Dysregulation of Long Non-coding RNAs and mRNAs in Plasma of Clear Cell Renal Cell Carcinoma Patients Using Microarray and Bioinformatic Analysis

Bing Zhang; Wei Chu; Feifei Wen; Li Zhang; Lixia Sun; Baoguang Hu; Jingjing Wang; Qingguo Su; Yanhui Mei; Jingyuan Cao; Jing Zheng; Xiaodong Mou; Hongliang Dong; Xiaoyan Lin; Nan Wang; Hong Ji

doi:10.3389/fonc.2020.559730

Dysregulation of Long Non-coding RNAs and mRNAs in Plasma of Clear Cell Renal Cell Carcinoma Patients Using Microarray and Bioinformatic Analysis

Front Oncol. 2020 Nov 27:10:559730. doi: 10.3389/fonc.2020.559730. eCollection 2020.

Authors

Bing Zhang¹, Wei Chu², Feifei Wen², Li Zhang³, Lixia Sun², Baoguang Hu⁴, Jingjing Wang², Qingguo Su¹, Yanhui Mei¹, Jingyuan Cao¹, Jing Zheng⁵, Xiaodong Mou², Hongliang Dong⁵, Xiaoyan Lin⁶, Nan Wang⁵, Hong Ji²

Affiliations

¹ Department of Urology, Binzhou Medical University Hospital, Binzhou Medical University, Binzhou, China.
² Department of Pathology, Binzhou Medical University Hospital, Binzhou Medical University, Binzhou, China.
³ Department of Anesthesiology, Binzhou Medical University Hospital, Binzhou Medical University, Binzhou, China.
⁴ Department of Gastrointestinal Surgery, Binzhou Medical University Hospital, Binzhou Medical University, Binzhou, China.
⁵ Clinical Medicine Laboratory, Binzhou Medical University Hospital, Binzhou Medical University, Binzhou, China.
⁶ Department of Pathology, Shandong Province Hospital, Jinan, China.

Abstract

Objective: The roles of long non-coding RNAs (lncRNAs) in the diagnosis of clear cell renal cell carcinoma (ccRCC) are still not well-defined. We aimed to identify differentially expressed lncRNAs and mRNAs in plasma of ccRCC patients and health controls systematically. Methods: Expression profile of plasma lncRNAs and mRNAs in ccRCC patients and healthy controls was analyzed based on microarray assay. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-based approaches were used to investigate biological function and signaling pathways mediated by the differentially expressed mRNAs. SOCS2-AS1 was selected for validation using Real-Time PCR. The differentially expressed lncRNAs and mRNAs were further compared with E-MTAB-1830 datasets using Venn and the NetworkAnalyst website. The GEPIA and ULCAN websites were utilized for the evaluation of the expression level of differentially expressed mRNA and their association with overall survival (OS). Results: A total of 3,664 differentially expressed lncRNAs were identified in the plasma of ccRCC patients, including 1,511 up-regulated and 2,153 down-regulated lncRNAs (fold change ≥2 and P < 0.05), respectively. There were 2,268 differentially expressed mRNAs, including 932 up-regulated mRNAs and 1,336 down-regulated mRNAs, respectively (fold change ≥2 and P < 0.05). Pathway analysis based on deregulated mRNAs was mainly involved in melanogenesis and Hippo signaling pathway (P < 0.05). In line with the lncRNA microarray findings, the SOCS2-AS1 was down-regulated in ccRCC plasma and tissues, as well as in cell lines. Compared with the E-MTAB-1830 gene expression profiles, we identified 18 lncRNAs and 87 mRNAs differently expressed in both plasma and neoplastic tissues of ccRCC. The expression of 10 mRNAs (EPB41L4B, CCND1, GGT1, CGNL1, CYSLTR1, PLAUR, UGT3A1, PROM2, MUC12, and PCK1) was correlated with the overall survival (OS) rate in ccRCC patients based on the GEPIA and ULCAN websites. Conclusions: We firstly reported differentially expressed lncRNAs in ccRCC patients and healthy controls systemically. Several differentially expressed lncRNAs and mRNAs were identified, which might serve as diagnostic or prognostic markers. The biological function of these lncRNAs and mRNAs should be further validated. Our study may contribute to the future treatment of ccRCC and provide novel insights into cancer biology.

Keywords: bioinformatics; clear cell renal cell carcinoma; differentially expressed gene; long non-coding RNA; mRNA; microarray.