Integrated bioinformatics and molecular docking identify novel key genes, pathways, and potential candidate drugs in papillary thyroid carcinoma

Abstract

Papillary thyroid carcinoma (PTC) is the most prevalent form of well-differentiated cancer of the thyroid gland. In the current study, we applied integrated bioinformatics analyses to introduce key genes with diagnostic and prognostic value, and decipher the signaling pathways involved in patients with PTC. We analyzed four integrated profiles from Gene Expression Omnibus (GEO) including, GSE58545, GSE3467, GSE29265, and GSE60542. GEO2R was utilized to analyze and detect differentially expressed genes (DEGs), and then the results of four datasets were integrated. Gene ontology (GO), KEGG-related pathway, protein-protein interaction (PPI) network, survival, and immunohistochemical assessment were performed by DAVID, ShinyGO, STRING, GEPIA, and Human Protein Atlas (HPA), respectively. In addition, we performed molecular docking of hub genes with 1615 FDA approved drugs. The findings of GO enrichment indicated that the up- and down-regulated genes were mostly participating in cell adhesion, extracellular region, and bicarbonate transport, proteinaceous extracellular receptor complex, respectively. Pathway enrichment indicated that the upregulated genes were linked with ECM-receptor interaction, and downregulated genes were largely involved in tyrosine metabolism and the JAK/STAT signaling pathway. The FN1, DPP, CD36, KIT, and ITGA2 proteins and hsa-mir-124-3p were identified as druggable target genes. According to docking analysis, Olysio, Gabapentin, Naldemedine, Imatinib and Enzacamene were drugs that exhibited strong interactions with the target proteins. The findings of the current study offer that FN1, DPP4, CD36, KIT, ITGA2 and hsa-miR-124-3p may be novel biosignatures and therapeutic targets for PTC. In addition, it was demonstrated that discovered pharmaceuticals may be employed as prospective PTC treatments.