Network Pharmacology and Bioinformatics Analysis Identifies Potential Therapeutic Targets of Paxlovid Against LUAD/COVID-19

被引:5
作者
Zhang, Wentao [1 ,2 ]
Yang, Zhe [1 ]
Zhou, Fengge [1 ]
Wei, Yanjun [3 ]
Ma, Xiaoqing [2 ]
机构
[1] Shandong First Med Unvers, Shandong Prov Hosp, Tumor Res & Therapy Ctr, Shandong, Peoples R China
[2] Shandong First Med Unvers, Jinan, Peoples R China
[3] Shandong Univ, Shandong Prov Hosp, Cheeloo Coll Med, Tumor Res & Therapy Ctr, Jinan, Peoples R China
来源
FRONTIERS IN ENDOCRINOLOGY | 2022年 / 13卷
关键词
Paxlovid; Lung adenocarcinoma (LUAD); COVID-19; SARS-CoV-2; bioinformatics; COVID-19; CANCER; PERSPECTIVES; RISK; DRUG;
D O I
10.3389/fendo.2022.935906
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a pandemic in many countries around the world. The virus is highly contagious and has a high fatality rate. Lung adenocarcinoma (LUAD) patients may have higher susceptibility and mortality to COVID-19. While Paxlovid is the first oral drug approved by the U.S. Food and Drug Administration (FDA) for COVID-19, its specific drug mechanism for lung cancer patients infected with COVID-19 remains to be further studied. Methods COVID-19 related genes were obtained from NCBI, GeneCards, and KEGG, and then the transcriptome data for LUAD was downloaded from TCGA. The drug targets of Paxlovid were revealed through BATMAN-TCM, DrugBank, SwissTargetPrediction, and TargetNet. The genes related to susceptibility to COVID-19 in LUAD patients were obtained through differential analysis. The interaction of LUAD/COVID-19 related genes was evaluated and displayed by STRING, and a COX risk regression model was established to screen and evaluate the correlation between genes and clinical characteristics. The Venn diagram was drawn to select the candidate targets of Paxlovid against LUAD/COVID-19, and the functional analysis of the target genes was performed using KEGG and GO enrichment analysis. Finally, Cytoscape was used to screen and visualize the Hub Gene, and Autodock was used for molecular docking between the drug and the target. Result Bioinformatics analysis was performed by combining COVID-19-related genes with the gene expression and clinical data of LUAD, including analysis of prognosis-related genes, survival rate, and hub genes screened out by the prognosis model. The key targets of Paxlovid against LUAD/COVID-19 were obtained through network pharmacology, the most important targets include IL6, IL12B, LBP. Furthermore, pathway analysis showed that Paxlovid modulates the IL-17 signaling pathway, the cytokine-cytokine receptor interaction, during LUAD/COVID-19 treatment. Conclusions Based on bioinformatics and network pharmacology, the prognostic signature of LUAD/COVID-19 patients was screened. And identified the potential therapeutic targets and molecular pathways of Paxlovid Paxlovid in the treatment of LUAD/COVID. As promising features, prognostic signatures and therapeutic targets shed light on improving the personalized management of patients with LUAD.
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页数:11
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