A Risk Signature with Autophagy-Related Long Noncoding RNAs for Predicting the Prognosis of Clear Cell Renal Cell Carcinoma: Based on the TCGA Database and Bioinformatics.

Yundong Xuan,Baojun Wang,Shidong Zuo,Xin Ma,Yu Gao,Xu Zhang,Weihao Chen,Kan Liu

doi:10.1155/2021/8849977

Abstract

Background Disorders of autophagic processes have been reported to affect the survival outcome of clear cell renal cell carcinoma (ccRCC) patients. The purpose of our study was to identify and validate the candidate prognostic long noncoding RNA signature of autophagy. Methods Transcriptome profiles were obtained from The Cancer Genome Atlas. The autophagy gene list was obtained from the Human Autophagy Database. Based on coexpression analysis, we obtained a list of autophagy-related lncRNAs (ARlncRNAs). GO enrichment analysis and KEGG pathway analysis were conducted to explore the functional annotation of these ARlncRNAs. Univariate and multivariate Cox regression analyses were conducted to elucidate the correlation between overall survival and the expression level of each ARlncRNAs. We then established a prognostic signature that was a linear combination of the regression coefficients from the multivariate Cox regression model (β) multiplied by the expression levels of the respective ARlncRNAs in the training cohort. The predictive performance was tested in the validation cohort. Additionally, the independence of the risk signature was assessed, and the relationship between the risk signature and conventional clinicopathological features was explored. Results Seven autophagy-related lncRNAs with prognostic value (SNHG3, SNHG17, MELTF-AS1, HOTAIRM1, EPB41L4A-DT, AP003352.1, and AC145423.2) were identified and integrated into a risk signature, dividing patients into low-risk and high-risk groups. The risk signature was independent of conventional clinical characteristics as a prognostic indicator of ccRCC (HR, 1.074, 95% confidence interval: 1.036-1.113, p < 0.001) and was valuable in the prediction of ccRCC progression. Conclusion Our risk signature has potential prognostic value in ccRCC, and these ARlncRNAs may play a significant role in ccRCC tumor biology.

Highlights

Renal cell carcinoma (RCC), a principal malignancy of the renal tubular epithelium, ranks third among urinary cancers1 [1]
The purpose was to help develop a deeper understanding of the autophagy process, and the results shown in Table 4 revealed that each of those prognostic ARlncRNAs was significantly associated with clinicopathological features that are closely connected with tumor progression, including International Society of Urological Pathology (ISUP) grade, American Joint Committee on Cancer (AJCC) stage, T stage, and N stage
Unlike previous studies that focused on the role of autophagy-related genes in tumorigenesis and progression [28,29,30], our study is aimed at improving prognostic prediction by finding autophagy-related Long noncoding RNAs (lncRNAs) associated with the poor prognosis of clear cell renal cell carcinoma (ccRCC) through comprehensive bioinformatics analysis in TCGA databases

Summary

Introduction

Renal cell carcinoma (RCC), a principal malignancy of the renal tubular epithelium, ranks third among urinary cancers1 [1]. Disorders of autophagic processes have been reported to affect the survival outcome of clear cell renal cell carcinoma (ccRCC) patients. The purpose of our study was to identify and validate the candidate prognostic long noncoding RNA signature of autophagy. We obtained a list of autophagy-related lncRNAs (ARlncRNAs). Seven autophagy-related lncRNAs with prognostic value (SNHG3, SNHG17, MELTF-AS1, HOTAIRM1, EPB41L4A-DT, AP003352.1, and AC145423.2) were identified and integrated into a risk signature, dividing patients into low-risk and high-risk groups. The risk signature was independent of conventional clinical characteristics as a prognostic indicator of ccRCC (HR, 1.074, 95% confidence interval: 1.036-1.113, p < 0:001) and was valuable in the prediction of ccRCC progression. Our risk signature has potential prognostic value in ccRCC, and these ARlncRNAs may play a significant role in ccRCC tumor biology

Objectives

Methods

Conclusion