Background
Cancer-associated fibroblasts (CAFs) are a crucial component of the tumor microenvironment (TME) and play significant roles in tumor initiation, progression, and immune evasion. Despite this, the specific exosomal proteins derived from CAFs and their functions in esophageal squamous cell carcinoma (ESCC) remain unknown. Therefore, this study aims to investigate the impact and prognostic significance of CAFs-derived exosomal proteins in ESCC. Materials and
Conclusion
In conclusion, our study has successfully established a robust prognostic signature based on CAFs-derived exosomal proteins, which can serve as a reliable biomarker for predicting prognosis and evaluating the immune microenvironment in ESCC.
Methods
Exosomes obtained from CAFs and normal fibroblasts (NFs) were isolated using ultracentrifugation, and the protein expression profiles of the exosomes were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Tumor proliferation was assessed using CCK-8 and colony formation assays, while cell invasion and migration were evaluated using transwell assays. Lasso regression analysis was employed to establish a signature based on CAFs-derived exosomal proteins using the TCGA database. The immunological and prognostic roles of this signature were comprehensively investigated through survival analysis, gene set enrichment analysis (GSEA), immune analysis, immunotherapy response analysis, and drug sensitivity analysis. The GSE160269 dataset was utilized for single-cell transcriptome analysis to further elucidate the role of the signature in the TME. Additionally, cDNA microarray analysis was utilized to validate the prognostic value of the signature.
Results
Our findings demonstrate that exosomes derived from CAFs significantly enhance the proliferation, invasion, and migration of esophageal cancer cells. We identified 842 differentially expressed exosomal proteins through LC-MS/MS analysis, and two key proteins were utilized to establish a risk signature. Survival analysis revealed a significantly worse prognosis in the high-risk group, with multivariate analysis indicating that the risk score serves as an independent prognostic factor. Moreover, we observed a significant correlation between the risk score and immune cell infiltration, immunotherapy response, and sensitivity to chemotherapeutic treatments in the study population. Lastly, single-cell transcriptome analysis further revealed the expression patterns of TNFRSF10B and ILF3 in different cell subpopulations.