AUTHOR=Xu An , Xu Xiang-Nan , Luo Zhou , Huang Xiao , Gong Rong-Quan , Fu De-Yuan 

TITLE=Identification of prognostic cancer-associated fibroblast markers in luminal breast cancer using weighted gene co-expression network analysis

JOURNAL=Frontiers in Oncology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1191660

DOI=10.3389/fonc.2023.1191660

ISSN=2234-943X

ABSTRACT=Luminal breast cancer (LBC) is a subtype of breast cancer characterized by the presence of estrogen and/or progesterone receptors on the surface of cancer cells. cancer-associated fibroblasts (CAFs) are present in the tumor microenvironment and have been shown to play a critical role in promoting tumor growth and progression, including in LBC. In this study, we used weighted gene co-expression network analysis (WGCNA) to identify CAF markers in LBC. Two transcriptome datasets were collected from publicly available databases and hub modules most correlated with stromal CAF infiltrations were identified. Univariate and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analyses were used to identify prognostic CAF markers. RIN2, THBS1, IL1R1, RAB31, and COL11A1 were identified as prognostic CAF markers and a five-gene CAF signature was constructed, capable of predicting prognosis and therapeutic responses in LBC. Our results suggest that the CAF model might be a novel anti-CAF therapeutic approach in LBC.