Abstract
BACKGROUND: The high heterogeneity of lung adenocarcinoma (LUAD) is largely due to its complex tumor immune microenvironment (TIME). Cancer-associated fibroblasts (CAFs) are a core matrix component of TIME. However, their functional heterogeneity and the specific molecular mechanisms driving tumor progression have not been fully elucidated. In addition, the role of nuclear receptor NR2F2 in tumor development is still controversial. METHOD: This study integrated scRNA-seq data from the GEO database with RNA-seq data from TCGA and GEO and then performed multiple levels of validation through in vitro experiments. We adopted a systematic computational biology strategy and analyzed the cellular composition, interaction networks and functional states of cancer-associated fibroblasts (CAFs) in lung adenocarcinoma using Seurat, CellChat, and AUCell. According to the marker genes of key CAF subgroup, prognostic risk models were constructed through LASSO-Cox regression and validated in an independent cohort (GSE72094). Afterwards, we carried out in vitro experiments and validated the biological role of NR2F2 through a coculture system. Functional validation was conducted through siRNA knockdown, plasmid overexpression, CCK-8 assay, EdU labeling, and Transwell experiments. RESULT: We noticed the CAF - 2 subgroup, characterized by the highest level of TGF - β signaling activation, sends various signals to different cell types. We constructed and verified a consistent prognostic signature made of 16 genes using the LASSO-Cox method. This model can effectively assess the risk of LUAD patients. The prognosis in high-risk group is worse. And we also do some analysis to find out that risk score is highly associated with immunosuppressive TME and high expressions of PD - L1. We have found in our further study that the expression of NR2F2 in CAF is associated with the promoting of matrix remodeling and metabolic reprogramming. From the coculture system and in vitro functional experiments, overexpression of NR2F2 in CAFs enhanced tumor cell proliferation and invasion, whereas knockdown of NR2F2 attenuated these malignant phenotypes. CONCLUSION: Using single-cell RNA sequencing data, we identified a CAF subgroup with the most active TGF-β signaling. Based on the marker genes of the subgroup, we constructed and validated an effective prognostic model, then we further screened and confirmed NR2F2 as a major pro-tumorigenic regulator from this feature gene set through single cell and transcriptome data as well as in vitro experiments. NR2F2 promotes malignant remodeling of TIME by synergistically enhancing TGF-β signaling and EMT processes. Our study provides not only a solid theoretical foundation but also a therapeutic target to explore new therapeutic options targeting the CAFs-TGF-β-EMT axis.