Dataset Information

YRNA expression predicts survival in bladder cancer patients.

ABSTRACT: Non-coding RNAs play an important role in human carcinogenesis. YRNAs (Ro-associated Y), a novel class of non-coding RNAs, have been identified as biomarker in various malignancies, but remain to be studied in urinary bladder cancer (BCA) patients.The expression of all four YRNAs (RNY1, RNY3, RNY4, RNY5) was determined in archival BCA (urothelial carcinoma, n = 88) and normal urothelial bladder (n = 30) tissues using quantitative real-time PCR. Associations with clinicopathological parameters and prognostic role for overall and cancer-specific survival were analysed.All YRNAs were significantly downregulated in BCA tissue. A low expression of RNY1, RNY3 and RNY4 was associated with muscle-invasive BCA, lymph node metastases and advanced grade. Furthermore, expression of RNY1 and RNY3 was predictive for BCA patients' overall (also RNY4) and cancer-specific survival as estimated using Kaplan-Meier and univariate (but not multivariate) Cox regression analyses. RNY1, RNY3 and RNY4 show good discriminative ability between tumor and normal tissue, as well as between muscle-invasive and non-muscle-invasive urothelial carcinoma.The expression of YRNAs is altered in BCA and associated with poor prognosis. Possible diagnostic role of YRNAs should be investigated in further studies.

SUBMITTER: Tolkach Y

PROVIDER: S-EPMC5681827 | biostudies-other | 2017 Nov

REPOSITORIES: biostudies-other

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YRNA expression predicts survival in bladder cancer patients.

Tolkach Yuri Y Stahl Anna Franziska AF Niehoff Eva-Maria EM Zhao Chenming C Kristiansen Glen G Müller Stefan Cajetan SC Ellinger Jörg J

BMC cancer 20171110 1

<h4>Background</h4>Non-coding RNAs play an important role in human carcinogenesis. YRNAs (Ro-associated Y), a novel class of non-coding RNAs, have been identified as biomarker in various malignancies, but remain to be studied in urinary bladder cancer (BCA) patients.<h4>Methods</h4>The expression of all four YRNAs (RNY1, RNY3, RNY4, RNY5) was determined in archival BCA (urothelial carcinoma, n = 88) and normal urothelial bladder (n = 30) tissues using quantitative real-time PCR. Associations wit ...[more]

PMID: 29126388

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Project description:BackgroundThe fatality and recurrence rates of bladder cancer (BC) have progressively increased. DNA methylation is an influential regulator associated with gene transcription in the pathogenesis of BC. We describe a comprehensive epigenetic study performed to analyse DNA methylation-driven genes in BC.MethodsData related to DNA methylation, the gene transcriptome and survival in BC were downloaded from The Cancer Genome Atlas (TCGA). MethylMix was used to detect BC-specific hyper-/hypo-methylated genes. Metascape was used to carry out gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was conducted to identify the characteristic dimension decrease and distinguish prognosis-related methylation-driven genes. Subsequently, we developed a six-gene risk evaluation model and a novel prognosis-related nomogram to predict overall survival (OS). A survival analysis was carried out to explore the individual prognostic significance of the six genes.ResultsIn total, 167 methylation-driven genes were identified. Based on the LASSO Cox regression, six genes, i.e., ARHGDIB, LINC00526, IDH2, ARL14, GSTM2, and LURAP1, were selected for the development of a risk evaluation model. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better OS (P?=?1.679e-05). The area under the curve (AUC) of this model was 0.698 at 3 years of OS. The verification performed in subgroups demonstrated the validity of the model. Then, we designed an OS-associated nomogram that included the risk score and clinical factors. The concordance index of the nomogram was 0.694. The methylation levels of IDH2 and ARL14 were appreciably related to the survival results. In addition, the methylation and gene expression-matched survival analysis revealed that ARHGDIB and ARL14 could be used as independent prognostic indicators. Among the six genes, 6 methylation sites in ARHGDIB, 3 in GSTM2, 1 in ARL14, 2 in LINC00526 and 2 in LURAP1 were meaningfully associated with BC prognosis. In addition, several abnormal methylated sites were identified as linked to gene expression.ConclusionWe discovered differential methylation in BC patients with better and worse survival and provided a risk evaluation model by merging six gene markers with clinical characteristics.

Project description:Bladder cancer (BLCA) is the most common urinary tract tumor and is the 11th most malignant cancer worldwide. With the development of in-depth multisystem sequencing, an increasing number of prognostic molecular markers have been identified. In this study, we focused on the role of protein-coding gene methylation in the prognosis of BLCA. We downloaded BLCA clinical and methylation data from The Cancer Genome Atlas (TCGA) database and used this information to identify differentially methylated genes and construct a survival model using lasso regression. We assessed 365 cases, with complete information regarding survival status, survival time longer than 30 days, age, gender, and tumor characteristics (grade, stage, T, M, N), in our study. We identified 353 differentially methylated genes, including 50 hypomethylated genes and 303 hypermethylated genes. After annotation, a total of 227 genes were differentially expressed. Of these, 165 were protein-coding genes. Three genes (zinc finger protein 382 (ZNF382), galanin receptor 1 (GALR1), and structural maintenance of chromosomes flexible hinge domain containing 1 (SMCHD1)) were selected for the final risk model. Patients with higher-risk scores represent poorer survival than patients with lower-risk scores in the training set (HR = 2.37, 95% CI 1.43-3.94, p = 0.001), in the testing group (HR = 1.85, 95% CI 1.16-2.94, p = 0.01), and in the total cohort (HR = 2.06, 95% CI 1.46-2.90, p < 0.001). Further univariate and multivariate analyses using the Cox regression method were conducted in these three groups, respectively. All the results indicated that risk score was an independent risk factor for BLCA. Our study screened the different methylation protein-coding genes in the BLCA tissues and constructed a robust risk model for predicting the outcome of BLCA patients. Moreover, these three genes may function in the mechanism of development and progression of BLCA, which should be fully clarified in the future.

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YRNA expression predicts survival in bladder cancer patients.

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YRNA expression predicts survival in bladder cancer patients.

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