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Genetic mutation patterns among glioblastoma patients in the Taiwanese population - insights from a single institution retrospective study.

Yu-Fen HuangMing-Tsang ChiaoTzu-Hung HsiaoYong-Xiang ZhanTse-Yu ChenChung-Hsin LeeSzu-Yuan LiuChih-Hsiang LiaoWen-Yu ChengChun-Ming YenChih-Ming LaiJun-Peng ChenChiung-Chyi ShenMeng-Yin Yang
Published in: Cancer gene therapy (2024)
This study utilized Next-Generation Sequencing (NGS) to explore genetic determinants of survival duration in Glioblastoma Multiforme (GBM) patients. We categorized 30 primary GBM patients into two groups based on their survival periods: extended survival (over two years, N = 17) and abbreviated survival (under two years, N = 13). For identifying pathogenic or likely pathogenic variants, we leveraged the ClinVar database. The cohort, aged 23 to 66 (median: 53), included 17 patients in Group A (survival >2 years, 10 males, 7 females), and 13 patients in Group B (survival <2 years, 8 males, 5 females), with a 60% to 40% male-to-female ratio. Identified mutations included CHEK2 (c.1477 G > A, p.E493K), IDH1 (c.395 G > A, p.R132H), and TP53 mutations. Non-coding regions exhibited variants in the TERT promoter (c.-146C > T, c.-124C > T) and TP53 RNA splicing site (c.376-2 A > C, c.376-2 A > G). While Group A had more mutations, statistical significance wasn't reached, likely due to sample size. Notably, TP53, and ATR displayed a trend toward significance. Surprisingly, TP53 mutations were more prevalent in Group A, contradicting Western findings on poorer GBM prognosis. In Taiwanese GBM patients, bevacizumab usage is linked to improved survival rates, affirming its safety and effectiveness. EGFR mutations are infrequent, suggesting potential distinctions in carcinogenic pathways. Further research on EGFR mutations and amplifications is essential for refining therapeutic approaches. TP53 mutations are associated with enhanced survival, but their functional implications necessitate detailed exploration. This study pioneers genetic analysis in Taiwanese GBM patients using NGS, advancing our understanding of their genetic landscape.
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