Integration of Tumour Sequencing and Case-Control Data to Assess Pathogenicity of RAD51C Missense Variants in Familial Breast Cancer

Integration of Tumour Sequencing and Case-Control Data to Assess Pathogenicity of RAD51C Missense Variants in Familial Breast Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research article Integration of Tumour Sequencing and Case-Control Data to Assess Pathogenicity of RAD51C Missense Variants in Familial Breast Cancer Belle WX Lim, Na Li, Simone M. Rowley, Ella R. Thompson, Simone McInerny, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-294874/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jan, 2022 Read the published version in npj Breast Cancer → Version 1 posted You are reading this latest preprint version Abstract Background: While protein truncating variants in RAD51C have been shown to predispose to triple negative breast cancer (TNBC) and ovarian cancer, little is known about the pathogenicity of missense (MS) variants. Methods: The frequency of rare RAD51C MS variants were assessed in the BEACCON study of 5,734 familial breast cancer cases and 14,382 population controls, and integrated with tumour sequencing data from 21 cases carrying a candidate variant to assess bi-allelic inactivation. Results: Collectively, a significant enrichment of rare missense variants was detected in cases (MAF 0.5 (OR 3.95, 95%CI 1.40 - 12.01, p = 0.006). Despite the large sample size, the majority of variants detected were very rare, precluding definitive conclusions about pathogenicity based solely on the case-control data. Sequencing of 21 tumours from carriers of one of eight candidate MS variants, identified four cases with bi-allelic inactivation through loss of the wild-type allele, while six lost the variant allele and ten remained heterozygous. Loss of the wild-type alleles corresponded strongly with ER- and triple-negative breast tumours and a high homologous recombination deficiency score. Conclusions: Using this approach, the p.Gly264Ser variant, which was previously suspected to be pathogenic based on small case-control analyses and loss of activity in in vitro functional assays, was shown to be benign with similar prevalence in cases and controls, and eight out of nine tumours showing loss of the variant allele or retention of heterozygosity. Conversely, the combined case-control and tumour sequencing data identified p.Ile144Thr, p.Arg212His, p.Gln143Arg and p.Gly114Arg as variants warranting further investigation. Cancer Biology familial breast cancer breast cancer predisposition RAD51C tumour sequencing Figures Figure 1 Background Protein truncating variants in RAD51C predispose to high grade serous ovarian cancer and triple negative breast cancer (TNBC), and when these cancers occur in carriers of truncating variants they exhibit bi-allelic inactivation ( 1 – 3 ). Few studies have investigated whether missense (MS) variants of RAD51C exert similar penetrance as protein truncating variants. Breast cancer case-control studies to date have identified potentially predisposing RAD51C MS variants, such as p.Gly264Ser ( 4 – 6 ), p.Gln143Arg ( 7 , 8 ) and pArg258His ( 9 , 10 ), while target protein and cellular assays have suggested functional impact and pathogenicity of variants including p.Cys135Tyr and p.Gly264Ser ( 5 , 8 , 9 ). However, the sample sizes in these studies were small, with conflicting evidence for many variants. We analysed data from the BEACCON study of 5,734 familial breast cancer cases and 14,382 population controls for rare RAD51C MS variants (MAF < 0.005). To further investigate the potential pathogenicity of candidate variants, we exploited the fact that RAD51C appears to conform to the Knudsen’s “two-hit” hypothesis, and performed tumour sequencing from variant carriers to assess for bi-allelic inactivation and associated homologous recombination deficiency (HRD). We have previously demonstrated the utility of this reproach for RAD51C loss of function (LoF) variants which revealed the presence of bi-allelic inactivation in the form of loss of heterozygosity (LOH) in TNBCs that was also associated with high HRD scores and mutational signature 3 ( 1 ). In this study, case-control analysis data was combined with tumour sequencing, in silico prediction tools and pedigree segregation to assess the pathogenicity of RAD51C missense variants. Methods Cohorts The case cohort comprised of female index patients diagnosed with breast cancer from 5,734 hereditary breast and ovarian cancer (HBOC) families identified from the Variants in Practice (ViP) Study (combined Victorian and Tasmanian Familial Cancer Centres, Australia) and Pathology North (NSW Health Pathology, Newcastle, Australia). The cases were determined eligible for clinical genetic testing for hereditary breast cancer predisposition genes based on personal and/or family history by a specialist Familial Cancer Clinic. All case subjects have been tested negative for BRCA1 / BRCA2 pathogenic variants prior to recruitment. The controls were 14,382 cancer-free female subjects from the Lifepool Study ( http://www.lifepool.org/) in Victoria, Australia (BreastScreen Victoria). The average age of first diagnosis in cases was 45.8 years (range, 17-85), while the average age of controls in this study was 64.4 years (range, 40-97), indicating a design that enrich for lifetime cancer-free controls. Family history of cancer was recorded for all cohort subjects by questionnaire or in-person interview. Cases ascertained through ViP study were provided with detailed pedigrees with breast and ovarian cancer family history verified against state cancer registries, and tumour pathology reports. Targeted sequencing of germline DNA of cases and controls The coding region and exon-intron boundaries (at least 10 bp of each intron) of RAD51C from germline DNA were amplified using a custom designed HaloPlex Targeted Enrichment Assay panel (Agilent Technologies, Santa Clara, CA) and the libraries were sequenced on a HiSeq2500 Genome Analyzer (Illumina, San Diego, CA) as previously described (11-14). Loss-of-function (LoF) variants were defined as stop-gained, frame-shift or essential splice-site variants. Missense (MS) variants were defined as non-synonymous single nucleotide variants. Sequencing of tumour DNA of RAD51C MS carriers Tumour DNA was collected from cancer cells in formalin fixed, paraffin embedded (FFPE) slides by needle microdissection under the microscope. For targeted sequencing, all exons of RAD51C and 487 additional genes (including 27 breast cancer driver genes, total targeted region of 1.337 Mb), and for whole-exome sequencing, all exons were amplified using an Agilent SureSelect XT Custom Panel (15) . For Sanger sequencing, the relevant RAD51C region was amplified using exon-specific primers through polymerase chain reaction and sequenced using ThermoFisher Scientific BigDye Terminator v3.1 kit. The libraries were sequenced on an Illumina Next Seq 500 (75 bp paired end reads). Promoter hyper-methylation was determined by Sanger sequencing of bisulfite-converted tumour DNA using Qiagen EpiTect Bisulfite Kit. Identification of MS variants Sequencing results were aligned to the g1 k x27 h19 reference genome using the Burrows-Wheeler Alignment tool (16), SNP variant calling was carried out using GATK UnifiedGenotyper v2.4 (Broad Institute, Cambridge, MA), Platypus (17) and Varscan (18), and variants were annotated using the Ensembl Variant Effect Predictor (19) as previously described (1). Rare MS variants were identified in canonical transcript by at least two variant callers, with sequencing quality ≥30, allele frequency ≥20% and MAF present at ≤0.005 for MS variants in non-Finnish European in gnomAD (Version 2.1, released 17 October 2018) (20). Manual examination of BAM files and Sanger sequencing was carried out for ambiguous variants to remove sequencing artefacts . Homologous recombination deficiency (HRD) score calculation A copy number plot was generated for each tumour using copywriteR package in R studio (21). From the plot, an HRD score was calculated for each tumour sample as a sum of the occurrence of telomeric allelic imbalances, large-scale state transitions and homologous recombination deficiency–loss of heterozygosity (HRD–LOH) as described previously (22). Sliding window analysis MS variants were separated into each unique window of N amino acids, then Fisher’s Exact Test was performed using the counts of variants in the case and control samples. P-values were then adjusted based on the null distribution estimated by randomising the sample labels of each variant and recalculating the optimal p-value for each iteration. Mutational Signature analysis Rare somatic mutations were identified after filtering against germline variants, removing intron variants, sequencing read depth ≥20, allele frequency ≥10% and MAF present at ≤0.0001 for in non-Finnish European in gnomAD. As the number of somatic mutations was low in individual targeted panel sequenced samples, mutations were pooled into groups according to variant type and/or tumour pathology. Mutational signatures were generated using the DeconstructSig package in R (23). Statistical analysis Odds ratios and Fisher’s exact test (2-sided) were examined for the case-control analysis, with a two-tailed p-value of ≤0.05 designated as statistically significant, and confidence intervals were calculated using conditional Maximum Likelihood Estimate. Benjamini-Hochberg adjustment was used for multiple test corrections (24). All calculations were carried out using R-in built function in R 3.3.2 (25). Results Likely Pathogenic Variants were Enriched in the Case Cohort A total of 51 unique rare MS variants (MAF < 0.005) were detected in 65 cases (1.13%) and 134 controls (0.91%) (OR 1.22, 95% CI 0.89–1.65, p = 0.21) (Table 1 ). Several parameters were used to enrich for potentially pathogenic variants including population frequency, location in known function domains, in silico pathogenicity prediction and tumour phenotype. Consistent with the hypothesis that rare variants are more likely to be deleterious ( 26 ), a reduction of the population frequency threshold resulted in increasing odds ratios that reached statistical significance at MAF < 0.0001 (OR 1.87, 95%CI 1.14–3.03, p = 0.01). Similarly, higher CADD and REVEL score thresholds that should enrich for pathogenic variants were associated with higher odds ratios, especially for a REVEL score of > 0.5 (OR 3.95, 95%CI 1.40–12.01, p = 0.006). Two overlapping functional domains are present in the N-terminal third of RAD51C protein (Holliday junction activity: amino acids 1-126; Interaction with RAD51B, RAD51D and XRCC3: amino acids 79–136) and a significant enrichment of MS variants in cases was observed in the interaction domain (OR 10.04, 95%CI 0.99–494.1, p = 0.03), although the number of variants was low (n = 5), resulting in a wide confidence interval. Table 1 Frequencies of RAD51C missense variants in case and control cohorts according to different filtering criteria to enrich for likely pathogenic variants. Groups Carrier Frequency Sample Size p-value OR (95% CI) Case (%) Control (%) Case Control Rarity MAF < 0.005 65 (1.13%) 134 (0.91%) 5734 14382 0.21 1.22 (0.89–1.65) MAF < 0.001 35 (0.61%) 56 (0.38%) 0.05 1.57 (1.00-2.44) MAF 20 59 (1.03%) 125 (0.85%) 0.29 1.19 (0.85–1.63) CADD > 25 17 (0.30%) 22 (0.15%) 0.05 1.94 (0.97–3.83) REVEL > 0.3 17 (0.30%) 19 (0.13%) 0.02 2.25 (1.10–4.57) REVEL > 0.5 11 (0.19%) 7 (0.05%) 0.006 3.95 (1.40-12.01) Functional domain Interaction domain 4 (0.070%) 1 (0.01%) 0.03 10.04 (0.99–493.1) Holliday domain 6 (0.10%) 7 (0.05%) 0.21 2.15 (0.60–7.48) Hormone receptor subtype ER-positive 23 (1.04%) 137 (0.93%) 2209 0.64 1.09 (0.67–1.71) ER-negative 20 (1.58%) 1262 0.04 1.67 (0.99–2.70) HER2-positive 7 (1.21%) 579 0.51 1.27 (0.50–2.7)1 HER2-negative 29 (1.20%) 2426 0.27 1.26 (0.81–1.89) TN 13 (1.49%) 871 0.11 1.58 (0.81–2.80) Non-TN 23 (1.08%) 2125 0.55 1.14 (0.70–1.78) MAF: Minor Allele Frequency; CADD: Combined Annotation-Dependent Depletion score ( 34 ); REVEL: rare exome variant ensemble learner score ( 35 ); ER: estrogen receptor; HER2: human epidermal growth factor receptor 2; TN: triple-negative. Subgroup analysis based on hormone receptor status was carried out on case subjects where detailed pathology data was available from the Variant in Practice (ViP) study (n = 3,645). Consistent with previous findings for RAD51C LoF carriers, rare MS variants were significantly enriched in the ER-negative breast cancer subgroup (OR 1.67, 95%CI 0.99–2.70, p = 0.04), with a similar but non-significant trend in TNBC cases (OR 1.58, 95%CI 0.81–2.80, p = 0.11). The distribution and frequency of rare MS variants across RAD51C in the 5,734 cases and 14,382 controls is summarised in Fig. 1 . While rare MS variants were distributed across the entire gene, cases showed higher frequencies in the first half of the gene. The position-based odds ratio analysis showed a higher case-control odds ratio for variants located between amino acid positions 82 and 136, coinciding with the interaction domain. Variants Of Interest Detected In Cases And Controls Details of the 51 rare RAD51C MS variants identified in this study including case-control numbers, in silico pathogenicity prediction and literature evidence are summarised in Supplementary Table 1. Also included is the reference variant p.Ala126Thr (MAF = 0.0054), a generally-accepted benign variant. All of the variants were very rare (MAF ≤ 0.0001), with the exception of p.Gly264Ser (MAF = 0.0034). Despite the large sample size, most variants were detected in less than three subjects, therefore the frequencies alone were not adequately powered to confirm or refute pathogenicity. The data did, however, suggest that two previously-identified variants, p.Ala126Thr and p.Gly264Ser, do not represent high penetrance alleles. p.Ala126Thr was detected in 68 (1.19%) cases and 133 (0.9%) controls (OR 1.29, p = 0.10), similar to the allele frequency reported in gnomAD database. Similarly, p.Gly264Ser was detected with equal frequencies in cases (n = 30, 0.52%) and controls (n = 80, 0.54%) (OR 0.96, p = 0.92). Sequencing Of Tumours From Ms Variant Carriers Twenty invasive breast tumours and one high grade serous ovarian tumour from 21 cases were sequenced using a targeted gene panel that included all exons and intron boundaries of RAD51C (Table 2 ). These tumours were from cases that carried one of eight heterozygous candidate variants (p.Gly264Ser, p.Gln143Arg, p.Ile144Thr, p.Arg212His, p.Asp242Asn, p.Ile244Val, p.Arg258His and p.Leu262Val) as well as one homozygous p.Gly264Ser carrier. Of the 20 germline heterozygous carrier tumours, four were found to harbour a second hit through loss of the wild-type allele (loss of heterozygosity, LOH). However, another five had lost the mutant allele while eleven others remained heterozygous. On further investigation, none of the heterozygous cases showed evidence of promoter hyper-methylation or somatic point mutations in RAD51C . Of the eight tumours from heterozygous carriers of the p.Gly264Ser allele, only four showed copy number loss with three of these involving loss of the variant allele. Importantly, both the p.Gly264Ser homozygous carrier and the case with loss of the wild-type allele had HRD scores below those indicative of loss of homologous recombination function ( 27 ). Table 2 Molecular analysis of 21 tumours from RAD51C missense variant carriers. Sample Variant Hormone Receptor/ HER2 Status Allele status HRD Score Promoter Hyper-Methylation Tp53 Somatic Mutation 1 p.Gly264Ser TN Germline homozygous 37 - Mutated 2 TN Wild-type loss 15 No Mutated 3 TN Variant loss 122 No Mutated 4 † TN Variant loss N/A No N/A 5 TN Heterozygous 39 NA Mutated 6 † ER-/ HER2- Variant loss 43 No Mutated 7 ER+/HER2- Heterozygous 10 NA Wild-type 8 ER+/HER2- Heterozygous 29 No Wild-type 9 ER+/HER2+ Heterozygous 28 No Mutated 10 p.Glu143Arg TN Variant loss 67 No Mutated 11 ER-/HER2+ Heterozygous 12 NA Wild-type 12 ER+/HER2- Heterozygous 6 No Wild-type 13 ER+/HER2- Heterozygous N/A No N/A 14 p.Ile144Thr TN Wild-type loss 78 No Mutated 15 ER+/HER2- Heterozygous 18 No Wild-type 16 p.Arg212His ER-/HER2+ Wild-type loss 47 No Mutated 17 ER+/HER2- Heterozygous 10 No Wild-type 18 p.Asp242Asn ER+/HER2+ Variant loss 49 No Wild-type 19 p.Ile244Val TN Variant loss 78 No Mutated 20 p.Arg258His OvCa Wild-type loss 70 No Mutated 21 p.Leu262Val ER+/HER2- Heterozygous 28 No Wild-type All samples were sequenced using targeted panel, with the exception of samples 11 and 20 with whole-exome and samples 4 and 13 with exon-specific Sanger sequencing. HRD: homologous recombination deficiency. † carriers are 1st degree related Loss of the wild-type allele was identified in two triple-negative tumours carrying p.Ile144Thr and p.Arg212His variants respectively, with both showing high HRD scores, while ER-positive tumours carrying these variants remained heterozygous. An ovarian tumour carrying p.Arg258His also showed LOH and had a high HRD score of 70. Among four tumours sequenced that carried the p.Glu143Arg variant, the one triple-negative case was found to have lost the variant allele, while the one ER-negative and two ER-positive tumours remained heterozygous. All three tumours carrying a germline p.Leu262Val, p.Ile244Val or p.Asp242Asn variant were also showed to remained heterozygous. Previous studies have shown that breast tumours from individuals carrying a LoF mutation in RAD51C accompanied with loss of the wild-type allele were associated with single base substitution mutational signature 3 ( 1 , 28 ), and this was assessed for tumours from carriers of candidate MS variants. To achieve the minimum recommended number of somatic mutations (n≥40) for mutational signature estimation, tumours were grouped into those carrying variants of unknown significance (VUS) and those carrying the benign variant p.Gly264Ser (Supplementary Fig. 1). The contribution of signature 3 in tumours carrying a VUS was similar to the tumours carrying the p.Gly264Ser variant. When stratified based on tumour pathology, triple-negative tumours had a higher proportion of signature 3 and higher HRD scores but these were similar in both VUS and benign variant carriers. Whole exome sequencing of a high grade serous ovarian cancer carrying the p.Arg258His variant (case 20) was shown to have lost the wild-type and accompanied by a large proportion of signature 3 and other smaller signatures related to nucleotide excision repair. Pedigree Segregation Of Ms Variant Carriers Nine additional family members from seven families, (representing three different variants), were available to examine the segregation of the germline variant detected in the index case (Supplementary Fig. 2). Four of the families carried the p.Gly264Ser variant which was found to be present in two affected first degree relatives (FDR) (ER + BC 43, BC 50), but absent in two affected second degree relatives (ER + BC 38, lobular ER + BC 56) of the respective index cases. The variant p.Gln143Arg was present in a first degree relative diagnosed with TNBC (age 55), ER-positive breast cancer (age 72) and high grade serous ovarian cancer (age 74), while none of the three unaffected FDR, tested from p.Gln143Arg families carried the variant. Finally, the daughter of an index case carrying the p.Gln137Arg variant remained unaffected but is currently only 35 years