Clinical Pathological Feature Analysis and Prognostic Value Exploration of BRCA1/2 Exon11 MutationExon 11 Mutations in Patients with Gynecological Malignancies

Clinical Pathological Feature Analysis and Prognostic Value Exploration of BRCA1/2 Exon11 MutationExon 11 Mutations in Patients with Gynecological Malignancies | 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 Clinical Pathological Feature Analysis and Prognostic Value Exploration of BRCA1/2 Exon11 MutationExon 11 Mutations in Patients with Gynecological Malignancies Xiaoli Wang, Siying Zhang, Danyu Ma, Cailu Shen, Xiaosong Ge This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7887649/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 Objective To clarify the associations of BRCA1/2 mutations (especially Exon11) with clinicopathological features and prognosis in patients with gynecological malignancies and to provide references for clinical risk stratification and individualized management. Methods A retrospective analysis of 258 gynecological malignancy patients (2016–2024) with next-generation sequencing data was performed, including 67 BRCA1/2 mutation-positive cases, was performed. Yates-corrected chi-square test, Kaplan-Meiertests, Kaplan‒Meier survival analysisanalyses, and Cox proportional hazards modelmodels were used for correlation and prognostic factor screening. Results The total BRCA1/2 mutation rate was 25.97%, which was highest in double primary tumors (100%, 13/13), followed by ovarian cancer (34.57%, 28/81), and lowest in breast cancer (16.43%, 23/140). Exon11Exon 11 was the primary mutation hotspot, accounting for 55.0% (22/40) of the BRCA1 mutations and 56.7% (17/30) of the BRCA2 mutations. Exon11 mutations correlated with advanced stage (62.2% III/IV, p = 0.048) and lymph node metastasis (64.1%, p = 0.038) but not with age or T/M stage (p > 0.05). Survival analysis revealed significantly shorter median OS (57.9 vs. not reached months) and EFS (36.8 vs. 96.6 months) in the Exon11 mutation group (p = 0.0186 and p = 0.0108, respectively). Multivariate Cox regression confirmed that Exon11 mutation was an independent poor prognostic factor (HR = 6.14, 95% CI: 1.04–13.53, p = 0.02). Conclusion BRCA1/2 Exon11exon 11 mutations are frequent in gynecological malignancies and are associated with tumor progression (advanced stage, lymph node metastasis) and poor prognosis; thus, these mutations may serve as potential prognostic biomarkers. (5 10) Figures Figure 1 Figure 2 Background BRCA1 and BRCA2 (BRCA1/2) serve as core regulatory genes in the homologous recombination repair (HRR) pathway and play pivotal roles in maintaining genomic stability and suppressing abnormal cell proliferation[ 1 ]. Extensive clinical research has confirmed that germline pathogenic mutations in BRCA1/2 are key genetic drivers of hereditary breast and ovarian cancers[ 2 ]. Specifically, women carrying BRCA1 mutations face a lifetime risk of 72% for breast cancer and 44% for ovarian cancer, whereas BRCA2 mutation carriers have corresponding lifetime risks of 69% for breast cancer and 17% for ovarian cancer[ 2 ]. Additionally, recent studies have revealed an association between BRCA1/2 mutations and the development of uterine malignancies: a subset of uterine cancer patients harbor pathogenic BRCA1/2 mutations, and these patients typically exhibit more aggressive biological behaviors and poorer prognostic outcomes[ 3 ].​ Given the critical role of BRCA1/2 in the pathogenesis and progression of gynecological malignancies, BRCA1/2 gene testing has become an indispensable tool in clinical practice[ 4 ]. [ 5 – 8 ].​ Exon11Exon 11 represents a key coding region of BRCA1/2, housing multiple structural domains that regulate protein function, and is recognized as one of the major mutation hotspots in these genes[ 9 , 10 ]. However, no systematic or definitive conclusions have been reached regarding two critical aspects: (1) the distribution pattern of BRCA1/2 Exon11exon 11 mutations across three primary gynecological malignancies (breast cancer, ovarian cancer, and uterine malignancies) and (2) the associations of these mutations with clinicopathological parameters, such as patient age, clinical stage, pathological type, and lymph node metastasis.​ Thus, in-depth analysis of BRCA1/2 Exon11 mutation characteristics in breast, ovarian, and uterine malignancies—along with clarification of the associations between Exon11 mutations and patients’ clinicopathological features and prognosis—will not only supplement clinical evidence regarding the region-specific effects of BRCA1/2 mutations but also provide essential references for optimizing risk stratification, prognostic evaluation, and individualized treatment strategies for these three gynecological malignancies. This work is of great significancehighly important for enhancing the precision of clinical diagnosis and treatment in gynecological oncology. Materials and methods Study Subjects A total of 258 patients with gynecological malignancies who underwent next-generation sequencing (NGS) at the Affiliated Hospital of Jiangnan University from 2016–2024, with a median age of 52 years, were enrolled in this study. Among these patients, 140 had pure breast cancer, 81 had pure ovarian cancer, 24 had pure uterine tumors, and 13 had two types of tumors concurrently (including 7 cases of ovarian cancer combined with breast cancer and 6 cases of other combined tumor types). Moreover, the clinicopathological data of 67 patients positive for BRCA1/2 mutations, including tumor stage, age, pathological type, treatment methods, and survival time, were collected and organized. BRCA1/2 gene detection and bioinformatics analysis methods For formalin-fixed paraffin-embedded (FFPE) tumor tissue samples, after the pathology department rechecked that the tumor cell content was ≥ 20%, a sufficient number of unstained samples were sectioned, or whole blood samples were used. Genomic DNA was extracted via a dedicated extraction kit, and quality control (QC) was performed via the fluorescence quantification method (Qubit) and a fragment analyzer (Agilent TapeStation/Bioanalyzer). After the samples were subjected to QC, high-throughput sequencing was conducted on the Illumina MiSeqDx platform. The amplicon-based method was used for library construction, and the target regions covered all coding exons, exon‒intron junctions, partial promoter regions, and untranslated regions (UTRs) of BRCA1 (NM_007294.4) and BRCA2 (NM_000059.4). For sequencing depth, the minimum depth required for blood samples was ≥ 50×, and the effective depth for tissue samples was ≥ 300×. The bioinformatics analysis workflow included the following steps: alignment to the hg19/hg38 reference genome via BWA; variant calling via GATK HaplotypeCaller (v4.x); and annotation with ANNOVAR/SnpEff. Variant filtering was performed with reference to databases such as gnomAD, COSMIC, and ClinVar, and pathogenicity classification (including pathogenic [P], likely pathogenic [LP], and variant of unknown significance [VUS]) was conducted in accordance with the ACMG/AMP guidelines (2015 and subsequent updates). Finally, pathogenic/likely pathogenic mutations and clinically relevant VUSs were reported, and mutation sites were standardized according to the HGVS nomenclature. Statistical analysis methods All the statistical analyses in this study were performed via SPSS 26.0. The comparison of categorical variables was conducted via the Yates-corrected chi-square test, whereas survival analysis was implemented via the Kaplan‒Meier method and Cox proportional hazards model. GraphPad Prism (8.0) was used only for the visualization of survival curves and was not included in the calculation process. Statistical significance was set at α = 0.05 (two-tailed test). Results Analysis of the BRCA1/2 mutation positivity rate Definition of mutation positivity: Through bioinformatics analysis and literature reports, pathogenic mutations, high-risk variants of unknown significance (VUS), and suspected pathogenic mutations were defined as positive mutations, whereas benign mutations were excluded from the statistical analysis. Overall mutation status: A total of 258 gynecological cancer patients who underwent BRCA1/2 mutation testing were included in this study. Among them, 191 patients had negative test results, and 67 had positive results, resulting in an overall BRCA1/2 mutation positivity rate of 25.97% (67/258) (Fig. 1A). Age comparison between mutation-positive and mutation-negative patients: Among the 258 patients, the median age of those with BRCA1/2 mutations was 52 years, whereas that of mutation-negative patients was 50 years. Distribution of BRCA1 and BRCA2 mutations: Among the 67 mutation-positive patients, 40 had BRCA1 mutations, and 30 had BRCA2 mutations. Notably, 3 patients had concurrent BRCA1/2 double mutations (Fig. 1B). BRCA1/2 mutation positivity rates across different tumor types: Pure ovarian cancer: A total of 81 patients, with 28 testing positive for BRCA1/2 mutations, resulting in a positivity rate of 34.57% (28/81). Pure breast cancer: A total of 140 patients, with 23 testing positive for BRCA1/2 mutations, were included, resulting in a positivity rate of 16.43% (23/140). Uterine and fallopian tube malignant tumors: A total of 24 patients, with 6 testing positive for BRCA1/2 mutations, were included, resulting in a positivity rate of 25% (6/24). Double primary tumors: A total of 13 patients, 13 of whom tested positive for BRCA1/2 mutations, resulted in a positivity rate of 100% (13/13). Analysis of BRCA1/2 mutation hotspots Among all mutation types, frameshift mutations accounted for the highest proportion (50.0%, 35/70), making them the most common mutation type. This was followed by missense mutations (20.0%, 14/70) and nonsense mutations (17.1%, 12/70). Splice site mutations accounted for 8.6% (6/70), whereas large fragment deletions accounted for the lowest proportion (4.3%, 3/70) (Fig. 1C). In terms of the genomic locations of the mutations, exon 11 was identified as a mutation hotspot, with 39 mutations detected, accounting for 55.7% of all mutations (39/70) (Fig. 1D). Specifically, there were 22 mutations in the BRCA1 gene (accounting for 55.0% of total BRCA1 mutations, 22/40) and 17 mutations in the BRCA2 gene (accounting for 56.7% of total BRCA2 mutations, 17/30). Importantly, in the 3 patients with concurrent BRCA1/2 mutations, no simultaneous mutations in exon 11 of either gene were observed. The nonexon 11 mutation group included 31 patients, accounting for 44.3% of all mutations (31/70). This group consisted of 24 mutations in other exons (34.3%, 24/70) and 7 intronic splice site mutations (10%, 7/70). Baseline balance testing between the two groups (Exon 11 mutation vs. nonexon 11 mutation) revealed no significant differences in age (median 54 years vs. 52 years, p = 0.32) or tumor type (similar proportions of ovarian cancer/breast cancer, p = 0.47). Correlation between Exon 11 mutation status and clinicopathological data In this study, clinicopathological parameters were compared between the Exon 11 mutation group and the non-Exon 11 mutation group to analyze their correlation. The chi-square test results (Table 1 ) revealed that Exon 11 mutations were not significantly associated with age at onset (p = 0.081), T stage (p = 0.47), or M stage (p = 0.808). However, significant associations were observed with clinical stage (p = 0.048) and lymph node metastasis status (p = 0.038). Among patients with early-stage tumors (stage I/II), those with exon 11 mutations accounted for only 28% (7/25), whereas those with nonexon 11 mutations accounted for 72% (18/25), indicating a lower incidence of exon 11 mutations in early-stage patients. In contrast, among patients with advanced-stage tumors (stage III/IV), those with exon 11 mutations accounted for 52.4% (22/42), whereas those with nonexon 11 mutations accounted for only 47.6% (20/42), suggesting a significantly greater incidence of exon 11 mutations in advanced-stage patients. Table 1 Correlation between BRCA exon11 mutation and clinicopathological characteristics Characteristics Cases BRCA1/2 mutation P value Exon11 Non-Exon 11 Age (median = 52) 0.081 < 52 29 13 16 ≥ 52 38 25 13 T status 0.130 T1-2 37 13 24 T3-4 30 16 14 N status 0.038* N0 34 11 23 N+ 33 18 15 M stage 0.808 M0 54 30 24 M1 13 8 5 Clinical Stages 0.048* I/II 25 7 18 III/IV 42 22 20 ∗ P < 0.05 Correlation between Exon 11 mutations and patient prognosis The follow-up period ranged from 6 to 219 months. K‒M survival analysis revealed a significant difference in survival between the Exon 11 mutation group and the non-Exon 11 mutation group. For overall survival (OS), the Exon 