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Novel insights into biomarkers associated with renal cell carcinoma.

ABSTRACT: Renal cell carcinoma (RCC) is a common form of cancer of the urinary tract. The present study aimed to identify driver genes in RCC using a bioinformatics approach. GSE53757 and GSE40435 microarray data were analyzed, and differentially expressed genes were filtered prior to gene ontology (GO) and pathway analysis. A protein-protein interaction (PPI) network was established. Overall survival and recurrence were investigated and based on data presented in cBioPortal. The COPS7B gene within the PPI network was selected for further study in vitro. The present study identified 174 and 149 genes possessing a significant signal to noise ratio in GSE53757 and GSE40435, respectively. In total, 53 of these genes were selected based upon inclusion in both datasets. GO analysis indicated that PRKCDBP, EHD2, KCNJ10, ATP1A1, KCNJ1 and EHD2 may be involved in various biological processes. Furthermore, ALDH6A1, LDHA, SUCLG1 and ABAT may be involved in the propanoate metabolism pathway. A network consisting of 106 genes, and one typical cluster were constructed. In addition, COPS7B was selected, as it was associated with decreased overall survival and increased recurrence rates, in order to elucidate its function in RCC. Furthermore, upregulation of COPS7B was demonstrated to be predictive of advanced stage disease and metastasis of RCC. Finally, COPS7B-knockdown inhibited RCC cell proliferation and invasion ability. Collectively, these results provided novel insights into COPS7B function, indicating that COPS7B may serve as a prognostic marker and therapeutic target in RCC.

SUBMITTER: Chen B

PROVIDER: S-EPMC6006415 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Novel insights into biomarkers associated with renal cell carcinoma.

Chen Binghai B Jiao Zhimin Z Yin Xifeng X Qian Zhounan Z Gu Jie J Sun Hao H

Oncology letters 20180508 1

Renal cell carcinoma (RCC) is a common form of cancer of the urinary tract. The present study aimed to identify driver genes in RCC using a bioinformatics approach. GSE53757 and GSE40435 microarray data were analyzed, and differentially expressed genes were filtered prior to gene ontology (GO) and pathway analysis. A protein-protein interaction (PPI) network was established. Overall survival and recurrence were investigated and based on data presented in cBioPortal. The COPS7B gene within the PP ...[more]

PMID: 29928389

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Project description:We investigated the expression profiles of microRNAs (miRNA) in 26 renal cell carcinoma (RCC) FFPE tissues (3 chRCC, 5 papRCC and 18 ccRCC), 4 urothelial cell carcinomas of the upper urinary tract (UT-UCs) and 20 normal kidneys by using the miRCURY LNA™ microRNA Array, 6th gen (Exiqon, Woburn MA), containing capture probes that target all miRNAs for all species registered in the miRBASE version 16.0. Real-time PCR (qRT-PCR) using appropriate endogenous controls was performed in order to validate the microarray results of the 27 most differentially expressed (DE) miRNAs. We identified 434 miRNAs that were significantly deregulated in all tumours compared to the normal kidney tissues. Overall, 126 miRNAs (29%) showed increased expression and 303 miRNAs (69.8%) had decreased expression in RCCs and UT-UCs vs. the normal kidneys. Specifically, 374, 420, 421 and 409 miRNAs were 90% consistently down-regulated in ccRCC, papRCC, chRCC and UT-UC, respectively. Unsupervised two-way hierarchical clustering (HCL) with Euclidian distance accurately discriminated between RCC and UT-UC. Apart from one chRCC sample that was clustered with ccRCCs, HCL also managed to successfully classify the 3 RCC subtypes among them. Furthermore, it showed that ccRCC is more closely related to papRCC and that both are distinct from chRCC or UT-UC. Ninety-four miRNAs were co-upregulated among ccRCC, papRCC and chRCC; and 11, 44 and 24 miRNAs were specifically up-regulated in each one of the three RCC subtypes (ccRCC, chRCC and papRCC), respectively. On the other hand, 222 miRNAs were co-down-regulated in the three RCC subtypes, whereas 16, 18 and 5 miRNAs were specifically down-regulated in ccRCC, chRCC and papRCC, respectively. When the DE miRNAs in each RCC subtype were combined with those in UT-UC, we identified 89 and 206 miRNAs, respectively, that were up- and down-regulated in all tumor types. miRNA profiling can distinguish between RCC and UT-UC as well as among distinct RCC subtypes. Our data validicate that miRNA expression tends to be down-regulated in RCC versus the normal kidney tissue.

Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is essentially a metabolic disorder characterized by reprogramming of several metabolic pathways. Acyl-coenzyme A thioesterases (ACOTs) are critical enzymes involved in fatty acid metabolism; however, the roles of ACOTs in ccRCC remain unclear. This study explored ACOTs expressions and their diagnostic and prognostic values in ccRCC.MethodsThree online ccRCC datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) were utilized to measure the expressions of ACOTs in paired normal and tumor tissues. Receiver operating characteristic (ROC) curves were depicted to assess the diagnostic values of ACOTs in ccRCC. Quantitative real-time PCR and immunohistochemical analysis were performed to validate the ACOT11 expression in ccRCC cell lines and clinical samples. Survival curves and Cox regression analysis were used to evaluate the predictive values of ACOTs in clinical outcome of ccRCC patients. Functional enrichment analyses and correlation analysis were carried out to predict the potential roles of ACOT8 in tumorigenesis and progression of ccRCC.ResultsACOT1/2/8/11/13 were found to be significantly downregulated in ccRCC samples. In particular, ACOT11 was decreased in almost every matched normal-tumor pair, and had extremely high diagnostic value as shown by ROC curve analysis (AUC = 0.964). The expression of ACOT11 was further verified in ccRCC cell lines and clinical samples at mRNA and protein levels. Furthermore, clinical correlation analysis and survival analysis indicated that ACOT8 was correlated with disease progression and was an independent predictor of unfavorable outcome in ccRCC. Moreover, functional analyses suggested potential roles of ACOT8 in the regulation of oxidative phosphorylation (OXPHOS), and correlation analysis revealed an association between ACOT8 and ferroptosis-related genes in ccRCC.ConclusionOur study revealed that ACOT11 and ACOT8 are promising biomarkers for diagnosis and prognosis of ccRCC, respectively, and ACOT8 may affect ccRCC development and progression through the regulation of OXPHOS and ferroptosis. These findings may provide new strategies for precise diagnosis and personalized therapy of ccRCC.

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Novel insights into biomarkers associated with renal cell carcinoma.

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Novel insights into biomarkers associated with renal cell carcinoma.

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