old. Discussion Germline protein truncating variants in RAD51C are known to be associated with predisposition to developing high grade serous ovarian cancer and TNBC ( 1 , 5 , 29 ) but whether there are missense variants of equivalent penetrance is unclear. Data from the BEACCON study has demonstrated that collectively, rare RAD51C MS variants are enriched in familial breast cancer, and consistent with protein truncating variants, are more strongly associated with ER-negative and TNBC. Based on an excess in cases and in silico predictions, this study has identified a number of potentially pathogenic variants, however definitive designation is challenging due to the low frequency among the population. Nevertheless, our data does exclude some variants as being moderate- to high-penetrance variants. For example, p.Gly264Ser has previously been reported in several small studies to be associated with ovarian and/or breast cancer ( 4 , 5 ) ( 6 ), which was consistent with functional assays showing this variant caused partial reduction of RAD51C cellular function including cell survival, mitomycin C sensitivity and homologous recombination activity ( 5 , 9 ). However, in the more highly powered BEACCON study, the p.Gly264Ser allele was detected at similar frequencies in cases and controls and was not associated with loss of the wild-type allele in breast cancers from carriers. In addition, the tumour from the homozygous p.Gly264Ser carrier did not show a high HRD score, indicating that its HR pathway remained intact. The data strongly suggests that despite in vitro functional assays showing p.Gly264Ser reduces the activity of RAD51C, it is not associated with increased risk of breast cancer. Taken together, our data conflict with the suggestion that this variant may be pathogenic and highlight the need for caution when extrapolating from the results of functional assays to clinical classification of variants. A number of rare variants previously have been reported as likely pathogenic, including p.Gln143Arg ( 7 , 8 ), p.Arg258His ( 7 , 9 , 10 ), p.Cys135Tyr ( 7 , 8 , 30 ), p.Ile144Thr ( 7 , 31 ) and p.Val169Ala ( 4 , 5 ). In this study, p.Gln143Arg was detected in 0.7% of cases (n = 4), including one TNBC and two with family history of ovarian cancer, and 0.2% of controls (n = 3), consistent with the observed RAD51C phenotypes. Pedigree segregation of family 22 also supported that the variant p.Gln143Arg segregated with two subjects affected with ductal breast cancer. Previously described as unlikely to be pathogenic ( 32 ), p.Arg212His was detected in this study in two cases (0.03%) and no controls, while also predicted as deleterious by all five in silico tools. p.Val169Ala on the other hand was identified in 12 control subjects, three-fold higher than the case frequency, making it unlikely to be a pathogenic variant. Among 12 tumours sequenced across seven germline variants, bi-allelic inactivation and high HRD scores were observed in ER-negative breast cancers and an ovarian cancer of p.Ile144Thr, p.Arg212His and p.Arg258His carriers but not in tumours of p.Glu143Arg, p.Asp242Asn, p.Ile244Val and p.Leu262Val carriers. Promoter hyper-methylation, which has been observed in BRCA1/2 tumours, appears unlikely to be an important mechanism for RAD51C ( 33 ), with no instances observed in the tumours examined. Although the number of tumours and family members sequenced for each variant was still low, when combined with the case-control results, the data provides support for further investigation of those variants identified in this study as candidates by expansion or pooling of databases. While this study generated evidence against the pathogenicity of p.Gly264Ser, there are several limitations to interpreting results for other variants. Despite a large sample size of ~ 20,000 subjects, the power of the study was limited in its capacity to identify and assess individual rare variants. For the variants examined here, most of which have a MAF of ~ 10 − 5 , to securely identifying an odds ratio of > 2 would require a sample size of several million (~ 4.7 million total cases and controls by standard power calculation). Such numbers seem unachievable even with extensive international collaboration. The statistical power is further eroded by the fact that recent findings indicate that only the rarer TN subset of breast cancer is attributable to RAD51C ( 1 – 3 ). Given these limitations of case control analyses, insights from tumour sequencing, that includes identifying a “second hit” and characteristic genome alterations may offer the best avenue for validating or refuting a role for RAD51C MS variants in breast cancer predisposition. Conclusions Evidence from this study supports an association of RAD51C MS variants with familial breast cancer but due to their rarity this study was not sufficiently powered on its own to identify individual pathogenic variants. Tumour sequencing provided an additional tool to interrogate the in vivo consequences of candidate variants and was able to robustly classify some variants a benign. Case-control and tumour sequencing show that the p.Gly264Ser variant is unlikely to be a moderate- to high- penetrance variant, despite in vitro assays showing partial functional impairment. These findings raise questions about the validity of functional assays as accurate predictors of variant pathogenicity. Overall, integrating case-control data with tumour sequencing provides a powerful strategy to clarify the role of RAD51C MS variants in breast cancer predisposition. Abbreviations TNBC Triple negative breast cancer MS Missense MAF Minor allele frequency HRD Homologous recombination deficiency LoF Loss-of-function LOH Loss of heterozygosity HBOC Hereditary breast and ovarian cancer FFPE Formalin fixed, paraffin embedded ViP Variant in Practice Study VUS Variant of unknown significance FDR First degree relative(s) Declarations Ethics approval and consent to participate This study was approved by the Human Research Ethics Committees at each participating ViP study recruitment centre and the Peter MacCallum Cancer Centre (Approval # 09/29). All participants provided informed consent for genetic analysis of their germline DNA (cases and controls) and tumour DNA (cases only). Consent for publication Not applicable Availability of data and materials All sequencing data are deposited to European Genome-phenome Archive which are available upon request to corresponding author. Standard R codes were used. Code requests should be addressed to Prof. Ian Campbell. Competing interests The authors declare no competing financial interests. Funding This work was supported by the National Breast Cancer Foundation (IF-15-004, I.G.C. and P.A.J.), Cancer Australia/National Breast Cancer Foundation (PdCCRS_1107870, I.G.C. and P.A.J.), the Victorian Cancer Agency (Tumor Stream Grant, P.A.J.) and the National Health and Medical Research Council of Australia (GNT1023698, P.A.J.; GNT1041975, I.G.C.). EKS is supported by NHMRC GNT1147498 and NBCF IIRS-20-025. NL is supported by Cancer Council Victoria. Authors’ contributions B.W.X.L. contributed to tumour processing and sequencing, data analysis, and manuscript writing; N.L. contributed to germline data collection and data analysis; S.M.R. contributed to generating sequencing libraries and sample management; E.R.T. contributed to study design and data analysis; M.Z. contributed to bioinformatics analysis and plotting; S.M. and L.D., contributed to collection of study materials or patients; R.J.S. contributed to provision of patients’ material and data interpretation; E.K.S. contributed to data interpretation and manuscript revision; P.A.J. contributed to study design, clinical interpretation, and manuscript revision; I.G.C. contributed to study design, data analysis and manuscript revision. All authors contributed to drafting, revising and final approval of the manuscript. Acknowledgements The authors thank all the participants of the ViP and Lifepool studies for donating their DNA samples and clinical information. We also thank Norah Grewal, the ViP study site principal investigators Geoffrey Lindeman, Marion Harris, Tom John, Ingrid Winship and Yoland Antill, and the staff at the Peter MacCallum Cancer Centre, Royal Melbourne Hospital, Monash Health, Cabrini Health and Barwon Health Familial Cancer Centres and the Austin and Tasmanian Clinical Genetics Services, who enrolled participants and provided clinical data. We thank the following staff from Peter MacCallum Cancer Centre: Tim Semple, Gisela Mir Arnau from Molecular Genomics core facility for sequencing the tumour DNA, Kaushalya Amarasinghe, Niko Thio, and Richard Lupat from Bioinformatics core facility for helping with the bioinformatic analysis, Christina Fennell, Mira Liu and Samantha Cauberg from Tissue Bank for preparing sections of tumor blocks and Heather Thorne, Lynda Williams and Genna Glavich from kConFab for assisting with obtaining the tumor blocks. 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Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Methodological). 1995;57(1):289–300. R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2016. MacArthur DG, Manolio TA, Dimmock DP, Rehm HL, Shendure J, Abecasis GR, et al. Guidelines for investigating causality of sequence variants in human disease. Nature. 2014;508(7497):469–76. Timms KM, Abkevich V, Hughes E, Neff C, Reid J, Morris B, et al. Association of BRCA1/2 defects with genomic scores predictive of DNA damage repair deficiency among breast cancer subtypes. Breast Cancer Res. 2014;16(6):475. Polak P, Kim J, Braunstein LZ, Karlic R, Haradhavala NJ, Tiao G, et al. A mutational signature reveals alterations underlying deficient homologous recombination repair in breast cancer. Nat Genet. 