Abstract
Background: Lung cancer patients have the worst outcomes when affected by coronavirus disease 2019 (COVID-19). The molecular mechanisms underlying the association between lung cancer and COVID-19 remain unknown. The objective of this investigation was to determine whether there is crosstalk in molecular perturbation between COVID-19 and lung cancer, and to identify a molecular signature, molecular networks and signaling pathways shared by the two diseases.
Methods: We analyzed publicly available gene expression data from 52 severely affected COVID-19 human lung samples, 594 lung tumor samples and 54 normal disease-free lung samples. We performed network and pathways analysis to identify molecular networks and signaling pathways shared by the two diseases.
Results: The investigation revealed a signature of genes associated with both diseases and signatures of genes uniquely associated with each disease, confirming crosstalk in molecular perturbation between COVID-19 and lung cancer. In addition, the analysis revealed molecular networks and signaling pathways associated with both diseases.
Conclusions: The investigation revealed crosstalk in molecular perturbation between COVID-19 and lung cancer, and molecular networks and signaling pathways associated with the two diseases. Further research on a population impacted by both diseases is recommended to elucidate molecular drivers of the association between the two diseases.
Keywords: COVID-19; SARS-CoV-2; coronavirus; gene expression; lung cancer; networks; signaling pathways.
【저자키워드】 COVID-19, SARS-CoV-2, coronavirus, Gene Expression, lung cancer, signaling pathways, networks, 【초록키워드】 coronavirus disease, Coronavirus disease 2019, Crosstalk, Diseases, Gene Expression, lung, outcome, molecular mechanism, lung cancer, human lung, Research, pathway, network, signaling pathway, molecular, disease, signaling pathways, association, Analysis, Pathways, molecular networks, cancer patient, molecular mechanisms, signature, lung cancer patients, analyzed, identify, performed, affected, addition, determine, molecular network, impacted, driver, 【제목키워드】 Perturbation, landscape,