Identification of differentially expressed genes in lung adenocarcinoma cells using single-cell RNA sequencing not detected using traditional RNA sequencing and microarray

Abstract

AbstractLung adenocarcinoma (LUAD) is the leading cause of cancer-related deaths worldwide. Traditional RNA sequencing data fails to detect the exact cellular and molecular changes in tumor cells as they make up only a small proportion of tumor tissue. 10× genomics single-cell RNA sequencing (10× scRNA-seq) and gene expression data of LUAD patients was obtained from the Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, ArrayExpress, TCGA, and GEO databases. Differentially expressed genes (DEGs) were identified in LUAD and alveolar cells (DEGs-scRNA-cancer_cell), tumor- and normal tissue-derived cells (DEGs-scRNA-sample), and normal and LUAD patients (DEGs-Bulk). Flow cytometry and qRT-PCR were performed to validate the significantly differentially expressed ligand–receptor pairs. We selected 159,219 cells and 594 samples in the scRNA-seq data and traditional RNA sequencing, respectively. A total of 1042 DEGs-scRNA-cancer_cell, 788 DEGs-scRNA-sample, and 2510 DEGs-Bulk were identified in this study. We also identified 57 DEGs that were only detected in DEGs-scRNA-cancer_cell (only-DEGs-scRNA-cancer_cell). To explore the relationship between only-DEGs-scRNA-cancer_cell and survival in LUAD, 14 and 22 only-DEGs-scRNA-cancer_cell, which were closely related with survival in TCGA and GEO cohorts were identified. Functional enrichment analyses showed these DEGs-scRNA-cancer_cells were mainly related to cell proliferation and immunoregulation. Our study detected and compared DEGs at different levels and revealed genes that may regulate tumor development. Our results provide a potential new protocol to determine the contribution of DEGs to cancer progression and to help identify potential therapeutic targets.Traditional RNA sequencing data may fail to detect the exact cellular changes in tumor cells. With comprehensively single-cell and traditional RNA-seq data, these authors detected and compared differentially expressed genes in lung adenocarcinoma. These results may improve our understanding of cellular and molecular differences between cancerous and non-malignant tissue and provide tumor markers as well as potential therapeutic targets.