2017;49(10):1476–86. Yang X, Song H, Leslie G, Engel C, Hahnen E, Auber B, et al. Ovarian and Breast Cancer Risks Associated With Pathogenic Variants in RAD51C and RAD51D. JNCI: Journal of the National Cancer Institute. 2020. Sanchez-Bermudez AI, Sarabia-Meseguer MD, Garcia-Aliaga A, Marin-Vera M, Macias-Cerrolaza JA, Henarejos PS, et al. Mutational analysis of RAD51C and RAD51D genes in hereditary breast and ovarian cancer families from Murcia (southeastern Spain). Eur J Med Genet. 2018;61(6):355–61. Kushnir A, Laitman Y, Shimon SP, Berger R, Friedman E. Germline mutations in RAD51C in Jewish high cancer risk families. Breast cancer research treatment. 2012;136(3):869–74. Pang Z, Yao L, Zhang J, Ouyang T, Li J, Wang T, et al. RAD51C germline mutations in Chinese women with familial breast cancer. Breast cancer research treatment. 2011;129(3):1019–20. Vos S, van Diest PJ, Moelans CB. A systematic review on the frequency of BRCA promoter methylation in breast and ovarian carcinomas of BRCA germline mutation carriers: Mutually exclusive, or not? Crit Rev Oncol Hematol. 2018;127:29–41. Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014;46(3):310–5. Ioannidis NM, Rothstein JH, Pejaver V, Middha S, McDonnell SK, Baheti S, et al. REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants. Am J Hum Genet. 2016;99(4):877–85. Supplementary Files Limet.al.Additionalfile1.docx Additional file 1.docx Contains supplementary tables and figures. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-294874","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":15085068,"identity":"37377a1a-086f-45b0-9849-956be6c9dbb6","order_by":0,"name":"Belle WX Lim","email":"","orcid":"https://orcid.org/0000-0002-4739-1526","institution":"Peter MacCallum Cancer Centre","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Belle","middleName":"WX","lastName":"Lim","suffix":""},{"id":15085069,"identity":"b3b938a0-42fd-402c-bc52-9b0d4e8150e5","order_by":1,"name":"Na Li","email":"","orcid":"","institution":"Peter MacCallum Cancer Centre","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Na","middleName":"","lastName":"Li","suffix":""},{"id":15085070,"identity":"726d7da2-86fd-4925-b8f2-28ff6b00ae0e","order_by":2,"name":"Simone M. Rowley","email":"","orcid":"","institution":"Murdoch Childrens Research Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Simone","middleName":"M.","lastName":"Rowley","suffix":""},{"id":15085071,"identity":"c74673d2-1610-4732-8327-caaf0c4fd3ec","order_by":3,"name":"Ella R. Thompson","email":"","orcid":"","institution":"Peter MacCallum Cancer Centre","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ella","middleName":"R.","lastName":"Thompson","suffix":""},{"id":15085072,"identity":"6746f06f-0333-4af1-a73b-3094d88149e3","order_by":4,"name":"Simone McInerny","email":"","orcid":"","institution":"Peter MacCallum Cancer Centre","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Simone","middleName":"","lastName":"McInerny","suffix":""},{"id":15085073,"identity":"3d9a1a16-549d-4961-8fa7-6f3f2c20df6c","order_by":5,"name":"Magnus Zethoven","email":"","orcid":"","institution":"Peter MacCallum Cancer Centre","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Magnus","middleName":"","lastName":"Zethoven","suffix":""},{"id":15085074,"identity":"402b905b-564d-47c1-8f5a-58a77fa35173","order_by":6,"name":"Rodney J. Scott","email":"","orcid":"","institution":"The University of Newcastle","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rodney","middleName":"J.","lastName":"Scott","suffix":""},{"id":15085075,"identity":"8d420d4e-a05e-419e-ab21-ccc1699184aa","order_by":7,"name":"Lisa Devereux","email":"","orcid":"","institution":"Peter MacCallum Cancer Centre","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lisa","middleName":"","lastName":"Devereux","suffix":""},{"id":15085076,"identity":"a71c815b-e555-4201-a4af-b352c7c9151a","order_by":8,"name":"Erica K. Sloan","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Erica","middleName":"K.","lastName":"Sloan","suffix":""},{"id":15085077,"identity":"88e0c8ea-6046-40d9-948e-86f84f1a07b4","order_by":9,"name":"Paul A. James","email":"","orcid":"","institution":"Peter MacCallum Cancer Centre","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Paul","middleName":"A.","lastName":"James","suffix":""},{"id":15085078,"identity":"8ffc62eb-d8d4-4e07-bc89-dab5c20c61fe","order_by":10,"name":"Ian G. Campbell","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYBACNhjDgIG58cAHErUwNhycwcAgQbx1IC2HeYjRwsd+9gDDj5pteebsjQ2HbXfY1PFLn0788IPBJl/eAYfDePISGHuO3S627DnYcDj3TJqEZF/uZskehjTLjQdw+SXHgJmB7XbihhuJQC1thyUMzvBukGZgOGxg2IBDC/8boJZ/QC33HzYctmz7L2F/hnfzb7xaJIC2MLaBbAF6n7HtgIQBD+82sC3yOLzPJvHG4GBvH8gviQ0He88kS844w7vNsscgzcAAhxb5/hzDBz++3QaG2OGDD37usOPn7+HdfONHhY2BPA6HgcABIE4AsxjhqoBWGBzArYUBixaQA/DYMgpGwSgYBSMKAACgk17f8Oop0wAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-7773-4155","institution":"Peter MacCallum Cancer Centre","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ian","middleName":"G.","lastName":"Campbell","suffix":""}],"badges":[],"createdAt":"2021-03-04 03:14:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-294874/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-294874/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41523-021-00373-y","type":"published","date":"2022-01-17T12:15:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":6995416,"identity":"6844b50f-ea16-44ec-8149-1ab4378f3f95","added_by":"auto","created_at":"2021-03-15 22:10:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":229545,"visible":true,"origin":"","legend":"The location and frequency of RAD51C missense variants detected in cases (n = 5,734) and controls (n = 14,382) generated using cBioPortal. Sliding window plot shows the case-control odds ratio in position-based analysis. Key variants are marked with protein change and variants of interest are pointed with arrows. Holliday junction domain includes protein position 1 to 126, domain interacting with RAD51B, RAD51D and XRCC3 include protein position 79 to 136. Note the y-axis scale is different for cases and controls, accounting for the control cohort being more than twice as larger than the case cohort. ","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-294874/v1/35bb802948fdd81f43150bbd.png"},{"id":17376531,"identity":"f3ab7f5f-1dd8-4161-8457-cf5ebf35865d","added_by":"auto","created_at":"2022-01-17 12:15:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6072571,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-294874/v1/ee51477e-0e79-4918-83fd-842f8cab76fe.pdf"},{"id":6995414,"identity":"c48b551d-04a6-4a64-ac7f-4ea64cc9e777","added_by":"auto","created_at":"2021-03-15 22:10:56","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":908932,"visible":true,"origin":"","legend":"Additional file 1.docx\nContains supplementary tables and figures.\n","description":"","filename":"Limet.al.Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-294874/v1/bfa8f46e8b6baa71b8d46de8.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eIntegration of Tumour Sequencing and Case-Control Data to Assess Pathogenicity of \u003cem\u003eRAD51C \u003c/em\u003eMissense Variants in Familial Breast Cancer\u003c/p\u003e","fulltext":[{"header":"Background","content":" \u003cp\u003eProtein truncating variants in \u003cem\u003eRAD51C\u003c/em\u003e predispose to high grade serous ovarian cancer and triple negative breast cancer (TNBC), and when these cancers occur in carriers of truncating variants they exhibit bi-allelic inactivation (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Few studies have investigated whether missense (MS) variants of \u003cem\u003eRAD51C\u003c/em\u003e exert similar penetrance as protein truncating variants. Breast cancer case-control studies to date have identified potentially predisposing \u003cem\u003eRAD51C\u003c/em\u003e MS variants, such as p.Gly264Ser (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), p.Gln143Arg (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and pArg258His (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), while target protein and cellular assays have suggested functional impact and pathogenicity of variants including p.Cys135Tyr and p.Gly264Ser (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). However, the sample sizes in these studies were small, with conflicting evidence for many variants. We analysed data from the BEACCON study of 5,734 familial breast cancer cases and 14,382 population controls for rare \u003cem\u003eRAD51C\u003c/em\u003e MS variants (MAF\u0026thinsp;\u0026lt;\u0026thinsp;0.005). To further investigate the potential pathogenicity of candidate variants, we exploited the fact that \u003cem\u003eRAD51C\u003c/em\u003e appears to conform to the Knudsen\u0026rsquo;s \u0026ldquo;two-hit\u0026rdquo; hypothesis, and performed tumour sequencing from variant carriers to assess for bi-allelic inactivation and associated homologous recombination deficiency (HRD). We have previously demonstrated the utility of this reproach for \u003cem\u003eRAD51C\u003c/em\u003e loss of function (LoF) variants which revealed the presence of bi-allelic inactivation in the form of loss of heterozygosity (LOH) in TNBCs that was also associated with high HRD scores and mutational signature 3 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In this study, case-control analysis data was combined with tumour sequencing, \u003cem\u003ein silico\u003c/em\u003e prediction tools and pedigree segregation to assess the pathogenicity of \u003cem\u003eRAD51C\u003c/em\u003e missense variants.\u003c/p\u003e "},{"header":"Methods","content":"\u003ch2\u003eCohorts\u003c/h2\u003e\n\u003cp\u003eThe case cohort comprised of female index patients diagnosed with breast cancer from 5,734 hereditary breast and ovarian cancer (HBOC) families identified from the Variants in Practice (ViP) Study (combined Victorian and Tasmanian Familial Cancer Centres, Australia) and Pathology North (NSW Health Pathology, Newcastle, Australia). The cases were determined eligible for clinical genetic testing for hereditary breast cancer predisposition genes based on personal and/or family history by a specialist Familial Cancer Clinic. All case subjects have been tested negative for \u003cem\u003eBRCA1\u003c/em\u003e/\u003cem\u003eBRCA2\u003c/em\u003e pathogenic variants prior to recruitment. The controls were 14,382 cancer-free female subjects from the Lifepool Study (\u003ca href=\"http://www.lifepool.org/)\"\u003ehttp://www.lifepool.org/)\u003c/a\u003e in Victoria, Australia (BreastScreen Victoria). The average age of first diagnosis in cases was 45.8 years (range, 17-85), while the average age of controls in this study was 64.4 years (range, 40-97), indicating a design that enrich for lifetime cancer-free controls. Family history of cancer was recorded for all cohort subjects by questionnaire or in-person interview. Cases ascertained through ViP study were provided with detailed pedigrees with breast and ovarian cancer family history verified against state cancer registries, and tumour pathology reports.\u003c/p\u003e\n\u003ch2\u003eTargeted sequencing of germline DNA of cases and controls\u003c/h2\u003e\n\u003cp\u003eThe coding region and exon-intron boundaries (at least 10 bp of each intron) of \u003cem\u003eRAD51C\u003c/em\u003e from germline DNA were amplified using a custom designed HaloPlex Targeted Enrichment Assay panel (Agilent Technologies, Santa Clara, CA) and the libraries were sequenced on a HiSeq2500 Genome Analyzer (Illumina, San Diego, CA) as previously described (11-14). Loss-of-function (LoF) variants were defined as stop-gained, frame-shift or essential splice-site variants. Missense (MS) variants were defined as non-synonymous single nucleotide variants.\u003c/p\u003e\n\u003ch2\u003eSequencing of tumour DNA of RAD51C MS carriers\u003c/h2\u003e\n\u003cp\u003eTumour DNA was collected from cancer cells in formalin fixed, paraffin embedded (FFPE) slides by needle microdissection under the microscope. For targeted sequencing, all exons of \u003cem\u003eRAD51C\u003c/em\u003e and 487 additional genes (including 27 breast cancer driver genes, total targeted region of 1.337 Mb), and for whole-exome sequencing, all exons were amplified using an Agilent SureSelect XT Custom Panel (15)\u003cem\u003e. For Sanger sequencing, the relevant RAD51C region was amplified using exon-specific primers through polymerase chain reaction and sequenced using ThermoFisher Scientific BigDye Terminator v3.1 kit. \u003c/em\u003eThe libraries were sequenced on an Illumina Next Seq 500 (75 bp paired end reads). Promoter hyper-methylation was determined by Sanger sequencing of bisulfite-converted tumour DNA using Qiagen EpiTect Bisulfite Kit.\u003c/p\u003e\n\u003ch2\u003eIdentification of MS variants\u003c/h2\u003e\n\u003cp\u003eSequencing results were aligned to the g1 k x27 h19 reference genome using the Burrows-Wheeler Alignment tool (16), SNP variant calling was carried out using GATK UnifiedGenotyper v2.4 (Broad Institute, Cambridge, MA), Platypus (17) and Varscan (18), and variants were annotated using the Ensembl Variant Effect Predictor (19) as previously described (1). Rare MS variants were identified in canonical transcript by at least two variant callers, with sequencing quality \u0026ge;30, allele frequency \u0026ge;20% and MAF present at \u0026le;0.005 for MS variants in non-Finnish European in gnomAD (Version 2.1, released 17 October 2018) (20). Manual examination of BAM files and Sanger sequencing was carried out for ambiguous variants to remove sequencing artefacts\u003cstrong\u003e.\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eHomologous recombination deficiency (HRD) score calculation\u003c/h2\u003e\n\u003cp\u003eA copy number plot was generated for each tumour using copywriteR package in R studio (21). From the plot, an HRD score was calculated for each tumour sample as a sum of the occurrence of telomeric allelic imbalances, large-scale state transitions and homologous recombination deficiency\u0026ndash;loss of heterozygosity (HRD\u0026ndash;LOH) as described previously (22).\u003c/p\u003e\n\u003ch2\u003eSliding window analysis\u003c/h2\u003e\n\u003cp\u003eMS variants were separated into each unique window of N amino acids, then Fisher\u0026rsquo;s Exact Test was performed using the counts of variants in the case and control samples. P-values were then adjusted based on the null distribution estimated by randomising the sample labels of each variant and recalculating the optimal p-value for each iteration.\u003c/p\u003e\n\u003ch2\u003eMutational Signature analysis\u003c/h2\u003e\n\u003cp\u003eRare somatic mutations were identified after filtering against germline variants, removing intron variants, sequencing read depth \u0026ge;20, allele frequency \u0026ge;10% and MAF present at \u0026le;0.0001 for in non-Finnish European in gnomAD. As the number of somatic mutations was low in individual targeted panel sequenced samples, mutations were pooled into groups according to variant type and/or tumour pathology. Mutational signatures were generated using the DeconstructSig package in R (23).\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eOdds ratios and Fisher\u0026rsquo;s exact test (2-sided) were examined for the case-control analysis, with a two-tailed p-value of \u0026le;0.05 designated as statistically significant, and confidence intervals were calculated using conditional Maximum Likelihood Estimate. Benjamini-Hochberg adjustment was used for multiple test corrections (24). All calculations were carried out using R-in built function in R 3.3.2 (25).\u003c/p\u003e"},{"header":"Results","content":" \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLikely Pathogenic Variants were Enriched in the Case Cohort\u003c/h2\u003e \u003cp\u003eA total of 51 unique rare MS variants (MAF\u0026thinsp;\u0026lt;\u0026thinsp;0.005) were detected in 65 cases (1.13%) and 134 controls (0.91%) (OR 1.22, 95% CI 0.89\u0026ndash;1.65, p\u0026thinsp;=\u0026thinsp;0.21) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Several parameters were used to enrich for potentially pathogenic variants including population frequency, location in known function domains, \u003cem\u003ein silico\u003c/em\u003e pathogenicity prediction and tumour phenotype. Consistent with the hypothesis that rare variants are more likely to be deleterious (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), a reduction of the population frequency threshold resulted in increasing odds ratios that reached statistical significance at MAF\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 (OR 1.87, 95%CI 1.14\u0026ndash;3.03, p\u0026thinsp;=\u0026thinsp;0.01). Similarly, higher CADD and REVEL score thresholds that should enrich for pathogenic variants were associated with higher odds ratios, especially for a REVEL score of \u0026gt;\u0026thinsp;0.5 (OR 3.95, 95%CI 1.40\u0026ndash;12.01, p\u0026thinsp;=\u0026thinsp;0.006). Two overlapping functional domains are present in the N-terminal third of RAD51C protein (Holliday junction activity: amino acids 1-126; Interaction with RAD51B, RAD51D and XRCC3: amino acids 79\u0026ndash;136) and a significant enrichment of MS variants in cases was observed in the interaction domain (OR 10.04, 95%CI 0.99\u0026ndash;494.1, p\u0026thinsp;=\u0026thinsp;0.03), although the number of variants was low (n\u0026thinsp;=\u0026thinsp;5), resulting in a wide confidence interval.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequencies of \u003cem\u003eRAD51C\u003c/em\u003e missense variants in case and control cohorts according to different filtering criteria to enrich for likely pathogenic variants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCarrier Frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCase (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eControl (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eCase\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eRarity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMAF\u0026thinsp;\u0026lt;\u0026thinsp;0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (1.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134 (0.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003e5734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"14\" rowspan=\"15\"\u003e \u003cp\u003e14382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.22 (0.89\u0026ndash;1.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMAF\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (0.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (0.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003e0.05\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.57 (1.00-2.44)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMAF\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (0.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (0.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003e0.01\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.87 (1.14\u0026ndash;3.03)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eIn-silico\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCADD\u0026thinsp;\u0026gt;\u0026thinsp;20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (1.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125 (0.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.19 (0.85\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCADD\u0026thinsp;\u0026gt;\u0026thinsp;25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (0.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (0.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003e0.05\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.94 (0.97\u0026ndash;3.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eREVEL\u0026thinsp;\u0026gt;\u0026thinsp;0.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (0.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (0.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003e0.02\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2.25 (1.10\u0026ndash;4.57)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eREVEL\u0026thinsp;\u0026gt;\u0026thinsp;0.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (0.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (0.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003e0.006\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3.95 (1.40-12.01)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFunctional domain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eInteraction domain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.070%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003e0.03\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e10.04 (0.99\u0026ndash;493.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHolliday domain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (0.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2.15 (0.60\u0026ndash;7.48)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eHormone receptor subtype\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eER-positive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (1.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e137 (0.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.09 (0.67\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eER-negative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (1.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003e0.04\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.67 (0.99\u0026ndash;2.70)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHER2-positive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (1.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.27 (0.50\u0026ndash;2.7)1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHER2-negative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (1.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.26 (0.81\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (1.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.58 (0.81\u0026ndash;2.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNon-TN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (1.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.14 (0.70\u0026ndash;1.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eMAF: Minor Allele Frequency; CADD: Combined Annotation-Dependent Depletion score (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e); REVEL: rare exome variant ensemble learner score (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e); ER: estrogen receptor; HER2: human epidermal growth factor receptor 2; TN: triple-negative.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSubgroup analysis based on hormone receptor status was carried out on case subjects where detailed pathology data was available from the Variant in Practice (ViP) study (n\u0026thinsp;=\u0026thinsp;3,645). Consistent with previous findings for \u003cem\u003eRAD51C\u003c/em\u003e LoF carriers, rare MS variants were significantly enriched in the ER-negative breast cancer subgroup (OR 1.67, 95%CI 0.99\u0026ndash;2.70, p\u0026thinsp;=\u0026thinsp;0.04), with a similar but non-significant trend in TNBC cases (OR 1.58, 95%CI 0.81\u0026ndash;2.80, p\u0026thinsp;=\u0026thinsp;0.11).\u003c/p\u003e \u003cp\u003eThe distribution and frequency of rare MS variants across RAD51C in the 5,734 cases and 14,382 controls is summarised in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. While rare MS variants were distributed across the entire gene, cases showed higher frequencies in the first half of the gene. The position-based odds ratio analysis showed a higher case-control odds ratio for variants located between amino acid positions 82 and 136, coinciding with the interaction domain.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \n\u003ch2\u003eVariants Of Interest Detected In Cases And Controls\u003c/h2\u003e\n \u003cp\u003eDetails of the 51 rare \u003cem\u003eRAD51C\u003c/em\u003e MS variants identified in this study including case-control numbers, \u003cem\u003ein silico\u003c/em\u003e pathogenicity prediction and literature evidence are summarised in Supplementary Table\u0026nbsp;1. Also included is the reference variant p.Ala126Thr (MAF\u0026thinsp;=\u0026thinsp;0.0054), a generally-accepted benign variant. All of the variants were very rare (MAF\u0026thinsp;\u0026le;\u0026thinsp;0.0001), with the exception of p.Gly264Ser (MAF\u0026thinsp;=\u0026thinsp;0.0034). Despite the large sample size, most variants were detected in less than three subjects, therefore the frequencies alone were not adequately powered to confirm or refute pathogenicity. The data did, however, suggest that two previously-identified variants, p.Ala126Thr and p.Gly264Ser, do not represent high penetrance alleles. p.Ala126Thr was detected in 68 (1.19%) cases and 133 (0.9%) controls (OR 1.29, p\u0026thinsp;=\u0026thinsp;0.10), similar to the allele frequency reported in gnomAD database. Similarly, p.Gly264Ser was detected with equal frequencies in cases (n\u0026thinsp;=\u0026thinsp;30, 0.52%) and controls (n\u0026thinsp;=\u0026thinsp;80, 0.54%) (OR 0.96, p\u0026thinsp;=\u0026thinsp;0.92).\u003c/p\u003e\n\u003ch2\u003eSequencing Of Tumours From Ms Variant Carriers\u003c/h2\u003e\n \u003cp\u003eTwenty invasive breast tumours and one high grade serous ovarian tumour from 21 cases were sequenced using a targeted gene panel that included all exons and intron boundaries of \u003cem\u003eRAD51C\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These tumours were from cases that carried one of eight heterozygous candidate variants (p.Gly264Ser, p.Gln143Arg, p.Ile144Thr, p.Arg212His, p.Asp242Asn, p.Ile244Val, p.Arg258His and p.Leu262Val) as well as one homozygous p.Gly264Ser carrier. Of the 20 germline heterozygous carrier tumours, four were found to harbour a second hit through loss of the wild-type allele (loss of heterozygosity, LOH). However, another five had lost the mutant allele while eleven others remained heterozygous. On further investigation, none of the heterozygous cases showed evidence of promoter hyper-methylation or somatic point mutations in \u003cem\u003eRAD51C\u003c/em\u003e. Of the eight tumours from heterozygous carriers of the p.Gly264Ser allele, only four showed copy number loss with three of these involving loss of the variant allele. Importantly, both the p.Gly264Ser homozygous carrier and the case with loss of the wild-type allele had HRD scores below those indicative of loss of homologous recombination function (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMolecular analysis of 21 tumours from \u003cem\u003eRAD51C\u003c/em\u003e missense variant carriers.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHormone Receptor/ HER2 Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAllele status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHRD Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePromoter Hyper-Methylation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTp53 Somatic Mutation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003ep.Gly264Ser\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGermline homozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWild-type loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVariant loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVariant loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER-/ HER2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVariant loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ep.Glu143Arg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVariant loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER-/HER2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep.Ile144Thr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWild-type loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep.Arg212His\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER-/HER2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWild-type loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep.Asp242Asn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVariant loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep.Ile244Val\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVariant loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep.Arg258His\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOvCa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWild-type loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMutated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep.Leu262Val\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER+/HER2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAll samples were sequenced using targeted panel, with the exception of samples 11 and 20 with whole-exome and samples 4 and 13 with exon-specific Sanger sequencing. HRD: homologous recombination deficiency.