Comprehensive Genomic Profiling through Panel-based and Whole-exome Sequencing in a Population-based Chinese Han Male Breast Cancer Cohort

Comprehensive Genomic Profiling through Panel-based and Whole-exome Sequencing in a Population-based Chinese Han Male Breast Cancer Cohort | 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comprehensive Genomic Profiling through Panel-based and Whole-exome Sequencing in a Population-based Chinese Han Male Breast Cancer Cohort Guan-Tian Lang, San-Jian Yu, Xiao-Ling Weng, Yun Liu, Xin Hu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7283126/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose The molecular characterization of male breast cancer (MaBC) has long been understudied, primarily due to its rare occurrence. Clinical management of MaBC remains profoundly challenging, with current therapeutic strategies largely extrapolated from female breast cancer protocols. Methods Through panel-based sequencing targeting BRCA1, BRCA2 and PALB2 variants, we delineated the genomic landscape of 96 MaBC cases. Subsequent whole exome sequencing (WES) of 84 BRCA1/2 and PALB2-mutation-negative MaBC patients, compared against 4,480 healthy controls, revealed compelling findings. Results Pathogenic variants in BRCA1/2 and PALB2 were identified in 14.6% (14/96) of MaBC cases, with BRCA2 mutations predominating at 12.5% (n = 12). Notably, one patient harbored the BRCA1 c.4015G > T stop_gained mutation, while another exhibited the PALB2 c.481_482dupGA alteration. Our analysis further uncovered 170 pathogenic/likely-pathogenic mutations and 388 rare variants of uncertain significance (VUS), with RAD50, DMD, ARSA, and ABCC6 demonstrating notable genetic pleiotropy. Conclusion As the inaugural germline genomic investigation of MaBC in a Han Chinese population, this work reveals clinically actionable alterations with diagnostic and therapeutic implications. These discoveries not only advance our understanding of MaBC's molecular architecture but also underscore the critical need for dedicated research into this malignancy. male breast cancer panel-based sequencing whole-exome sequencing BRCA1/2 PALB2 Figures Figure 1 Figure 2 Figure 3 Introduction Male breast cancer (MaBC) represents a rare malignancy, constituting approximately 1% of all breast carcinomas and less than 1% of total cancer diagnoses in males [ 1 , 2 ]. Epidemiological data from 2016 estimated 2400 new cases and 440 breast cancer-associated mortalities among MaBC patients in the United States [ 3 ]. The limited availability of comprehensive clinical data - including patient demographics, tumor biology, therapeutic interventions, and prognostic outcomes - stems from the disease's low incidence. Current clinical management predominantly relies on therapeutic paradigms extrapolated from female breast cancer studies, with insufficient characterization of MaBC-specific clinicopathological features. Furthermore, molecular profiling of MaBC remains inadequately explored. In this investigation, we performed panel-based sequencing analysis of BRCA1, BRCA2, and PALB2 genes in 96 consecutive MaBC patients of Chinese Han ethnicity. Our primary objectives were to: (1) determine the prevalence and spectrum of germline mutations in BRCA1/2 and PALB2 among Chinese male breast cancer patients, and (2) conduct whole-exome sequencing (WES) to identify potential driver mutations underlying clinical manifestations in MaBC. Material and methods Study population A prospective cohort comprising 96 MaBC patients was consecutively enrolled at Fudan University Shanghai Cancer Center (Shanghai, China) between January 2014 and November 2018. The study cohort comprised 4,480 healthy control subjects obtained from a publicly available genetic database maintained by Zhejiang University School of Medicine[ 1 – 3 ]. Each participant signed a written informed consent form and ethical consent. Peripheral blood specimens and comprehensive phenotypic data were systematically collected from all study participants. Genomic DNA extraction was performed using the VAZYME Blood Genomic DNA Kit (Vazyme Medical Technology, Nanjing, China) following manufacturer's protocols. This study received ethical approval from the Institutional Review Board of Fudan University Shanghai Cancer Center, with written informed consent obtained from all participants prior to sample collection and data acquisition. Clinical significant germline mutations were determined in our cohort of 96 unselected MaBC patients according to Fig. 1. Targeted Sequencing The target-specific primers for the coding sequences of the BRCA1 (NM_007300), BRCA2(NM_000059) and PALB2 (NM_024675) were designed using Primer3 as described previously [ 1 ]. The universal sequences (CS1: ACACTGACGACATGGTTCTACA and CS2: TACGGTAGCAGAGACTTGGTCT) were appended at the 5’-end of each left and right primer, respectively. Pre-amplification for tagged amplicon deep sequencing (TAm-Seq): The coding sequences of the two genes were amplified using a 6 ml PCR reaction mixture containing 3 ml of KAPA 2G Robust HotStart ReadyMix (2X) (Kapa Biosystems, Boston, Massachusetts, United States), 1 ml of primer mix (500 nM) and 2 ml of DNA template (10 ng/ml). PCR conditions were as follows: initial denaturation for 2 min at 95°C; 45 cycles of denaturation for 30 s at 95°C, 30 s annealing at 56°C, and 1 min extension at 72°C; and a final extension step for 5 min at 72°C. Following PCR amplification, 1.5 ml of Shrimp Aalkaline Phosphatase (SAP, Affymetrixx, Santa Clara, California)/Exonuclease I (Exo I, BioLabss, Ipswich, Massachusetts) mix was added to 2.5 ml of PCR product and incubated for 60 min at 37°C, then for 20 min at 80°C. SAP/Exo I mix contained 600 ml of SAP (1 U/ml), 240 ml of SAP buffer, 150 ml of Exo I (20,000 U/ml), 200 ml of Exo I buffer and 3000 ml of ddH2O. Sequencing adaptor and barcode primer addition were performed as described previously. The barcode primers (Fluidigmm Corporation, South San Francisco, California) consisted of the PE1 and PE2 sequences for Illumina cluster generation, a 10-bp barcode, and the CS1 and CS2 adaptors, used in pairs: PE1-CS1 with PE2-BC-CS2, and PE1-CS2 with PE2-BC-CS1. For each sample, 1 µl of the 100-fold diluted PCR product was added to one of two PCR plates containing 9 µl of pre-sample mix containing 0.4 µl of 1 U/µl KAPA HiFi HotStart DNA Polymerase, 4 µl of 5× KAPA HiFi Buffer, 120 µM of each dNTP and 4 µl of ddH2O. In the first plate, 10 µl of one primer pair containing an individual 10-base barcode (BC) sequence and tags for reading in one direction (PE1-BC-CS1 + PE2-CS2) was added to each well. In the second plate, 10 µl of primers containing (PE1-BC-CS2 + PE2-CS1) was added to each well. The corresponding wells in both plates contained primers with the same barcode sequence. Plated reaction products were amplified for 12 cycles: 95°C for 10 min; 12 cycles of 95°C for 15 s; 60°C for 30 s; 72°C for 3 min; and 1 cycle of 72°C for 3 min. For the DNA library, PCR products were barcoded and analyzed using gel electrophoresis to ensure the expected insertion size was obtained. Products were then pooled together with an equal volume and purified using AMPure XP beads s (Beckman Coulter, Indianapolis, United States). The targeted DNA fragment was selected and extracted using E-Gel Precast Agarose Electrophoresis (ThermoFisher Scientific, Waltham, Massachusetts) and QIAquick Gel Extraction Kit. The library was quantified by Agilent BioAnalyzer and sequenced using the Illumina Xten platforms with paired-end reads of 150-bp per the manufacturer’s instructions. Custom sequencing primers targeted to CS1 and CS2 targeted the paired reads and 10-base indexing (barcode) read per the recommendations of Fluidigm. Whole-exome sequencing Briefly, 1 µg of DNA was sheared into short fragments (200–300 bp) using a Covaris S220 ultrasonicator. The DNA fragments were then end repaired to generate adenylated 3′ ends. Adaptors with barcode sequences were then ligated to both ends of the fragments, and E-Gels were used to select DNA fragments of the targeted size. Next, 10 PCR cycles were performed, and the resulting product was purified. Whole exome capture was performed using a TruSeq Exome Enrichment kit (Illumina) according to the manufacturer’s protocol with slight modifications. After the Illumina sequencing libraries were amplified with 10 PCR cycles, capture probes were added, and the reaction mixtures were incubated at 65°C for 24 h. The hybridized mixtures were then amplified with an additional 10 PCR cycles. Captured DNA libraries were sequenced with the Illumina HiSeq 2500 Genome Analyzer, yielding 200 (2 × 100) base pairs from the final library fragments. NGS data processing and variant calling Sequencing reads were aligned to the hg19 reference genome using Burrows-Wheeler Aligner (BWA) [ 4 ], and the Genome Analysis Toolkit (GATK) [ 5 ] was used for base quality score recalibration, indel realignment, and variant calling. We used GATK to filter the variants, required (i) QD < 2.0; (ii) MQ < 40.0; (iii) MQRankSum<-12.5; and (iv) ReadPosRankSum<-8.0. Variant functions were predicted using SnpEff ( http://snpeff.sourceforge.net ), PolyPhen-2 ( http://genetics.bwh.harvard.edu/pph2/ ), PROVEAN ( http://provean.jcvi.org/index.php ), and SIFT ( https://omictools.com/sift-tool ). Variant population frequency was annotated with ExAC ( http://exac.broadinstitute.org ), the 1000 Genomes database, and an internal database. Variant interpretation In this study, only novel variants or variants with < 1% population frequency in 1000 Genomes or ExAC were collected. Clinical significance of each variant was annotated according to the ACMG/AMP guidelines, using association results in this study, known clinical significance information from ClinVar ( http://www.ncbi.nlm.nih.gov/clinvar/ ), computational data by in silico programs, and functional data. We manually inspected each variant using the Integrative Genomics Viewer to rule out false positives. After the annotation, the results were compared with classifications in ClinVar to identify additional information and determine the final classification of each variant, collapsed from a 5-tier to 3-tier classification system: pathogenic, benign, and uncertain significance. Variants classified to be pathogenic