SNAI2 as a Prognostic Biomarker Based on Cancer-Associated Fibroblasts in Patients With Lung Adenocarcinoma

Abstract

Background: Lung adenocarcinoma (LUAD) is a common type of malignant tumor with therapeutic challenges. Cancer-associated fibroblasts (CAFs) promote LUAD growth and metastasis, regulate the tumor immune response, and influence tumor treatment responses and drug resistance. However, the molecular mechanisms through which CAFs control LUAD progression are largely unknown. In this study, we aimed to determine the correlations between CAF-related genes and overall survival (OS) in patients with LUAD. Methods: We acquired the gene expression data and clinical information of 522 patients with LUAD patients from The Cancer Genome Atlas (TCGA) and 442 patients with LUAD from the Gene Expression Omnibus (GEO) databases. CAF infiltration levels were assessed using the Microenvironment Cell Population (MCP) counter, the Estimating the Proportions of Immune and Cancer cells (EPIC) algorithm, and Tumor Immune Dysfunction and Exclusion (TIDE) scores. A CAF-related gene network was constructed using the Weighted gene co-expression network analysis (WGCNA). Based on the CAF-related genes, univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analyses were performed to identify prognostic genes. Gene expression levels within the prognostic model were validated using the Cancer Cell Line Encyclopedia (CCLE) databases and Western blotting. Results: Our results demonstrated that high CAF scores were associated with lower survival rates in patients with LUAD. Gene modules that were highly correlated with high CAF scores were closely associated with tissue characteristics and extracellular matrix structures in LUAD. In addition, correlations between CAF scores and responses to immunotherapy and chemotherapy were observed. Finally, we found that SNAI2 expression was higher in lung cancer tissues than in normal tissues. Conclusion: Deepening our understanding of the influence of CAFs on tumor progression and treatment response at the molecular level can aid the development of more effective therapeutic strategies. This study provides important insights into the functional mechanisms of action of CAFs in LUAD and highlights their clinical implications.