We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Gene expression signature for predicting homologous recombination deficiency in triple-negative breast cancer.
- Authors
Pan, Jia-Wern; Tan, Zi-Ching; Ng, Pei-Sze; Zabidi, Muhammad Mamduh Ahmad; Nur Fatin, Putri; Teo, Jie-Ying; Hasan, Siti Norhidayu; Islam, Tania; Teoh, Li-Ying; Jamaris, Suniza; See, Mee-Hoong; Yip, Cheng-Har; Rajadurai, Pathmanathan; Looi, Lai-Meng; Taib, Nur Aishah Mohd; Rueda, Oscar M.; Caldas, Carlos; Chin, Suet-Feung; Lim, Joanna; Teo, Soo-Hwang
- Abstract
Triple-negative breast cancers (TNBCs) are a subset of breast cancers that have remained difficult to treat. A proportion of TNBCs arising in non-carriers of BRCA pathogenic variants have genomic features that are similar to BRCA carriers and may also benefit from PARP inhibitor treatment. Using genomic data from 129 TNBC samples from the Malaysian Breast Cancer (MyBrCa) cohort, we developed a gene expression-based machine learning classifier for homologous recombination deficiency (HRD) in TNBCs. The classifier identified samples with HRD mutational signature at an AUROC of 0.93 in MyBrCa validation datasets and 0.84 in TCGA TNBCs. Additionally, the classifier strongly segregated HRD-associated genomic features in TNBCs from TCGA, METABRIC, and ICGC. Thus, our gene expression classifier may identify triple-negative breast cancer patients with homologous recombination deficiency, suggesting an alternative method to identify individuals who may benefit from treatment with PARP inhibitors or platinum chemotherapy.
- Subjects
TRIPLE-negative breast cancer; HOMOLOGOUS recombination; GENE expression; BREAST cancer; BRCA genes
- Publication
NPJ Breast Cancer, 2024, Vol 10, Issue 1, p1
- ISSN
2374-4677
- Publication type
Article
- DOI
10.1038/s41523-024-00671-1