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.

Many breast cancer predisposition genes are involved in DNA damage repair, leading to genome instability that can impact immunosurveillance, neoantigen formation, and the composition of the tumor immune microenvironment. Here, we explored associations between germline protein truncating variants (PTVs) in 34 (putative) breast cancer predisposition genes, of which 26 involved in DNA damage repair, with the abundance of four immune cell markers, i.e., CD8 + , FOXP3 + , CD20 + and CD163 + , across 7,969 invasive breast tumors of women of European ancestry. The most apparent associations were those of CD163, a marker of M2-like tumor-associated macrophages, with genes involved in double- and single-strand break DNA repair, and with the 12 known breast cancer predisposition genes combined. Specifically, DNA damage repair genes, BRCA1, BRCA2, PALB2, RAD51D, and MSH6 were associated with a 1.3 to twofold abundance of CD163-positive cells. Estrogen receptor status was found to mediate associations to a limited extent. Our findings support a role of rare pathogenic germline variants involved in DNA damage repair, and particularly those predisposing to breast cancer, in the immune landscape of breast tumors. These insights may help guide the development of immunomodulatory strategies for breast cancer prevention and treatment.

Breast cancer immune response is important to patient outcome, but the prognostic interaction between tissue-infiltrating immune cell (TIIC) types is not well-characterized. We evaluated the associations between CD8 +, FOXP3+, CD20 +, and CD163+ TIICs and breast cancer-specific survival (BCSS). We developed an AI in Halo to score TIIC percentage by compartment (overall, stromal, or intra-tumoral) in 99,051 microarray images from 12,285 female breast cancers. The associations between log-transformed TIIC scores and BCSS were assessed using Cox regression. CD8+ and FOXP3+ TIICs were associated with better BCSS in ER-negative disease; CD8+ and CD20+ TIICs were associated with a better prognosis in ER-positive disease; and CD163+ TIICs were associated with a poorer prognosis in ER-positive disease in multi-marker models. These results may have implications for breast cancer immunotherapy.

BACKGROUND:The average age of natural menopause (ANM) for European women is 50-52 years. Reproductive risk and lifestyle factors have been found to be associated with ANM. Furthermore, a genome-wide association study found that women with a CHEK2 variant reach ANM 3.49 years later than women without a CHEK2 variant ('non-carriers'). With this study, we aim to validate this association within CHEK2 c.1100delC families. METHODS:As part of the HEreditary Breast and Ovarian cancer Netherlands (Hebon) study, all women who underwent genetic testing for pathogenic variants associated with breast or ovarian cancer were invited to participate and complete a questionnaire on established risk factors. We compared the reported ANM between groups and within selected birth cohorts. HRs and 95% CIs for the association of CHEK2 status with ANM were estimated via Cox regression models, adjusted for age of menarche, parity, smoking status and hormonal contraceptive use. RESULTS:We included 661 CHEK2 c.1100delC heterozygotes, 175 non-carrier relatives and 8839 unrelated non-carriers. CHEK2 c.1100delC women reached ANM at a significantly later age (51.8±4.8 years) compared with non-carrier relatives (50.3±4.0 years) and unrelated non-carriers (49.6±4.8 years). Similar patterns were found within the birth cohorts. In Cox regression analysis, heterozygotes were associated with a later ANM compared with unrelated non-carriers (HR 1.58; 95% CI 1.21 to 2.08) and non-carrier relatives (HR 1.83; 95% CI 1.13 to 2.95). CONCLUSION:CHEK2 c.1100delC is associated with 1.5-2.2 years later ANM compared with non-carriers, underlining the independence of CHEK2 c.1100delC irrespective of heritability of ANM within families.

