TP53-Specific Mutations Serve as a Potential Biomarker for Homologous Recombination Deficiency in Breast Cancer: A Clinical Next-Generation Sequencing Study

Life Sciences Cell Biology Genetics Medicine Oncology Immunology Biochemistry
next-generation sequencing homologous recombination deficiency TP53 breast cancer biomarker

Breast cancer is one of the most common malignant tumors among women worldwide, with a complex pathogenesis involving multiple gene mutations and signaling pathway abnormalities. Homologous Recombination Deficiency (HRD) is a significant molecular characteristic in breast cancer, closely related to patients’ sensitivity to PARP inhibitor (PARPi) therapy. HRD is typically caused by mutations in the BRCA1/2 genes, but increasing evidence suggests that mutations in other genes may also lead to HRD. TP53 is one of the most frequently mutated genes in breast cancer, playing a crucial role in cell cycle regulation, DNA repair, and genomic stability. However, the relationship between TP53 mutations and HRD has not been fully elucidated. This study aims to explore the potential role of TP53-specific mutations in breast cancer HRD using clinical Next-Generation Sequencing (NGS) technology and evaluate their potential as biomarkers for PARPi therapy.

Source of the Paper

This paper was co-authored by Yongsheng Huang, Shuwei Ren, Linxiaoxiao Ding, and others, affiliated with the Cellular & Molecular Diagnostics Center of Sun Yat-sen Memorial Hospital, the Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, the Department of Clinical Laboratory at the Sixth Affiliated Hospital of Sun Yat-sen University, and other institutions. The paper was published on April 9, 2024, in the journal Precision Clinical Medicine, with the DOI 10.1093/pcmedi/pbae009.

Research Process

Study Subjects and Data Collection

The study enrolled 119 breast cancer patients (BRCA-119 cohort) and 47 breast cancer patients (HRD test cohort), all from Sun Yat-sen Memorial Hospital. Tumor tissues and matched blood samples were collected from the patients, and sequencing of 520 genes was performed using NGS technology. Additionally, clinical pathological data such as age, gender, estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 were collected.

DNA Extraction and NGS Sequencing

Genomic DNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissues and matched blood samples using Qiagen’s DNeasy Blood and DNA FFPE Tissue Kit. NGS library construction required at least 50 ng of high-quality DNA, followed by end repair, phosphorylation, adapter ligation, and sequencing using the Illumina NextSeq 550 sequencer with an average sequencing depth of 1000×.

Data Analysis

Sequencing data were rapidly mapped to the hg19 reference genome using BWA Picard, and gene variants were detected using VarScan and the Genome Analysis Toolkit (GATK). Variant annotation was performed using ANNOVAR and SnpEff, and DNA translocation detection was conducted using FACTERA. All mutations were confirmed using the Integrative Genomics Viewer system.

HRD Score Calculation

HRD scores were calculated based on genomic scars, including Loss of Heterozygosity (LOH), Large-Scale State Transitions (LST), and Telomeric Allelic Imbalance (TAI). An in-house script, Burning Rock Instability Detection of the Genome (BRIDGE), was developed for HRD score calculation.

Key Findings

TP53 Mutations and Clinicopathological Characteristics

Among the 119 patients, 68 carried TP53 pathogenic mutations, all of somatic origin. TP53 mutations were significantly associated with ER and PR protein expression and were distributed differently across breast cancer subtypes. The frequency of TP53 mutations was significantly higher in the high HRD score group (HRD score ≥42) compared to the low HRD score group (HRD score <42).

TP53 Mutations and Genomic Scar Scores

Patients with TP53 mutations had significantly higher HRD scores than those without TP53 mutations, particularly in LST and TAI. These results were further validated in the HRD test cohort and TCGA breast cancer patient data.

Genomic Features of TP53-Specific Mutation Subgroups

Based on the distribution of TP53 mutations in the high and low HRD score groups, the study categorized TP53 mutations into HRD-low-specific mutations, HRD-high-specific mutations, and HRD-common mutations. Significant differences in genomic features and Tumor Mutation Burden (TMB) were observed among the subgroups.

TP53-Specific Mutation Combinations Predict HRD Status

TP53 pathogenic mutations predicted breast cancer HRD status with an AUC of 0.61. The combination of HRD-high-specific mutations and HRD-common mutations showed the best predictive performance, with an AUC of 0.80. The model had an accuracy of 0.82, precision of 0.68, recall of 0.76, specificity of 0.86, Youden index of 0.61, and F1 score of 0.71.

Conclusion

This study provides the first comprehensive analysis of the role of TP53-specific mutations in breast cancer HRD, revealing a significant association between TP53 mutations and HRD scores. TP53-specific mutation combinations effectively predicted HRD status in breast cancer patients, suggesting that TP53 mutations may serve as potential biomarkers for PARPi therapy. This finding offers new insights and evidence for precision treatment in breast cancer.

Research Highlights

  1. First Comprehensive Analysis of TP53 Mutations and HRD: This study fills a research gap by comprehensively analyzing the role of TP53 mutations in breast cancer HRD using large-scale NGS data.
  2. Predictive Performance of TP53-Specific Mutation Combinations: The combination of HRD-high-specific mutations and HRD-common mutations effectively predicted HRD status, providing a new biomarker for precision treatment in breast cancer.
  3. Application of Genomic Scar Scores: The study quantified HRD using genomic scar scores (LOH, LST, TAI), offering a new method for HRD assessment in breast cancer.

Research Value

The scientific value of this study lies in its revelation of the critical role of TP53 mutations in breast cancer HRD, providing new perspectives on the molecular mechanisms of breast cancer. The practical value lies in the potential use of TP53-specific mutation combinations as biomarkers for PARPi therapy, which could guide precision treatment in breast cancer and improve patient survival rates and quality of life.