11 mutation group had poorer survival outcomes, with a median OS of 57.9 months, whereas the median OS of the nonexon 11 mutation group was not reached, indicating a higher survival rate in the nonexon 11 mutation group (Fig. 2A, P = 0.0186). Additionally, event-free survival (EFS) was analyzed. The results revealed that the median EFS of the Exon 11 mutation group was 36.8 months, whereas that of the nonexon 11 mutation group was 96.6 months, with a significant difference between the two groups (Fig. 2B, P = 0.0108). Cox multivariate regression analysis, after adjusting for age, T stage, lymph node metastasis, and distant metastasis, revealed that Exon 11 mutation remained an independent prognostic factor (HR = 6.14, 95% CI 1.04–13.53; p = 0.02). However, distant metastasis had a stronger impact (HR = 8.16, p = 0.009) (Table 2 , Fig. 3). Table 2 Univariate and multivariate analysis for overall survival (Cox proportional hazards regression model) Risk factors Univariate Mutivariate HR P value 95% CI HR P value 95% CI Exon 11 (WT/MT) 3.76 0.04* 1.04–13.53 6.14 0.02* 1.30- 28.85 Age (<52/≥52) 1.01 0.66 0.96–1.06 0.97 0.54 0.91–1.04 T (T1-2/T3-4) 1.29 0.37 0.73–2.30 0.78 0.48 0.40–1.54 N (N0/N+) 1.37 0.30 0.74–2.52 1.35 0.43 0.62–2.94 M (M0/M1) 4.10 0.024* 1.20–14.00 8.16 0.009* 1.66–39.91 HR; Hazard ratio, * P <0.05, Discussion​ This study analyzed the BRCA1/2 mutation status in 258 patients with gynecological cancer, focusing on the associations among Exon 11 mutations, clinicopathological features, and patient prognosis. The key findings are discussed below in the context of existing research.​ The overall BRCA1/2 mutation rate was 25.9% (67/258). Ovarian cancer patients had a higher mutation rate (34.6%) than did breast cancer patients (16.4%), and all patients with double primary tumors (13 patients) were mutation positive (100%). Consistent with the finding that the percentage of ovarian cancer patients with a BRCA1/2 mutation was 39% and 11%, respectively[ 11 ], our 100% mutation rate in double primary tumors further confirms that BRCA1/2 mutations are drivers of the development of multiple cancers[ 12 ]. This highlights the need for early genetic testing in such patients to guide family risk management.​ Among the mutation types, frameshift and missense mutations accounted for 70% of all mutations (Fig. 2C). Frameshift mutations disrupt the gene reading frame, causing premature protein termination or truncated proteins that impair functions such as DNA damage repair and cell cycle regulation; missense mutations alter amino acids, also affecting protein function[ 13 , 14 ]. Notably, Exon 11 was a hotspot, accounting for 55% of the BRCA1 mutations and 56.7% of the BRCA2 mutations. This is functionally relevant: BRCA1 Exon 11 encodes the domain that recruits downstream proteins for DNA repair, whereas BRCA2 Exon 11 contains RAD51-binding motifs critical for homologous recombination repair[ 15 ].​ In terms of exon 11 mutation and tumor progression, the exon 11 mutation group was more likely to have advanced disease, lymph node metastasis, and a poorer prognosis. Functionally, Exon 11 mutations abolish the homologous recombination repair capacity of BRCA1/2, increasing genomic instability and accelerating tumor invasion/metastasis[ 16 – 18 ]. Multivariate analysis confirmed that Exon 11 mutation was an independent prognostic factor (HR = 6.14, P = 0.02), indicating that it can complement traditional indicators (clinical stage, lymph node status) to refine prognostic assessment and guide follow-up plans.​ This study has several limitations. First, the mutation-positive sample size was small (67 patients), especially the PARP inhibitor (PARPi)-treated subgroup (21 patients), reducing the statistical power and precluding analysis of the correlation of Exon 11 mutation with PARPi efficacy. Larger, multicenter studies are needed for validation. Second, we did not distinguish between BRCA1 and BRCA2 Exon 11 mutations, despite Kuchenbaecker et al .’s suggestion that BRCA1 mutations may worsen prognosis—an area for further research[ 2 ]. Third, we did not analyze other homologous recombination repair genes (e.g., PALB2 and RAD51C), whose mutations may synergize with BRCA1/2 mutations to affect prognosis[ 19 ].​ Despite these limitations, our findings offer clinical value: BRCA1/2 Exon 11 mutations are useful biomarkers for evaluating gynecological cancer progression and prognosis. For patients with Exon 11 mutations, enhanced monitoring for lymph node/distant metastasis is recommended; genetic testing should prioritize the Exon 11 region to ensure accurate detection of high-frequency mutations (e.g., frameshift, missense). In summary, detailed analysis of BRCA1/2 Exon 11 mutations helps optimize individualized gynecological cancer management. Abbreviations OS Overall survival EFS Event-free survival BRCA1 Breast Cancer 1 Susceptibility Protein 1 BRCA2 Breast Cancer 1 Susceptibility Protein 2 HRR homologous recombination repair Declarations Acknowledgments Not applicable. Funding This work was supported by the Youth Fund of the National Natural Science Foundation of China (Grant No. 81502042), the Natural Science Foundation for Young Scholars of Jiangsu Province, China (Grant No. BK20140171), and the Guiding Project of Jiangsu Provincial Health Commission (Z2023020). Availability of data and materials The datasets generated and/or analyzed in the current study are available from the corresponding author upon reasonable request. Author Contributions Conceptualization: Di Shen, Xiaoli Wang Data curation: Xiaoli Wang, Cailu Shen, and Danyu Ma Formal analysis: Xiaosong Ge, Siying Zhang Investigation: Xiaosong Ge Methodology: Xiaoli Wang Project administration: Xiaosong Ge Resources: Xiaosong Ge Writing – original draft: Xiaoli Wang, Siying Zhang Writing – review and editing: All authors All the authors have read and approved the final manuscript. Ethics approval of human participants In line with the World Medical Association Declaration of Helsinki and Chinese regulations, written informed consent was waived—this study used existing deidentified data without patient intervention or privacy risks. The study was approved by the Ethics Committee of the Affiliated Hospital of Jiangnan University (Ethics Approval No: LS2025338). All procedures adhered to ethical standards and national laws. Patient consent for publication Not applicable. Competing Interests The authors declare that they have no competing interests. Use of artificial intelligence tools We used artificial intelligence tools for language editing and proofreading during the preparation of this manuscript. References Lim J, Ju YS. Leveraging Whole-Exome Sequencing and Mutational Signatures to Detect Homologous Recombination Deficiency in Cancer. Cancer Res. 2025;85(13):2348–50. Kuchenbaecker KB, Hopper JL, Barnes DR, Phillips KA, Mooij TM, Roos-Blom MJ, Jervis S, van Leeuwen FE, Milne RL, Andrieu N, et al. Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers. JAMA. 2017;317(23):2402–16. de Jonge MM, de Kroon CD, Jenner DJ, Oosting J, de Hullu JA, Mourits MJE, Gomez Garcia EB, Ausems M, Margriet Collee J, van Engelen K, et al. 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08:36:09","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78669,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7887649/v1/7c36487ebd47827e5a512cc6.html"},{"id":96800367,"identity":"05c11f9c-4b9d-4f64-ba66-76c014f7e734","added_by":"auto","created_at":"2025-11-26 08:36:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":297647,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7887649/v1/7cc63a1f7a19c7e923202de4.png"},{"id":96800368,"identity":"b2409ce6-2709-46fc-a359-6c71a0448dda","added_by":"auto","created_at":"2025-11-26 08:36:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":63338,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7887649/v1/839ddd30445825984f8e804a.png"},{"id":97669433,"identity":"accaa8f5-37f4-4f0d-b607-d3258776adb5","added_by":"auto","created_at":"2025-12-08 09:27:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":864961,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7887649/v1/4f4c47f9-27d7-45a1-98ba-6b7c30442faf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Pathological Feature Analysis and Prognostic Value Exploration of BRCA1/2 Exon11 MutationExon 11 Mutations in Patients with Gynecological Malignancies","fulltext":[{"header":"Background","content":"\u003cp\u003eBRCA1 and BRCA2 (BRCA1/2) serve as core regulatory genes in the homologous recombination repair (HRR) pathway and play pivotal roles in maintaining genomic stability and suppressing abnormal cell proliferation[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Extensive clinical research has confirmed that germline pathogenic mutations in BRCA1/2 are key genetic drivers of hereditary breast and ovarian cancers[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Specifically, women carrying BRCA1 mutations face a lifetime risk of 72% for breast cancer and 44% for ovarian cancer, whereas BRCA2 mutation carriers have corresponding lifetime risks of 69% for breast cancer and 17% for ovarian cancer[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Additionally, recent studies have revealed an association between BRCA1/2 mutations and the development of uterine malignancies: a subset of uterine cancer patients harbor pathogenic BRCA1/2 mutations, and these patients typically exhibit more aggressive biological behaviors and poorer prognostic outcomes[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].​\u003c/p\u003e\u003cp\u003eGiven the critical role of BRCA1/2 in the pathogenesis and progression of gynecological malignancies, BRCA1/2 gene testing has become an indispensable tool in clinical practice[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].​\u003c/p\u003e\u003cp\u003eExon11Exon 11 represents a key coding region of BRCA1/2, housing multiple structural domains that regulate protein function, and is recognized as one of the major mutation hotspots in these genes[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, no systematic or definitive conclusions have been reached regarding two critical aspects: (1) the distribution pattern of BRCA1/2 Exon11exon 11 mutations across three primary gynecological malignancies (breast cancer, ovarian cancer, and uterine malignancies) and (2) the associations of these mutations with clinicopathological parameters, such as patient age, clinical stage, pathological type, and lymph node metastasis.​\u003c/p\u003e\u003cp\u003eThus, in-depth analysis of BRCA1/2 Exon11 mutation characteristics in breast, ovarian, and uterine malignancies\u0026mdash;along with clarification of the associations between Exon11 mutations and patients\u0026rsquo; clinicopathological features and prognosis\u0026mdash;will not only supplement clinical evidence regarding the region-specific effects of BRCA1/2 mutations but also provide essential references for optimizing risk stratification, prognostic evaluation, and individualized treatment strategies for these three gynecological malignancies. This work is of great significancehighly important for enhancing the precision of clinical diagnosis and treatment in gynecological oncology.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eStudy Subjects\u003c/p\u003e\u003cp\u003eA total of 258 patients with gynecological malignancies who underwent next-generation sequencing (NGS) at the Affiliated Hospital of Jiangnan University from 2016\u0026ndash;2024, with a median age of 52 years, were enrolled in this study. Among these patients, 140 had pure breast cancer, 81 had pure ovarian cancer, 24 had pure uterine tumors, and 13 had two types of tumors concurrently (including 7 cases of ovarian cancer combined with breast cancer and 6 cases of other combined tumor types). Moreover, the clinicopathological data of 67 patients positive for BRCA1/2 mutations, including tumor stage, age, pathological type, treatment methods, and survival time, were collected and organized.