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003ecarriers are 1st degree related\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLoss of the wild-type allele was identified in two triple-negative tumours carrying p.Ile144Thr and p.Arg212His variants respectively, with both showing high HRD scores, while ER-positive tumours carrying these variants remained heterozygous. An ovarian tumour carrying p.Arg258His also showed LOH and had a high HRD score of 70. Among four tumours sequenced that carried the p.Glu143Arg variant, the one triple-negative case was found to have lost the variant allele, while the one ER-negative and two ER-positive tumours remained heterozygous. All three tumours carrying a germline p.Leu262Val, p.Ile244Val or p.Asp242Asn variant were also showed to remained heterozygous.\u003c/p\u003e \u003cp\u003ePrevious studies have shown that breast tumours from individuals carrying a LoF mutation in \u003cem\u003eRAD51C\u003c/em\u003e accompanied with loss of the wild-type allele were associated with single base substitution mutational signature 3 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), and this was assessed for tumours from carriers of candidate MS variants. To achieve the minimum recommended number of somatic mutations (n\u0026ge;40) for mutational signature estimation, tumours were grouped into those carrying variants of unknown significance (VUS) and those carrying the benign variant p.Gly264Ser (Supplementary Fig.\u0026nbsp;1). The contribution of signature 3 in tumours carrying a VUS was similar to the tumours carrying the p.Gly264Ser variant. When stratified based on tumour pathology, triple-negative tumours had a higher proportion of signature 3 and higher HRD scores but these were similar in both VUS and benign variant carriers. Whole exome sequencing of a high grade serous ovarian cancer carrying the p.Arg258His variant (case 20) was shown to have lost the wild-type and accompanied by a large proportion of signature 3 and other smaller signatures related to nucleotide excision repair.\u003c/p\u003e \n\u003ch2\u003ePedigree Segregation Of Ms Variant Carriers\u003c/h2\u003e\n \u003cp\u003eNine additional family members from seven families, (representing three different variants), were available to examine the segregation of the germline variant detected in the index case (Supplementary Fig.\u0026nbsp;2). Four of the families carried the p.Gly264Ser variant which was found to be present in two affected first degree relatives (FDR) (ER\u0026thinsp;+\u0026thinsp;BC 43, BC 50), but absent in two affected second degree relatives (ER\u0026thinsp;+\u0026thinsp;BC 38, lobular ER\u0026thinsp;+\u0026thinsp;BC 56) of the respective index cases. The variant p.Gln143Arg was present in a first degree relative diagnosed with TNBC (age 55), ER-positive breast cancer (age 72) and high grade serous ovarian cancer (age 74), while none of the three unaffected FDR, tested from p.Gln143Arg families carried the variant. Finally, the daughter of an index case carrying the p.Gln137Arg variant remained unaffected but is currently only 35 years old.\u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eGermline protein truncating variants in \u003cem\u003eRAD51C\u003c/em\u003e are known to be associated with predisposition to developing high grade serous ovarian cancer and TNBC (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) but whether there are missense variants of equivalent penetrance is unclear. Data from the BEACCON study has demonstrated that collectively, rare \u003cem\u003eRAD51C\u003c/em\u003e MS variants are enriched in familial breast cancer, and consistent with protein truncating variants, are more strongly associated with ER-negative and TNBC. Based on an excess in cases and \u003cem\u003ein silico\u003c/em\u003e predictions, this study has identified a number of potentially pathogenic variants, however definitive designation is challenging due to the low frequency among the population. Nevertheless, our data does exclude some variants as being moderate- to high-penetrance variants. For example, p.Gly264Ser has previously been reported in several small studies to be associated with ovarian and/or breast cancer (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), which was consistent with functional assays showing this variant caused partial reduction of RAD51C cellular function including cell survival, mitomycin C sensitivity and homologous recombination activity (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). However, in the more highly powered BEACCON study, the p.Gly264Ser allele was detected at similar frequencies in cases and controls and was not associated with loss of the wild-type allele in breast cancers from carriers. In addition, the tumour from the homozygous p.Gly264Ser carrier did not show a high HRD score, indicating that its HR pathway remained intact. The data strongly suggests that despite \u003cem\u003ein vitro\u003c/em\u003e functional assays showing p.Gly264Ser reduces the activity of RAD51C, it is not associated with increased risk of breast cancer. Taken together, our data conflict with the suggestion that this variant may be pathogenic and highlight the need for caution when extrapolating from the results of functional assays to clinical classification of variants.\u003c/p\u003e \u003cp\u003eA number of rare variants previously have been reported as likely pathogenic, including p.Gln143Arg (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), p.Arg258His (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), p.Cys135Tyr (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), p.Ile144Thr (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) and p.Val169Ala (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In this study, p.Gln143Arg was detected in 0.7% of cases (n\u0026thinsp;=\u0026thinsp;4), including one TNBC and two with family history of ovarian cancer, and 0.2% of controls (n\u0026thinsp;=\u0026thinsp;3), consistent with the observed \u003cem\u003eRAD51C\u003c/em\u003e phenotypes. Pedigree segregation of family 22 also supported that the variant p.Gln143Arg segregated with two subjects affected with ductal breast cancer. Previously described as unlikely to be pathogenic (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), p.Arg212His was detected in this study in two cases (0.03%) and no controls, while also predicted as deleterious by all five \u003cem\u003ein silico\u003c/em\u003e tools. p.Val169Ala on the other hand was identified in 12 control subjects, three-fold higher than the case frequency, making it unlikely to be a pathogenic variant. Among 12 tumours sequenced across seven germline variants, bi-allelic inactivation and high HRD scores were observed in ER-negative breast cancers and an ovarian cancer of p.Ile144Thr, p.Arg212His and p.Arg258His carriers but not in tumours of p.Glu143Arg, p.Asp242Asn, p.Ile244Val and p.Leu262Val carriers. Promoter hyper-methylation, which has been observed in \u003cem\u003eBRCA1/2\u003c/em\u003e tumours, appears unlikely to be an important mechanism for \u003cem\u003eRAD51C\u003c/em\u003e (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), with no instances observed in the tumours examined. Although the number of tumours and family members sequenced for each variant was still low, when combined with the case-control results, the data provides support for further investigation of those variants identified in this study as candidates by expansion or pooling of databases.\u003c/p\u003e \u003cp\u003eWhile this study generated evidence against the pathogenicity of p.Gly264Ser, there are several limitations to interpreting results for other variants. Despite a large sample size of ~\u0026thinsp;20,000 subjects, the power of the study was limited in its capacity to identify and assess individual rare variants. For the variants examined here, most of which have a MAF of ~\u0026thinsp;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e, to securely identifying an odds ratio of \u0026gt;\u0026thinsp;2 would require a sample size of several million (~\u0026thinsp;4.7\u0026nbsp;million total cases and controls by standard power calculation). Such numbers seem unachievable even with extensive international collaboration. The statistical power is further eroded by the fact that recent findings indicate that only the rarer TN subset of breast cancer is attributable to \u003cem\u003eRAD51C\u003c/em\u003e (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Given these limitations of case control analyses, insights from tumour sequencing, that includes identifying a \u0026ldquo;second hit\u0026rdquo; and characteristic genome alterations may offer the best avenue for validating or refuting a role for RAD51C MS variants in breast cancer predisposition.\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eEvidence from this study supports an association of \u003cem\u003eRAD51C\u003c/em\u003e MS variants with familial breast cancer but due to their rarity this study was not sufficiently powered on its own to identify individual pathogenic variants. Tumour sequencing provided an additional tool to interrogate the \u003cem\u003ein vivo\u003c/em\u003e consequences of candidate variants and was able to robustly classify some variants a benign. Case-control and tumour sequencing show that the p.Gly264Ser variant is unlikely to be a moderate- to high- penetrance variant, despite \u003cem\u003ein vitro\u003c/em\u003e assays showing partial functional impairment. These findings raise questions about the validity of functional assays as accurate predictors of variant pathogenicity. Overall, integrating case-control data with tumour sequencing provides a powerful strategy to clarify the role of \u003cem\u003eRAD51C\u003c/em\u003e MS variants in breast cancer predisposition.