Dataset Information

Urine cell-free microRNA as biomarkers for transitional cell carcinoma.

ABSTRACT: MicroRNA (miRNA) are short nucleotide strands with a regulatory function in the cell. Several miRNAs have been shown to be useful as biomarkers for different neoplasms. The aim of this project was to assess whether levels of miRNA in cell free urine could be used as a biomarker in transitional cell carcinoma (TCC).cDNA libraries were produced based on small RNAs in urine samples of fourteen TCC patients and twenty healthy volunteers. Resulting reads were deep sequenced on Illumina HiSeq sequencer with the intent of characterizing cell free urine miRNA profiles. A statistically significant difference was found for a single miRNA; miR-210 was > sixfold higher in the TCC group compared to the control group. Furthermore, we were able to produce a diagnostic score by summing of standardized levels of overexpressed miRNA. This score was considerably higher in TCC patients with a sensitivity of 0.93, specificity of 0.76 and negative predictive value > 0.97.

SUBMITTER: Geva GA

PROVIDER: S-EPMC5708087 | biostudies-other | 2017 Nov

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Urine cell-free microRNA as biomarkers for transitional cell carcinoma.

Geva Gil A GA Gielchinsky Ilan I Aviv Nina N Max Klaas E A KEA Gofrit Ofer N ON Gur-Wahnon Devorah D Ben-Dov Iddo Z IZ

BMC research notes 20171129 1

<h4>Objective</h4>MicroRNA (miRNA) are short nucleotide strands with a regulatory function in the cell. Several miRNAs have been shown to be useful as biomarkers for different neoplasms. The aim of this project was to assess whether levels of miRNA in cell free urine could be used as a biomarker in transitional cell carcinoma (TCC).<h4>Results</h4>cDNA libraries were produced based on small RNAs in urine samples of fourteen TCC patients and twenty healthy volunteers. Resulting reads were deep se ...[more]

PMID: 29187235

Similar Datasets

Project description:PurposeNo liquid biomarkers are approved in metastatic renal cell carcinoma (mRCC) despite the need to predict and monitor response noninvasively to tailor treatment choices. Urine and plasma free glycosaminoglycan profiles (GAGomes) are promising metabolic biomarkers in mRCC. The objective of this study was to explore if GAGomes could predict and monitor response in mRCC.Patients and methodsWe enrolled a single-center prospective cohort of patients with mRCC elected for first-line therapy (ClinicalTrials.gov identifier: NCT02732665) plus three retrospective cohorts (ClinicalTrials.gov identifiers: NCT00715442 and NCT00126594) for external validation. Response was dichotomized as progressive disease (PD) versus non-PD every 8-12 weeks. GAGomes were measured at treatment start, after 6-8 weeks, and every third month in a blinded laboratory. We correlated GAGomes with response and developed scores to classify PD versus non-PD, which were used to predict response at treatment start or after 6-8 weeks.ResultsFifty patients with mRCC were prospectively included, and all received tyrosine kinase inhibitors (TKIs). PD correlated with alterations in 40% of GAGome features. We developed plasma, urine, and combined glycosaminoglycan progression scores that monitored PD at each response evaluation visit with the area under the receiving operating characteristic curve (AUC) of 0.93, 0.97, and 0.98, respectively. For internal validation, the scores predicted PD at treatment start with the AUC of 0.66, 0.68, and 0.74 and after 6-8 weeks with the AUC of 0.76, 0.66, and 0.75. For external validation, 70 patients with mRCC were retrospectively included and all received TKI-containing regimens. The plasma score predicted PD at treatment start with the AUC of 0.90 and at 6-8 weeks with the AUC of 0.89. The pooled sensitivity and specificity were 58% and 79% at treatment start. Limitations include the exploratory study design.ConclusionGAGomes changed in association with mRCC response to TKIs and may provide biologic insights into mRCC mechanisms of response.

Project description:BACKGROUND:MicroRNA (miR)s are promising diagnostic biomarkers of cancer. Recent next generation sequencer (NGS) studies have found that isoforms of micro RNA (isomiR) circulate in the bloodstream similarly to mature micro RNA (miR). We hypothesized that combination of circulating miR and isomiRs detected by NGS are potentially powerful cancer biomarker. The present study aimed to investigate their application in esophageal cancer. METHODS:Serum samples from patients with esophageal squamous cell carcinoma (ESCC) and age and sex matched healthy control (HC) individuals were investigated for the expression of miR/isomiRs using NGS. Candidate miR/isomiRs which met the criteria in the 1st group (ESCC = 18 and HC = 12) were validated in the 2nd group (ESCC = 30 and HC = 30). A diagnostic panel was generated using miR/isomiRs that were consistently confirmed in the 1st and 2nd groups. Accuracy of the panel was tested then in the 3rd group (ESCC = 18 and HC = 18). Their use was also investigated in 22 paired samples obtained pre- and post-treatment, and in patients with esophageal adenocarcinoma (EAD) and high-grade dysplasia (HGD). RESULTS:Twenty-four miR/isomiRs met the criteria for diagnostic biomarker in the 1st and 2nd group. A multiple regression model selected one mature miR (miR-30a-5p) and two isomiRs (isoform of miR-574-3p and miR-205-5p). The index calculated from the diagnostic panel was significantly higher in ESCC patients than in the HCs (13.3±8.9 vs. 3.1±1.3, p<0.001). The area under the receiver operating characteristics (ROC) curves of the panel index was 0.95. Sensitivity and specificity were 93.8%, and 81% in the 1st and 2nd groups, and 88.9% and 72.3% in the 3rd group, respectively. The panel index was significantly lower in patients with EAD (6.2±4.5) and HGD (4.2±1.7) than in those with ESCC and was significantly decreased at post-treatment compared with pre-treatment (6.2±5.6 vs 11.6±11.5, p = 0.03). CONCLUSION:Our diagnostic panel had high accuracy in the diagnosis of ESCC. MiR/isomiRs detected by NGS could serve as novel biomarkers of ESCC.

Dataset Information

Urine cell-free microRNA as biomarkers for transitional cell carcinoma.

Publications

Urine cell-free microRNA as biomarkers for transitional cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets