Predicting the immune microenvironment and prognosis with a anoikis - related signature in breast cancer.

ABSTRACT:

Background

Tumor heterogeneity is widely recognized as a crucial factor impacting the prognosis of breast cancer (BC) patients. However, there remains an insufficient understanding of the underlying impact of anoikis on the prognosis of BC patients.

Methods

The researchers utilized the TCGA-BRCA dataset to screen and analyze the differentially expressed genes of anoikis-related genes (ARGs) in BC and normal breast tissue. Prognostic gene signatures were established through univariate, LASSO, and multivariate Cox regression analyses. These signatures were evaluated using Kaplan-Meier curve and receiver operating characteristic (ROC) analyses, resulting in the development of an anoikis-related index (ACI). The training dataset was TCGA-BRCA, while METABRIC and GSE96058 were us

SUBMITTER: Lu X 

PROVIDER: S-EPMC10353543 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature