Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China (mainland).
School of Basic Medical Sciences, Hebei Medical University, Shijiazhuang, Hebei, China (mainland).
Med Sci Monit. 2020 May 16;26:e921855. doi: 10.12659/MSM.921855.
BACKGROUND Esophageal carcinoma (ESCA) is associated with a poor prognosis and high mortality rate. Autophagy plays important roles in promoting or suppressing tumor cell survival at different stages of cancer development. However, the roles of autophagy-related genes (ARGs) during ESCA progression and in patient prognosis remain unclear. Accordingly, in this study, we aimed to identify the relationships of ARGs with ESCA progression and patient prognosis. MATERIAL AND METHODS Clinicopathological information for patients with ESCA was downloaded from The Cancer Genome Atlas (TCGA) database. Transcriptome expression profiles were downloaded from TCGA and GTEx databases, and ARGs were downloaded from the Human Autophagy Database. We investigated the functions of ARGs by bioinformatics analysis. Moreover, statistical analysis of these genes was performed to identify independent prognostic markers. RESULTS Differentially expressed genes between normal and tumor tissues were detected and identified. GO and KEGG analyses of differentially expressed ARGs were performed. Moreover, we derived a risk signature based on the identified independent prognostic markers. The identified genes also could predict the clinicopathological features of ESCA. CONCLUSIONS ARGs were key participants in the tumorigenesis and development of ESCA. Our findings may be useful for developing improved therapeutic approaches for ESCA.
食管癌（ESCA）预后差，死亡率高。自噬在癌症发展的不同阶段促进或抑制肿瘤细胞存活中发挥重要作用。然而，自噬相关基因（ARGs）在 ESCA 进展和患者预后中的作用尚不清楚。因此，在本研究中，我们旨在确定 ARGs 与 ESCA 进展和患者预后的关系。
从癌症基因组图谱（TCGA）数据库下载 ESCA 患者的临床病理信息。从 TCGA 和 GTEx 数据库下载转录组表达谱，从人类自噬数据库下载 ARGs。我们通过生物信息学分析研究 ARGs 的功能。此外，对这些基因进行统计学分析，以确定独立的预后标志物。
检测并鉴定了正常组织和肿瘤组织之间差异表达的基因。对差异表达的 ARGs 进行了 GO 和 KEGG 分析。此外，我们基于鉴定的独立预后标志物得出了一个风险特征。这些基因还可以预测 ESCA 的临床病理特征。
ARGs 是 ESCA 发生和发展的关键参与者。我们的研究结果可能有助于开发 ESCA 的改进治疗方法。
