Identification of Cancer-Associated Fibroblast Subtype of Triple-Negative Breast Cancer.

ABSTRACT:

Background

There is limited knowledge about the role of cancer-associated fibroblasts (CAF) in the tumor microenvironment of triple-negative breast cancer (TNBC).

Methods

Three hundred and thirty-five TNBC samples from four datasets were retrieved and analyzed. In order to determine the CAF subtype by combining gene expression profiles, an unsupervised clustering analysis was adopted. The prognosis, enriched pathways, immune cells, immune scores, and tumor purity were compared between CAF subtypes. The genes with the highest importance were selected by bioinformatics analysis. The machine learning model was built to predict the TNBC CAF subtype by these selected genes.

Results

TNBC samples were classified into two CAF subtypes (CAF+ and CAF-). The CAF- subtype of TNBC

SUBMITTER: Wang M 

PROVIDER: S-EPMC9057104 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature