Identification of potential biomarkers for progression and prognosis of renal clear cell carcinoma by comprehensive bioinformatics analysis

Author:

Dong Haonan11,He Zexi121,Wang Haifeng1,Ding Mingxia1,Huang Yinglong1,Li Haihao1,Shi Hongjin1,Mao Lan1,Hu Chongzhi1,Wang Jiansong1

Affiliation:

1. Department of Urology, The Second Affiliate Hospital of Kunming Medical University, Yunnan Institute of Urology, Kunming, Yunnan, China

2. Department of Urology, The Second People’s Hospital of Foshan, Foshan, Guangdong, China

Abstract

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of renal cell carcinoma (RCC), and effective biomarkers will improve diagnosis and treatment. OBJECTIVE: This study investigated NPEPL1 expression in ccRCC through public databases and clinical samples and assessed its correlation with clinicopathological features and patient prognosis. METHOD: Data from The Cancer Genome Atlas and clinical specimens were gathered, NPEPL1 expression levels were analyzed; a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of NPEPL1; and clinicopathological data was used to study the correlations between expression and clinical parameters. NPEPL1’s prognostic value was appraised using a Kaplan–Meier (K–M) survival curve, Cox regression analysis, and a nomogram model; Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differently expressed genes between tissues with high and low NPEPL1 expression were used to estimate the underlying mechanisms involved. RESULTS: NPEPL1 was significantly higher-expressed in ccRCC tissue. ROC analysis showed that NPEPL1 had noteworthy diagnostic efficacy. NPEPL1 expression was closely related to clinicopathological parameters, such as T and M stage. K–M analysis showed that overall survival was significantly shortened with high NPEPL1 expression. Cox regression analysis showed that NPEPL1 expression was an independent risk factor predicting overall survival. The nomogram showed a significantly high clinical value in predicting the 1-, 3-, and 5-year survival probabilities in ccRCC. GO and KEGG enrichment analysis suggested that NPEPL1 may promote the occurrence and development of ccRCC via the Ras signaling and other pathways. CONCLUSION: NPEPL1 expression in ccRCC was higher than that in normal kidney tissues and was significantly associated with advanced clinical stage and poor prognosis. Therefore, NPEPL1 is a promising prognostic biomarker.

Publisher

IOS Press

Subject

Health Informatics,Biomedical Engineering,Information Systems,Biomaterials,Bioengineering,Biophysics

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