or likely pathogenic were considered pathogenic in this study. All pathogenic variants were validated by Sanger sequencing. Statistical analysis Statistical comparisons of mutational status across clinicopathological characteristics in BRCA mutation carriers were conducted using Pearson's chi-square test supplemented by Fisher's exact test where appropriate. All statistical analyses were performed with SPSS Statistics software (Version 20.0; IBM Corporation, Armonk, NY, USA). A two-tailed alpha level of 0.05 was established a priori as the threshold for statistical significance throughout the study. Results BRCA1/2 and PALB2 Germline Mutations in Male Breast Cancer Through targeted sequencing, our present investigation identified twelve deleterious germline mutations in BRCA1/2 and PALB2 genes among twelve of ninety-seven unselected MaBC patients, as detailed in Table 1 . The observed prevalence rates exhibited marked heterogeneity in their distribution patterns: BRCA1 mutations were identified in a single MaBC case, BRCA2 mutations manifested in ten cases, with PALB2 mutations detected in a separate case. Molecular characterization revealed that the ten BRCA2 mutations comprised six nonsense variants and four frameshift alterations. Notably, one patient exhibited a pathogenic BRCA1 c.4015G > T stop-gained mutation, while another carried a PALB2 c.481_482dupGA frameshift mutation confirmed as deleterious through clinical interpretation. Table 1 BRCA1/2 and PALB2 pathogenic/likely pathogenic mutations identified in 12 male breast cancer cases. Sample Gene Systematic nomenclature HGVS protein change Annotation Clinical significance 1 BRCA2 c.8878C > T p.Gln2960* stop_gained Pathogenic 2 BRCA2 c.2471T > G p.Leu824* stop_gained Pathogenic 3 BRCA2 c.7558C > T p.Arg2520* stop_gained Pathogenic 4 BRCA2 c.8172delG p.Trp2725fs frameshift_variant Likely_pathogenic 5 BRCA2 c.6415G > T p.Glu2139* stop_gained Likely_pathogenic 6 BRCA2 c.5722_5723delCT p.Leu1908fs frameshift_variant Pathogenic 7 PALB2 c.481_482dupGA p.Asp161fs frameshift_variant Likely_pathogenic 8 BRCA2 c.37G > T p.Glu13* stop_gained Pathogenic 9 BRCA2 c.1773_1776delTTAT p.Ile591fs frameshift_variant Pathogenic 10 BRCA2 c.3109C > T p.Gln1037* stop_gained Pathogenic 11 BRCA2 c.8820_8823delACAA p.Gln2941fs frameshift_variant Likely_pathogenic 12 BRCA1 c.4015G > T p.Glu1339* stop_gained Pathogenic Potential Germline Driver Mutations in Male Breast Cancer Subsequently, we employed whole-exome sequencing (WES) to investigate the potential impact of additional driver mutations in a cohort comprising 85 male breast cancer (MaBC) patients and 4,480 healthy controls. Following quality control assessment, 21 patients were excluded due to insufficient DNA integrity and quantity. Comprehensive analysis of WES data derived from the remaining 64 MaBC cases revealed 170 pathogenic variants (Fig. 2 and Suppl. Table 1) alongside 388 variants of uncertain significance (VUS) (Fig. 3 and Suppl. Table 2), with 25 VUS excluded based on comparative analysis with control population data. Our WES analysis revealed two additional BRCA2 mutations (c.5073delA and c.3387G > C) that were not detected in the targeted sequencing platform. Table 2 enumerates the four most prevalent pathogenic/likely pathogenic germline mutations identified, notably RAD50, DMD, ARSA, and ABCC6 genes, which were recurrently identified in three or more cases. These genetic aberrations potentially constitute critical drivers in the oncogenesis and progression of MaBC. The mutational spectrum of the seven most frequently identified VUS-associated genes—TTN, ATN1, ATXN3, SCN5A, DYSF, MYO7A, and POLE—is exhaustively documented in Table 3 , with these alterations detected recurrently in four or more independent cases. It is worth noting that TTN mutations were identified in 15 MaBC patients within our cohort. Table 2 The top 4 pathogenic/likely pathogenic germline mutation-genes in 64 male breast cancer cases. ID Gene Systematic nomenclature HGVS protein change Annotation Clinical significance ly6876 RAD50 c.2165delA p.Lys722fs frameshift_variant Pathogenic ly6853 RAD50 c.1245 + 2C > A splice_donor_variant&intron_variant Likely_pathogenic ly6762 RAD50 c.2165dupA p.Glu723fs frameshift_variant Pathogenic ly6825 DMD c.4000G > T p.Gly1334* stop_gained Pathogenic/Likely_pathogenic ly6885 DMD c.5697delA p.Lys1899fs frameshift_variant Pathogenic ly6886 DMD c.5530C > T p.Arg1844* stop_gained Pathogenic ly6820 ARSA c.418delC p.His140fs frameshift_variant Likely_pathogenic ly6870 ARSA c.1492delC p.Arg498fs frameshift_variant Likely_pathogeni ly6853 ARSA c.302delG p.Gly101fs frameshift_variant Pathogenic ly6884 ABCC6 c.1990C > T p.Pro664Ser missense_variant Pathogenic ly6820 ABCC6 c.196dupT p.Ser66fs frameshift_variant Pathogenic ly6865 ABCC6 c.3412C > T p.Arg1138Trp missense_variant Pathogenic Table 3 The top 7 VUS germline mutation-genes in 64 male breast cancer cases. ID Gene Systematic nomenclature HGVS protein change Annotation Clinical significance ly6860 TTN c.57242T > C p.Ile19081Thr missense_variant Uncertain_significance ly6862 TTN c.24358C > T p.Pro8120Ser missense_variant Uncertain_significance ly6862 TTN c.45725G > A p.Arg15242Lys missense_variant Uncertain_significance ly6866 TTN c.32194G > T p.Glu10732* stop_gained Uncertain_significance ly6825 TTN c.24454G > A p.Val8152Ile missense_variant Uncertain_significance ly6826 TTN c.70492G > A p.Gly23498Ser missense_variant Uncertain_significance ly6875 TTN c.11855G > T p.Gly3952Val missense_variant Uncertain_significance ly6876 TTN c.39820C > T p.Pro13274Ser missense_variant&splice_region_variant Uncertain_significance ly6851 TTN c.75997G > T p.Gly25333Cys missense_variant Uncertain_significance ly6854 TTN c.74527A > G p.Asn24843Asp missense_variant Uncertain_significance ly6856 TTN c.59236G > T p.Gly19746Cys missense_variant Uncertain_significance ly6886 TTN c.81527G > A p.Arg27176His missense_variant Uncertain_significance ly6817 TTN c.88106G > T p.Gly29369Val missense_variant Uncertain_significance ly6819 TTN c.107080C > G p.Leu35694Val missense_variant Uncertain_significance ly6891 TTN c.89924C > T p.Ala29975Val missense_variant Uncertain_significance ly6859 ATN1 c.1503_1508delGCAGCA p.Gln501_Gln502del disruptive_inframe_deletion Uncertain_significance ly6860 ATN1 c.1506_1508dupGCA p.Gln502dup disruptive_inframe_insertion Uncertain_significance ly6861 ATN1 c.1485_1508delGCAGCAGCAGCAGCAGCAGCAGCA p.Gln495_Gln502del disruptive_inframe_deletion Uncertain_significance ly6862 ATN1 c.1503_1508dupGCAGCA p.Gln501_Gln502dup disruptive_inframe_insertion Uncertain_significance ly6865 ATN1 c.1491_1508delGCAGCAGCAGCAGCAGCA p.Gln497_Gln502del disruptive_inframe_deletion Uncertain_significance ly6866 ATN1 c.1494_1508delGCAGCAGCAGCAGCA p.Gln498_Gln502del disruptive_inframe_deletion Uncertain_significance ly6823 ATN1 c.1500_1508delGCAGCAGCA p.Gln500_Gln502del disruptive_inframe_deletion Uncertain_significance ly6874 ATN1 c.1488_1508delGCAGCAGCAGCAGCAGCAGCA p.Gln496_Gln502del disruptive_inframe_deletion Uncertain_significance ly6852 ATN1 c.1494_1508dupGCAGCAGCAGCAGCA p.Gln498_Gln502dup disruptive_inframe_insertion Uncertain_significance ly6879 ATN1 c.1506_1508delGCA p.Gln502del disruptive_inframe_deletion Uncertain_significance ly6881 ATN1 c.1497_1508dupGCAGCAGCAGCA p.Gln499_Gln502dup disruptive_inframe_insertion Uncertain_significance ly6872 ATXN3 c.943_944insAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGC p.Gly315delinsGluGlnGlnGlnGlnGlnGlnGlnGlnGlnGlnGlnGlrg inframe_insertion Uncertain_significance ly6859 ATXN3 c.943_944insAGCAGCAGCAGCAGCAGC p.Gly315delinsGluGlnGlnGlnGlnGlrg inframe_insertion Uncertain_significance ly6860 ATXN3 c.943_944insAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGC p.Gly315delinsGluGlnGlnGlnGlnGlnGlnGlnGlnGlnGlrg inframe_insertion Uncertain_significance ly6876 ATXN3 c.943_944insAGCAGCAGCAGC p.Gly315delinsGluGlnGlnGlrg inframe_insertion Uncertain_significance ly6852 ATXN3 c.943_944insAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGC p.Gly315delinsGluGlnGlnGlnGlnGlnGlnGlnGlnGlnGlnGlrg inframe_insertion Uncertain_significance ly6856 ATXN3 c.943_944insAGCAGCAGCAGCAGCAGCAGCAGC p.Gly315delinsGluGlnGlnGlnGlnGlnGlnGlrg inframe_insertion Uncertain_significance ly6857 ATXN3 c.943_944insAGC p.Gly315delinsGluArg inframe_insertion Uncertain_significance ly6856 SCN5A c.5216G > A p.Arg1739Gln missense_variant Uncertain_significance ly6763 SCN5A c.3556G > A p.Ala1186Thr missense_variant Uncertain_significance ly6873 SCN5A c.4018G > A p.Val1340Ile missense_variant Uncertain_significance ly6862 SCN5A c.677C > T p.Ala226Val missense_variant Uncertain_significance ly6878 SCN5A c.1840C > A p.Pro614Thr missense_variant Uncertain_significance ly6876 POLE c.968C > G p.Thr323Ser missense_variant Uncertain_significance ly6850 POLE c.3019G > T p.Ala1007Ser missense_variant Uncertain_significance ly6883 POLE c.6539C > T p.Ala2180Val missense_variant Uncertain_significance ly6824 POLE c.4337_4338delTG p.Val1446fs frameshift_variant Uncertain_significance ly6847 MYO7A c.4757A > G p.Asn1586Ser missense_variant Uncertain_significance ly6822 MYO7A c.3503G > A p.Arg1168Gln missense_variant&splice_region_variant Uncertain_significance ly6870 MYO7A c.4450C > A p.Leu1484Ile missense_variant Uncertain_significance ly6873 MYO7A c.1945C > T p.Arg649Trp missense_variant Uncertain_significance ly6893 DYSF c.2257C > A p.His753Asn missense_variant Uncertain_significance ly6854 DYSF c.4037C > T p.Ala1346Val missense_variant Uncertain_significance ly6887 DYSF c.6100A > C p.Ser2034Arg missense_variant Uncertain_significance ly6819 DYSF c.4859G > A p.Arg1620His missense_variant Uncertain_significance Associations between MaBC patients’ characteristics and mutation status We further explored the correlations between clinicopathological features of MaBCs and BRCA1/2 or PALB2 gene mutation status, with detailed results presented in Table 4. All identified mutations occurred in invasive breast carcinomas, including one case of encapsulated papillary carcinoma. All mutation carriers exhibited ER/PR-positive and HER2-negative molecular subtypes. Comparative analysis revealed potential differences in proliferative activity and tumor differentiation between mutation-positive and negative groups. Specifically, the BRCA1/2 or PALB2 mutation