\u003c/p\u003e\u003cp\u003eBRCA1/2 gene detection and bioinformatics analysis methods\u003c/p\u003e\u003cp\u003eFor formalin-fixed paraffin-embedded (FFPE) tumor tissue samples, after the pathology department rechecked that the tumor cell content was \u0026ge;\u0026thinsp;20%, a sufficient number of unstained samples were sectioned, or whole blood samples were used. Genomic DNA was extracted via a dedicated extraction kit, and quality control (QC) was performed via the fluorescence quantification method (Qubit) and a fragment analyzer (Agilent TapeStation/Bioanalyzer). After the samples were subjected to QC, high-throughput sequencing was conducted on the Illumina MiSeqDx platform. The amplicon-based method was used for library construction, and the target regions covered all coding exons, exon‒intron junctions, partial promoter regions, and untranslated regions (UTRs) of BRCA1 (NM_007294.4) and BRCA2 (NM_000059.4). For sequencing depth, the minimum depth required for blood samples was \u0026ge;\u0026thinsp;50\u0026times;, and the effective depth for tissue samples was \u0026ge;\u0026thinsp;300\u0026times;. The bioinformatics analysis workflow included the following steps: alignment to the hg19/hg38 reference genome via BWA; variant calling via GATK HaplotypeCaller (v4.x); and annotation with ANNOVAR/SnpEff. Variant filtering was performed with reference to databases such as gnomAD, COSMIC, and ClinVar, and pathogenicity classification (including pathogenic [P], likely pathogenic [LP], and variant of unknown significance [VUS]) was conducted in accordance with the ACMG/AMP guidelines (2015 and subsequent updates). Finally, pathogenic/likely pathogenic mutations and clinically relevant VUSs were reported, and mutation sites were standardized according to the HGVS nomenclature.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis methods\u003c/h2\u003e\u003cp\u003eAll the statistical analyses in this study were performed via SPSS 26.0. The comparison of categorical variables was conducted via the Yates-corrected chi-square test, whereas survival analysis was implemented via the Kaplan‒Meier method and Cox proportional hazards model. GraphPad Prism (8.0) was used only for the visualization of survival curves and was not included in the calculation process. Statistical significance was set at α\u0026thinsp;=\u0026thinsp;0.05 (two-tailed test).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAnalysis of the BRCA1/2 mutation positivity rate\u003c/p\u003e\u003cp\u003eDefinition of mutation positivity: Through bioinformatics analysis and literature reports, pathogenic mutations, high-risk variants of unknown significance (VUS), and suspected pathogenic mutations were defined as positive mutations, whereas benign mutations were excluded from the statistical analysis. Overall mutation status: A total of 258 gynecological cancer patients who underwent BRCA1/2 mutation testing were included in this study. Among them, 191 patients had negative test results, and 67 had positive results, resulting in an overall BRCA1/2 mutation positivity rate of 25.97% (67/258) (Fig.\u0026nbsp;1A). Age comparison between mutation-positive and mutation-negative patients: Among the 258 patients, the median age of those with BRCA1/2 mutations was 52 years, whereas that of mutation-negative patients was 50 years. Distribution of BRCA1 and BRCA2 mutations: Among the 67 mutation-positive patients, 40 had BRCA1 mutations, and 30 had BRCA2 mutations. Notably, 3 patients had concurrent BRCA1/2 double mutations (Fig.\u0026nbsp;1B). BRCA1/2 mutation positivity rates across different tumor types: Pure ovarian cancer: A total of 81 patients, with 28 testing positive for BRCA1/2 mutations, resulting in a positivity rate of 34.57% (28/81). Pure breast cancer: A total of 140 patients, with 23 testing positive for BRCA1/2 mutations, were included, resulting in a positivity rate of 16.43% (23/140). Uterine and fallopian tube malignant tumors: A total of 24 patients, with 6 testing positive for BRCA1/2 mutations, were included, resulting in a positivity rate of 25% (6/24). Double primary tumors: A total of 13 patients, 13 of whom tested positive for BRCA1/2 mutations, resulted in a positivity rate of 100% (13/13).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnalysis of BRCA1/2 mutation hotspots\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong all mutation types, frameshift mutations accounted for the highest proportion (50.0%, 35/70), making them the most common mutation type. This was followed by missense mutations (20.0%, 14/70) and nonsense mutations (17.1%, 12/70). Splice site mutations accounted for 8.6% (6/70), whereas large fragment deletions accounted for the lowest proportion (4.3%, 3/70) (Fig.\u0026nbsp;1C). In terms of the genomic locations of the mutations, exon 11 was identified as a mutation hotspot, with 39 mutations detected, accounting for 55.7% of all mutations (39/70) (Fig.\u0026nbsp;1D). Specifically, there were 22 mutations in the BRCA1 gene (accounting for 55.0% of total BRCA1 mutations, 22/40) and 17 mutations in the BRCA2 gene (accounting for 56.7% of total BRCA2 mutations, 17/30). Importantly, in the 3 patients with concurrent BRCA1/2 mutations, no simultaneous mutations in exon 11 of either gene were observed. The nonexon 11 mutation group included 31 patients, accounting for 44.3% of all mutations (31/70). This group consisted of 24 mutations in other exons (34.3%, 24/70) and 7 intronic splice site mutations (10%, 7/70). Baseline balance testing between the two groups (Exon 11 mutation vs. nonexon 11 mutation) revealed no significant differences in age (median 54 years vs. 52 years, p\u0026thinsp;=\u0026thinsp;0.32) or tumor type (similar proportions of ovarian cancer/breast cancer, p\u0026thinsp;=\u0026thinsp;0.47).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCorrelation between Exon 11 mutation status and clinicopathological data\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn this study, clinicopathological parameters were compared between the Exon 11 mutation group and the non-Exon 11 mutation group to analyze their correlation. The chi-square test results (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed that Exon 11 mutations were not significantly associated with age at onset (p\u0026thinsp;=\u0026thinsp;0.081), T stage (p\u0026thinsp;=\u0026thinsp;0.47), or M stage (p\u0026thinsp;=\u0026thinsp;0.808). However, significant associations were observed with clinical stage (p\u0026thinsp;=\u0026thinsp;0.048) and lymph node metastasis status (p\u0026thinsp;=\u0026thinsp;0.038). Among patients with early-stage tumors (stage I/II), those with exon 11 mutations accounted for only 28% (7/25), whereas those with nonexon 11 mutations accounted for 72% (18/25), indicating a lower incidence of exon 11 mutations in early-stage patients. In contrast, among patients with advanced-stage tumors (stage III/IV), those with exon 11 mutations accounted for 52.4% (22/42), whereas those with nonexon 11 mutations accounted for only 47.6% (20/42), suggesting a significantly greater incidence of exon 11 mutations in advanced-stage patients.