PURPOSE:Germline CHEK2 c.1100delC-associated breast cancer (BC) patients have been reported with worse prognosis than patients without the variant. However, results are based on older cohorts and treatment regimens. As part of the Hebon-CHEK2 study, we aim to study prognosis in a Dutch cohort of genetically tested ER-positive BC patients diagnosed from 2006 onwards. METHODS:All patients underwent genetic testing based on personal and family history risk, and data on BC outcomes were collected. Hazard ratios (HRs) and 95 % confidence intervals (CI) for the association of CHEK2-status with prognosis were estimated via delayed entry Cox regression models, adjusted for age and year of diagnosis, tumor size, nodal status, and primary treatment regimens. Furthermore, we meta-analyzed our results with previous studies. RESULTS:We included 480 CHEK2 BC patients and 944 BC patients without the variant. Median follow-up was 6.0 years. Heterozygotes were more often diagnosed with small tumors, and lymph node positive disease. No significant difference was found for recurrent disease and distant disease-free survival, neither before 5 years (HR = 0.73; 95 %CI = 0.35-1.53 and HR = 0.99; 95 %CI = 0.44-2.21, respectively), nor after 5 years follow-up (HR = 0.29; 95 %CI = 0.06-1.28 and HR = 0.39; 95 %CI = 0.10-1.39, respectively). Also no significant difference in BC-specific survival (HR = 0.77; 95 %CI = 0.42-1.39) or overall survival (HR = 0.69; 95 %CI = 0.43-1.08) was found. Meta-analysis of our results with previous studies showed a worse BC-specific survival for heterozygotes. CONCLUSION:In our study, with more recent years of diagnosis and treatment, we found no difference in prognosis, as opposed to previous studies. Further research is needed to validate our findings.

CHEK2 is a tumor suppressor gene in multiple types of cancers, notably estrogen receptor-positive (ER+) breast cancer (BC). We previously revealed that CHEK2-derived BC genomes have specific genomic features that are dissimilar from BRCA1/2-initiated BC genomes suggesting a different underlying biology. In the study, we aimed to identify estrogen receptor-positive (ER+) samples that are wild-type for CHEK2 but which exhibit similar properties to CHEK2 mutated tumors to reveal additional genetic drivers of this phenotype. Using whole genome sequencing data of primary and metastatic BC from different subtypes, we categorized the size distribution of structural variants (SVs) such as inversions (INV), tandem duplications (DUP), and deletions (DEL) separately, and established CHEK2-specific SV profiles. We calculated cosine similarity (CS) scores for all samples comparing the SV profile of a sample to that of the baseline SV profile of CHEK2 samples. We labeled ER+ samples without CHEK2 mutation as ER+ CHEK2-like samples if their CS scores were higher than the average + 1 SD of the actual CHEK2 samples. We also studied the location of SVs, defined CHEK2-specific sizes of SVs, and investigated the genes with SVs of these sizes. Lastly, we compared germline mutation frequencies of ER+ CHEK2-like and ER+ CHEK2-unlike tumors. The SV size distributions of 926 primary BCs were established for INV, DUP, and DELs. The INV SV profile of CHEK2 tumors proved very similar in all ER+ tumors and was not used in the classification. Using the CS scores of ER+ tumors to the CHEK2-specific DUP and DEL size distributions, 31 and 47 samples, respectively, were classified as ER+ CHEK2-like tumors. Interestingly, DUPs in CHEK2 and ER+ CHEK2-like tumors were localized, mainly on recurrently affected chromosomes 11 and 17 for ER+ BC. However, no regions or genes specific for CHEK2 tumors were observed in the ER+ CHEK2-like tumors compared to ER+ CHEK2-unlike tumors. Evaluating germline genetic variations in ER+ CHEK2-like and -unlike tumors, we found 7 genes, EBLN2, TAAR2, FAM166B, PNPLA7, IL1RAPL1, ABCC12, and SLC23A2, with increased mutation frequency in ER+ CHEK2-likes (p<0.05), but none of them remained significant after correction for multiple testing. Our method of selecting ER+ samples with similar SV profiles as CHEK2 tumors appeared successful and will likely facilitate the identification of potential CHEK2-associated pathways. Tandem duplications in CHEK2 and CHEK2-like cancers mapped to specific chromosomes but did not pin-point recurrent genes. Only four potential genes with increased germline mutation frequency in ER+ CHEK2-likes (TAAR2, PNPLA7, ABCC12, SLC23A2) have been associated in literature with BC or its subtypes, but none of them connected to CHEK2-related biology. Shuoying Qu, Marcel Smid, John Martens, Antoinette Hollestelle. Analyzing CHEK2’s role in breast cancer via CHEK2-specific genomic profiles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5031.

