Li Yawei, Zhang Huarong, Guo You, Cai Hao, Li Xiangyu, He Jun, Lai Hung-Ming, Guan Qingzhou, Wang Xianlong, Guo Zheng
Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Medical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Front Oncol. 2019 Jul 10;9:629. doi: 10.3389/fonc.2019.00629. eCollection 2019.
Previously reported transcriptional signatures for predicting the prognosis of stage I-III bladder cancer (BLCA) patients after surgical resection are commonly based on risk scores summarized from quantitative measurements of gene expression levels, which are highly sensitive to the measurement variation and sample quality and thus hardly applicable under clinical settings. It is necessary to develop a signature which can robustly predict recurrence risk of BLCA patients after surgical resection. The signature is developed based on the within-sample relative expression orderings (REOs) of genes, which are qualitative transcriptional characteristics of the samples. A signature consisting of 12 gene pairs (12-GPS) was identified in training data with 158 samples. In the first validation dataset with 114 samples, the low-risk group of 54 patients had a significantly better overall survival than the high-risk group of 60 patients (HR = 3.59, 95% CI: 1.349.62, = 6.61 × 10). The signature was also validated in the second validation dataset with 57 samples (HR = 2.75 × 10, 95% CI: 0Inf, = 0.05). Comparison analysis showed that the transcriptional differences between the low- and high-risk groups were highly reproducible and significantly concordant with DNA methylation differences between the two groups. The 12-GPS signature can robustly predict the recurrence risk of stage I-III BLCA patients after surgical resection. It can also aid the identification of reproducible transcriptional and epigenomic features characterizing BLCA metastasis.
先前报道的用于预测Ⅰ-Ⅲ期膀胱癌(BLCA)患者手术切除后预后的转录特征通常基于基因表达水平定量测量得出的风险评分,这些评分对测量变异和样本质量高度敏感,因此在临床环境中几乎无法应用。有必要开发一种能够可靠预测BLCA患者手术切除后复发风险的特征。该特征是基于样本内基因的相对表达顺序(REO)开发而成的——样本的定性转录特征。在包含158个样本的训练数据中鉴定出了一个由12个基因对组成的特征(12-GPS)。在第一个包含114个样本的验证数据集中,54例低风险组患者的总生存期显著优于60例高风险组患者(HR = 3.59;95% CI:1.349.62;P = 6.61×1)。该特征在第二个包含57个样本的验证数据集中也得到了验证(HR = 2.75×1;95% CI:OInf;P = 0.05)。比较分析表明,低风险组和高风险组之间的转录差异具有高度可重复性,并且与两组之间的DNA甲基化差异显著一致。12-GPS特征能够可靠地预测Ⅰ-Ⅲ期BLCA患者手术切除后的复发风险。它还有助于识别表征BLCA转移的可重复的转录和表观基因组特征。