Oncology Department, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Department of Radiotherapy, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
J Cell Biochem. 2019 Jan;120(1):592-600. doi: 10.1002/jcb.27416. Epub 2018 Sep 22.
Esophageal cancer (EC) is characteristic of early regional lymph node metastasis (LNM) and most patients with metastasis have a poor prognosis. However, the current diagnostic techniques do not enable precise differentiation of EC LNM, prognostic stratification, and individual survival estimation. To identify potential molecular biomarkers for EC patients with LNM, we explored differently expressed genes in The Cancer Genome Atlas database between 77 non-LNM cases and 88 LNM cases by limma package R. Then, according to univariate and multivariate Cox regression analyses, we constructed an 8-messenger RNA (mRNA) prognostic signature model, which could predict the outcome in a more exact way. The area under the curve of the risk score is significantly higher than other clinical information, indicating that the 8-mRNA-based risk score is a good indicator for prognosis. Then, combined with other individual risk factors, such as age, sex, T stage, M stage, etc, we could precisely calculate the individual 1-, 3-, and 5-year survival rates. The Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analysis indicate that the risk model is mainly associated with cancer-related pathways, such as cell division, cellular meiosis, and cell cycle regulation. In summary, the 8-mRNA-based risk score model that we developed successfully predicts the survival of EC. It is independent of clinical information and performing better than other clinical information for prognosis.
食管癌(EC)的特点是早期区域淋巴结转移(LNM),大多数转移患者预后不良。然而,目前的诊断技术无法准确区分 EC 的 LNM、进行预后分层和个体生存估计。为了鉴定有 LNM 的食管癌患者的潜在分子生物标志物,我们通过 limma 软件包 R 在 The Cancer Genome Atlas 数据库中对 77 例非 LNM 病例和 88 例 LNM 病例的差异表达基因进行了探索。然后,根据单变量和多变量 Cox 回归分析,我们构建了一个 8-信使 RNA(mRNA)预后签名模型,该模型可以更准确地预测结局。风险评分的曲线下面积明显高于其他临床信息,表明基于 8-mRNA 的风险评分是预后的良好指标。然后,我们可以结合其他个体风险因素,如年龄、性别、T 分期、M 分期等,精确计算个体 1、3 和 5 年的生存率。基因集富集分析、基因本体论和京都基因与基因组百科全书分析表明,风险模型主要与癌症相关途径相关,如细胞分裂、细胞减数分裂和细胞周期调节。总之,我们成功开发的基于 8-mRNA 的风险评分模型可以预测 EC 的生存情况。它独立于临床信息,并且在预后方面优于其他临床信息。