The breast cancer risk conferred by germline protein truncating variants (PTVs) in known and putative breast cancer genes has been extensively investigated. However, the effect of FANCM PTVs on breast cancer risk remains unclear. Our previous clinical, genetic and functional results on the N-terminal p.Arg658∗ and the two C-terminal p.Gln1701∗ and p.Gly1906Alafs∗12 variants suggested that FANCM PTVs may confer different risks for ER-negative (ER-neg) and triple-negative (TN) breast cancer subtypes. Here, we performed meta-analyses of seven studies totaling 144 681 breast cancer cases and 123 632 controls. FANCM PTVs were tested for association with breast cancer risk overall and the disease clinical subtypes by single variant and burden analyses. Two CRISPR-Cas9-based functional assays were also conducted to test the fitness of cells after knock-in of the p.Arg658∗, p.Gln1701∗ and p.Gly1906Alafs∗12 PTVs and the sensitivity of different FANCM regions to genome editing. Our results suggest that the N-terminal FANCM region upstream of p.Tyr725 harbors essential functions, whereas downstream regions appear dispensable. This is supported by our genetic data which indicate that all FANCM PTVs, excluding the two C-terminal p.Gln1701∗ and p.Gly1906Alafs∗12, are associated with an increased risk of ER-neg (OR = 1.41, P = 0.023) and TN (OR = 1.64, P = 0.0023). Notably, PTVs upstream of AA position 670 are associated with a moderate risk of developing TN breast cancer, and that even when the p.Arg658∗ carriers were excluded from the analysis. Importantly, our results confirm previous data indicating that p.Arg658∗ carriers are at moderate risk of developing ER-neg (OR = 2.08, P = 0.030) and TN (OR = 3.26; P = 0.0034), whereas carriers of p.Gln1701∗ and p.Gly1906Alafs∗12 should not be considered at increased risk. Our data are useful for counseling carriers of FANCM PTVs, but further analyses are warranted to obtain more precise risk estimates.

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.

Purpose CHEK2 c.1100delC is associated with an increased breast cancer risk in women. While this variant is prevalent in the Netherlands (1% in the general population), knowledge of aetiology and prognosis of breast cancer and other tumours in CHEK2 c.1100delC carriers is lacking. The nationwide HEreditary Breast and Ovarian cancer study the Netherlands (Hebon) cohort aims to answer study questions in families with an increased risk of breast cancer and ovarian cancer. While initially focusing on BRCA1/2-variant families, Hebon gradually expanded to include pathogenic variants in other genes associated with breast and/or ovarian cancer over time. This provides an excellent setting to establish a cohort to ultimately study the impact of CHEK2 c.1100delC on cancer risk prediction and surveillance, breast cancer treatment and prognosis.Participants We invited all heterozygous and homozygous CHEK2 c.1100delC indexes and tested female relatives. 1802 women were included, of whom 1374 were heterozygotes and 938 were breast cancer cases. Pedigrees were collected from all clinical genetic departments. Furthermore, participants completed a detailed questionnaire on hormonal and lifestyle factors, family history, cancer diagnosis and treatment.Findings to date Mean age at study inclusion was 53 years. Linkage with the Netherlands Cancer Registry showed a younger age at diagnosis in homozygotes (mean age 41.7 years) and heterozygotes (47.9 years) than non-carriers (51.2 years). Furthermore, carriers were more often diagnosed with grade 2, oestrogen receptor-positive breast cancer and more often developed contralateral breast cancer than non-carriers. Most women consumed alcohol regularly and about half never smoked.Future plans Further data linkages with the Netherlands Cancer Registry will allow prospective follow-up and breast cancer risk assessment in unaffected women at the time of genetic testing, risk of contralateral breast cancer and survival in patients with breast cancer. Also, linkage with the nationwide network and registry of histopathology and cytopathology in The Netherlands (PALGA) allows us to retrieve tumour samples to study tumourigenesis.

