Dual-Function RNA Biomarkers: Integrating Relapse Prediction and Immune Profiling in Triple-Negative Breast Cancer.

ABSTRACT: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with a high risk of recurrence and poor clinical outcomes. However, the factors contributing to its relapse remain inadequately understood. In this study, we utilized transcriptomic data from The Cancer Genome Atlas (TCGA) to identify lncRNA pairs associated with both recurrence and immune response. A risk prediction model was constructed through the integration of LASSO regression, Cox proportional hazards analysis, and random forest algorithms. To validate its predictive capability, we employed an external validation cohort along with a backpropagation neural network (BPNN) to assess the model's performance. Our findings indicate that the proposed risk model correlates strongly with multiple clinical features, in

SUBMITTER: Wen Y 

PROVIDER: S-EPMC12434821 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature