Bioinformatic analysis of ligand-receptor interaction profiles and prognostic effects in esophageal squamous cell carcinoma
Objective To explore the role of tumor microenvironment(TME)and key ligand-receptor(LR)pairs in esophageal squamous cell carcinoma(ESCC)and their impact on prognosis,in order to deepen the understanding of the prognostic mechanisms of ESCC.Methods Based on the TCGA-ESCC dataset,key gene expression and cell-type inter-actions in ESCC samples were studied through analysis of single-cell RNA sequencing(scRNA-seq)data.Using the ex-pression of 16 LRs,79 ESCC samples were divided into two groups,and key genes were identified through Lasso analy-sis.Furthermore,this study revealed cell types and interactions in ESCC through analysis of the GSE154763 dataset.Results Lasso analysis identified four key genes:IL1A,LAMA3,TMEM45A and IGF2BP2,which significantly im-pact ESCC survival,leading to the construction of an effective prognostic model.Through further analysis of the GSE154763 dataset,19 clusters and 10 cell types were identified,with significant expression differences of four cell clusters between ESCC and normal tissues.Conclusion Through the analysis of single-cell RNA and TCGA-ESCC data,key LR and cell subgroups in ESCC were revealed.The prognostic model based on four genes that we constructed shows excellent predictive ability,providing new biomarkers and potential therapeutic targets for the treatment of ESCC.
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