PURPOSE:Female CHEK2 c.1100delC heterozygotes are eligible for additional breast surveillance because of an increased breast cancer risk. Increased risks for other cancers have been reported. We studied whether CHEK2 c.1100delC is associated with an increased risk for other cancers within these families. METHODS:Including 10,780 individuals from 609 families, we calculated standardized incidence rates (SIRs) and absolute excess risk (AER, per 10,000 person-years) by comparing first-reported cancer derived from the pedigrees with general Dutch population rates from 1970 onward. Attained-age analyses were performed for sites in which significant increased risks were found. Considering the study design, we primarily focused on cancer risk in women. RESULTS:We found significant increased risks of colorectal cancer (CRC; SIR = 1.43, 95% CI = 1.14-1.76; AER = 1.43) and hematological cancers (SIR = 1.32; 95% CI = 1.02-1.67; AER = 0.87). CRC was significantly more frequent from age 45 onward. CONCLUSION:A significantly increased risk of CRC, and hematological cancers in women was found, starting at a younger age than expected. Currently, colorectal surveillance starts at age 45 in high-risk individuals. Our results suggest that some CHEK2 c.1100delC families might benefit from this surveillance as well; however, further research is needed to determine who may profit from this additional colorectal surveillance.

The publisher regrets that the version of record of the above article contained a number of errors. The correct and final version follows. The publisher would like to apologise for any inconvenience caused. The benefit of adding polygenic risk scores, lifestyle factors, and breast density to family history and genetic status for breast cancer risk and surveillance classification of unaffected women from germline CHEK2 c.1100delC familiesThe BreastVol. 73PreviewTo determine the changes in surveillance category by adding a polygenic risk score based on 311 breast cancer (BC)-associated variants (PRS311), questionnaire-based risk factors and breast density on personalized BC risk in unaffected women from Dutch CHEK2 c.1100delC families. In total, 117 unaffected women (58 heterozygotes and 59 non-carriers) from CHEK2 families were included. Blood-derived DNA samples were genotyped with the GSAMDv3-array to determine PRS311. Lifetime BC risk was calculated in CanRisk, which uses data from the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). Full-Text PDF Open AccessThe benefit of adding polygenic risk scores, lifestyle factors, and breast density to family history and genetic status for breast cancer risk and surveillance classification of unaffected women from germline CHEK2 c.1100delC familiesThe BreastPreviewTo determine the changes in surveillance category by adding a polygenic risk score based on 311 breast cancer (BC)-associated variants (PRS311), questionnaire-based risk factors and breast density on personalized BC risk in unaffected women from Dutch CHEK2 c.1100delC families. In total, 117 unaffected women (58 heterozygotes and 59 non-carriers) from CHEK2 families were included. Blood-derived DNA samples were genotyped with the GSAMDv3-array to determine PRS311. Lifetime BC risk was calculated in CanRisk, which uses data from the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). Full-Text PDF Open Access

Tumors with a pathogenic BRCA1/2 mutation are homologous recombination (HR)-deficient (HRD) and consequently sensitive to platinum-based chemotherapy and Poly-[ADP-Ribose]-Polymerase inhibitors (PARPi). We hypothesized that functional HR status better reflects real-time HR status than BRCA1/2 mutation status. Therefore, we determined the functional HR status of 53 breast cancer (BC) and 38 ovarian cancer (OC) cell lines by measuring the formation of RAD51 foci after irradiation. Discrepancies between functional HR and BRCA1/2 mutation status were investigated using exome sequencing, methylation and gene expression data from 50 HR-related genes. A pathogenic BRCA1/2 mutation was found in 10/53 (18.9%) of BC and 7/38 (18.4%) of OC cell lines. Among BRCA1/2-mutant cell lines, 14/17 (82.4%) were HR-proficient (HRP), while 1/74 (1.4%) wild-type cell lines was HRD. For most (80%) cell lines, we explained the discrepancy between functional HR and BRCA1/2 mutation status. Importantly, 12/14 (85.7%) BRCA1/2-mutant HRP cell lines were explained by mechanisms directly acting on BRCA1/2. Finally, functional HR status was strongly associated with COSMIC single base substitution signature 3, but not BRCA1/2 mutation status. Thus, the majority of BRCA1/2-mutant cell lines do not represent a suitable model for HRD. Moreover, exclusively determining BRCA1/2 mutation status may not suffice for platinum-based chemotherapy or PARPi patient selection.