\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\u003eCorrelation between BRCA exon11 mutation and clinicopathological characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eBRCA1/2 mutation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExon11\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-Exon 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colname=\"c5\"\u003e\u003cp\u003e0.130\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT1-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT3-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.038*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.808\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical Stages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.048*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI/II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIII/IV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026lowast;\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCorrelation between Exon 11 mutations and patient prognosis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe follow-up period ranged from 6 to 219 months. K‒M survival analysis revealed a significant difference in survival between the Exon 11 mutation group and the non-Exon 11 mutation group. For overall survival (OS), the Exon 11 mutation group had poorer survival outcomes, with a median OS of 57.9 months, whereas the median OS of the nonexon 11 mutation group was not reached, indicating a higher survival rate in the nonexon 11 mutation group (Fig.\u0026nbsp;2A, P\u0026thinsp;=\u0026thinsp;0.0186).\u003c/p\u003e\u003cp\u003eAdditionally, event-free survival (EFS) was analyzed. The results revealed that the median EFS of the Exon 11 mutation group was 36.8 months, whereas that of the nonexon 11 mutation group was 96.6 months, with a significant difference between the two groups (Fig.\u0026nbsp;2B, P\u0026thinsp;=\u0026thinsp;0.0108). Cox multivariate regression analysis, after adjusting for age, T stage, lymph node metastasis, and distant metastasis, revealed that Exon 11 mutation remained an independent prognostic factor (HR\u0026thinsp;=\u0026thinsp;6.14, 95% CI 1.04\u0026ndash;13.53; p\u0026thinsp;=\u0026thinsp;0.02). However, distant metastasis had a stronger impact (HR\u0026thinsp;=\u0026thinsp;8.16, p\u0026thinsp;=\u0026thinsp;0.009) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;3).\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\u003e Univariate and multivariate analysis for overall survival (Cox proportional hazards regression model)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRisk factors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eUnivariate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eMutivariate\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExon 11 (WT/MT)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.04\u0026ndash;13.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e6.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.02*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.30- 28.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (\u0026lt;52/\u0026ge;52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.96\u0026ndash;1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.91\u0026ndash;1.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT (T1-2/T3-4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.73\u0026ndash;2.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.40\u0026ndash;1.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN (N0/N+)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.74\u0026ndash;2.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.62\u0026ndash;2.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM (M0/M1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.024*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.20\u0026ndash;14.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e8.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.009*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.66\u0026ndash;39.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eHR; Hazard ratio, * \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion​","content":"\u003cp\u003eThis study analyzed the BRCA1/2 mutation status in 258 patients with gynecological cancer, focusing on the associations among Exon 11 mutations, clinicopathological features, and patient prognosis. The key findings are discussed below in the context of existing research.​\u003c/p\u003e\u003cp\u003eThe overall BRCA1/2 mutation rate was 25.9% (67/258). Ovarian cancer patients had a higher mutation rate (34.6%) than did breast cancer patients (16.4%), and all patients with double primary tumors (13 patients) were mutation positive (100%). Consistent with the finding that the percentage of ovarian cancer patients with a BRCA1/2 mutation was 39% and 11%, respectively[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], our 100% mutation rate in double primary tumors further confirms that BRCA1/2 mutations are drivers of the development of multiple cancers[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This highlights the need for early genetic testing in such patients to guide family risk management.​\u003c/p\u003e\u003cp\u003eAmong the mutation types, frameshift and missense mutations accounted for 70% of all mutations (Fig.\u0026nbsp;2C). Frameshift mutations disrupt the gene reading frame, causing premature protein termination or truncated proteins that impair functions such as DNA damage repair and cell cycle regulation; missense mutations alter amino acids, also affecting protein function[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Notably, Exon 11 was a hotspot, accounting for 55% of the BRCA1 mutations and 56.7% of the BRCA2 mutations. This is functionally relevant: BRCA1 Exon 11 encodes the domain that recruits downstream proteins for DNA repair, whereas BRCA2 Exon 11 contains RAD51-binding motifs critical for homologous recombination repair[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].