A novel risk model based on immune response predicts clinical outcomes and characterizes immunophenotypes in triple-negative breast cancer.

ABSTRACT: Triple-negative breast cancer (TNBC) is highly heterogeneous in prognosis. The current TNM staging system shows its limitation in accurate risk evaluation. Immune response and immune cell abundances in the tumor immune microenvironment (TIME) are critical for cancer progression, clinical outcome and therapeutic response in TNBC. However, there is a lack of an effective risk model based on the overall transcriptional alterations relevant to different immune responses. In this study, multiple bioinformatics and statistical approaches were used to develop an immune-related risk (IRR) signature based on the differentially expressed genes between the immune-active and immune-inactive samples. The IRR model showed great performance in risk stratification, immune landscape evaluation and immunoth

SUBMITTER: Lu X 

PROVIDER: S-EPMC9442003 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature