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• W4379285871 abstract "e14041 Background: The gender, age and family history of patients are important factors leading to the mutation of tumor-related genes. Currently, the relationship between these factors and tumor gene mutations in glioma is unclear. Therefore, we identified the effect of gender, age, and family history on cancer-susceptibility gene mutations in patients with glioma through retrospective analysis. Methods: A total of 735 FFPE tissue samples were collected from 2019 to 2022 in glioma patients, and sequenced by HapOnco StarPanel NGS Assay (covering 1326 genes + 3 viral sequences). Results: (1) These mutations were categorized into four subgroups according to the age of the patients. In the 0-20 years group, the main mutated genes were TP53 (63.64%), BRAF (36.36%), and H3F3A (22.73%) in females (n = 22) and TP53 (26.92%), BRAF (46.15%) and H3F3A (19.23%) in males (n = 26), respectively. In the 21-40 age group, the gene mutation rates of TP53, IDH1, and TERT were 71.43%, 58.57%, and 21.43% in female (n = 70), whereas these genes ( TP53, 72.90%; IDH1, 63.55%; TERT, 35.51%) displayed higher mutation frequency in males (n = 107). In the 41-60 age group, TERT (61.70%), TP53 (43.97%), and IDH1 (36.88%) in females (n = 141) showed obvious difference compared with that ( TERT, 54.33%; TP53, 47.12%; IDH1, 42.31%) in male (n = 208). Aged patients, especially those over 61 years, the most mutated genes were TERT (63.08%), EGFR (60.00%), and TP53 (49.23%) in female (n = 65), respectively. However, the most commonly mutated genes in male presented apparently different than the genes in female such as LRP1B, CSMD3, SYNE1, NF1, ATM, PTEN, RB1, TERT, MET, and TP53. (2) Generally, the peak incidence of patients with glioma is between 41-60 years old. We found the percentage of the total incidence of glioma patients was associated with the family history (positive, 56.25%; negative, 47.68%). Conclusions: The gene mutated rates were depending on the age, sex, and family history in glioma, which might reveal potential effect for biomarker detection in combination with these categories in clinical." @default.
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• W4379285871 date "2023-06-01" @default.
• W4379285871 modified "2023-10-15" @default.
• W4379285871 title "Mutation profiling of gliomas based on sex, age, and family history." @default.
• W4379285871 doi "https://doi.org/10.1200/jco.2023.41.16_suppl.e14041" @default.
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