statistics fine-mapping methods offer advantages over classical methods, including avoiding data-sharing constraints and improved modelling of correlated variables and sparse effects. However, its performance has not been comprehensively evaluated in breast cancer using real-world data. Previous multinomial stepwise regression (MNR) fine-mapping analyses for breast cancer identified 196 credible sets. Here, we apply summary statistics fine-mapping, compare methods, and assess parameters influencing performance. Using summary statistics from the Breast Cancer Association Consortium, we compared finiMOM, SuSiE, and FINEMAP to published MNR results across 129 regions. Performance was assessed by recall using in-sample and out-of-sample LD. Discordant credible sets were examined for technical factors, and target genes were defined using the INQUISIT pipeline. SuSiE showed the closest agreement with MNR. Results varied across regions depending on the assumed number of causal variants (L), with higher values reducing recall and no single L maximising performance. At optimal L per region, SuSiE identified 8,192 CCVs in 244 credible sets, with recall of 88%, 86%, and 72% for overall, ER-positive, and ER-negative breast cancer. Thirty MNR sets were missed. Discordance was partially explained by allele flips, imputation quality, and array heterogeneity. Fifty-two MNR-identified genes, including BRCA2, WNT7B and CREBBP were not recovered, while additional candidate genes were identified. Using out-of-sample LD reduced recall by 3% but identified novel variants. Fine-mapping results vary across methods, and no single approach is sufficient. The choice of L strongly influences results, and combining analytical approaches with functional validation can improve causal variant identification.

BACKGROUND:Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. METHODS:Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) <0.2 was used to identify associations with strong statistical evidence. RESULTS:Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend<0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend<0.001 and <0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend<0.001 and <0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. CONCLUSION:This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

Abstract Breast cancer in women with germline BRCA1/2 pathogenic variants (gBRCA1/2) are generally treated with platinum-based therapies and PARP inhibitors (PARPi) with resistance commonly emerging. As the tumor microenvironment (TME) in gBRCA1 triple-negative breast cancer (TNBC) is enriched with tumor-infiltrating lymphocytes (TILs) and CD8 T cells, treatment trials have been done combining PARPi and immune checkpoint inhibitors (ICIs) in BRCA1 TNBC. This combination has not been shown to be more effective than PARPi alone. Evaluating the TME in gBRCA1/2 TNBC may help identify tumors most likely to benefit from PARPi/ICI therapy. We performed a detailed spatial proteomic analysis to characterize tumor-immune cell interactions in patients with gBRCA1/2 and wild-type (WT) TNBC with spatial tissue multiplexing (PhenoCycler) in 101 gBRCA1, 24 gBRCA2, and 30 WT TNBCs with matched RNAseq for 34 gBRCA1, 8 gBRCA2, and 16 WT TNBCs. A 43-plex antibody panel was developed featuring markers of DNA damage and repair, immune subtypes and exhaustion. We detected single tumor cells (PANCK+) in S/G2 phase (Geminin+) with double-stranded DNA breaks (yH2AX+) and DNA repair capacity (RAD51+) across all three cohorts. gBRCA1/2 TNBC patients exhibited a significantly lower proportion of tumor cells with homologous recombination proficiency (HRP) (gBRCA1 p = 0.006; gBRCA2 p = 0.007) compared to WT TNBC. CD4 & CD8 T cells, and CD20 B cells had intact DNA repair in WT and gBRCA1/2 TNBC. The frequency of CD8+ T (p=0.016) and CD20 B (p=0.003) cells was significantly higher in gBRCA1 compared to WT TNBC; BRCA2 and WT TNBC showed no differences. A detailed characterization of CD8 T cells revealed significantly increased numbers of potentially dysfunctional CD8 T cells in BRCA1 (TOX, p<0.0001; LAG-3, p=0.028; PD-1, p=0.033) and BRCA2 (LAG-3, p=0.033) compared to WT TNBC. We observed two types of TMEs in gBRCA1 TNBC: 1) CD8 low (mean<9.38%) with 1.4-fold increased immune checkpoint (PD-1) expression (mean: 15.4%) and high DNA damage in tumor cells; and 2) CD8 high (>9.38%) with reduced PD-1 and low DNA damage in tumor cells. Our findings suggest that although gBRCA1/2 variants lead to DNA damage and impaired repair in tumor cells, T cells (CD4, CD8) and B cells (CD20) retain intact DNA repair mechanisms. We also found that gBRCA1/2 TNBCs exhibit higher levels of immune checkpoint proteins LAG-3 and PD-1 on CD8 T cells compared to WT TNBC. This finding suggests the potential utility of additional ICI (LAG-3, PD-1) beyond PD-L1 blockade. Importantly, patients with gBRCA1-associated TNBC exhibit two different TMEs, suggesting that the response to ICI- and DNA-damaging-based therapies may differ between tumors, and anticipated prior to treatment. Defining treatment-naïve TME is crucial for designing personalized, targeted ICI strategies for individuals with BRCA-mutated TNBC. Citation Format: Dana Pueschl, Danielle Bragen, Jia-Ren Lin, Anupma Nayak, Derek A. Oldridge, Kate Bennett, Victoria Fang, kConFab Investigators, Kenneth Offit, Andrew K. Godwin, Paul A. James, Phuong L. Mai, Soo Hwang Teo, Antonis Antoniou, Georgia Chenevix-Trench, E. John Wherry, Susan M. Domchek, Katherine L. Nathanson. A single-cell spatial proteomic analysis of the TNBC microenvironment defines genotype-specific features [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4966.

