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Background <p>Germline mutations in cancer-predisposition genes are critical for clinical risk assessment and therapeutic decisions in breast cancer, yet large-scale genomic studies and population-specific tools remain limited for Asian populations.</p> Methods <p>In this prospective clinic-based cohort study, 2700 unselected Chinese breast cancer patients underwent germline sequencing for single nucleotide variations, insertion/deletions, and large genomic rearrangements using a clinically validated 32-gene panel. Multiplex ligation-dependent probe amplification was used for confirmation of copy number variations. A multivariate logistic regression model (PEEKABOO) was developed to predict mutation probability. Therapeutic impact was assessed in 632 patients receiving neoadjuvant therapy.</p> Results <p>The overall prevalence of deleterious germline variants was 11.4%, predominantly <i>BRCA2</i> (3.7%) and <i>BRCA1</i> (3.1%) with protein-truncating variants accounting for 81.8% of alterations. Mutation prevalence progressively increased across hereditary risk tiers: 4.9% for the NeoFHS-zero group, 13.1% for the NeoFHS-low group, and 19.9% for the NeoFHS-high group (<i>p</i> &lt; 0.001). In HER2-negative breast cancer, germline homologous recombination repair gene mutations (gHRRm) independently predicted higher pathological complete response (pCR) rates (OR, 2.24; 95% CI, 1.09–4.66; <i>p</i> = 0.028). A numerically higher pCR rate was observed in gHRR-mutant TNBC patients receiving neoadjuvant immunotherapy combined with chemotherapy (80.0% vs 55.6%, <i>p</i> = 0.6). The PEEKABOO model exhibited strong performance in predicting mutation probability in both panel genes (area under curve [AUC], 0.73; accuracy, 57%; sensitivity/specificity, 76%/54%; PPV/NPV, 17%/95%) and <i>BRCA1/2</i> (AUC, 0.80; accuracy, 62%; sensitivity/specificity, 81%/61%; PPV/NPV, 13%/98%).</p> Conclusions <p>Our study establishes a unique germline mutation profile of Chinese breast cancer in a large-scale targeted sequencing cohort. Germline HRR gene mutation status is a potential biomarker for response to neoadjuvant treatment with DNA-damaging chemotherapeutics for HER2-negative breast cancer. The population-specific PEEKABOO model improves the predictive efficiency of germline mutations and represents a clinically applicable tool for risk stratification in Chinese patients.</p>

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Comprehensive genomic profiling of breast cancer reveals mutational landscape and the PEEKABOO model: a population-specific assessment tool for predicting germline mutations

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月4日

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  • Jinbo Wu,
  • Yaqian Xu,
  • Fei Xie,
  • Liu Yang,
  • Huan Li,
  • Miao Liu,
  • Houpu Yang,
  • Chaobin Wang,
  • Yuan Peng,
  • Yang Yang,
  • Wei Du,
  • Shu Wang

摘要

Background

Germline mutations in cancer-predisposition genes are critical for clinical risk assessment and therapeutic decisions in breast cancer, yet large-scale genomic studies and population-specific tools remain limited for Asian populations.

Methods

In this prospective clinic-based cohort study, 2700 unselected Chinese breast cancer patients underwent germline sequencing for single nucleotide variations, insertion/deletions, and large genomic rearrangements using a clinically validated 32-gene panel. Multiplex ligation-dependent probe amplification was used for confirmation of copy number variations. A multivariate logistic regression model (PEEKABOO) was developed to predict mutation probability. Therapeutic impact was assessed in 632 patients receiving neoadjuvant therapy.

Results

The overall prevalence of deleterious germline variants was 11.4%, predominantly BRCA2 (3.7%) and BRCA1 (3.1%) with protein-truncating variants accounting for 81.8% of alterations. Mutation prevalence progressively increased across hereditary risk tiers: 4.9% for the NeoFHS-zero group, 13.1% for the NeoFHS-low group, and 19.9% for the NeoFHS-high group (p < 0.001). In HER2-negative breast cancer, germline homologous recombination repair gene mutations (gHRRm) independently predicted higher pathological complete response (pCR) rates (OR, 2.24; 95% CI, 1.09–4.66; p = 0.028). A numerically higher pCR rate was observed in gHRR-mutant TNBC patients receiving neoadjuvant immunotherapy combined with chemotherapy (80.0% vs 55.6%, p = 0.6). The PEEKABOO model exhibited strong performance in predicting mutation probability in both panel genes (area under curve [AUC], 0.73; accuracy, 57%; sensitivity/specificity, 76%/54%; PPV/NPV, 17%/95%) and BRCA1/2 (AUC, 0.80; accuracy, 62%; sensitivity/specificity, 81%/61%; PPV/NPV, 13%/98%).

Conclusions

Our study establishes a unique germline mutation profile of Chinese breast cancer in a large-scale targeted sequencing cohort. Germline HRR gene mutation status is a potential biomarker for response to neoadjuvant treatment with DNA-damaging chemotherapeutics for HER2-negative breast cancer. The population-specific PEEKABOO model improves the predictive efficiency of germline mutations and represents a clinically applicable tool for risk stratification in Chinese patients.