Cargando…
Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy
Circular RNAs (circRNAs) may act as novel cancer biomarkers. However, a genome-wide evaluation of circRNAs in clear cell renal cell carcinoma (ccRCC) has yet to be conducted. Therefore, the objective of this study was to identify and validate circRNAs in ccRCC tissue with a focus to evaluate their p...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826865/ https://www.ncbi.nlm.nih.gov/pubmed/31575051 http://dx.doi.org/10.3390/cancers11101473 |
_version_ | 1783465192002158592 |
---|---|
author | Franz, Antonia Ralla, Bernhard Weickmann, Sabine Jung, Monika Rochow, Hannah Stephan, Carsten Erbersdobler, Andreas Kilic, Ergin Fendler, Annika Jung, Klaus |
author_facet | Franz, Antonia Ralla, Bernhard Weickmann, Sabine Jung, Monika Rochow, Hannah Stephan, Carsten Erbersdobler, Andreas Kilic, Ergin Fendler, Annika Jung, Klaus |
author_sort | Franz, Antonia |
collection | PubMed |
description | Circular RNAs (circRNAs) may act as novel cancer biomarkers. However, a genome-wide evaluation of circRNAs in clear cell renal cell carcinoma (ccRCC) has yet to be conducted. Therefore, the objective of this study was to identify and validate circRNAs in ccRCC tissue with a focus to evaluate their potential as prognostic biomarkers. A genome-wide identification of circRNAs in total RNA extracted from ccRCC tissue samples was performed using microarray analysis. Three relevant differentially expressed circRNAs were selected (circEGLN3, circNOX4, and circRHOBTB3), their circular nature was experimentally confirmed, and their expression—along with that of their linear counterparts—was measured in 99 malignant and 85 adjacent normal tissue samples using specifically established RT-qPCR assays. The capacity of circRNAs to discriminate between malignant and adjacent normal tissue samples and their prognostic potential (with the endpoints cancer-specific, recurrence-free, and overall survival) after surgery were estimated by C-statistics, Kaplan-Meier method, univariate and multivariate Cox regression analysis, decision curve analysis, and Akaike and Bayesian information criteria. CircEGLN3 discriminated malignant from normal tissue with 97% accuracy. We generated a prognostic for the three endpoints by multivariate Cox regression analysis that included circEGLN3, circRHOBT3 and linRHOBTB3. The predictive outcome accuracy of the clinical models based on clinicopathological factors was improved in combination with this circRNA-based signature. Bootstrapping as well as Akaike and Bayesian information criteria confirmed the statistical significance and robustness of the combined models. Limitations of this study include its retrospective nature and the lack of external validation. The study demonstrated the promising potential of circRNAs as diagnostic and particularly prognostic biomarkers in ccRCC patients. |
format | Online Article Text |
id | pubmed-6826865 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68268652019-11-18 Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy Franz, Antonia Ralla, Bernhard Weickmann, Sabine Jung, Monika Rochow, Hannah Stephan, Carsten Erbersdobler, Andreas Kilic, Ergin Fendler, Annika Jung, Klaus Cancers (Basel) Article Circular RNAs (circRNAs) may act as novel cancer biomarkers. However, a genome-wide evaluation of circRNAs in clear cell renal cell carcinoma (ccRCC) has yet to be conducted. Therefore, the objective of this study was to identify and validate circRNAs in ccRCC tissue with a focus to evaluate their potential as prognostic biomarkers. A genome-wide identification of circRNAs in total RNA extracted from ccRCC tissue samples was performed using microarray analysis. Three relevant differentially expressed circRNAs were selected (circEGLN3, circNOX4, and circRHOBTB3), their circular nature was experimentally confirmed, and their expression—along with that of their linear counterparts—was measured in 99 malignant and 85 adjacent normal tissue samples using specifically established RT-qPCR assays. The capacity of circRNAs to discriminate between malignant and adjacent normal tissue samples and their prognostic potential (with the endpoints cancer-specific, recurrence-free, and overall survival) after surgery were estimated by C-statistics, Kaplan-Meier method, univariate and multivariate Cox regression analysis, decision curve analysis, and Akaike and Bayesian information criteria. CircEGLN3 discriminated malignant from normal tissue with 97% accuracy. We generated a prognostic for the three endpoints by multivariate Cox regression analysis that included circEGLN3, circRHOBT3 and linRHOBTB3. The predictive outcome accuracy of the clinical models based on clinicopathological factors was improved in combination with this circRNA-based signature. Bootstrapping as well as Akaike and Bayesian information criteria confirmed the statistical significance and robustness of the combined models. Limitations of this study include its retrospective nature and the lack of external validation. The study demonstrated the promising potential of circRNAs as diagnostic and particularly prognostic biomarkers in ccRCC patients. MDPI 2019-09-30 /pmc/articles/PMC6826865/ /pubmed/31575051 http://dx.doi.org/10.3390/cancers11101473 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Franz, Antonia Ralla, Bernhard Weickmann, Sabine Jung, Monika Rochow, Hannah Stephan, Carsten Erbersdobler, Andreas Kilic, Ergin Fendler, Annika Jung, Klaus Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy |
title | Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy |
title_full | Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy |
title_fullStr | Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy |
title_full_unstemmed | Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy |
title_short | Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy |
title_sort | circular rnas in clear cell renal cell carcinoma: their microarray-based identification, analytical validation, and potential use in a clinico-genomic model to improve prognostic accuracy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826865/ https://www.ncbi.nlm.nih.gov/pubmed/31575051 http://dx.doi.org/10.3390/cancers11101473 |
work_keys_str_mv | AT franzantonia circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT rallabernhard circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT weickmannsabine circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT jungmonika circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT rochowhannah circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT stephancarsten circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT erbersdoblerandreas circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT kilicergin circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT fendlerannika circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy AT jungklaus circularrnasinclearcellrenalcellcarcinomatheirmicroarraybasedidentificationanalyticalvalidationandpotentialuseinaclinicogenomicmodeltoimproveprognosticaccuracy |