Wang Ying, Yao Yinhui, Zhao Jingyi, Cai Chunhua, Hu Junhui, Zhao Yanwu
Department of Pharmacy, The Affiliated Hospital of Chengde Medical College, Chengde 067000, China.
Department of Functional Center, Chengde Medical College, Chengde 067000, China.
J Oncol. 2021 Feb 18;2021:8810849. doi: 10.1155/2021/8810849. eCollection 2021.
Kidney renal clear cell carcinoma (KIRC) is a fatal malignancy of the urinary system. Autophagy is implicated in KIRC occurrence and development. Here, we evaluated the prognostic value of autophagy-related genes (ARGs) in kidney renal clear cell carcinoma.
We analyzed RNA sequencing and clinical KIRC patient data obtained from TCGA and ICGC to develop an ARG prognostic signature. Differentially expressed ARGs were further evaluated by functional assessment and bioinformatic analysis. Next, ARG score was determined in 215 KIRC patients using univariable Cox and LASSO regression analyses. An ARG nomogram was built based on multivariable Cox analysis. The prognosis nomogram model based on the ARG signatures and clinicopathological information was evaluated for discrimination, calibration, and clinical usefulness.
A total of 47 differentially expressed ARGs were identified. Of these, 8 candidates that significantly correlated with KIRC overall survival were subjected to LASSO analysis and an ARG score built. Functional enrichment and bioinformatic analysis were used to reveal the differentially expressed ARGs in cancer-related biological processes and pathways. Multivariate Cox analysis was used to integrate the ARG nomogram with the ARG signature and clinicopathological information. The nomogram exhibited proper calibration and discrimination (C-index = 0.75, AUC = >0.7). Decision curve analysis also showed that the nomogram was clinically useful.
KIRC patients and doctors could benefit from ARG nomogram use in clinical practice.
肾透明细胞癌（KIRC）是泌尿系统的一种致命恶性肿瘤。自噬与KIRC的发生和发展有关。在此，我们评估了自噬相关基因（ARGs）在肾透明细胞癌中的预后价值。
我们分析了从TCGA和ICGC获得的RNA测序和临床KIRC患者数据，以建立一个ARGs预后特征。通过功能评估和生物信息学分析进一步评估差异表达的ARGs。接下来，使用单变量Cox和LASSO回归分析确定215例KIRC患者的ARGs评分。基于多变量Cox分析构建ARGs列线图。评估基于ARGs特征和临床病理信息的预后列线图模型的区分度、校准度和临床实用性。
共鉴定出47个差异表达的ARGs。其中，8个与KIRC总生存期显著相关的候选基因进行了LASSO分析并构建了ARGs评分。功能富集和生物信息学分析用于揭示癌症相关生物学过程和通路中差异表达的ARGs。多变量Cox分析用于将ARGs列线图与ARGs特征和临床病理信息整合。列线图显示出良好的校准度和区分度（C指数 = 0.75，AUC = >0.7）。决策曲线分析也表明列线图具有临床实用性。
KIRC患者和医生可从临床实践中使用ARGs列线图中获益。
