Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods

Li Gao; Guo-Sheng Li; Jian-Di Li; Juan He; Yu Zhang; Hua-Fu Zhou; Jin-Liang Kong; Gang Chen

doi:10.1016/j.csbj.2021.11.026

Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods

Comput Struct Biotechnol J. 2021:19:6229-6239. doi: 10.1016/j.csbj.2021.11.026. Epub 2021 Nov 20.

Authors

Li Gao¹, Guo-Sheng Li¹, Jian-Di Li¹, Juan He¹, Yu Zhang², Hua-Fu Zhou³, Jin-Liang Kong⁴, Gang Chen¹

Affiliations

¹ Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Rd, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China.
² Department of Pathology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No. 324. Jingwu Rd, Jinan, Shandong 250021, PR China.
³ Department of Cardio-Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Rd, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China.
⁴ Ward of Pulmonary and Critical Care Medicine, Department of Respiratory Medicine, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Rd, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China.

Abstract

Introduction: The risk of infection with COVID-19 is high in lung adenocarcinoma (LUAD) patients, and there is a dearth of studies on the molecular mechanism underlying the high susceptibility of LUAD patients to COVID-19 from the perspective of the global differential expression landscape.

Objectives: To fill the research void on the molecular mechanism underlying the high susceptibility of LUAD patients to COVID-19 from the perspective of the global differential expression landscape.

Methods: Herein, we identified genes, specifically the differentially expressed genes (DEGs), correlated with the susceptibility of LUAD patients to COVID-19. These were obtained by calculating standard mean deviation (SMD) values for 49 SARS-CoV-2-infected LUAD samples and 24 non-affected LUAD samples, as well as 3931 LUAD samples and 3027 non-cancer lung samples from 40 pooled RNA-seq and microarray datasets. Hub susceptibility genes significantly related to COVID-19 were further selected by weighted gene co-expression network analysis. Then, the hub genes were further analyzed via an examination of their clinical significance in multiple datasets, a correlation analysis of the immune cell infiltration level, and their interactions with the interactome sets of the A549 cell line.

Results: A total of 257 susceptibility genes were identified, and these genes were associated with RNA splicing, mitochondrial functions, and proteasomes. Ten genes, MEA1, MRPL24, PPIH, EBNA1BP2, MRTO4, RABEPK, TRMT112, PFDN2, PFDN6, and NDUFS3, were confirmed to be the hub susceptibility genes for COVID-19 in LUAD patients, and the hub susceptibility genes were significantly correlated with the infiltration of multiple immune cells.

Conclusion: In conclusion, the susceptibility genes for COVID-19 in LUAD patients discovered in this study may increase our understanding of the high risk of COVID-19 in LUAD patients.

Keywords: CI, confidence interval; COVID-19; COVID-19, coronavirus disease 2019; DEG; DEG, differentially expressed genes; FC, fold change; FPKM, fragments per kilobase per million; GTEx, Genotype-tissue Expression; HPA, human protein atlas; IHC, immunohistochemistry; Immune infiltration; LUAD; LUAD, lung adenocarcinoma; PPI, protein-to-protein interaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; SMD, standard mean difference; SROC, summarized receiver’s operating characteristics; Susceptibility; TF, transcription factor; TPM, transcripts per million reads; WGCNA; WGCNA, weighted gene co-expression network analysis.