摘要

   自噬异常与癌症的发生发展密切相关。许多研究表明，自噬在肾透明细胞癌（ccRCC）的生物学功能中起重要作用。本研究旨在构建基于自噬相关基因（ARG）的 ccRCC 预后特征，以预测 ccRCC 的预后。差异表达的 ARG 从癌症基因组图谱 (TCGA) 数据库中的 ccRCC RNA-seq 数据中获得。 ARGs 被基因本体论 (GO) 和京都基因和基因组百科全书 (KEGG) 丰富。通过 Cox 回归分析确定用于构建总体生存 (OS) 和无病生存 (DFS) 风险评分模型的预后 ARG。根据风险评分的中值，将患者分为高危组和低危组。 OS和DFS采用Kaplan-Meier法进行分析。预测准确性由受试者工作特征 (ROC) 曲线分析确定。此外，我们根据不同的临床变量进行了分层分析，并评估了风险评分与临床变量之间的相关性。差异表达的 ARGs 主要富集在铂类耐药通路中。构建了基于 OS 的 11 个 ARG 和 DFS 的 5 个 ARG 的预后特征，表明高危组的生存时间显着短于低危组（P < 0.001）。 OS 的 ROC 曲线表现出良好的预测准确性，曲线下面积为 0.738。在分层分析中，高危组的 OS 时间短于按不同临床变量分层的低危组。总之，我们构建的OS自噬相关特征可以独立预测ccRCC患者的预后，并深入了解ccRCC中自噬的潜在生物学机制。

  Abnormal autophagy is closely related to the development of cancer. Many studies have demonstrated that autophagy plays an important role in biological function in clear cell renal cell carcinoma (ccRCC). This study aimed to construct a prognostic signature for ccRCC based on autophagy-related genes (ARGs) to predict the prognosis of ccRCC. Differentially expressed ARGs were obtained from ccRCC RNA-seq data in The Cancer Genome Atlas (TCGA) database. ARGs were enriched by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The prognostic ARGs used to construct the risk score models for overall survival (OS) and disease-free survival (DFS) were identified by Cox regression analyses. According to the median value of the risk score, patients were divided into a high-risk group and a low-risk group. The OS and DFS were analyzed by the Kaplan-Meier method. The predictive accuracy was determined by a receiver operating characteristic (ROC) curve analysis. Additionally, we performed stratification analyses based on different clinical variables and evaluated the correlation between the risk score and the clinical variables. The differentially expressed ARGs were mainly enriched in the platinum drug resistance pathway. The prognostic signatures based on 11 ARGs for OS and 5 ARGs for DFS were constructed and showed that the survive time was significantly shorter in the high-risk group than in the low-risk group (P < 0.001). The ROC curve for OS exhibited good predictive accuracy, with an area under the curve value of 0.738. In the stratification analyses, the OS time of the high-risk group was shorter than that of the low-risk group stratified by different clinical variables. In conclusion, an autophagy-related signature for OS we constructed can independently predict the prognosis of ccRCC patient, and provide a deep understanding of the potential biological mechanisms of autophagy in ccRCC.
    Keywords: autophagy, clear cell renal cell carcinoma, prognosis, the cancer genome atlas, platinum drug resistance

  https://www.scirp.org/journal/paperinformation.aspx?paperid=98871