Functional impact assessment of tissue-specific missense variants in the PTPRH gene using a multi-tool computational...

Cancer is driven by genetic alterations that disrupt cellular processes, and one key gene involved in this progression is Protein Tyrosine Phosphatase Receptor Type H (PTPRH). Acting as both a tumor suppressor and oncogene, the role of PTPRH varies across cancer types. Mutations in PTPRH can either promote cancer or act as tumor suppressors, depending on the type of tissue in which they occur. This project investigates missense variants of PTPRH using in silico analysis. From the COSMIC database, 478 unique missense variants were identified, with 14 variants consistently predicted as damaging across eight computational tools (fathmm, PROVEAN, PolyPhen-2, SIFT, PANTHER, Align-GVGD, SNPs&GO, and PhD-SNP). These variants were analyzed for their impact on protein stability using several prediction tools (MUpro, I-Mutant, MCSM, Missense3D, SDM, DUET, DynaMut, and ENCoM), with 10 variants showing potential disruption of PTPRH protein stability. Evolutionary conservation analysis revealed high conservation scores for all 14 variants, indicating the structural importance of these variants. The domain profiling also revealed their location in key regions of the protein. The 3D protein structures were constructed by homology modeling using the Swiss-Model server. Further analysis using GeneMANIA and STRING highlighted the broader impacts of these mutations on PTPRH interactions and cellular pathways. Investigating the association of PTPRH mutations with various cancer types using CanSAR.ai, cBioPortal, Kaplan-Meier Plotter, and GEPIA revealed their significance in cancer progression. These findings emphasize the utility of in silico analysis in prioritizing cancer-associated variants and provide a rational foundation for future experimental validation and targeted therapeutic investigation.