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Updated: Jan 10, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Identification of Poor Prognostic Markers in Triple-Negative Breast Cancer Using Whole Exome Sequencing.
Seungju Lee1,2, Hyun Yul Kim1, Youn Joo Jung1
1Department of Surgery, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Korea.
Distinct mutational profiles in triple-negative breast cancer (TNBC) correlate with PD-L1 status. Specific gene variants in PD-L1-negative TNBC may indicate poorer survival, aiding prognostic stratification.
Area of Science:
- Oncology
- Genomics
- Cancer Research
Background:
- Triple-negative breast cancer (TNBC) is an aggressive subtype with limited prognostic markers.
- Programmed death ligand 1 (PD-L1) is a biomarker, but its utility is restricted, especially in PD-L1-negative cases.
- Identifying new molecular markers is crucial for better prognostication and treatment in TNBC.
Purpose of the Study:
- To investigate distinct mutational landscapes in TNBC based on PD-L1 expression.
- To identify novel prognostic variants associated with survival outcomes in TNBC.
- To explore the role of genomic profiling in refining TNBC prognostic stratification.
Main Methods:
- Whole-exome sequencing of 38 TNBC tumor tissues.
- Immunohistochemistry to assess PD-L1 expression (positive/negative).
- Analysis of somatic variants and mutational signatures; survival analyses.
Main Results:
- TNBC tumors showed distinct mutational signatures based on PD-L1 status (SBS5 for PD-L1-negative, SBS6 for PD-L1-positive).
- Twelve PD-L1-negative-specific and seven PD-L1-positive-specific variants were identified.
- Mutations in ANGPTL5 and KIAA1549L were linked to worse overall survival in PD-L1-negative TNBC.
Conclusions:
- PD-L1 status defines distinct mutational profiles and prognostic variants in TNBC.
- ANGPTL5 and KIAA1549L variants show potential as prognostic markers for PD-L1-negative TNBC.
- Genomic data integration can enhance prognostic accuracy for TNBC patients.
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