膀胱癌
转录组
医学
肿瘤科
基因签名
癌症
基因
内科学
成对比较
免疫疗法
生物信息学
基因表达
计算生物学
生物
计算机科学
遗传学
人工智能
作者
Huaping Liu,Wei Jia,Gaohaer Kadeerhan,Bo Xue,Wenmin Guo,Lu Niu,Xiaoliang Wang,Xiaolin Wu,Haitao Li,Jun Tian,Dongwen Wang,Hung-Ming Lai
标识
DOI:10.1016/j.tranon.2023.101629
摘要
TP53 is the most frequently mutated gene in muscle invasive bladder cancer (MIBC) and there are two gene signatures regarding TP53 developed for MIBC prognosis. However, they are limited to immune genes only and unable to be used individually across platforms due to their quantitative manners. We used 827 gene expression profiles from seven MIBC cohorts with varied platforms to build a pairwise TP53-derived transcriptome signature, 13 gene pairs (13-GPs). Since the 13-GPs model is a single sample prognostic predictor, it can be applied individually in practice and is applicable to any gene-expression platforms without specific normalization requirements. Survival difference between high-risk and low-risk patients stratified by the 13-GPs test was statistically significant (HR range: 2.26-2.76, all P < .0001). Discovery and validation sets showed that the 13-GPs was an independent prognostic factor after adjusting other clinical features (HR range: 2.21-2.82, all P < .05). Moreover, it was a potential supplement to the consensus molecular classification of MIBC to further stratify the LumP subtype (patients with better prognoses). High- and low-risk patients by the 13-GPs model presented distinct immune microenvironment and DDR mutation rates, suggesting that it might have the potential for immunotherapy. Being a general approach to other cancer types, this study demonstrated how we integrated gene variants with pairwise gene panels to build a single sample prognostic test in translational oncology.
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