- European Journal of Biology
- Vol: 79 Issue: 2
- Somatic Missense Mutations of Histone Variant H3.3 in Central Nervous System Cancers
Somatic Missense Mutations of Histone Variant H3.3 in Central Nervous System Cancers
Authors : Burcu Biterge Sut
Pages : 75-82
View : 15 | Download : 20
Publication Date : 2020-12-25
Article Type : Research
Abstract :ABSTRACT Objective: Histone variants are important modulators of chromatin functions. Studies have pointed out that epigenetic factors are often dysregulated in carcinogenesis. Although some cancer-associated mutations of the histone variant H3.3 have been identified previously, a complete list of H3.3 mutations and their potential effects is yet to be uncovered. Therefore, this study aims to identify the missense mutations of the histone variant H3.3 in central nervous system (CNS) cancers and to computationally predict their functional consequences on pathogenicity, protein stability and structure. Materials and Methods: A complete set of human H3.3 mutations was acquired from the COSMIC v90 database and missense mutations were selected. The potential effects of these mutations were assessed using PredictSNP2 and FATHMM-XF. Structural outcomes were predicted using MUpro and HOPE servers. Results: We identified 45 unique missense H3.3 substitutions in several tissues including CNS. PredictSNP2 and FATHMM-XF predicted 17 and 42 mutations as deleterious respectively, most of which caused decreased protein stability. Amino acid alterations in CNS cancers were predicted to cause alterations of the 3D structure. Conclusion: Histone variants play significant roles in epigenetic regulation and are often mutated in cancers. Our results showed that H3.3 mutations detected in CNS cancers could affect the genomic distribution of post-translational modifications and histone variants, hence dramatically alter the gene expression profile and contribute to carcinogenesis. Keywords: Epigenetics, histone variant H3.3, mutation analysis, cancerKeywords : Epigenetics, histone variant H3.3, mutation analysis, cancer