Xiong Jie, Guo Shengyu, Bing Zhitong, Su Yanlin, Guo Le
Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Department of Computational Physics, Institute of Modern Physics of Chinese Academy of Sciences, Lanzhou, China.
Front Genet. 2019 Jan 4;9:696. doi: 10.3389/fgene.2018.00696. eCollection 2018.
Clinicopathological characteristics alone are not enough to predict the survival of patients with cervical squamous cell carcinoma (CESC) due to clinical heterogeneity. In recent years, many genes and non-coding RNAs have been shown to be oncogenes or tumor-suppressors in CESC cells. This study aimed to develop a comprehensive transcriptomic signature for CESC patient prognosis. Univariate, multivariate, and Least Absolute Shrinkage and Selection Operator penalized Cox regression were used to identify prognostic signatures for CESC patients from transcriptomic data of The Cancer Genome Atlas. A normalized prognostic index (NPI) was formulated as a synthetical index for CESC prognosis. Time-dependent receiver operating characteristic curve analysis was used to compare prognostic signatures. A prognostic transcriptomic signature was identified, including 1 microRNA, 1 long non-coding RNA, and 6 messenger RNAs. Decreased survival was associated with CESC patients being in the high-risk group stratified by NPI. The NPI was an independent predictor for CESC patient prognosis and it outperformed the known clinicopathological characteristics, microRNA-only signature, gene-only signature, and previously identified microRNA and gene signatures. Function and pathway enrichment analysis revealed that the identified prognostic RNAs were mainly involved in angiogenesis. In conclusion, we proposed a transcriptomic signature for CESC prognosis and it may be useful for effective clinical risk management of CESC patients. Moreover, RNAs in the transcriptomic signature provided clues for downstream experimental validation and mechanism exploration.
由于临床异质性,仅靠临床病理特征不足以预测宫颈鳞状细胞癌(CESC)患者的生存期。近年来,许多基因和非编码RNA已被证明是CESC细胞中的癌基因或肿瘤抑制因子。本研究旨在开发一种用于CESC患者预后的综合转录组特征。使用单变量、多变量以及最小绝对收缩和选择算子惩罚Cox回归,从癌症基因组图谱的转录组数据中识别CESC患者的预后特征。制定了一个标准化预后指数(NPI)作为CESC预后的综合指标。采用时间依赖性受试者工作特征曲线分析来比较预后特征。识别出一种预后转录组特征,包括1个微小RNA、1个长链非编码RNA和6个信使RNA。CESC患者处于由NPI分层的高危组与生存期降低相关。NPI是CESC患者预后的独立预测因子,并且它优于已知的临床病理特征、仅微小RNA特征、仅基因特征以及先前识别出的微小RNA和基因特征。功能和通路富集分析表明,识别出的预后RNA主要参与血管生成。总之,我们提出了一种用于CESC预后的转录组特征,它可能有助于对CESC患者进行有效的临床风险管理。此外,转录组特征中的RNA为下游实验验证和机制探索提供了线索。