Transcriptome-based insights into the role of cancer-associated fibroblasts in lung adenocarcinoma prognosis and therapy.

Abstract

Cancer-associated fibroblasts (CAFs) are related to drug resistance and prognosis of tumor patients. This study aimed to investigate the relationship between prognosis and drug treatment response in patients with CAF and lung adenocarcinoma (LUAD). The data pertaining to LUAD patients were obtained from The Cancer Genome Atlas-LUAD and GSE68465 datasets. Four different algorithms were used to quantify CAF infiltration and stromal scores. Weighted gene network co-expression analysis was used to identify CAF-related modules and hub genes. Univariate Cox regression analysis, least absolute shrinkage and selection operator regression analysis, and multivariate Cox regression analysis were used to construct CAF signatures, whose ability to predict prognosis was verified by individual CAF scores. The CAF-related signature of eight genes was constructed, and the CAF score was calculated. The prognosis of LUAD patients with high CAF scores was significantly worse than that of patients with low CAF scores. CAF score was an independent risk factor for LUAD prognosis. Patients with high CAF scores were sensitive to some chemotherapy drugs, and in most cases, they were non-responsive to immunotherapy. Eight-gene CAF signature may predict LUAD patient prognosis and evaluate clinical responses to chemotherapy and immunotherapy, enabling individualized treatment for the patients.