\u003c/p\u003e "},{"header":"Abbreviations","content":" \u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTriple negative breast cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMissense\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMAF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMinor allele frequency\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHRD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHomologous recombination deficiency\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLoF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLoss-of-function\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLOH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLoss of heterozygosity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHBOC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHereditary breast and ovarian cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFFPE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFormalin fixed, paraffin embedded\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eViP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVariant in Practice Study\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVariant of unknown significance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFDR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFirst degree relative(s)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Human Research Ethics Committees at each participating ViP study recruitment centre and the Peter MacCallum Cancer Centre (Approval # 09/29). All participants provided informed consent for genetic analysis of their germline DNA (cases and controls) and tumour DNA (cases only).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll sequencing data are deposited to European Genome-phenome Archive which are available upon request to corresponding author. Standard R codes were used. Code requests should be addressed to Prof. Ian Campbell.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Breast Cancer Foundation (IF-15-004, I.G.C. and P.A.J.), Cancer Australia/National Breast Cancer Foundation (PdCCRS_1107870, I.G.C. and P.A.J.), the Victorian Cancer Agency (Tumor Stream Grant, P.A.J.) and the National Health and Medical Research Council of Australia (GNT1023698, P.A.J.; GNT1041975, I.G.C.). EKS is supported by NHMRC GNT1147498 and NBCF IIRS-20-025. NL is supported by Cancer Council Victoria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eB.W.X.L. contributed to tumour processing and sequencing, data analysis, and manuscript writing; N.L. contributed to germline data collection and data analysis; S.M.R. contributed to generating sequencing libraries and sample management; E.R.T. contributed to study design and data analysis; M.Z. contributed to bioinformatics analysis and plotting; S.M. and L.D., contributed to collection of study materials or patients; R.J.S. contributed to provision of patients\u0026rsquo; material and data interpretation; E.K.S. contributed to data interpretation and manuscript revision; P.A.J. contributed to study design, clinical interpretation, and manuscript revision; I.G.C. contributed to study design, data analysis and manuscript revision. All authors contributed to drafting, revising and final approval of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the participants of the ViP and Lifepool studies for donating their DNA samples and clinical information. We also thank Norah Grewal, the ViP study site principal investigators Geoffrey Lindeman, Marion Harris, Tom John, Ingrid Winship and Yoland Antill, and the staff at the Peter MacCallum Cancer Centre, Royal Melbourne Hospital, Monash Health, Cabrini Health and Barwon Health Familial Cancer Centres and the Austin and Tasmanian Clinical Genetics Services, who enrolled participants and provided clinical data.\u003c/p\u003e\n\u003cp\u003eWe thank the following staff from Peter MacCallum Cancer Centre: Tim Semple, Gisela Mir Arnau from Molecular Genomics core facility for sequencing the tumour DNA, Kaushalya Amarasinghe, Niko Thio, and Richard Lupat from Bioinformatics core facility for helping with the bioinformatic analysis, Christina Fennell, Mira Liu and Samantha Cauberg from Tissue Bank for preparing sections of tumor blocks and Heather Thorne, Lynda Williams and Genna Glavich from kConFab for assisting with obtaining the tumor blocks.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi N, McInerny S, Zethoven M, Cheasley D, Lim BWX, Rowley SM, et al. Combined tumor sequencing and case/control analyses of RAD51C in breast cancer. Journal of the National Cancer Institute. 2019.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCouch FJ, Hart SN, Sharma P, Toland AE, Wang X, Miron P, et al. Inherited mutations in 17 breast cancer susceptibility genes among a large triple-negative breast cancer cohort unselected for family history of breast cancer. J Clin Oncol. 2015;33(4):304\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShimelis H, LaDuca H, Hu C, Hart SN, Na J, Thomas A, et al. Triple-Negative Breast Cancer Risk Genes Identified by Multigene Hereditary Cancer Panel Testing. Journal of the National Cancer Institute. 2018.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLoveday C, Turnbull C, Ruark E, Xicola RM, Ramsay E, Hughes D, et al. Germline RAD51C mutations confer susceptibility to ovarian cancer. Nat Genet. 2012;44(5):475\u0026ndash;6. author reply 6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeindl A, Hellebrand H, Wiek C, Erven V, Wappenschmidt B, Niederacher D, et al. Germline mutations in breast and ovarian cancer pedigrees establish RAD51C as a human cancer susceptibility gene. Nat Genet. 2010;42(5):410\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThompson ER, Boyle SE, Johnson J, Ryland GL, Sawyer S, Choong DY, et al. Analysis of RAD51C germline mutations in high-risk breast and ovarian cancer families and ovarian cancer patients. Hum Mutat. 2012;33(1):95\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJonson L, Ahlborn LB, Steffensen AY, Djursby M, Ejlertsen B, Timshel S, et al. Identification of six pathogenic RAD51C mutations via mutational screening of 1228 Danish individuals with increased risk of hereditary breast and/or ovarian cancer. 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Am J Hum Genet. 2016;99(4):877\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"familial breast cancer, breast cancer predisposition, RAD51C, tumour sequencing","lastPublishedDoi":"10.21203/rs.3.rs-294874/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-294874/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e While protein truncating variants in \u003cem\u003eRAD51C\u003c/em\u003e have been shown to predispose to triple negative breast cancer (TNBC) and ovarian cancer, little is known about the pathogenicity of missense (MS) variants. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThe frequency of rare \u003cem\u003eRAD51C\u003c/em\u003e MS variants were assessed in the BEACCON study of 5,734 familial breast cancer cases and 14,382 population controls, and integrated with tumour sequencing data from 21 cases carrying a candidate variant to assess bi-allelic inactivation. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Collectively, a significant enrichment of rare missense variants was detected in cases (MAF \u0026lt; 0.001, OR 1.57, 95%CI 1.00 - 2.44, p = 0.05), particularly for variants with a REVEL score \u0026gt; 0.5 (OR 3.95, 95%CI 1.40 - 12.01, p = 0.006).\u003cstrong\u003e \u003c/strong\u003eDespite the large sample size, the majority of variants detected were very rare, precluding definitive conclusions about pathogenicity based solely on the case-control data. Sequencing of 21 tumours from carriers of one of eight candidate MS variants, identified four cases with bi-allelic inactivation through loss of the wild-type allele, while six lost the variant allele and ten remained heterozygous. Loss of the wild-type alleles corresponded strongly with ER- and triple-negative breast tumours and a high homologous recombination deficiency score. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Using this approach, the p.Gly264Ser variant, which was previously suspected to be pathogenic based on small case-control analyses and loss of activity in \u003cem\u003ein vitro\u003c/em\u003e functional assays, was shown to be benign with similar prevalence in cases and controls, and eight out of nine tumours showing loss of the variant allele or retention of heterozygosity. Conversely, the combined case-control and tumour sequencing data identified p.Ile144Thr, p.Arg212His, p.Gln143Arg and p.Gly114Arg as variants warranting further investigation.\t\u003c/p\u003e","manuscriptTitle":"Integration of Tumour Sequencing and Case-Control Data to Assess Pathogenicity of RAD51C Missense Variants in Familial Breast Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-03-15 22:10:52","doi":"10.21203/rs.3.rs-294874/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7d897840-0736-4c22-9266-f15641eca2bc","owner":[],"postedDate":"March 15th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":2967467,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2022-01-17T12:15:44+00:00","versionOfRecord":{"articleIdentity":"rs-294874","link":"https://doi.org/10.1038/s41523-021-00373-y","journal":{"identity":"npj-breast-cancer","isVorOnly":false,"title":"npj Breast Cancer"},"publishedOn":"2022-01-17 12:15:44","publishedOnDateReadable":"January 17th, 2022"},"versionCreatedAt":"2021-03-15 22:10:52","video":"","vorDoi":"10.1038/s41523-021-00373-y","vorDoiUrl":"https://doi.org/10.1038/s41523-021-00373-y","workflowStages":[]},"version":"v1","identity":"rs-294874","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-294874","identity":"rs-294874","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}