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Gene expression analysis of MCF7 cell lines of breast cancer treated with herbal extract of Cissampelos pareira revealed association with viral diseases

BACKGROUND: It is necessary to assess the cellular, molecular, and pathogenetic characteristics of COVID-19 and attention is required to understand highly effective gene targets and mechanisms. In this study, we suggest understandings into the fundamental pathogenesis of COVID-19 through gene expres...

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Detalles Bibliográficos
Autor principal: Güven, Emine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062415/
https://www.ncbi.nlm.nih.gov/pubmed/33907720
http://dx.doi.org/10.1016/j.genrep.2021.101169
Descripción
Sumario:BACKGROUND: It is necessary to assess the cellular, molecular, and pathogenetic characteristics of COVID-19 and attention is required to understand highly effective gene targets and mechanisms. In this study, we suggest understandings into the fundamental pathogenesis of COVID-19 through gene expression analyses using the microarray data set GSE156445 publicly reachable at NIH/NCBI Gene Expression Omnibus database. The data set consists of MCF7 which is a human breast cancer cell line with estrogen, progesterone and glucocorticoid receptors. The cell lines treated with different quantities of Cissampelos pareira (Cipa). Cipa is a traditional medicinal plant which would possess an antiviral potency in preventing viral diseases such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: Utilizing Biobase, GEOquery, gplots packages in R studio, the differentially expressed genes (DEGs) were identified. The gene ontology (GO) of pathway enrichments employed by utilizing DAVID and KEGG enrichment analyses were studied. We further constructed a human protein-protein interaction (PPI) network and performed, based upon that, a subnetwork module analysis for significant signaling pathways. RESULTS: The study identified 418 differentially expressed genes (DEGs) using bioinformatics tools. The gene ontology of pathway enrichments employed by GO and KEGG enrichment analyses of down-regulated and up-regulated DEGs were studied. Gene expression analysis utilizing gene ontology and KEGG results uncovered biological and signaling pathways such as “cell adhesion molecules”, “plasma membrane adhesion molecules”, “synapse assembly”, and “Interleukin-3-mediated signaling” which are mostly linked to COVID-19. Our results provide in silico evidence for candidate genes which are vital for the inhibition, adhesion, and encoding cytokine protein including LYN, IGFBP5, IL-1R1, and IL-13RA1 that may have strong biomarker potential for infectious diseases such as COVID-19 related therapy targets.