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

Area of Science:

• Genomics and Bioinformatics
• Cancer Biology
• Computational Biology

Background:

• Genetic alterations drive cancer, with Protein Tyrosine Phosphatase Receptor Type H (PTPRH) playing a dual role as a tumor suppressor and oncogene.
• The function of PTPRH mutations varies by cancer type, necessitating detailed investigation of specific variants.

Purpose of the Study:

• To computationally identify and analyze missense variants of PTPRH associated with cancer progression.
• To assess the impact of these variants on protein stability, structure, and interactions.

Main Methods:

• In silico analysis of 478 missense variants from the COSMIC database using multiple prediction tools.
• Evaluation of variant impact on protein stability, evolutionary conservation, domain location, and 3D structure.
• Analysis of PTPRH interaction networks and association with cancer patient data.

Main Results:

• Identified 14 consistently damaging PTPRH missense variants across eight computational tools.
• Found 10 variants potentially disrupting PTPRH protein stability, located in critical functional regions.
• Demonstrated significant associations between PTPRH mutations and cancer progression across various datasets.

Conclusions:

• In silico methods effectively prioritize cancer-associated PTPRH variants.
• Identified variants provide a basis for future experimental validation and targeted cancer therapies.