Development of an Autophagy Score Signature for Predicting Overall Survival in Papillary Renal Cell Carcinoma

• Main Authors: Xiang Gu, Xiaojun Chen, Lei Zhu, Wenbo Song, Ali Wang, Junfeng Chu, Tao Wang, Peng Jiang, Yizhi Ge
• Format: Article
• Language: English
• Published: Hindawi Limited 2020-01-01
• Series: Disease Markers
• Online Access: http://dx.doi.org/10.1155/2020/8867019

Background. Autophagy is considered to be closely associated with cancer, functioning as either an anticancer or procancer mechanism depending on the cancer stage. However, the prognostic value of autophagy on papillary renal cell carcinoma (pRCC) remains unclear. In this study, our purpose was to determine the autophagy-related mRNA signature to predict the overall survival of patients with pRCC. Materials and Methods. A total of 284 patients with pathologic confirmed pRCC in The Cancer Genome Atlas (TCGA) dataset were recruited and included. We choose patients who have smoked less than 15 years but staging 3 or 4 (including nontobacco exposure) vs. more than 15 years but staging 1 or 2. Fourteen differentially expressed mRNAs were found with fold change>2 and P value < 0.001 through limma package after making a pair between nontobacco exposure or less than 15 years and tobacco exposure more than 15 years by matchIt package. Results. Six mRNAs were identified to be significantly associated with overall survival. Then, using a risk score based on the signature of these six mRNAs, we divided the patients into low-risk and high-risk groups with significantly different OS. Further multivariate Cox regression analyses revealed that the 6-mRNA signature was independent of age, TNM stage, and tumor type. In the present study, a novel 6-mRNA signature that is useful in survival prediction in pRCC patients was developed. If validated, this mRNA signature might assist in selecting high-risk subpopulation that needs more aggressive therapeutic intervention. The risk score involved in several cancer-related pathways was identified using gene set enrichment analysis. Conclusion. We initially generated a six autophagy-related genes’ signature, which correlates with AJCC N stage, tumor type, and pathological stage and independently predicts OS.