Evidence map›Paper›PMID 41188832›Full record

ArticleJournal of translational medicine2025

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

Jinbo Wu, Yaqian Xu, Fei Xie, Liu Yang, Huan Li, Miao Liu, Houpu Yang, Chaobin Wang, Yuan Peng, Yang Yang and 2 more

Abstract read
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Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Jinbo Wu *Breast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Yaqian Xu *Breast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Fei XieBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Liu YangBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Huan LiBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Miao LiuBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Houpu YangBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Chaobin WangBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Yuan PengBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Yang YangBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Wei DuBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China.
Shu WangBreast Center, Peking University People's Hospital, Beijing, 100044, People's Republic of China. shuwang@pkuph.edu.cn.ORCID 0000-0002-8651-4795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGermline 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.

methodsIn 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.

resultsThe 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%).

conclusionsOur 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.

Indexed as

Breast NeoplasmsGenomicsGerm-Line MutationAdultAgedFemaleGenetic Predisposition to DiseaseHumansMiddle AgedBreast cancerChinese populationNeoadjuvant therapyNext-generation sequencingPEEKABOO

Identifiers

PMID41188832
PMCPMC12584271

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