Genome-wide association studies (GWAS) have identified more than 220 loci associated with breast cancer susceptibility, yet identifying effector genes, their modes of action and prioritising therapeutic targets remains a significant challenge. To address this, we performed pooled CRISPR knockout and inhibition screens to identify genes at risk loci that influence cytotoxic T lymphocyte (CTL) killing of MCF7 breast cancer cells in co-culture. These screens uncovered 33 candidate modulating genes, of which we validated six by single gene editing in two cell lines. Deletion of IRF1, ATF7IP, and CASP8 conferred resistance to CTL killing, while disruption of CFLAR, CREBBP and PRMT7 enhanced sensitivity. Analysis of clinical data showed that PRMT7 expression is negatively correlated with CD8+ infiltration and survival in breast cancer patient cohorts. Pharmacological inhibition of PRMT7 sensitized breast cells to CTL killing in vitro, and Prmt7-deficient tumors exhibited reduced growth and increased CD8+ T cell infiltration in immunocompetent mice. Enhanced Prmt7-dependent tumor growth was not observed in immunodeficient mice, implicating Prmt7 in immune evasion. This study underscores the utility of CRISPR screens for high-throughput functional follow-up of GWAS findings and identifies PRMT7 inhibition as a promising therapeutic strategy.

BACKGROUND:Ovarian cancer is characterised by high mortality and lacks effective screening, making prevention critical. Polygenic risk scores (PRS), which aggregate the effects of multiple common alleles, may capture a proportion of currently unexplained genetic risk. While PRS have been evaluated for risk prediction, their association with treatment response and survival remains unclear. This study assessed the utility of a PRS for predicting high-grade serous ovarian cancer (HGSOC) risk in an Australian population and its association with chemotherapy response and outcomes. METHODS:PRS were calculated for 1,097 HGSOC, and 812 controls using data from Australian research programs. Associations between PRS, OC risk, chemotherapy response, and survival were analysed. RESULTS:Each standard-deviation increase in PRS was associated with a 40% increase in HGSOC risk (OR 1.40, p < 0.001). Women in the top 1% of the PRS distribution had a lifetime OC risk approaching 3%. Higher PRS values showed a trend toward poorer outcomes, however these associations were not consistent across analyses. CONCLUSIONS:PRS were not clearly associated with chemotherapy response or survival but represent a significant risk factor for the development of HGSOC. Incorporating PRS into clinical models may improve risk stratification and support targeted prevention. IMPACT:As the first study to evaluate how PRS relate to both HGSOC risk and chemotherapy response and outcomes, we show that PRS are unlikely to serve as therapeutic biomarkers but support their use for enhanced risk-stratified prevention.

BACKGROUND:Whether carriers of BRCA1 or BRCA2 pathogenic variants have increased risks of childhood, adolescent, and young adult cancers is controversial. We aimed to evaluate this risk and to inform clinical care of young BRCA1 and BRCA2 pathogenic variant carriers and genetic testing for childhood, adolescent, and young adult cancer patients. METHODS:Using data from 47 117 individuals from 3086 BRCA1 or BRCA2 families, we conducted pedigree analysis to estimate relative risks (RRs) for cancers diagnosed before age 30 years. RESULTS:Our data included 274 cancers diagnosed before age 30 years: 139 breast cancers, 10 ovarian cancers, and 125 nonbreast nonovarian cancers. Associations for breast cancer in young adulthood (aged 20-29 years) were found with relative risks of 11.4 (95% confidence interval [CI] = 5.5 to 23.7) and 5.2 (95% CI = 1.6 to 17.7) for BRCA1 and BRCA2 pathogenic variant carriers, respectively. No association was found for any other investigated childhood, adolescent, and young adult cancer or for all nonbreast nonovarian cancers combined; the relative risks were 0.4 (95% CI = 0.1 to 1.4) and 1.4 (95% CI = 0.7 to 3.0) in BRCA1 and BRCA2 pathogenic variant carriers, respectively. CONCLUSION:We found no evidence that BRCA1 and BRCA2 pathogenic variant carriers have an increased childhood, adolescent, and young adult cancer risk aside from breast cancer in women aged between 20 and 30 years. Our results, along with a critical evaluation of previous germline sequencing studies, suggest that the childhood and adolescent cancer risk conferred by BRCA1 and BRCA2 pathogenic variant would be low (ie, RR < 2) if it existed. Our findings do not support pathogenic variant testing for offspring of BRCA1 and BRCA2 pathogenic variant carriers at ages younger than 18 years or for conducting BRCA1 and BRCA2 pathogenic variant testing for childhood and adolescent cancer patients.

Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

Background:Breast cancer is multifactorial. Focusing on limited risk factors may miss high-risk individuals. Methods:We assessed the performance and overlap of various risk factors in identifying high-risk individuals for invasive breast cancer (BrCa) and ductal carcinoma in situ (DCIS) in 161,849 European-ancestry and 18,549 Asian-ancestry women. Discriminatory ability was evaluated using the area under the receiver operating characteristic curve (AUC). High-risk criteria included: 5-year absolute risk ≥1·66% by the Gail model [GAILbinary]; first-degree family history of breast cancer [FHbinary]; 5-year absolute risk ≥1·66% by a 313-variants polygenic risk score [PRSbinary]; and carriers of pathogenic variants in breast cancer predisposition genes [PTVbinary]. Findings:The 5-year absolute risk by PRS outperformed the Gail model in predicting BrCa (Europeansvs controls: AUCPRS=0·635 [0·632-0·638] vs AUCGail=0·492 [0·489-0·495]; Asiansvs controls: AUCPRS=0·564 [0·556-0·573] vs AUCGail=0·506 [0·497-0·514]). PRSbinary and GAILbinary identified more high-risk European than Asia individuals. High-risk proportions were higher among BrCa (16-26%) and DCIS (20-33%) compared to controls (9-15%) among young Europeans and all Asians. Fewer than 7% of BrCa, 10% of DCIS, and 3% of controls were classified as high-risk by multiple risk classifiers. Overlap between PRSbinary and PTVbinary was minimal (<0·65% Europeans, <0·15% Asians) compared to the proportion at high risk using PTVbinary alone (Europeans: 4·6%, Asians: 4·4%) and PRSbinary alone (Europeans: 13·9%, Asians: 8·5%). PRSbinary and FHbinary uniquely identified 5-6% and 9-11% of young BrCa, respectively. Interpretation:The incomplete overlap between high-risk individuals identified by PRSbinary, GAILbinary, FHbinary, and PTVbinary highlights the need for a comprehensive approach to breast cancer risk prediction.

