Identifying Potential Gene Defect Patterns Related to COVID-19 Based on Pharmacological and Bioinformatics Analysis for Lung Adenocarcinoma

Abstract

Background: Coronavirus disease 2019 (COVID-19) greatly affects cancer patients, especially those with lung cancer. This study aimed to identify potential drug targets for lung adenocarcinoma (LUAD) patients with COVID-19. Methods: LUAD samples were obtained from public databases. Differentially expressed genes (DEGs) related to COVID-19 were screened. Protein–protein interactions among COVID-19-related genes, the traditional Chinese medicine (TCM) and TCM target genes were analyzed by CytoScape. The correlation between tumor microenvironment and COVID-19 target genes were assessed by Pearson correlation analysis. Unsupervised consensus clustering was conducted to categorize molecular subtypes. Results: We filtered 26 COVID-19 target genes related to TCM for LUAD. Interleukin (IL)-17 signaling pathway and tumor necrosis factor (TNF) signaling pathway were significantly enriched in these 26 genes. A strong correlation was found between COVID-19 target genes and tumor microenvironment (TME), cell death. Importantly, interleukin-1beta (IL1B) was identified as a core gene in the protein–protein interactions (PPI) network. Based on the 26 target genes, two molecular subtypes showing distinct overall survival, TME and response to target therapy were developed. Conclusions: This study explored 26 COVID-19 target genes, which could serve as potential therapeutic drug targets for LUAD. IL1B was verified as a critical target for developing new molecular drugs. Furthermore, two novel molecular subtypes showed the potential to guide personalized therapies in clinical practice.