Whole-Genome Sequencing Reveals a Novel GATA2 Mutation in Lower-Grade Glioma: Bioinformatics Analysis of Functional and Therapeutic Implications

Handoko, null and Lau, Vincent and Susanto, Eka and Aman, Renindra Ananda and Heriyanto, Didik Setyo and Gondhowiardjo, Soehartati A. (2025) Whole-Genome Sequencing Reveals a Novel GATA2 Mutation in Lower-Grade Glioma: Bioinformatics Analysis of Functional and Therapeutic Implications. Cancers, 17 (20): 3338. ISSN 20726694

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Abstract

Background/Objectives: Lower-grade gliomas, particularly IDH-mutant astrocytomas, represent a distinct molecular subtype with unique therapeutic challenges. Whole-genome sequencing (WGS) plays a crucial role in uncovering genetic alterations that drive glioma pathogenesis and therapeutic resistance. This study identifies and evaluates a novel GATA2 p.Arg396Trp mutation in a clinical sample of lower-grade glioma, assessing its structural impact and implications for drug binding. Methods: A WHO Grade II astrocytoma specimen from a 33-year-old female patient was analyzed using WGS with Oxford Nanopore sequencing, followed by comprehensive bioinformatics processing to identify genomic variants. The GATA2 p.Arg396Trp mutation was evaluated using protein modeling, structural analysis, and pathogenicity prediction tools. Drug affinity analysis was conducted using molecular docking simulations to assess the computational impact of the mutation on drug binding. Results: The GATA2 p.Arg396Trp mutation was identified as a computationally predicted pathogenic variant, potentially disrupting protein interactions within critical functional domains. Structural analysis revealed altered binding dynamics with key anti-neoplastic agents, suggesting potential implications for therapeutic response. These findings represent computational predictions requiring experimental validation. Conclusions: Our preliminary findings suggest a potential role of the GATA2 p.Arg396Trp mutation in lower-grade glioma pathogenesis. The mutation predicted impact on transcriptional regulation and drug affinity suggests GATA2 as a possible biomarker candidate. Extensive experimental validation in larger patient cohorts is needed to establish clinical relevance and explore targeted therapeutic strategies. © 2025 by the authors.

Item Type: Article
Additional Information: Cited by: 0; All Open Access; Gold Open Access; Green Open Access
Uncontrolled Keywords: antineoplastic agent; biological marker; protein p53; transcription factor GATA 2; transcriptome; adult; Article; astrocytoma; bioinformatics; cancer grading; cancer prognosis; carcinogenesis; case report; clinical article; cohort analysis; controlled study; copy number variation; DNA extraction; DNA methylation; female; flow cytometry; gene expression; gene mutation; gene ontology; gene set enrichment analysis; glioblastoma; glioma; high throughput sequencing; human; human tissue; machine learning; missense mutation; molecular docking; overall survival; pathogenicity; personalized medicine; phenotype; polymerase chain reaction; prediction; protein expression; protein function; real time polymerase chain reaction; risk factor; RNA sequencing; Sanger sequencing; simulation; single nucleotide polymorphism; somatic mutation; transcriptomics; treatment response; whole exome sequencing
Subjects: R Medicine > RB Pathology
Divisions: Faculty of Medicine, Public Health and Nursing > Non Surgical Divisions
Depositing User: Ani PURWANDARI
Date Deposited: 22 Jul 2026 02:00
Last Modified: 22 Jul 2026 02:00
URI: https://ir.lib.ugm.ac.id/id/eprint/28281

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