Background The immune response in breast tumors has an important role in prognosis, but the role of spatial localization of immune cells and of interaction between subtypes is not well characterized. We evaluated the association between spatially resolved tissue infiltrating immune cells (TIICs) and breast cancer specific survival (BCSS) in a large multicenter study. Patients and methods Tissue microarrays with tumor cores from 17,265 breast cancer patients of European descent were stained for CD8, FOXP3, CD20, and CD163. We developed a machine learning based tissue segmentation and immune cell detection algorithm using Halo to score each image for the percentage of marker positive cells by compartment (overall, stroma, or tumor). We assessed the association between log transformed TIIC scores and BCSS using Cox regression. Results Total CD8+ and CD20+ TIICs (stromal and intra-tumoral) were associated with better BCSS in women with ER-negative (HR per standard deviation = 0.91 [95% CI 0.85 - 0.98] and 0.89 [0.84 - 0.94] respectively) and ER-positive disease (HR = 0.92 [95% CI 0.87 - 0.98] and 0.93 [0.86 - 0.99] respectively) in multi-marker models. In contrast, CD163+ macrophages were associated with better BCSS in ER-negative disease (0.94 [0.87 - 1.00]) and a poorer BCSS in ER-positive disease 1.04 [0.99 - 1.10]. There was no association between FOXP3 and BCSS. The observed associations tended to be stronger for intra-tumoral than stromal compartments for all markers. However, the TIIC markers account for only 7.6 percent of the variation in BCSS explained by the multi-marker fully-adjusted model for ER-negative cases and 3.0 percent for ER-positive cases. Conclusions The presence of intra-tumoral and stromal TIICs is associated with better BCSS in both ER-negative and ER-positive breast cancer. This may have implications for the use of immunotherapy. However, the addition of TIICs to existing prognostic models would only result in a small improvement in model performance. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement BCAC was supported by Cancer Research UK grant: PPRPGM-Nov20\100002 and by core funding from the NIHR Cambridge Biomedical Research Centre (NIHR203312). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The B-CAST project was supported by the Horizon 2020 Research and Innovation Programs of the European Union B (grant number: 633784) and the NIHR Cambridge Biomedical Research Centre. AJB was supported by the NIH/Oxcam doctoral programme. The funding of the contributing studies is listed in Supplementary Table 8. ### 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: All participants provided written informed consent. The ethics committees or institutional review boards responsible for oversight of the individual studies are listed in Supplementary Table 9. 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 The tissue segmentation and TIIC scores generated by the Halo algorithm together with the phenotype data, the imputed datasets and the analysis code will be available at the European Genome Phenome Archive on publication (https://ega-archive.org/).

To determine the changes in surveillance category by adding a polygenic risk score based on 311 breast cancer (BC)-associated variants (PRS311), questionnaire-based risk factors and breast density on personalized BC risk in unaffected women from Dutch CHEK2 c.1100delC families.In total, 117 unaffected women (58 heterozygotes and 59 non-carriers) from CHEK2 families were included. Blood-derived DNA samples were genotyped with the GSAMDv3-array to determine PRS311. Lifetime BC risk was calculated in CanRisk, which uses data from the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). Women, were categorized into three surveillance groups.The surveillance advice was reclassified in 20 (34.5%) heterozygotes and 21 (35.6%) non-carriers after adding PRS311. Including questionnaire-based risk factors resulted in an additional change in 11 (20.0%) heterozygotes and 8 (15.1%) non-carriers; and a sub-analysis showed that adding breast density on top shifted another 9 (23.1%) heterozygotes and 5 (27.8%) non-carriers. Overall, the majority of heterozygotes were reclassified to a less intensive surveillance, while non-carriers would require intensified surveillance.The addition of PRS311, questionnaire-based risk factors and breast density to family history resulted in a more personalized BC surveillance advice in CHEK2-families, which may lead to more efficient use of surveillance.

PDF file, 107K, Summary characteristics of the participating BCAC case-control studies.

Association results between minor alleles of 467 variants incorportated in cross tissue gene expression prediction model for the gene of CRHR1.

Table S1: Description of the BCAC studies contributing to COGS. Table S2: Predicted effects of BRCA1 and BRCA2 variants included in the iCOGS array on protein function. Table S3: Frequency of BRCA1 and BRCA2 variants from iCOGS in breast cancer cases and controls. Table S4: Family studies of Y3035S showing scores for each family by constant relative risk and 75% penetrance. Supplementary References.

A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity-findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.