摘要

    背景
几项研究表明自噬在食管癌发展过程中的重要性。该研究的目的是根据食管癌病例中主要自噬相关基因（ARG）的表达谱构建评分系统。

方法
癌症基因组图谱用于获得食道癌数据。此后，使用在线数据库Oncolnc（http://www.oncolnc.org/）验证了我们结果的准确性。根据我们的结果，纳入的ARG与总体生存期（OS）相关。

结果
我们检测到ARG在食管癌和正常食管组织中的表达模式。此外，我们鉴定了自噬相关基因集，包括14个在预测食管癌预后中显示出显着意义的基因。 Cox回归结果显示，筛选了7个ARG（包括TBK1，ATG5，HSP90AB1，VAMP7，DNAJB1，GABARAPL2和MAP2K7）以计算ARG得分。通常，具有较高ARGs得分的患者与较差的OS相关。此外，接受者操作特征（ROC）曲线分析表明，ARG可以准确地区分食管癌患者和健康人，曲线下面积（AUC）值> 0.6。

    Background
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.

Methods
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).

Results
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.

    https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-07303-4