Clinical genetic testing identifies variants causal for hereditary cancer, information that is used for risk assessment and clinical management. Unfortunately, some variants identified are of uncertain clinical significance (VUS), complicating patient management. Case-control data is one evidence type used to classify VUS. As an initiative of the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Analytical Working Group we analyze germline sequencing data of BRCA1 and BRCA2 from 96,691 female breast cancer cases and 302,116 controls from three studies: the BRIDGES study of the Breast Cancer Association Consortium, the Cancer Risk Estimates Related to Susceptibility consortium, and the UK Biobank. We observe 11,207 BRCA1 and BRCA2 variants, with 6909 being coding, covering 23.4% of BRCA1 and BRCA2 VUS in ClinVar and 19.2% of ClinVar curated (likely) benign or pathogenic variants. Case-control likelihood ratio (ccLR) evidence is highly consistent with ClinVar assertions for (likely) benign or pathogenic variants; exhibiting 99.1% sensitivity and 95.3% specificity for BRCA1 and 93.3% sensitivity and 86.6% specificity for BRCA2. This approach provides case-control evidence for 787 unclassified variants; these include 579 with strong or moderate benign evidence and 10 with strong pathogenic evidence for which ccLR evidence is sufficient to alter clinical classification.

Polygenic risk scores (PRS) have been shown to be predictive of breast cancer (BC) risk in European BRCA1 and BRCA2 pathogenic variant (PV) carriers, but their utility in Asian populations has not been evaluated. In this study, we evaluated the association of two breast cancer PRS developed for the East Asian general population and three versions of a PRS developed for the European general population in 604 BRCA1 (390 affected by breast cancer) and 785 BRCA2 (552 affected by breast cancer) PV female carriers of Asian ancestry. Only the Asian-based PRS, constructed using approximately 1 million single-nucleotide variations (SNVs), showed a significant association with breast cancer risk (Hazard Ratio per standard deviation (95% Confidence Interval) is 1.47 (1.10-1.95) for BRCA1 and 1.43 (1.04-1.95) for BRCA2). Incorporating this PRS into risk prediction models may improve cancer risk assessment among PV carriers of Asian ancestry.

Background The nucleocytoplasmic shuttling of ERK5 has gained recent attention as a regulator of its diverse roles in cancer progression but the exact mechanisms for this shuttling are still under investigation. Methods Using in vitro, in vivo and in silico studies, we investigated the roles of shorter ERK5 isoforms in regulating the nucleocytoplasmic shuttling of active phosphorylated-ERK5 (pERK5). Retrospective cohorts of primary and metastatic breast cancer cases were used to evaluate the association of the subcellular localization of pERK5 with clinicopathological features. Results Extranuclear localization of pERK5 was observed during cell migration in vitro and at the invasive fronts of metastatic tumors in vivo . The nuclear and extranuclear cell fractions contained different isoforms of pERK5, which are encoded by splice variants expressed in breast and other cancers in the TCGA data. One isoform, isoform-3, lacks the C-terminal transcriptional domain and the nuclear localization signal. The co-expression of isoform-3 and full-length ERK5 associated with high epithelial-to-mesenchymal transition (EMT) and poor patient survival. Experimentally, expressing isoform-3 with full-length ERK5 in breast cancer cells increased cell migration, drove EMT and led to tamoxifen resistance. In breast cancer patient samples, pERK5 showed variable subcellular localizations where its extranuclear localization associated with aggressive clinicopathological features, metastasis, and poor survival. Conclusion Our studies support a model of ERK5 nucleocytoplasmic shuttling driven by splice variants in an interplay between mesenchymal and epithelial states during metastasis. Using ERK5 as a biomarker and a therapeutic target should account for its splicing and context-dependent biological functions. Graphical Abstract ERK5 isoform-3 expression deploys active ERK5 (pERK5) outside the nucleus to facilitate EMT and cell migration. In cells dominantly expressing isoform-1, pERK5 shuttles to the nucleus to drive cell expansion.