group demonstrated a trend toward higher Ki-67 expression levels (85.7% vs. 59.8% with ≥ 15% positivity threshold, P = 0.061). Similarly, histological grading showed a higher proportion of grade 3 tumors in the mutation-positive cohort (42.9% vs. 18.3%, P = 0.077), though neither comparison reached statistical significance. Both groups demonstrated comparable distributions in tumor size (T classification), lymph node status, and TNM staging parameters. Discussion The number of MaBC cases diagnosed is limited, and it has worse outcome compared with female breast cancer patients[ 6 ]. Therefore, multi-institutional collaborative efforts will be essential to identify specific biomarkers for MaBC and further elucidate the molecular pathogenesis of this malignancy. Utilizing a hospital-based cohort, this investigation presents the first comprehensive genomic landscape of MaBC in the Chinese population. Our analysis revealed 14 deleterious germline mutations in BRCA1/2 and PALB2 genes, along with 170 pathogenic/likely pathogenic variants and 388 variants of VUS. This study establishes foundational germline mutation profiles for MaBC, which constitutes a valuable reference for advancing mechanistic research and therapeutic development in this understudied disease entity. Accurate interpretation of BRCA1/2 variants is critical for risk assessment and precise treatment of breast cancer [ 7 – 9 ]. PALB2 is an important DNA repair gene that is essential for its function in homologous recombination [ 10 ]. In the DNA damage response, PALB2 links BRCA1 and BRCA2, implementing the recombinational repair and checkpoint functions of BRCA2 in maintaining genome integrity [ 11 ]. This genomic profiling study systematically analyzed BRCA1/2 and PALB2 mutations in 96 consecutive MaBC cases without familial predisposition screening. The mutation spectrum revealed recurrent pathogenic variants in BRCA2 (12.5%), significantly exceeding mutation rates observed in BRCA1 (1.04%) and PALB2 (1.04%). Targeted sequencing identified four exon 11 truncating mutations in BRCA2 (p.Leu824*, p.Glu2139*, p.Leu1908fs, p.Gln1037*) as detailed in, with whole-exome sequencing uncovering two additional exon 11 variants (p.Lys1691fs and p.Gln1129His) documented in Supplementary Table 1. Notably, two novel exon 22 mutations (p.Gln2960* and p.Gln2941fs) were detected in functionally critical regions of BRCA2. These findings corroborate our prior research cohort (n = 46) showing 15.2% BRCA2 mutation prevalence without BRCA1 carriers. Comparatively, population-level data from UK MaBC cases demonstrates 6% BRCA2 mutation frequency, consistent with the established predominance of BRCA2 over BRCA1 alterations in male breast carcinogenesis[ 12 ]. A US-based study examined 115 male breast cancer patients and identified 18 individuals carrying pathogenic BRCA2 genetic mutations[ 13 ]. Our analysis demonstrates a statistically significant predominance of BRCA2 mutations over BRCA1 mutations in male breast cancer cohorts. Genetic profiling within our cohort identified a pathogenic BRCA1 nonsense mutation (c.4015G > T, p.Glu1339Ter) in one patient and a deleterious PALB2 frameshift variant (c.482_483delAG, p.Asp161GlyfsTer7) in another case. These findings align with previous research by Silvestri et al. (2021), who reported the recurrent BRCA1 c.1984A > T (p.Lys662*) nonsense mutation through targeted sequencing of PALB2 in 48 BRCA1/2-negative MaBC specimens[ 14 ]. The mutagenic characteristics elucidated through our comprehensive panel-based genomic profiling not only delineate the epidemiological distribution and mutational landscape of BRCA1/2 and PALB2 genes in MaBC, but also advance our understanding of their pathogenic mechanisms in this malignancy. Most recently, Al Assaad M et al. used whole-genome sequencing (WGS) in 28 MaBC cases to demonstrate the genomic landscape of MaBC. Their findings showed somatic mutations in key driver genes, such as FAT1, GATA3, SMARCA4, and ARID2 [ 15 ]. The current study describes an in-depth exome analysis of the germline mutational landscape of MaBC. Among the significant MaBC related genes identified in our study, RAD50, DMD, ARSA and ABCC6 showed extensive genetic pleiotropy. RAD50, a cancer susceptibility gene, encodes a component of MRN (Mre11-Rad50-Nbs1), which participates in DNA double-strand break repair and DNA-damage checkpoint activation [ 16 – 18 ]. DMD plays roles in numerous biochemical processes [ 19 , 20 ]. ARSA takes part in nervous system development [ 21 , 22 ]. ABCC6 is involved in cardiovascular diseases [ 23 , 24 ]. The role of these deleterious mutations in MaBC progress remains to be defined. In summary, this study constitutes a omprehensive exome-wide profiling of MaBC mutations. Our panel-based and whole-exome sequencing analyses delineated distinctive mutational characteristics specific to Chinese MaBC populations. These novel findings significantly advance our comprehension of mutational processes in MaBC pathogenesis through their genotoxic manifestations. The identification of recurrently mutated novel target genes provides critical insights into the evolutionary dynamics underlying complex mutational profiles during MaBC progression. Moreover, prioritizing the investigation of mutagenic mechanisms implicated in MaBC initiation should constitute a critical research focus. Systematic functional validation studies will be conducted to elucidate the potential utility of these genetic markers for MaBC risk assessment and early detection. Declarations Disclosure: The authors have declared no conflicts of interest. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Fudan University Shanghai Cancer Center. Funding Declaration Author Contribution Zhen Hu and Zhi-Ming Shao contributed to the study conception and design. Material preparation, data collection and analysis were performed by Guan-Tian Lang, San-Jian Yu, Xiao-Ling Weng, Yun Liu and Xin Hu. The first draft of the manuscript was written by Guan-Tian Lang, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data availability The datasets generated during the current study are available from the corresponding author on reasonable request. References Zhu XW, Liu KQ, Wang PY, Liu JQ, Chen JY, Xu XJ, Xu JJ, Qiu MC, Sun Y, Liu C et al : Cohort profile: the Westlake BioBank for Chinese (WBBC) pilot project. BMJ Open 2021, 11(6):e045564. Cong PK, Bai WY, Li JC, Yang MY, Khederzadeh S, Gai SR, Li N, Liu YH, Yu SH, Zhao WW et al : Genomic analyses of 10,376 individuals in the Westlake BioBank for Chinese (WBBC) pilot project. Nat Commun 2022, 13(1):2939. 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Al Assaad M, Michaud O, Semaan A, Sigouros M, Tranquille M, Phan A, Levine MF, Gundem G, Medina-Martinez JS, Papaemmanuil E et al : Whole-Genome Sequencing Analysis of Male Breast Cancer Unveils Novel Structural Events and Potential Therapeutic Targets. Modern pathology: an official journal of the United States and Canadian Academy of Pathology, Inc 2024, 37(4):100452. Karamat U, Ejaz S: Overexpression of RAD50 is the Marker of Poor Prognosis and Drug Resistance in Breast Cancer Patients. Current cancer drug targets 2021, 21(2):163–176. George TJ, Lee JH, DeRemer DL, Hosein PJ, Staal S, Markham MJ, Jones D, Daily KC, Chatzkel JA, Ramnaraign BH et al : Phase II Trial of the PARP Inhibitor, Niraparib, in BAP1 and Other DNA Damage Response Pathway-Deficient Neoplasms. JCO precision oncology 2024, 8:e2400406. Zetrini AE, Abbasi AZ, He C, Lip H, Alradwan I, Rauth AM, Henderson JT, Wu XY: Targeting DNA damage repair mechanism by using RAD50-silencing siRNA nanoparticles to enhance radiotherapy in triple negative breast cancer. Materials today Bio 2024, 28:101206. Le Borgne J, Gomez L, Heikkinen S, Amin N, Ahmad S, Choi SH, Bis J, Grenier-Boley B, Rodriguez OG, Kleineidam L et al : X-chromosome-wide association study for Alzheimer's disease. Molecular psychiatry 2024. Jepsen WM, Fazenbaker A, Ramsey K, Bonfitto A, Naymik M, Turner B, Sloan J, Tiwari N, Bernes SM, Neilson DE et al : Duchenne Muscular Dystrophy in Two Half-Brothers Due to Inherited 306 Kb Inverted Insertion of 10p15.1 into Intron 44 of the Dp427m Transcript of the DMD Gene. International journal of molecular sciences 2024, 25(22). Mahendran G, Breger K, McCown PJ, Hulewicz JP, Bhandari T, Addepalli B, Brown JA: Multi-Omics Approach Reveals Genes and Pathways Affected in Miller-Dieker Syndrome. Molecular neurobiology 2024. Rabin R, Hirsch Y, Booth KTA, Hall PL, Yachelevich N, Mistry PK, Ekstein J, Pappas J: ARSA Variant Associated With Late Infantile Metachromatic Leukodystrophy and Carrier Rate in Individuals of Ashkenazi Jewish Ancestry. American journal of medical genetics Part A 2024:e63919. Harmsen IM, Visseren FLJ, Kok M, de Jong PA, Spiering W: Arterial calcification volume is associated with a higher risk of cardiovascular events in pseudoxanthoma elasticum. Atherosclerosis 2024, 400:119051. Desai D, Maheta D, Agrawal SP, Soni Z, Frishman WH, Aronow WS: Cardiovascular Manifestations of Pseudoxanthoma Elasticum: Pathophysiology, Management, and Research. Cardiology in review 2024. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.doc SupplementaryTable2.