Novel Gene Signatures Predictive of Patient Recurrence-free Survival in HR+HER2- Breast Cancer

Abstract

Abstract Purpose Predicting relapse-free survival (RFS) and understanding the molecular characteristics of endocrine therapy resistance are crucial for determining the treatment decision-making process in HR+/HER2- breast cancer patients. To address this, the main purpose of this study was to develop a signature to predict RFS in HR+/HER2- breast cancer patients Methods We analyzed transcriptome and clinical data from 856 patients with HR + HER2- breast cancer in the FUSCC cohort and 1140 patients in the METABRIC cohort. We identified 21 genes that were differentially expressed between endocrine therapy-sensitive and endocrine therapy -resistant tumors. Using the least absolute shrinkage and selection operator (LASSO) and stepwise Cox regression analysis, we developed a 13-gene signature, named the endocrine therapy resistant prognosis signature (ETRPS), to predict RFS in HR+/HER2-related breast cancer patients. Results Our analysis identified 21 genes that were differentially expressed between endocrine therapy-sensitive and endocrine therapy-resistant tumors. The ETRPS, a 13-gene signature, effectively predicted RFS in HR+/HER2- breast cancer patients, even in patients with negative lymph nodes. To validate the utility of ETRPS, we applied it to five external cohorts, demonstrating its widespread application value. Conclusion These findings provide valuable insights into the prediction of RFS and endocrine therapy resistance in HR+/HER2- breast cancer patients. The ETRPS signature may serve as a useful tool for determining treatment decision-making processes and for predicting patient outcomes in this breast cancer subtype.