Background Breast cancer is multifactorial. Focusing on limited risk factors may miss high-risk individuals. Methods We assessed the performance and overlap of various risk factors in identifying high-risk individuals for invasive breast cancer (BrCa) and ductal carcinoma in situ (DCIS) in 161,849 European-ancestry and 18,549 Asian-ancestry women. Discriminatory ability was evaluated using the area under the receiver operating characteristic curve (AUC). High-risk criteria included: 5-year absolute risk greater or equal to 1.66% by the Gail model [GAILbinary]; first-degree family history of breast cancer [FHbinary]; 5-year absolute risk greater or equal to 1.66% by a 313-variants polygenic risk score [PRSbinary]; and carriers of pathogenic variants in breast cancer predisposition genes [PTVbinary]. Findings The 5-year absolute risk by PRS outperformed the Gail model in predicting BrCa (Europeansvs controls: AUCPRS=0.635 [0.632-0.638] vs AUCGail=0.492 [0.489-0.495]; Asiansvs controls: AUCPRS=0.564 [0.556-0.573] vs AUCGail=0.506 [0.497-0.514]). PRSbinary and GAILbinary identified more high-risk European than Asia individuals. High-risk proportions were higher among BrCa (16-26%) and DCIS (20-33%) compared to controls (9-15%) among young Europeans and all Asians. Fewer than 7% of BrCa, 10% of DCIS, and 3% of controls were classified as high-risk by multiple risk classifiers. Overlap between PRSbinary and PTVbinary was minimal (<0.65% Europeans, <0.15% Asians) compared to the proportion at high risk using PTVbinary alone (Europeans: 4.6%, Asians: 4.4%) and PRSbinary alone (Europeans: 13.9%, Asians: 8.5%). PRSbinary and FHbinary uniquely identified 5-6% and 9-11% of young BrCa, respectively. Interpretation The incomplete overlap between high-risk individuals identified by PRSbinary, GAILbinary, FHbinary, and PTVbinary highlights the need for a comprehensive approach to breast cancer risk prediction. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study is funded by the Agency for Science, Technology and Research (A*STAR) and PRECISION Health Research, Singapore (PRECISE). The breast cancer genome-wide association analyses in BCAC were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministere de l'Economie, de la Science et de l'Innovation du Quebec through Genome Quebec and grant PSR-SIIRI-701, The National Institutes of Health (U19 CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710), and The European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935). All studies and funders are listed in Additional Materials (BCAC Funding and Acknowledgments). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was approved by the A*STAR Institutional Review Board (reference number: 2022-041). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Availability of data and materials The data used in our analyses are available upon reasonable request through BCAC, subject to data access committee approval.

Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We meta-analyzed >22 million variants for 398,238 women from the Ovarian Cancer Association Consortium (OCAC), UK Biobank (UKBB) and Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA) to identify novel HGSOC susceptibility loci. Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was TP53 3’-UTR SNP rs78378222-T’s association with HGSOC (per-T-allele relative risk (RR) = 1.44, 95% CI:1.28–1.62, P = 1.76 × 10−9). Polygenic scores (PGS) were developed using OCAC and CIMBA data and trained on FinnGen data. The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95% CI:1.37–1.54) per standard deviation when validated in the UKBB. This study represents the largest HGSOC GWAS to date – demonstrating that improvements in imputation reference panels and increased sample sizes help to identify HGSOC associated variants that previously went undetected, ultimately improving PGS which can improve personalized HGSOC risk prediction.

