Nedjadi Taoufik, Ansari Hifzur, Khan Muhammad A, Sannan Naif, Al-Mansour Mubarak, Al-Maghrabi Jaudah, Dallol Ashraf
King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, P.O Box 9515, Jeddah, 21423, Saudi Arabia.
College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
Sci Rep. 2025 Jul 2;15(1):23292. doi: 10.1038/s41598-025-04363-z.
Bladder cancer (BC) displays a huge phenotypic variation and widespread clinical outcomes, attributed to the high mutational heterogeneity of the disease. Mutational landscaping became integral to cancer patient management as it unveils driver genes and yields genotype-phenotype associations. This study aims to identify somatic mutations, their frequencies and their associations with clinical and prognostic outcomes in BC. Eighty-one BC patients were analyzed by next-generation sequencing using the Ion AmpliSeq Cancer Hotspots Panel v2. Bioinformatics analysis, correlation studies and Kaplan-Meier curve were used to evaluate the relationship between genes' mutational status and patients' clinical parameters and outcomes. Our results indicated that the BC cohort exhibited a higher mutation burden than the TCGA data. Mutations were identified in 46 out of 50 genes, including 21 novel mutations not previously reported in BC. The TP53 gene was mutated in 82.5% of the analyzed cohort, followed by PIK3 CA (45%), FGFR3 (43.75%) and APC (35%). TP53 mutations were associated with poor survival (p = 0.003) while the FGFR3 mutation group exhibited signs of good prognosis (p = 0.018). Bioinformatics highlighted significant gene interactions associated with poor prognosis. These findings underline the importance of identifying novel genetic mutations that could significantly improve prognostic stratification and expand therapeutic options for managing BC patients.
膀胱癌(BC)表现出巨大的表型变异和广泛的临床结果,这归因于该疾病的高突变异质性。突变图谱对于癌症患者管理至关重要,因为它揭示了驱动基因并产生基因型 - 表型关联。本研究旨在识别BC中的体细胞突变、其频率以及它们与临床和预后结果的关联。使用Ion AmpliSeq癌症热点面板v2通过下一代测序对81例BC患者进行了分析。生物信息学分析、相关性研究和Kaplan-Meier曲线用于评估基因的突变状态与患者临床参数和结果之间的关系。我们的结果表明,BC队列的突变负担高于TCGA数据。在50个基因中的46个中鉴定出突变,包括21个先前在BC中未报道的新突变。在82.5%的分析队列中TP53基因发生突变,其次是PIK3 CA(45%)、FGFR3(43.75%)和APC(35%)。TP53突变与较差的生存率相关(p = 0.003),而FGFR3突变组表现出良好预后的迹象(p = 0.018)。生物信息学突出了与不良预后相关的显著基因相互作用。这些发现强调了识别新基因突变的重要性,这些新基因突变可以显著改善预后分层并扩大治疗BC患者的选择。