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board 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-7283126","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":503565620,"identity":"33cf006e-6b02-4326-8546-04d93ac7cd78","order_by":0,"name":"Guan-Tian Lang","email":"","orcid":"","institution":"Department of Breast Surgery, Precision Cancer Medicine Center, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Guan-Tian","middleName":"","lastName":"Lang","suffix":""},{"id":503565621,"identity":"9c661d0e-3b15-4d04-b0be-61843bbfd53d","order_by":1,"name":"San-Jian Yu","email":"","orcid":"","institution":"Department of Breast Surgery, Precision Cancer Medicine Center, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"San-Jian","middleName":"","lastName":"Yu","suffix":""},{"id":503565622,"identity":"2106fa7e-6f6e-4cf1-a60c-4f8f0c5ff0db","order_by":2,"name":"Xiao-Ling Weng","email":"","orcid":"","institution":"Shanghai Key Laboratory of Systems Regulation and Clinical Translation for Cancer, State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Xiao-Ling","middleName":"","lastName":"Weng","suffix":""},{"id":503565623,"identity":"034fcb1a-ea75-4650-a434-954ffcf53e3a","order_by":3,"name":"Yun Liu","email":"","orcid":"","institution":"Shanghai Key Laboratory of Systems Regulation and Clinical Translation for Cancer, State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Yun","middleName":"","lastName":"Liu","suffix":""},{"id":503565624,"identity":"04b64e4d-031f-47bb-a8bf-576051eea145","order_by":4,"name":"Xin Hu","email":"","orcid":"","institution":"Department of Breast Surgery, Precision Cancer Medicine Center, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Hu","suffix":""},{"id":503565625,"identity":"fa8a8b51-3ca3-47f0-9d7c-3fbd399ae453","order_by":5,"name":"Zhi-Ming Shao","email":"","orcid":"","institution":"Department of Breast Surgery, Precision Cancer Medicine Center, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Zhi-Ming","middleName":"","lastName":"Shao","suffix":""},{"id":503565626,"identity":"dd25902c-bb04-40bd-8977-a5166158b16b","order_by":6,"name":"Zhen Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYDACCQYGZgYGG34GhgQQl5loLWmSDaRqOUyCFvnZzcceF7adlzA4nvzsAUOFdWID+9kDeLUwzjmWbjyz7baEwZln5gYMZ9ITG3jyEvBqYZbIMZPmbbtdZ3AjwUyCse1wYoMEjwFeLWwS+d+AWs5JGNxI/ybB+I8ILTwSOWxALQeAWnKAtjQQoUVCIs1MmudcsoTkmTdlEglAj7Xx5ODXIj8j+Zk0T5mdBN/x9G0SH2qsZfvZz+DXggoSQL4jQf0oGAWjYBSMAhwAAHFRPpCz/QrLAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Breast Surgery, Precision Cancer Medicine Center, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center","correspondingAuthor":true,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2025-08-03 11:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7283126/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7283126/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89976072,"identity":"c17305a8-18a4-4cbc-af24-118b7a24b435","added_by":"auto","created_at":"2025-08-27 06:00:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":217937,"visible":true,"origin":"","legend":"\u003cp\u003eStudy design and workflow.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-7283126/v1/2df1ebfda3ca3a9ca42874c3.png"},{"id":89976074,"identity":"36e860d4-19d4-4b0e-b199-896b4cc53b79","added_by":"auto","created_at":"2025-08-27 06:00:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":388443,"visible":true,"origin":"","legend":"\u003cp\u003eThe spectrum of the pathogenic/likely pathogenic germline mutations by whole-exome sequencing analysis.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-7283126/v1/f15500682ddf4ed66550b5c0.png"},{"id":89976077,"identity":"747e8955-0caa-41c3-9f8c-bf6de048349c","added_by":"auto","created_at":"2025-08-27 06:00:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":524528,"visible":true,"origin":"","legend":"\u003cp\u003eThe spectrum of the VUS germline mutations by whole-exome sequencing analysis.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-7283126/v1/1bcb9de1d462554ed8677d5e.png"},{"id":93538235,"identity":"1de7336d-808e-4329-b1df-738f439f237e","added_by":"auto","created_at":"2025-10-15 02:08:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2098277,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7283126/v1/fa906e94-de89-4819-91f0-bd232fa18c31.pdf"},{"id":89976071,"identity":"41e84c2c-efa9-4375-b4f2-1b8ad76ebceb","added_by":"auto","created_at":"2025-08-27 06:00:07","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":304128,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.doc","url":"https://assets-eu.researchsquare.com/files/rs-7283126/v1/86758cb84b42d6ef2a65de3a.doc"},{"id":89976076,"identity":"764aae4d-2aa4-408e-a114-d8ca28debd6a","added_by":"auto","created_at":"2025-08-27 06:00:08","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":464384,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.doc","url":"https://assets-eu.researchsquare.com/files/rs-7283126/v1/f9899e7308b3685c2bea17ef.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive Genomic Profiling through Panel-based and Whole-exome Sequencing in a Population-based Chinese Han Male Breast Cancer Cohort","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMale breast cancer (MaBC) represents a rare malignancy, constituting approximately 1% of all breast carcinomas and less than 1% of total cancer diagnoses in males [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Epidemiological data from 2016 estimated 2400 new cases and 440 breast cancer-associated mortalities among MaBC patients in the United States [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The limited availability of comprehensive clinical data - including patient demographics, tumor biology, therapeutic interventions, and prognostic outcomes - stems from the disease's low incidence. Current clinical management predominantly relies on therapeutic paradigms extrapolated from female breast cancer studies, with insufficient characterization of MaBC-specific clinicopathological features. Furthermore, molecular profiling of MaBC remains inadequately explored.\u003c/p\u003e\u003cp\u003eIn this investigation, we performed panel-based sequencing analysis of BRCA1, BRCA2, and PALB2 genes in 96 consecutive MaBC patients of Chinese Han ethnicity. Our primary objectives were to: (1) determine the prevalence and spectrum of germline mutations in BRCA1/2 and PALB2 among Chinese male breast cancer patients, and (2) conduct whole-exome sequencing (WES) to identify potential driver mutations underlying clinical manifestations in MaBC.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy population\u003c/h2\u003e\u003cp\u003eA prospective cohort comprising 96 MaBC patients was consecutively enrolled at Fudan University Shanghai Cancer Center (Shanghai, China) between January 2014 and November 2018. The study cohort comprised 4,480 healthy control subjects obtained from a publicly available genetic database maintained by Zhejiang University School of Medicine[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Each participant signed a written informed consent form and ethical consent. Peripheral blood specimens and comprehensive phenotypic data were systematically collected from all study participants. Genomic DNA extraction was performed using the VAZYME Blood Genomic DNA Kit (Vazyme Medical Technology, Nanjing, China) following manufacturer's protocols. This study received ethical approval from the Institutional Review Board of Fudan University Shanghai Cancer Center, with written informed consent obtained from all participants prior to sample collection and data acquisition. Clinical significant germline mutations were determined in our cohort of 96 unselected MaBC patients according to Fig.\u0026nbsp;1.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTargeted Sequencing\u003c/h3\u003e\n\u003cp\u003eThe target-specific primers for the coding sequences of the BRCA1 (NM_007300), BRCA2(NM_000059) and PALB2 (NM_024675) were designed using Primer3 as described previously [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The universal sequences (CS1: ACACTGACGACATGGTTCTACA and CS2: TACGGTAGCAGAGACTTGGTCT) were appended at the 5\u0026rsquo;-end of each left and right primer, respectively. Pre-amplification for tagged amplicon deep sequencing (TAm-Seq): The coding sequences of the two genes were amplified using a 6 ml PCR reaction mixture containing 3 ml of KAPA 2G Robust HotStart ReadyMix (2X) (Kapa Biosystems, Boston, Massachusetts, United States), 1 ml of primer mix (500 nM) and 2 ml of DNA template (10 ng/ml). PCR conditions were as follows: initial denaturation for 2 min at 95\u0026deg;C; 45 cycles of denaturation for 30 s at 95\u0026deg;C, 30 s annealing at 56\u0026deg;C, and 1 min extension at 72\u0026deg;C; and a final extension step for 5 min at 72\u0026deg;C. Following PCR amplification, 1.5 ml of Shrimp Aalkaline Phosphatase (SAP, Affymetrixx, Santa Clara, California)/Exonuclease I (Exo I, BioLabss, Ipswich, Massachusetts) mix was added to 2.5 ml of PCR product and incubated for 60 min at 37\u0026deg;C, then for 20 min at 80\u0026deg;C. SAP/Exo I mix contained 600 ml of SAP (1 U/ml), 240 ml of SAP buffer, 150 ml of Exo I (20,000 U/ml), 200 ml of Exo I buffer and 3000 ml of ddH2O.\u003c/p\u003e\u003cp\u003eSequencing adaptor and barcode primer addition were performed as described previously. The barcode primers (Fluidigmm Corporation, South San Francisco, California) consisted of the PE1 and PE2 sequences for Illumina cluster generation, a 10-bp barcode, and the CS1 and CS2 adaptors, used in pairs: PE1-CS1 with PE2-BC-CS2, and PE1-CS2 with PE2-BC-CS1. For each sample, 1 \u0026micro;l of the 100-fold diluted PCR product was added to one of two PCR plates containing 9 \u0026micro;l of pre-sample mix containing 0.4 \u0026micro;l of 1 U/\u0026micro;l KAPA HiFi HotStart DNA Polymerase, 4 \u0026micro;l of 5\u0026times; KAPA HiFi Buffer, 120 \u0026micro;M of each dNTP and 4 \u0026micro;l of ddH2O. In the first plate, 10 \u0026micro;l of one primer pair containing an individual 10-base barcode (BC) sequence and tags for reading in one direction (PE1-BC-CS1\u0026thinsp;+\u0026thinsp;PE2-CS2) was added to each well. In the second plate, 10 \u0026micro;l of primers containing (PE1-BC-CS2\u0026thinsp;+\u0026thinsp;PE2-CS1) was added to each well. The corresponding wells in both plates contained primers with the same barcode sequence. Plated reaction products were amplified for 12 cycles: 95\u0026deg;C for 10 min; 12 cycles of 95\u0026deg;C for 15 s; 60\u0026deg;C for 30 s; 72\u0026deg;C for 3 min; and 1 cycle of 72\u0026deg;C for 3 min.\u003c/p\u003e\u003cp\u003eFor the DNA library, PCR products were barcoded and analyzed using gel electrophoresis to ensure the expected insertion size was obtained. Products were then pooled together with an equal volume and purified using AMPure XP beads s (Beckman Coulter, Indianapolis, United States). The targeted DNA fragment was selected and extracted using E-Gel Precast Agarose Electrophoresis (ThermoFisher Scientific, Waltham, Massachusetts) and QIAquick Gel Extraction Kit. The library was quantified by Agilent BioAnalyzer and sequenced using the Illumina Xten platforms with paired-end reads of 150-bp per the manufacturer\u0026rsquo;s instructions. Custom sequencing primers targeted to CS1 and CS2 targeted the paired reads and 10-base indexing (barcode) read per the recommendations of Fluidigm.\u003c/p\u003e\n\u003ch3\u003eWhole-exome sequencing\u003c/h3\u003e\n\u003cp\u003eBriefly, 1 \u0026micro;g of DNA was sheared into short fragments (200\u0026ndash;300 bp) using a Covaris S220 ultrasonicator. The DNA fragments were then end repaired to generate adenylated 3\u0026prime; ends. Adaptors with barcode sequences were then ligated to both ends of the fragments, and E-Gels were used to select DNA fragments of the targeted size. Next, 10 PCR cycles were performed, and the resulting product was purified. Whole exome capture was performed using a TruSeq Exome Enrichment kit (Illumina) according to the manufacturer\u0026rsquo;s protocol with slight modifications. After the Illumina sequencing libraries were amplified with 10 PCR cycles, capture probes were added, and the reaction mixtures were incubated at 65\u0026deg;C for 24 h. The hybridized mixtures were then amplified with an additional 10 PCR cycles. Captured DNA libraries were sequenced with the Illumina HiSeq 2500 Genome Analyzer, yielding 200 (2 \u0026times; 100) base pairs from the final library fragments.\u003c/p\u003e\n\u003ch3\u003eNGS data processing and variant calling\u003c/h3\u003e\n\u003cp\u003eSequencing reads were aligned to the hg19 reference genome using Burrows-Wheeler Aligner (BWA) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and the Genome Analysis Toolkit (GATK) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] was used for base quality score recalibration, indel realignment, and variant calling. We used GATK to filter the variants, required (i) QD\u0026thinsp;\u0026lt;\u0026thinsp;2.0; (ii) MQ\u0026thinsp;\u0026lt;\u0026thinsp;40.0; (iii) MQRankSum\u0026lt;-12.5; and (iv) ReadPosRankSum\u0026lt;-8.0. Variant functions were predicted using SnpEff (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://snpeff.sourceforge.net\u003c/span\u003e\u003cspan address=\"http://snpeff.sourceforge.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), PolyPhen-2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://genetics.bwh.harvard.edu/pph2/\u003c/span\u003e\u003cspan address=\"http://genetics.bwh.harvard.edu/pph2/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), PROVEAN (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://provean.jcvi.org/index.php\u003c/span\u003e\u003cspan address=\"http://provean.jcvi.org/index.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and SIFT (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://omictools.com/sift-tool\u003c/span\u003e\u003cspan address=\"https://omictools.com/sift-tool\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Variant population frequency was annotated with ExAC (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://exac.broadinstitute.org\u003c/span\u003e\u003cspan address=\"http://exac.broadinstitute.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), the 1000 Genomes database, and an internal database.\u003c/p\u003e\n\u003ch3\u003eVariant interpretation\u003c/h3\u003e\n\u003cp\u003eIn this study, only novel variants or variants with \u0026lt;\u0026thinsp;1% population frequency in 1000 Genomes or ExAC were collected. Clinical significance of each variant was annotated according to the ACMG/AMP guidelines, using association results in this study, known clinical significance information from ClinVar (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/clinvar/\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/clinvar/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), computational data by in silico programs, and functional data. We manually inspected each variant using the Integrative Genomics Viewer to rule out false positives. After the annotation, the results were compared with classifications in ClinVar to identify additional information and determine the final classification of each variant, collapsed from a 5-tier to 3-tier classification system: pathogenic, benign, and uncertain significance. Variants classified to be pathogenic or likely pathogenic were considered pathogenic in this study. All pathogenic variants were validated by Sanger sequencing.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStatistical comparisons of mutational status across clinicopathological characteristics in BRCA mutation carriers were conducted using Pearson's chi-square test supplemented by Fisher's exact test where appropriate. All statistical analyses were performed with SPSS Statistics software (Version 20.0; IBM Corporation, Armonk, NY, USA). A two-tailed alpha level of 0.05 was established a priori as the threshold for statistical significance throughout the study.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eBRCA1/2 and PALB2 Germline Mutations in Male Breast Cancer\u003c/h2\u003e\u003cp\u003eThrough targeted sequencing, our present investigation identified twelve deleterious germline mutations in BRCA1/2 and PALB2 genes among twelve of ninety-seven unselected MaBC patients, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The observed prevalence rates exhibited marked heterogeneity in their distribution patterns: BRCA1 mutations were identified in a single MaBC case, BRCA2 mutations manifested in ten cases, with PALB2 mutations detected in a separate case. Molecular characterization revealed that the ten BRCA2 mutations comprised six nonsense variants and four frameshift alterations. Notably, one patient exhibited a pathogenic BRCA1 c.4015G\u0026thinsp;\u0026gt;\u0026thinsp;T stop-gained mutation, while another carried a PALB2 c.481_482dupGA frameshift mutation confirmed as deleterious through clinical interpretation.\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\u003eBRCA1/2 and PALB2 pathogenic/likely pathogenic mutations identified in 12 male breast cancer cases.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\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\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSystematic nomenclature\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHGVS protein change\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAnnotation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eClinical significance\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\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.8878C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln2960*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\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=\"c2\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.2471T\u0026thinsp;\u0026gt;\u0026thinsp;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Leu824*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\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=\"c2\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.7558C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg2520*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.8172delG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Trp2725fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLikely_pathogenic\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=\"c2\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.6415G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Glu2139*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLikely_pathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.5722_5723delCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Leu1908fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\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=\"c2\"\u003e\u003cp\u003ePALB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.481_482dupGA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Asp161fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLikely_pathogenic\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=\"c2\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.37G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Glu13*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\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=\"c2\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1773_1776delTTAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ile591fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\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\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.3109C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln1037*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\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=\"c2\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.8820_8823delACAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln2941fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLikely_pathogenic\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=\"c2\"\u003e\u003cp\u003eBRCA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.4015G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Glu1339*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePotential Germline Driver Mutations in Male Breast Cancer\u003c/h2\u003e\u003cp\u003eSubsequently, we employed whole-exome sequencing (WES) to investigate the potential impact of additional driver mutations in a cohort comprising 85 male breast cancer (MaBC) patients and 4,480 healthy controls. Following quality control assessment, 21 patients were excluded due to insufficient DNA integrity and quantity. Comprehensive analysis of WES data derived from the remaining 64 MaBC cases revealed 170 pathogenic variants (Fig.\u0026nbsp;2 and Suppl. Table\u0026nbsp;1) alongside 388 variants of uncertain significance (VUS) (Fig.\u0026nbsp;3 and Suppl. Table\u0026nbsp;2), with 25 VUS excluded based on comparative analysis with control population data. Our WES analysis revealed two additional BRCA2 mutations (c.5073delA and c.3387G\u0026thinsp;\u0026gt;\u0026thinsp;C) that were not detected in the targeted sequencing platform. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e enumerates the four most prevalent pathogenic/likely pathogenic germline mutations identified, notably RAD50, DMD, ARSA, and ABCC6 genes, which were recurrently identified in three or more cases. These genetic aberrations potentially constitute critical drivers in the oncogenesis and progression of MaBC. The mutational spectrum of the seven most frequently identified VUS-associated genes\u0026mdash;TTN, ATN1, ATXN3, SCN5A, DYSF, MYO7A, and POLE\u0026mdash;is exhaustively documented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, with these alterations detected recurrently in four or more independent cases. It is worth noting that TTN mutations were identified in 15 MaBC patients within our cohort.\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\u003eThe top 4 pathogenic/likely pathogenic germline mutation-genes in 64 male breast cancer cases.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSystematic nomenclature\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHGVS protein change\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAnnotation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eClinical significance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRAD50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.2165delA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Lys722fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6853\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRAD50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1245\u0026thinsp;+\u0026thinsp;2C\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003esplice_donor_variant\u0026amp;intron_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLikely_pathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6762\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRAD50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.2165dupA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Glu723fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6825\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDMD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.4000G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly1334*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic/Likely_pathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6885\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDMD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.5697delA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Lys1899fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDMD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.5530C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg1844*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6820\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eARSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.418delC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.His140fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLikely_pathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6870\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eARSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1492delC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg498fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLikely_pathogeni\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6853\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eARSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.302delG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly101fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eABCC6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1990C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Pro664Ser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6820\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eABCC6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.196dupT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ser66fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eABCC6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.3412C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg1138Trp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePathogenic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe top 7 VUS germline mutation-genes in 64 male breast cancer cases.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSystematic nomenclature\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHGVS protein change\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAnnotation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eClinical significance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.57242T\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ile19081Thr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.24358C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Pro8120Ser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.45725G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg15242Lys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6866\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.32194G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Glu10732*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estop_gained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6825\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.24454G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Val8152Ile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.70492G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly23498Ser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.11855G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly3952Val\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.39820C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Pro13274Ser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u0026amp;splice_region_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6851\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.75997G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly25333Cys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.74527A\u0026thinsp;\u0026gt;\u0026thinsp;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Asn24843Asp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.59236G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly19746Cys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.81527G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg27176His\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6817\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.88106G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly29369Val\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6819\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.107080C\u0026thinsp;\u0026gt;\u0026thinsp;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Leu35694Val\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.89924C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ala29975Val\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1503_1508delGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln501_Gln502del\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_deletion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1506_1508dupGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln502dup\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6861\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1485_1508delGCAGCAGCAGCAGCAGCAGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln495_Gln502del\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_deletion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1503_1508dupGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln501_Gln502dup\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1491_1508delGCAGCAGCAGCAGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln497_Gln502del\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_deletion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6866\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1494_1508delGCAGCAGCAGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln498_Gln502del\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_deletion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1500_1508delGCAGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln500_Gln502del\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_deletion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6874\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1488_1508delGCAGCAGCAGCAGCAGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln496_Gln502del\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_deletion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1494_1508dupGCAGCAGCAGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln498_Gln502dup\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6879\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1506_1508delGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln502del\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_deletion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6881\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1497_1508dupGCAGCAGCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gln499_Gln502dup\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edisruptive_inframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6872\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATXN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.943_944insAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly315delinsGluGlnGlnGlnGlnGlnGlnGlnGlnGlnGlnGlnGlrg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003einframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATXN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.943_944insAGCAGCAGCAGCAGCAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly315delinsGluGlnGlnGlnGlnGlrg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003einframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATXN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.943_944insAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly315delinsGluGlnGlnGlnGlnGlnGlnGlnGlnGlnGlrg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003einframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATXN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.943_944insAGCAGCAGCAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly315delinsGluGlnGlnGlrg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003einframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATXN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.943_944insAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly315delinsGluGlnGlnGlnGlnGlnGlnGlnGlnGlnGlnGlrg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003einframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATXN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.943_944insAGCAGCAGCAGCAGCAGCAGCAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly315delinsGluGlnGlnGlnGlnGlnGlnGlrg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003einframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATXN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.943_944insAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Gly315delinsGluArg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003einframe_insertion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCN5A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.5216G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg1739Gln\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCN5A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.3556G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ala1186Thr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCN5A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.4018G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Val1340Ile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCN5A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.677C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ala226Val\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCN5A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1840C\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Pro614Thr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOLE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.968C\u0026thinsp;\u0026gt;\u0026thinsp;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Thr323Ser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6850\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOLE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.3019G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ala1007Ser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOLE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.6539C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ala2180Val\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOLE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.4337_4338delTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Val1446fs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eframeshift_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6847\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMYO7A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.4757A\u0026thinsp;\u0026gt;\u0026thinsp;G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Asn1586Ser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMYO7A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.3503G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg1168Gln\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u0026amp;splice_region_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6870\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMYO7A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.4450C\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Leu1484Ile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMYO7A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.1945C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg649Trp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6893\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDYSF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.2257C\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.His753Asn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDYSF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.4037C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ala1346Val\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6887\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDYSF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.6100A\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Ser2034Arg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ely6819\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDYSF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ec.4859G\u0026thinsp;\u0026gt;\u0026thinsp;A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep.Arg1620His\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUncertain_significance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eAssociations between MaBC patients\u0026rsquo; characteristics and mutation status\u003c/h2\u003e\u003cp\u003eWe further explored the correlations between clinicopathological features of MaBCs and BRCA1/2 or PALB2 gene mutation status, with detailed results presented in Table\u0026nbsp;4. All identified mutations occurred in invasive breast carcinomas, including one case of encapsulated papillary carcinoma. All mutation carriers exhibited ER/PR-positive and HER2-negative molecular subtypes. Comparative analysis revealed potential differences in proliferative activity and tumor differentiation between mutation-positive and negative groups. Specifically, the BRCA1/2 or PALB2 mutation group demonstrated a trend toward higher Ki-67 expression levels (85.7% vs. 59.8% with \u0026ge;\u0026thinsp;15% positivity threshold, P\u0026thinsp;=\u0026thinsp;0.061). Similarly, histological grading showed a higher proportion of grade 3 tumors in the mutation-positive cohort (42.9% vs. 18.3%, P\u0026thinsp;=\u0026thinsp;0.077), though neither comparison reached statistical significance. Both groups demonstrated comparable distributions in tumor size (T classification), lymph node status, and TNM staging parameters.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe number of MaBC cases diagnosed is limited, and it has worse outcome compared with female breast cancer patients[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, multi-institutional collaborative efforts will be essential to identify specific biomarkers for MaBC and further elucidate the molecular pathogenesis of this malignancy. Utilizing a hospital-based cohort, this investigation presents the first comprehensive genomic landscape of MaBC in the Chinese population. Our analysis revealed 14 deleterious germline mutations in BRCA1/2 and PALB2 genes, along with 170 pathogenic/likely pathogenic variants and 388 variants of VUS. This study establishes foundational germline mutation profiles for MaBC, which constitutes a valuable reference for advancing mechanistic research and therapeutic development in this understudied disease entity.\u003c/p\u003e\u003cp\u003eAccurate interpretation of BRCA1/2 variants is critical for risk assessment and precise treatment of breast cancer [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. PALB2 is an important DNA repair gene that is essential for its function in homologous recombination [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In the DNA damage response, PALB2 links BRCA1 and BRCA2, implementing the recombinational repair and checkpoint functions of BRCA2 in maintaining genome integrity [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This genomic profiling study systematically analyzed BRCA1/2 and PALB2 mutations in 96 consecutive MaBC cases without familial predisposition screening. The mutation spectrum revealed recurrent pathogenic variants in BRCA2 (12.5%), significantly exceeding mutation rates observed in BRCA1 (1.04%) and PALB2 (1.04%). Targeted sequencing identified four exon 11 truncating mutations in BRCA2 (p.Leu824*, p.Glu2139*, p.Leu1908fs, p.Gln1037*) as detailed in, with whole-exome sequencing uncovering two additional exon 11 variants (p.Lys1691fs and p.Gln1129His) documented in Supplementary Table\u0026nbsp;1. Notably, two novel exon 22 mutations (p.Gln2960* and p.Gln2941fs) were detected in functionally critical regions of BRCA2. These findings corroborate our prior research cohort (n\u0026thinsp;=\u0026thinsp;46) showing 15.2% BRCA2 mutation prevalence without BRCA1 carriers. Comparatively, population-level data from UK MaBC cases demonstrates 6% BRCA2 mutation frequency, consistent with the established predominance of BRCA2 over BRCA1 alterations in male breast carcinogenesis[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A US-based study examined 115 male breast cancer patients and identified 18 individuals carrying pathogenic BRCA2 genetic mutations[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Our analysis demonstrates a statistically significant predominance of BRCA2 mutations over BRCA1 mutations in male breast cancer cohorts. Genetic profiling within our cohort identified a pathogenic BRCA1 nonsense mutation (c.4015G\u0026thinsp;\u0026gt;\u0026thinsp;T, p.Glu1339Ter) in one patient and a deleterious PALB2 frameshift variant (c.482_483delAG, p.Asp161GlyfsTer7) in another case. These findings align with previous research by Silvestri et al. (2021), who reported the recurrent BRCA1 c.1984A\u0026thinsp;\u0026gt;\u0026thinsp;T (p.Lys662*) nonsense mutation through targeted sequencing of PALB2 in 48 BRCA1/2-negative MaBC specimens[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The mutagenic characteristics elucidated through our comprehensive panel-based genomic profiling not only delineate the epidemiological distribution and mutational landscape of BRCA1/2 and PALB2 genes in MaBC, but also advance our understanding of their pathogenic mechanisms in this malignancy.\u003c/p\u003e\u003cp\u003eMost recently, Al Assaad M et al. used whole-genome sequencing (WGS) in 28 MaBC cases to demonstrate the genomic landscape of MaBC. Their findings showed somatic mutations in key driver genes, such as FAT1, GATA3, SMARCA4, and ARID2 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The current study describes an in-depth exome analysis of the germline mutational landscape of MaBC. Among the significant MaBC related genes identified in our study, RAD50, DMD, ARSA and ABCC6 showed extensive genetic pleiotropy. RAD50, a cancer susceptibility gene, encodes a component of MRN (Mre11-Rad50-Nbs1), which participates in DNA double-strand break repair and DNA-damage checkpoint activation [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. DMD plays roles in numerous biochemical processes [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. ARSA takes part in nervous system development [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. ABCC6 is involved in cardiovascular diseases [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The role of these deleterious mutations in MaBC progress remains to be defined.