Comprehensive analysis of cancer-associated fibroblasts based on single-cell RNA sequencing in lung adenocarcinoma patients

Background: Cancer-associated fibroblasts (CAFs) in lung adenocarcinoma (LUAD) are important parts of the tumor microenvironment and are related to the prognosis. This study explores the biological characteristics of CAFs in LUAD tissue, and prognosis-related genes were screened. Methods: Using single-cell RNA sequencing data, we identified CAFs in LUAD tissue and analyzed them according to their RNA information. We evaluated their biological function, screened CAF-specific high-expression genes, and identified survival-related genes by combining the results with data from LUAD patients in The Cancer Genome Atlas (TCGA) database. All bioinformatics analyses were based on R-language software packages. Results: In total, 88,144 cells were collected from 22 tumor tissues and adjacent normal tissues of LUAD patients, and 68,881 cells were analyzed after quality control. Unsupervised clustering analysis was performed by graph clustering in Seurat, and 22 clusters were identified. Cluster 13 had 2140 cells that were identified as fibroblasts with genes COL1A1, COL3A1, DCN, and LUM. Of these, 840 cells were from tumor tissue, and 1300 cells were from adjacent normal tissue. RPS19, PMEPA1, and CTHRC1 were highly expressed in CAFs, and high expression of these genes indicated poor 10-year survival rate. SPARCL1, BTG2, ABCA8, CHRDL1, ADH18, GPX3, and SFTPC had low expression in CAFs of tumor tissue, anfigd low expression was also associated with poor 10-year survival rate. Conclusion: Single-cell analysis revealed the heterogeneity and complexity of CAF functions, and a group of abnormally expressed genes may be related to LUAD patients' survival.