Immune cells transcriptome-based drug repositioning for multiple sclerosis

Abstract

ObjectiveFinding target genes and target pathways of existing drugs for drug repositioning in multiple sclerosis (MS) based on transcriptomic changes in MS immune cells.Materials and MethodsBased on transcriptome data from Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) in MS patients without treatment were identified by bioinformatics analysis according to the type of immune cells, as well as DEGs in MS patients before and after drug administration. Hub target genes of the drug for MS were analyzed by constructing the protein-protein interaction network, and candidate drugs targeting 2 or more hub target genes were obtained through the connectivity map (CMap) database and Drugbank database. Then, the enriched pathways of MS patients without treatment and the enriched pathways of MS patients before and after drug administration were intersected to obtain the target pathways of the drug for MS, and the candidate drugs targeting 2 or more target pathways were obtained through Kyoto Encyclopedia of Genes and Genomes (KEGG) database.ResultsWe obtained 50 hub target genes for CD4+ T cells in Fingolimod for MS, 15 hub target genes for Plasmacytoid dendritic cells (pDCs) and 7 hub target genes for Peripheral blood mononuclear cells (PBMC) in interferon-β (IFN-β) for MS. 6 candidate drugs targeting two or more hub targets (Fostamatinib, Copper, Artenimol, Phenethyl isothiocyanate, Aspirin and Zinc) were obtained. In addition, we obtained 4 target pathways for CD19+ B cells and 15 target pathways for CD4+ T cells in Fingolimod for MS, 7 target pathways for pDCs and 6 target pathways for PBMC in IFN-β for MS, most of which belong to the immune system and viral infectious disease pathways. We obtained 69 candidate drugs targeting two target pathways.ConclusionWe found that applying candidate drugs that target both the “PI3K-Akt signaling pathway” and “Chemokine signaling pathway” (e.g., Nemiralisib and Umbralisib) or applying tyrosine kinase inhibitors (e.g., Fostamatinib) may be potential therapies for the treatment of MS.

An AI Approach to Identifying Novel Therapeutics for Rheumatoid Arthritis

“…Comparisons of the disease gene signature against a perturbation gene expression database revealed potential markers and candidate drugs as promising therapeutics for the condition. Another study in multiple sclerosis, a complex inflammatory disease involving multiple disease pathways, used the CMap approach to analyse immune cell changes in transcriptomic datasets to identify potential target genes and candidate drugs from the CMAP database and Drug-Bank database that can be repositioned to engage multiple treatment pathways [59]. Cystic fibrosis and Huntington's disease studies have validated the effectiveness of the CMap approach to identify small molecules with the potential to inhibit the disease state or regulate the expression of a small number of genes.…”

Insrr Regulates IFN-β through Regulation of Actin Cytoskeleton Pathway in Rat Hepatocellular Carcinoma

“…9C) PI3K-Akt signaling pathway, HIF-1 signaling pathway, Jak-STAT signaling pathway, cAMP signaling pathway, Endocytosis, Ras signaling pathway, AMPK signaling pathway, Chemokine signaling pathway, and other pathways are able to regulate IFN-β. [19][20][21] Therefore, we screened the genes that may affect the expression of IFN-β during the development of rat hepatocellular carcinoma, and the genes were ranked in descending order of the degree of up-regulation of the genes in rat hepatocellular carcinoma as Ckmt1, Ncam1, Tnfsf18, Ccl11, Insrr, Htr1b, Rasal1, Cldn18, LOC298795, Izumo1r, and Pde1c. Next, we will validate the obtained candidate genes.…”