Dataset Information

A three-microRNA signature as a diagnostic and prognostic marker in clear cell renal cancer: An In Silico analysis.

ABSTRACT: Accumulating evidence has demonstrated that some specific miRNAs were aberrantly expressed in renal clear cell carcinoma and participated in many biological processes. The aim of this study was to investigate a panel of miRNA signature for diagnosis and prognosis of renal clear cell carcinoma (KIRC). Here, we performed a comprehensive analysis for miRNA expression profiles and corresponding clinical information of 516 KIRC patients from The Cancer Genome Atlas (TCGA). In the study, a total of 63 differentially expressed miRNAs were identified, of which 34 were up-regulated and 29 were down-regulated. We constructed a panel of three-miRNA that were significantly associated with KIRC diagnosis and KIRC patients' prognosis. The three-miRNA signature reached a sensitivity of 98.3% and a specificity of 97.2% in the diagnosis of KIRC. Using the three-miRNA signature, we classified the KIRC patients into high-risk group and low-risk group. The Kaplan- Meier curves showed that KIRC patients with high risk scores had significantly worsen overall survival (OS) and disease free survival (DFS) than KIRC patients with low risk scores. In the univariate and multivariate Cox regression analysis, three-miRNA signature was an independent prognostic factor in OS. In conclusion, the three-miRNA signature could be used as a diagnostic and prognostic biomarker in KIRC, and therefore, may help to provide significant clinical implication for the treatment of KIRC.

SUBMITTER: Liang B

PROVIDER: S-EPMC5491330 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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A three-microRNA signature as a diagnostic and prognostic marker in clear cell renal cancer: An In Silico analysis.

Liang Bin B Zhao Jianying J Wang Xuan X

PloS one 20170629 6

Accumulating evidence has demonstrated that some specific miRNAs were aberrantly expressed in renal clear cell carcinoma and participated in many biological processes. The aim of this study was to investigate a panel of miRNA signature for diagnosis and prognosis of renal clear cell carcinoma (KIRC). Here, we performed a comprehensive analysis for miRNA expression profiles and corresponding clinical information of 516 KIRC patients from The Cancer Genome Atlas (TCGA). In the study, a total of 63 ...[more]

PMID: 28662155

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Project description:Purpose: In this study, we have undertaken the whole proteomic analysis and got a better understanding of biological processes involved in the development and progression of ccRCC. We hope promising biomarkers can be uncovered to facilitate early diagnosis, predict the prognosis and progression, more importantly, to be applied as potential therapeutic targets. Experimental design: Fresh frozen tissue samples were surgically resected from patients with local or locally advanced ccRCC. Trypsin digested proteins were analyzed using TMT-based LC-MS/MS proteomic approach, followed by bioinformatic analysis. A potential prognostic marker FMNL1, annotated with actin cytoskeleton assembly and cell migration, was chosen to be validated in TCGA_KIRC datasets(n=597), further validation sets(n=20) and expanded validation sets(n=97). Results: A total of 657 differentially expressed proteins were identified and quantified between ccRCC and adjacent normal tissues (p-value<0.05, FC>2 or<1/2), of which 186 proteins were up-regulated and 471 proteins were down-regulated. Bioinformatic analysis showed enriched metabolic biological processes and pathways including oxidative phosphorylation, valine, leucine and isoleucine degeneration, propanoate metabolism, fatty-acid degeneration, TCA cycle, glycolysis/gluconeogenesis, etc. Univariate and multivariate analysis defined FMNL1 as an independent negative prognostic marker in the TCGA datasets. High expression of FMNL1 correlated significantly with tumor stage, T stage, lymph node metastasis(P<0.05), and distant metastasis(P<0.05) both in the TCGA-KIRC datasets and expanded validation sets. And KM survival curve illustrated that patients with high FMNL1 protein level had shorter OS time in the expanded validation sets (p=0.0273) Conclusion and clinical relevance: The proteomic results uncovered sophisticated metabolic reprogramming of ccRCC and indicated that the upregulation of rate-limiting enzymes in glycolysis and mitochondrial impairment may be the cause of metabolic reprogramming in ccRCC. Moreover, FMNL1 has been identified as a diagnostic and prognostic marker, and may be implicated in the progression of ccRCC.

Project description:BACKGROUND:The rising incidence of renal cell carcinomas (RCC) constitutes a significant challenge owing to risk of overtreatment. Because aberrant microRNA (miR) promoter methylation contributes to cancer development, we investigated whether altered miR-30a-5p expression associates with DNA promoter methylation and evaluated the usefulness as clear cell RCC (ccRCC) diagnostic and prognostic markers. METHODS:Genome-wide methylome and RNA sequencing data from a set of ccRCC and normal tissue samples from The Cancer Genome Atlas (TCGA) database were integrated to identify candidate CpG loci involved in cancer onset. MiR-30a-5p expression and promoter methylation were quantitatively assessed by PCR in a tissue set (Cohort #1) and urine sets (Cohorts #2 and 3) from IPOPorto and Homburg University Hospital. Non-parametric tests were used for comparing continuous variables. MiR-30a-5p promoter methylation (miR-30a-5pme) performance as diagnostic (receiver operator characteristics [ROC] - validity estimates) and prognostic [metastasis-free (MFS) and disease-specific survival (DSS)] biomarker was further validated in urine samples from ccRCC patients by Kaplan Meier curves (with log rank) and both univariable and multivariable analysis. RESULTS:Two significant hypermethylated CpG loci in TCGA ccRCC samples, correlating with miR-30a-5p transcriptional downregulation, were disclosed. MiR-30a-5pme in ccRCC tissues was confirmed in an independent patient's cohort of IPOPorto and associated with shorter time to relapse. In urine samples, miR-30a-5pme levels identified cancer both in testing and validation cohorts, with 83% sensitivity/53% specificity and 63% sensitivity/67% specificity, respectively. Moreover, higher miR-30a-5pme levels independently predicted metastatic dissemination and survival. CONCLUSION:To the best of our knowledge, this is the first study validating the diagnostic and prognostic potential of miR-30a-5pme for ccRCC in urine samples, providing new insights for its clinical usefulness as non-invasive cancer biomarker.

Dataset Information

A three-microRNA signature as a diagnostic and prognostic marker in clear cell renal cancer: An In Silico analysis.

Publications

A three-microRNA signature as a diagnostic and prognostic marker in clear cell renal cancer: An In Silico analysis.

Similar Datasets

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