\u003c/p\u003e\u003cp\u003eIn summary, this study constitutes a omprehensive exome-wide profiling of MaBC mutations. Our panel-based and whole-exome sequencing analyses delineated distinctive mutational characteristics specific to Chinese MaBC populations. These novel findings significantly advance our comprehension of mutational processes in MaBC pathogenesis through their genotoxic manifestations. The identification of recurrently mutated novel target genes provides critical insights into the evolutionary dynamics underlying complex mutational profiles during MaBC progression. Moreover, prioritizing the investigation of mutagenic mechanisms implicated in MaBC initiation should constitute a critical research focus. Systematic functional validation studies will be conducted to elucidate the potential utility of these genetic markers for MaBC risk assessment and early detection.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eDisclosure:\u003c/h2\u003e\u003cp\u003eThe authors have declared no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003cp\u003e This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Fudan University Shanghai Cancer Center.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eDeclaration\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZhen Hu and Zhi-Ming Shao contributed to the study conception and design. Material preparation, data collection and analysis were performed by Guan-Tian Lang, San-Jian Yu, Xiao-Ling Weng, Yun Liu and Xin Hu. The first draft of the manuscript was written by Guan-Tian Lang, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhu XW, Liu KQ, Wang PY, Liu JQ, Chen JY, Xu XJ, Xu JJ, Qiu MC, Sun Y, Liu C \u003cem\u003eet al\u003c/em\u003e: Cohort profile: the Westlake BioBank for Chinese (WBBC) pilot project. \u003cem\u003eBMJ Open\u003c/em\u003e 2021, 11(6):e045564.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCong PK, Bai WY, Li JC, Yang MY, Khederzadeh S, Gai SR, Li N, Liu YH, Yu SH, Zhao WW \u003cem\u003eet al\u003c/em\u003e: Genomic analyses of 10,376 individuals in the Westlake BioBank for Chinese (WBBC) pilot project. \u003cem\u003eNat Commun\u003c/em\u003e 2022, 13(1):2939.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCong PK, Khederzadeh S, 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562(7726):217\u0026ndash;222.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBhaskaran SP, Chandratre K, Gupta H, Zhang L, Wang X, Cui J, Kim YC, Sinha S, Jiang L, Lu B \u003cem\u003eet al\u003c/em\u003e: Germline variation in BRCA1/2 is highly ethnic-specific: Evidence from over 30,000 Chinese hereditary breast and ovarian cancer patients. \u003cem\u003eInternational journal of cancer\u003c/em\u003e 2019, 145(4):962\u0026ndash;973.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang F, Ma J, Wu J, Ye L, Cai H, Xia B, Yu X: PALB2 links BRCA1 and BRCA2 in the DNA-damage response. \u003cem\u003eCurrent biology: CB\u003c/em\u003e 2009, 19(6):524\u0026ndash;529.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSy SM, Huen MS, Zhu Y, Chen J: PALB2 regulates recombinational repair through chromatin association and oligomerization. \u003cem\u003eThe Journal of biological chemistry\u003c/em\u003e 2009, 284(27):18302\u0026ndash;18310.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBasham VM, Lipscombe JM, Ward JM, Gayther SA, Ponder BA, Easton DF, Pharoah PD: BRCA1 and BRCA2 mutations in a population-based study of male breast cancer. \u003cem\u003eBreast Cancer Res\u003c/em\u003e 2002, 4(1):R2.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDing YC, Steele L, Kuan CJ, Greilac S, Neuhausen SL: Mutations in BRCA2 and PALB2 in male breast cancer cases from the United States. \u003cem\u003eBreast Cancer Res Treat\u003c/em\u003e 2011, 126(3):771\u0026ndash;778.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSilvestri V, Zelli V, Valentini V, Rizzolo P, Navazio AS, Coppa A, Agata S, Oliani C, Barana D, Castrignano T \u003cem\u003eet al\u003c/em\u003e: Whole-exome sequencing and targeted gene sequencing provide insights into the role of PALB2 as a male breast cancer susceptibility gene. \u003cem\u003eCancer\u003c/em\u003e 2017, 123(2):210\u0026ndash;218.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAl Assaad M, Michaud O, Semaan A, Sigouros M, Tranquille M, Phan A, Levine MF, Gundem G, Medina-Martinez JS, Papaemmanuil E \u003cem\u003eet al\u003c/em\u003e: Whole-Genome Sequencing Analysis of Male Breast Cancer Unveils Novel Structural Events and Potential Therapeutic Targets. \u003cem\u003eModern pathology: an official journal of the United States and Canadian Academy of Pathology, Inc\u003c/em\u003e 2024, 37(4):100452.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaramat U, Ejaz S: Overexpression of RAD50 is the Marker of Poor Prognosis and Drug Resistance in Breast Cancer Patients. \u003cem\u003eCurrent cancer drug targets\u003c/em\u003e 2021, 21(2):163\u0026ndash;176.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeorge TJ, Lee JH, DeRemer DL, Hosein PJ, Staal S, Markham MJ, Jones D, Daily KC, Chatzkel JA, Ramnaraign BH \u003cem\u003eet al\u003c/em\u003e: Phase II Trial of the PARP Inhibitor, Niraparib, in BAP1 and Other DNA Damage Response Pathway-Deficient Neoplasms. \u003cem\u003eJCO precision oncology\u003c/em\u003e 2024, 8:e2400406.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZetrini AE, Abbasi AZ, He C, Lip H, Alradwan I, Rauth AM, Henderson JT, Wu XY: Targeting DNA damage repair mechanism by using RAD50-silencing siRNA nanoparticles to enhance radiotherapy in triple negative breast cancer. \u003cem\u003eMaterials today Bio\u003c/em\u003e 2024, 28:101206.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLe Borgne J, Gomez L, Heikkinen S, Amin N, Ahmad S, Choi SH, Bis J, Grenier-Boley B, Rodriguez OG, Kleineidam L \u003cem\u003eet al\u003c/em\u003e: X-chromosome-wide association study for Alzheimer's disease. \u003cem\u003eMolecular psychiatry\u003c/em\u003e 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJepsen WM, Fazenbaker A, Ramsey K, Bonfitto A, Naymik M, Turner B, Sloan J, Tiwari N, Bernes SM, Neilson DE \u003cem\u003eet al\u003c/em\u003e: Duchenne Muscular Dystrophy in Two Half-Brothers Due to Inherited 306 Kb Inverted Insertion of 10p15.1 into Intron 44 of the Dp427m Transcript of the DMD Gene. \u003cem\u003eInternational journal of molecular sciences\u003c/em\u003e 2024, 25(22).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMahendran G, Breger K, McCown PJ, Hulewicz JP, Bhandari T, Addepalli B, Brown JA: Multi-Omics Approach Reveals Genes and Pathways Affected in Miller-Dieker Syndrome. \u003cem\u003eMolecular neurobiology\u003c/em\u003e 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRabin R, Hirsch Y, Booth KTA, Hall PL, Yachelevich N, Mistry PK, Ekstein J, Pappas J: ARSA Variant Associated With Late Infantile Metachromatic Leukodystrophy and Carrier Rate in Individuals of Ashkenazi Jewish Ancestry. \u003cem\u003eAmerican journal of medical genetics Part A\u003c/em\u003e 2024:e63919.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarmsen IM, Visseren FLJ, Kok M, de Jong PA, Spiering W: Arterial calcification volume is associated with a higher risk of cardiovascular events in pseudoxanthoma elasticum. \u003cem\u003eAtherosclerosis\u003c/em\u003e 2024, 400:119051.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDesai D, Maheta D, Agrawal SP, Soni Z, Frishman WH, Aronow WS: Cardiovascular Manifestations of Pseudoxanthoma Elasticum: Pathophysiology, Management, and Research. \u003cem\u003eCardiology in review\u003c/em\u003e 2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"male breast cancer, panel-based sequencing, whole-exome sequencing, BRCA1/2, PALB2","lastPublishedDoi":"10.21203/rs.3.rs-7283126/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7283126/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eThe molecular characterization of male breast cancer (MaBC) has long been understudied, primarily due to its rare occurrence. Clinical management of MaBC remains profoundly challenging, with current therapeutic strategies largely extrapolated from female breast cancer protocols.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThrough panel-based sequencing targeting BRCA1, BRCA2 and PALB2 variants, we delineated the genomic landscape of 96 MaBC cases. Subsequent whole exome sequencing (WES) of 84 BRCA1/2 and PALB2-mutation-negative MaBC patients, compared against 4,480 healthy controls, revealed compelling findings.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePathogenic variants in BRCA1/2 and PALB2 were identified in 14.6% (14/96) of MaBC cases, with BRCA2 mutations predominating at 12.5% (n\u0026thinsp;=\u0026thinsp;12). Notably, one patient harbored the BRCA1 c.4015G\u0026thinsp;\u0026gt;\u0026thinsp;T stop_gained mutation, while another exhibited the PALB2 c.481_482dupGA alteration. Our analysis further uncovered 170 pathogenic/likely-pathogenic mutations and 388 rare variants of uncertain significance (VUS), with RAD50, DMD, ARSA, and ABCC6 demonstrating notable genetic pleiotropy.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eAs the inaugural germline genomic investigation of MaBC in a Han Chinese population, this work reveals clinically actionable alterations with diagnostic and therapeutic implications. These discoveries not only advance our understanding of MaBC's molecular architecture but also underscore the critical need for dedicated research into this malignancy.\u003c/p\u003e","manuscriptTitle":"Comprehensive Genomic Profiling through Panel-based and Whole-exome Sequencing in a Population-based Chinese Han Male Breast Cancer Cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-27 06:00:03","doi":"10.21203/rs.3.rs-7283126/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":"b6694e1f-6570-4685-bf57-5abef99bb769","owner":[],"postedDate":"August 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-15T02:08:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-27 06:00:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7283126","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7283126","identity":"rs-7283126","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}