Integrative analyses identified ion channel genes GJB2 and SCNN1B as prognostic biomarkers and therapeutic targets for lung adenocarcinoma

Objectives: Abnormal expressions of ion channel genes are associated with the occurrence and progression of tumors. At present, their roles in the carcinogenesis of lung adenocarcinoma (LUAD) are not clear. Materials and methods: Differentially expressed (DE) genes in the tumorigenesis were identified from 328 ion channel genes in 102 LUAD and paired adjacent normal samples. Similar analyses were performed between 177 metastatic and 286 non-metastatic LUAD samples to identify DE ion channel genes in the progression of LUAD. Independent prognostic factors selected from DE ion channel genes were used to construct a prognostic model. Correlation analysis and drugs-drug targets interaction network were used to screen the potential drugs for LUAD patients stratified by GJB2 or SCNN1B. Results: Six ion channel genes (GJB2, CACNA1D, KCNQ1, SCNN1B, SCNN1G and TRPV6) were continuous differentially expressed in the tumorigenesis and progression of LUAD. The survival analysis in four datasets with 522 LUAD samples showed that GJB2 and SCNN1B were independent prognostic biomarkers. Patients with overexpression of GJB2 or underexpression of SCNN1B had shorter overall survival. Moreover, multi-omics analysis showed that hypomethylation of GJB2 and hypermethylation of SCNN1B in the promoter region may contribute to their aberrant expressions. KEGG enrichment analysis showed that the overexpressed genes in the group with high GJB2 or low SCNN1B were enriched in cancer-related pathways, while the underexpressed genes were enriched in metabolism-related pathways. The prognostic model with GJB2 and SCNN1B can stratify all LUAD patients into two groups with significantly different survival. Correlation analysis and drugs-drug targets interaction network suggested that GJB2 and SCNN1B expression might have indicative therapeutic values for LUAD patients. Finally, pan-cancer analysis in other eight cancer types showed that GJB2 and SCNN1B might be also potential prognostic factors for KIRC. Conclusions: GJB2 and SCNN1B were identified as prognostic biomarkers and therapeutic targets for LUAD.