Identification of a Novel Gene Model-Based Homologous Recombination Deficiency Score to Improve Survival Prediction of TNBC.

Abstract Background Triple-negative breast cancer (TNBC) is a specific histological type of breast cancer with a poor prognosis, early recurrence, which lacks durable chemotherapy responses and effective targeted therapies. We aimed to construct an accurate prognostic risk model based on homologous recombination deficiency (HRD) - gene expression profiles for improving prognosis prediction of TNBC. Methods Triple-negative breast cancer RNA sequencing data and sample clinical information were downloaded from the breast invasive carcinoma (BRCA) cohort in the Cancer Genome Atlas (TCGA) database. Combined with the HRD database, tumor samples were divided into two sets. We screened differentially expressed genes (DEGs) and then identified HRD-related prognostic genes using weighted gene co-expression network analysis (WGCNA) and Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to identifying key prognostic genes. Risk scores were calculated and compared with HRD score, Kaplan–Meier (KM) survival analysis were used to assess its prognostic power. GSE103091 dataset from GEO (Gene Expression Omnibus) database was used to validate the signature. Univariate and multivariate Cox regression were performed to independently verify the prognosis of the risk score. A nomogram was constructed and revealed by time-dependent ROC curves to guide clinical practice. Results We found that HRD tumor samples (HRD score > = 42) in TNBC patients were associated with poor overall survival (p = 0.027). We identified a total of 147 differential genes including 203 up-regulated and 213 down-regulated genes, among which 29 were prognosis-related genes. Through the LASSO method, 6 key prognostic genes ((MUCL1, IVL, FAM46C, CHI3L1, PRR15L, and CLEC3A) were selected and a 6-gene risk score was constructed. We found risk score was negatively associated with homologous recombination deficiency (HRD) scores (r = -0.22, p = 0.019). Compared with the low-risk group, Kaplan-Meier survival analysis shows that the high-risk group has an obvious poorer prognosis (P < 0.0001). Finally, we integrated the risk score model and clinical factors of TNBC (AJCC-stage, HRD score, T stage, and N stage) to construct a compound nomogram. Time-dependent ROC curves showed the risk score performed better in 1-, 3- and 5-year survival predictions compared with AJCC-stage. Conclusions Based on HRD gene expression data, our six HRD-related gene signature and nomogram could be practical and reliable tools for predicting OS in patients with TNBC.