression models adjusted for age, cancer history, and ancestry. An optimized PRS was validated in 2 independent cohorts (n = 13,174; n = 141,160). RESULTS: Within the training cohort (n = 24,259), 4,291 women (18%) had a personal history of breast cancer and 8,725 women (36%) reported breast cancer in a first-degree relative. The optimized PRS included 86 variants and was highly predictive of breast cancer status in both validation cohorts (P = 6.4 × 10-66; P < 10-325). The odds ratio (OR) per unit standard deviation was consistent between validations (OR, 1.45 [95% CI, 1.39 to 1.52]; OR 1.47 [95% CI, 1.45 to 1.49]). In a direct comparison, the 86-SNP PRS outperformed a previously described PRS of 77 SNPs. CONCLUSION: The validation and implementation of a PRS for women without pathogenic variants in known breast cancer susceptibility genes offers potential for risk stratification to guide surveillance recommendations.

Association of a Polygenic Risk Score With Breast Cancer Among Women Carriers of High- and Moderate-Risk Breast Cancer Genes.

Importance: To date, few studies have examined the extent to which polygenic single-nucleotide variation (SNV) (formerly single-nucleotide polymorphism) scores modify risk for carriers of pathogenic variants (PVs) in breast cancer susceptibility genes. In previous reports, polygenic risk modification was reduced for BRCA1 and BRCA2 PV carriers compared with noncarriers, but limited information is available for carriers of CHEK2, ATM, or PALB2 PVs. Objective: To examine an 86-SNV polygenic risk score (PRS) for BRCA1, BRCA2, CHEK2, ATM, and PALB2 PV carriers. Design, Setting, and Participants: A retrospective case-control study using data on 150 962 women tested with a multigene hereditary cancer panel between July 19, 2016, and January 11, 2019, was conducted in a commercial testing laboratory. Participants included women of European ancestry between the ages of 18 and 84 years. Main Outcomes and Measures: Multivariable logistic regression was used to examine the association of the 86-SNV score with invasive breast cancer after adjusting for age, ancestry, and personal and/or family cancer history. Effect sizes, expressed as standardized odds ratios (ORs) with 95% CIs, were assessed for carriers of PVs in each gene as well as for noncarriers. Results: The median age at hereditary cancer testing of the population was 48 years (range, 18-84 years); there were 141 160 noncarriers in addition to carriers of BRCA1 (n = 2249), BRCA2 (n = 2638), CHEK2 (n = 2564), ATM (n = 1445), and PALB2 (n = 906) PVs included in the analysis. The 86-SNV score was associated with breast cancer risk in each of the carrier populations (P < 1 × 10-4). Stratification was more pronounced for noncarriers (OR, 1.47; 95% CI, 1.45-1.49) and CHEK2 PV carriers (OR, 1.49; 95% CI, 1.36-1.64) than for carriers of BRCA1 (OR, 1.20; 95% CI, 1.10-1.32) or BRCA2 (OR, 1.23; 95% CI, 1.12-1.34) PVs. Odds ratios for ATM (OR, 1.37; 95% CI, 1.21-1.55) and PALB2 (OR, 1.34; 95% CI, 1.16-1.55) PV carrier populations were intermediate between those for BRCA1/2 and CHEK2 noncarriers. Conclusions and Relevance: In this study, the 86-SNV score was associated with modified risk for carriers of BRCA1, BRCA2, CHEK2, ATM, and PALB2 PVs. This finding supports previous reports of reduced PRS stratification for BRCA1 and BRCA2 PV carriers compared with noncarriers. Modification of risk in CHEK2 carriers associated with the 86-SNV score appeared to be similar to that observed in women without a PV. Larger studies are needed to provide more refined estimates of polygenic modification of risk for women with PVs in other moderate-penetrance genes.

Characterisation of homologous recombination deficiency in paired primary and recurrent high-grade serous ovarian cancer.

BACKGROUND: Homologous recombination deficiency (HRD) is shown to predict response to DNA-damaging therapies in patients with high-grade serous ovarian cancer (HGSOC); however, changes in HRD during progression remains unknown. METHODS: HRD scores were evaluated in paired primary and/or recurrent HGSOC samples (N = 107) from 54 patients with adjuvant platinum-based chemotherapy. BRCA1/2 mutation, BRCA1 methylation, loss of heterozygosity (LOH), and HRD scores were characterised using tumour DNA-based next-generation sequencing assays. RESULTS: Among 50 evaluable pairs (N = 100 samples), high intra-patient correlation in HRD score was observed (r2 = 0.93). BRCA1/2 mutations, BRCA1/2 LOH, and HRD were maintained between primary and recurrent samples, except for one pair in which a BRCA1 reversion mutation was identified in the recurrent sample. Despite the reversion, both samples were classified as having high HRD scores ( ≥ 42). All samples with BRCA1/2 mutations exhibited high HRD scores; however, high HRD scores were more prevalent than BRCA1/2 mutations (55% vs. 30%, respectively). CONCLUSION: Markers of HRD were maintained between the primary and recurrent samples, regardless of other genomic changes that occurred during recurrence. HRD score/markers in primary tumours may be valuable and adequate for selection of platinum-based therapy and/or poly-ADP-ribose-polymerase (PARP) inhibitors in recurrent HGSOC.