Department of Intensive Care Unit, State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Dong Road, Guangzhou, 510060, People's Republic of China.
Guangzhou Institute of Respiratory Diseases, State Key Laboratory of Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
BMC Cancer. 2020 Aug 24;20(1):797. doi: 10.1186/s12885-020-07303-4.
Several works suggest the importance of autophagy during esophageal carcinoma development. The aim of the study is to construct a scoring system according to the expression profiles of major autophagy-related genes (ARGs) among esophageal carcinoma cases.
The Cancer Genome Atlas was employed to obtain the esophageal carcinoma data. Thereafter, the online database Oncolnc ( http://www.oncolnc.org/ ) was employed to verify the accuracy of our results. According to our results, the included ARGs were related to overall survival (OS).
We detected the expression patterns of ARG within esophageal carcinoma and normal esophageal tissues. In addition, we identified the autophagy related gene set, including 14 genes displaying remarkable significance in predicting the esophageal carcinoma prognosis. The cox regression results showed that, 7 ARGs (including TBK1, ATG5, HSP90AB1, VAMP7, DNAJB1, GABARAPL2, and MAP2K7) were screened to calculate the ARGs scores. Typically, patients with higher ARGs scores were associated with poorer OS. Moreover, the receiver operating characteristic (ROC) curve analysis suggested that, ARGs accurately distinguished the healthy people from esophageal carcinoma patients, with the area under curve (AUC) value of > 0.6.
A scoring system is constructed in this study based on the main ARGs, which accurately predicts the outcomes for esophageal carcinoma.
多项研究表明自噬在食管癌发展过程中的重要性。本研究旨在根据食管癌病例中主要自噬相关基因（ARGs）的表达谱构建评分系统。
采用癌症基因组图谱（The Cancer Genome Atlas）获取食管癌数据。然后，使用在线数据库 Oncolnc（http://www.oncolnc.org/）验证我们结果的准确性。根据我们的结果，所纳入的 ARGs 与总生存期（OS）相关。
我们检测了 ARG 在食管癌和正常食管组织中的表达模式。此外，我们确定了自噬相关基因集，包括 14 个在预测食管癌预后方面具有显著意义的基因。Cox 回归结果表明，7 个 ARG（包括 TBK1、ATG5、HSP90AB1、VAMP7、DNAJB1、GABARAPL2 和 MAP2K7）被筛选出来计算 ARGs 评分。通常，具有更高 ARGs 评分的患者与较差的 OS 相关。此外，受试者工作特征（ROC）曲线分析表明，ARGs 能够准确地区分健康人和食管癌患者，曲线下面积（AUC）值>0.6。
本研究基于主要的 ARGs 构建了评分系统，能够准确预测食管癌的预后。