Introduction Established personal and familial risk factors contribute collectively to a woman’s risk of breast or ovarian cancer. Existing clinical services offer genetic testing for pathogenic variants in high-risk genes to investigate these risks but recent information on the role of common genomic variants, in the form of a Polygenic Risk Score (PRS), has provided the potential to further personalise breast and ovarian cancer risk assessment. Data from cohort studies support the potential of an integrated risk assessment to improve targeted risk management but experience of this approach in clinical practice is limited.Methods and analysis The polygenic risk modification trial is an Australian multicentre prospective randomised controlled trial of integrated risk assessment including personal and family risk factors with inclusion of breast and ovarian PRS vs standard care. The study will enrol women, unaffected by cancer, undergoing predictive testing at a familial cancer clinic for a pathogenic variant in a known breast cancer (BC) or ovarian cancer (OC) predisposition gene (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D). Array-based genotyping will be used to generate breast cancer (313 SNP) and ovarian cancer (36 SNP) PRS. A suite of materials has been developed for the trial including an online portal for patient consent and questionnaires, and a clinician education programme to train healthcare providers in the use of integrated risk assessment. Long-term follow-up will evaluate differences in the assessed risk and management advice, patient risk management intentions and adherence, patient-reported experience and outcomes, and the health service implications of personalised risk assessment.Ethics and dissemination This study has been approved by the Human Research Ethics Committee of Peter MacCallum Cancer Centre and at all participating centres. Study findings will be disseminated via peer-reviewed publications and conference presentations, and directly to participants.Trial registration number ACTRN12621000009819.

The 313-variant polygenic risk score (PRS313) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed. We explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank. The mean PRS was calculated by country in the BCAC dataset and by country of birth in the UK Biobank. We explored different approaches to reduce the observed heterogeneity in the mean PRS across the countries, and investigated the implications of the distribution variability in risk prediction. The mean PRS313 differed markedly across European countries, being highest in individuals from Greece and Italy and lowest in individuals from Ireland. Using the overall European PRS313 distribution to define risk categories, leads to overestimation and underestimation of risk in some individuals from these countries. Adjustment for principal components explained most of the observed heterogeneity in the mean PRS. The mean estimates derived when using an empirical Bayes approach were similar to the predicted means after principal component adjustment. Our results demonstrate that PRS distribution differs even within European ancestry populations leading to underestimation or overestimation of risk in specific European countries, which could potentially influence clinical management of some individuals if is not appropriately accounted for. Population-specific PRS distributions may be used in breast cancer risk estimation to ensure predicted risks are correctly calibrated across risk categories.

Co-observation of a gene variant with a pathogenic variant in another gene that explains the disease presentation has been designated as evidence against pathogenicity for commonly used variant classification guidelines. Multiple variant curation expert panels have specified, from consensus opinion, that this evidence type is not applicable for the classification of breast cancer predisposition gene variants. Statistical analysis of sequence data for 55,815 individuals diagnosed with breast cancer from the BRIDGES sequencing project was undertaken to formally assess the utility of co-observation data for germline variant classification. Our analysis included expected loss-of-function variants in 11 breast cancer predisposition genes and pathogenic missense variants in BRCA1, BRCA2, and TP53. We assessed whether co-observation of pathogenic variants in two different genes occurred more or less often than expected under the assumption of independence. Co-observation of pathogenic variants in each of BRCA1, BRCA2, and PALB2 with the remaining genes was less frequent than expected. This evidence for depletion remained after adjustment for age at diagnosis, study design (familial versus population-based), and country. Co-observation of a variant of uncertain significance in BRCA1, BRCA2, or PALB2 with a pathogenic variant in another breast cancer gene equated to supporting evidence against pathogenicity following criterion strength assignment based on the likelihood ratio and showed utility in reclassification of missense BRCA1 and BRCA2 variants identified in BRIDGES. Our approach has applicability for assessing the value of co-observation as a predictor of variant pathogenicity in other clinical contexts, including for gene-specific guidelines developed by ClinGen Variant Curation Expert Panels.