​\u003c/p\u003e\u003cp\u003eIn terms of exon 11 mutation and tumor progression, the exon 11 mutation group was more likely to have advanced disease, lymph node metastasis, and a poorer prognosis. Functionally, Exon 11 mutations abolish the homologous recombination repair capacity of BRCA1/2, increasing genomic instability and accelerating tumor invasion/metastasis[\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Multivariate analysis confirmed that Exon 11 mutation was an independent prognostic factor (HR\u0026thinsp;=\u0026thinsp;6.14, P\u0026thinsp;=\u0026thinsp;0.02), indicating that it can complement traditional indicators (clinical stage, lymph node status) to refine prognostic assessment and guide follow-up plans.​\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, the mutation-positive sample size was small (67 patients), especially the PARP inhibitor (PARPi)-treated subgroup (21 patients), reducing the statistical power and precluding analysis of the correlation of Exon 11 mutation with PARPi efficacy. Larger, multicenter studies are needed for validation. Second, we did not distinguish between BRCA1 and BRCA2 Exon 11 mutations, despite Kuchenbaecker \u003cem\u003eet al\u003c/em\u003e.\u0026rsquo;s suggestion that BRCA1 mutations may worsen prognosis\u0026mdash;an area for further research[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Third, we did not analyze other homologous recombination repair genes (e.g., PALB2 and RAD51C), whose mutations may synergize with BRCA1/2 mutations to affect prognosis[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].​\u003c/p\u003e\u003cp\u003eDespite these limitations, our findings offer clinical value: BRCA1/2 Exon 11 mutations are useful biomarkers for evaluating gynecological cancer progression and prognosis. For patients with Exon 11 mutations, enhanced monitoring for lymph node/distant metastasis is recommended; genetic testing should prioritize the Exon 11 region to ensure accurate detection of high-frequency mutations (e.g., frameshift, missense). In summary, detailed analysis of BRCA1/2 Exon 11 mutations helps optimize individualized gynecological cancer management.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOverall survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEFS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEvent-free survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBRCA1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBreast Cancer 1 Susceptibility Protein 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBRCA2\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBreast Cancer 1 Susceptibility Protein 2\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHRR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehomologous recombination repair\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003eAcknowledgments\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis work was supported by the Youth Fund of the National Natural Science Foundation of China (Grant No. 81502042), the Natural Science Foundation for Young Scholars of Jiangsu Province, China (Grant No. BK20140171), and the Guiding Project of Jiangsu Provincial Health Commission (Z2023020).\u003c/p\u003e\n\u003ch3\u003eAvailability of data and materials\u003c/h3\u003e\n\u003cp\u003eThe datasets generated and/or analyzed in the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch3\u003eAuthor Contributions\u003c/h3\u003e\n\u003cp\u003eConceptualization: Di Shen, Xiaoli Wang\u003c/p\u003e\n\u003cp\u003eData curation: Xiaoli Wang, Cailu Shen, and Danyu Ma\u003c/p\u003e\n\u003cp\u003eFormal analysis: Xiaosong Ge, Siying Zhang\u003c/p\u003e\n\u003cp\u003eInvestigation: Xiaosong Ge\u003c/p\u003e\n\u003cp\u003eMethodology: Xiaoli Wang\u003c/p\u003e\n\u003cp\u003eProject administration: Xiaosong Ge\u003c/p\u003e\n\u003cp\u003eResources: Xiaosong Ge\u003c/p\u003e\n\u003cp\u003eWriting – original draft: Xiaoli Wang, Siying Zhang\u003c/p\u003e\n\u003cp\u003eWriting – review and editing: All authors\u003c/p\u003e\n\u003cp\u003eAll the authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval of human participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn line with the World Medical Association Declaration of Helsinki and Chinese regulations, written informed consent was waived—this study used existing deidentified data without patient intervention or privacy risks. The study was approved by the Ethics Committee of the Affiliated Hospital of Jiangnan University (Ethics Approval No: LS2025338). All procedures adhered to ethical standards and national laws.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch3\u003eCompeting Interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch3\u003eUse of artificial intelligence tools\u003c/h3\u003e\n\u003cp\u003eWe used artificial intelligence tools for language editing and proofreading during the preparation of this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLim J, Ju YS. Leveraging Whole-Exome Sequencing and Mutational Signatures to Detect Homologous Recombination Deficiency in Cancer. Cancer Res. 2025;85(13):2348\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKuchenbaecker KB, Hopper JL, Barnes DR, Phillips KA, Mooij TM, Roos-Blom MJ, Jervis S, van Leeuwen FE, Milne RL, Andrieu N, et al. Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers. JAMA. 2017;317(23):2402\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Jonge MM, de Kroon CD, Jenner DJ, Oosting J, de Hullu JA, Mourits MJE, Gomez Garcia EB, Ausems M, Margriet Collee J, van Engelen K, et al. Endometrial Cancer Risk in Women With Germline BRCA1 or BRCA2 Mutations: Multicenter Cohort Study. J Natl Cancer Inst. 2021;113(9):1203\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDitsch N, Aktas B, Banys-Paluchowski M, Speiser D, Golas MM, Fasching PA. Preventive Measures for Patients With an Elevated Genetic Risk for Gynecological Malignancies, in Particular Familial Breast and Ovarian Cancer. Deutsches Arzteblatt Int 2025(Forthcoming).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAhmad H, Ali A, Ali R, Khalil AT, Khan I, Khan MM, Alorini M. Preliminary insights on the mutational spectrum of BRCA1 and BRCA2 genes in Pakhtun ethnicity breast cancer patients from Khyber Pakhtunkhwa (KP), Pakistan. Neoplasia (New York NY). 2024;51:100989.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJimenez-Sainz J, Mathew J, Moore G, Lahiri S, Garbarino J, Eder JP, Rothenberg E, Jensen RB. BRCA2 BRC missense variants disrupt RAD51-dependent DNA repair. eLife 2022, 11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYue W, Li X, Zhan X, Wang L, Ma J, Bi M, Wang Q, Gu X, Xie B, Liu T, et al. PARP inhibitors suppress tumors via centrosome error-induced senescence independent of DNA damage response. EBioMedicine. 2024;103:105129.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu Y, Wang Y, Shen Z, Shen L, Liu H, Xiang L, Huang X, Gou W, Wang M, Zang R et al. gBRCA1 and gBRCA2 mutations in specific different domains affect ovarian cancer prognosis: A multicenter retrospective study. Chin Med J 2025.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim JH, Yoon HJ, Ha HI, Kim ET, Kim DE, Kim S, Bae JK, Lim MC. Survival Outcomes Associated with the Location of BRCA Mutations in Ovarian Cancer: A Systematic Review and Meta-Analysis. Cancers 2025, 17(10).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhan S, Burney IA, Nasir M, Saleem H, Irfan M, Shakeel M, Khan IA. Spectrum of BRCA1/2 pathogenic variants in Southern and Western Asia-a systematic review. Mutat Res Reviews Mutat Res. 2025;796:108549.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNeff RT, Senter L, Salani R. BRCA mutation in ovarian cancer: testing, implications and treatment considerations. Therapeutic Adv Med Oncol 2017, 9(8):519\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi S, Silvestri V, Leslie G, Rebbeck TR, Neuhausen SL, Hopper JL, Nielsen HR, Lee A, Yang X, McGuffog L, et al. Cancer Risks Associated With BRCA1 and BRCA2 Pathogenic Variants. J Clin oncology: official J Am Soc Clin Oncol. 2022;40(14):1529\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi Y, Xu G, Zhang L, Zhao K, Zhao Y, Han D. Multiple drug resistance caused by germline mutation of exon 27 of BRCA2 gene in triple-negative breast cancer: a case report and literature review. Front Oncol. 2025;15:1602870.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRechsteiner M, Dedes K, Fink D, Pestalozzi B, Sobottka B, Moch H, Wild P, Varga Z. Somatic BRCA1 mutations in clinically sporadic breast cancer with medullary histological features. J Cancer Res Clin Oncol. 2018;144(5):865\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoy R, Chun J, Powell SN. BRCA1 and BRCA2: different roles in a common pathway of genome protection. Nat Rev Cancer. 2011;12(1):68\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLe Page C, Amuzu S, Rahimi K, Gotlieb W, Ragoussis J, Tonin PN. Lessons learned from understanding chemotherapy resistance in epithelial tubo-ovarian carcinoma from BRCA1and BRCA2mutation carriers. Sem Cancer Biol. 2021;77:110\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSaito R, Kuroda T, Yoshida H, Sudo K, Saito M, Tanabe H, Takano H, Yamada K, Kiyokawa T, Yonemori K, et al. Genetic characteristics of platinum-sensitive ovarian clear cell carcinoma. Jpn J Clin Oncol. 2023;53(9):781\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNesic K, Krais JJ, Wang Y, Vandenberg CJ, Patel P, Cai KQ, Kwan T, Lieschke E, Ho GY, Barker HE, et al. BRCA1 secondary splice-site mutations drive exon-skipping and PARP inhibitor resistance. Mol Cancer. 2024;23(1):158.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNepomuceno TC, De Gregoriis G, de Oliveira FMB, Suarez-Kurtz G, Monteiro AN, Carvalho MA. The Role of PALB2 in the DNA Damage Response and Cancer Predisposition. Int J Mol Sci 2017, 18(9).\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":"(5, 10)","lastPublishedDoi":"10.21203/rs.3.rs-7887649/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7887649/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo clarify the associations of BRCA1/2 mutations (especially Exon11) with clinicopathological features and prognosis in patients with gynecological malignancies and to provide references for clinical risk stratification and individualized management.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA retrospective analysis of 258 gynecological malignancy patients (2016\u0026ndash;2024) with next-generation sequencing data was performed, including 67 BRCA1/2 mutation-positive cases, was performed. Yates-corrected chi-square test, Kaplan-Meiertests, Kaplan‒Meier survival analysisanalyses, and Cox proportional hazards modelmodels were used for correlation and prognostic factor screening.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe total BRCA1/2 mutation rate was 25.97%, which was highest in double primary tumors (100%, 13/13), followed by ovarian cancer (34.57%, 28/81), and lowest in breast cancer (16.43%, 23/140). Exon11Exon 11 was the primary mutation hotspot, accounting for 55.0% (22/40) of the BRCA1 mutations and 56.7% (17/30) of the BRCA2 mutations. Exon11 mutations correlated with advanced stage (62.2% III/IV, p\u0026thinsp;=\u0026thinsp;0.048) and lymph node metastasis (64.1%, p\u0026thinsp;=\u0026thinsp;0.038) but not with age or T/M stage (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Survival analysis revealed significantly shorter median OS (57.9 vs. not reached months) and EFS (36.8 vs. 96.6 months) in the Exon11 mutation group (p\u0026thinsp;=\u0026thinsp;0.0186 and p\u0026thinsp;=\u0026thinsp;0.0108, respectively). Multivariate Cox regression confirmed that Exon11 mutation was an independent poor prognostic factor (HR\u0026thinsp;=\u0026thinsp;6.14, 95% CI: 1.04\u0026ndash;13.53, p\u0026thinsp;=\u0026thinsp;0.02).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eBRCA1/2 Exon11exon 11 mutations are frequent in gynecological malignancies and are associated with tumor progression (advanced stage, lymph node metastasis) and poor prognosis; thus, these mutations may serve as potential prognostic biomarkers.\u003c/p\u003e","manuscriptTitle":"Clinical Pathological Feature Analysis and Prognostic Value Exploration of BRCA1/2 Exon11 MutationExon 11 Mutations in Patients with Gynecological Malignancies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 08:36:04","doi":"10.21203/rs.3.rs-7887649/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":"93b050b2-ebae-4b76-a5f3-fc3564e691a5","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-05T01:23:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-26 08:36:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7887649","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7887649","identity":"rs-7887649","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}