Exemestane for COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARSCoV 2) is a coronavirus variation responsible for COVID19, the respiratory disease that triggered the COVID19 pandemic. The primary aim of our study is to elucidate the complex network of interactions between SARS CoV 2, tuberculosis, and lung cancer employing a bioinformatics and network biology approach. Lung cancer is the leading cause of significant illness and death connected to cancer worldwide. Tuberculosis (TB) is a prevalent medical condition induced by the Mycobacterium bacteria. It mostly affects the lungs but may also have an influence on other areas of the body. Coronavirus disease (COVID19) causes a risk of respiratory complications between lung cancer and tuberculosis. SARSCoV 2 impacts the lower respiratory system and causes severe pneumonia, which can significantly increase the mortality risk in individuals with lung cancer. We conducted transcriptome analysis to determine molecular biomarkers and common pathways in lung cancer, TB, and COVID19, which provide understanding into the association of SARSCoV 2 to lung cancer and tuberculosis. Based on the compatible RNA-seq data, our research employed GREIN and NCBI's Gene Expression Omnibus (GEO) to perform differential gene expression analysis. Our study exploited three RNAseq datasets from the Gene Expression Omnibus (GEO) GSE171110, GSE89403, and GSE81089 to identify distinct relationships between differentially expressed genes (DEGs) in SARSCoV 2, tuberculosis, and lung cancer. We identified 30 common genes among SARSCoV 2, tuberculosis, and lung cancer (25 upregulated genes and 5 downregulated genes). We analyzed the following five databases: WikiPathway, KEGG, Bio Carta, Elsevier Pathway and Reactome. Using Cytohubba's MCC and Degree methods, We determined the top 15 hub genes resulting from the PPI interaction. These hub genes can serve as potential biomarkers, leading to novel treatment strategies for disorders under investigation. Transcription factors (TFs) and microRNAs (miRNAs) were identified as the molecules that control the differentially expressed genes (DEGs) of interest, either during transcription or after transcription. We identified 35 prospective therapeutic compounds that form significant differentially expressed genes (DEGs) in SARSCoV 2, lung cancer, and tuberculosis, which could potentially serve as medications. We hypothesized that the potential medications that emerged from this investigation may have therapeutic benefits.

AbstractHuman organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single‐cell RNA sequencing (scRNA‐seq) technology and genome‐wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait‐relevant cell types or states. Here, we constructed a computational framework to integrate atlas‐level organoid scRNA‐seq data, GWAS summary statistics, expression quantitative trait loci, and gene–drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID‐19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID‐19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID‐19‐damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID‐19, and this cell subset showed a notable increase in cell‐to‐cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID‐19 in a cell‐type‐specific manner. Overall, our results showcase that host genetic determinants have cellular‐specific contribution to COVID‐19 severity, and identification of cell type‐specific drug targets may facilitate to develop effective therapeutics for treating severe COVID‐19 and its complications.