Prognostic Implication Of The Expression Level Of Pecam-1 In Non-Small Cell Lung Cancer

Background: Lung cancer is a malignant disease that threatens human health. Hence, it is crucial to identify effective prognostic factors and treatment targets. Single-cell RNA sequencing can quantify the expression profiles of transcripts in individual cells.Methods: profiles were downloaded from the Gene Expression Omnibus database. Key ligand-receptor genes in the tumor and the normal groups were screened to identify integrated differentially expressed genes (DEGs) from the GSE118370 and The Cancer Genome Atlas Lung Adenocarcinoma databases. DEGs associated with more ligand-receptor pairs were selected as candidate DEGs for Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and survival analysis. In addition, we conducted validation immunohistochemical experiments on postoperative specimens of 30 patients with lung cancer.Results: A total of 18 candidate DEGs were identified from the tumor and the normal groups. The analysis of the GO biological process revealed that these DEGs were mainly enriched in wound healing, in response to wounding, cell migration, cell motility, and regulation of cell motility, while the KEGG pathway analysis found that these DEGs were mainly enriched in proteoglycans in cancer, bladder cancer, malaria, tyrosine kinase inhibitor resistance in Epidermal Growth Factor Receptor (EGFR), and the ERBB signaling pathway. Survival analysis showed that a high, rather than a low, expression of platelet endothelial cell adhesion molecule-1 (PECAM-1) was associated with improved survival. Similarly, in postoperative patients with lung cancer, we found that the overall survival of the PECAM-1 high-expression group shows a better trend than the PECAM-1 low-expression group (p = 0.172).Conclusions: The candidate DEGs identified in this study may play some important roles in the occurrence and development of lung cancer, especially PECAM-1, which may present potential prognostic biomarkers for the outcome.