Helmholtz Gemeinschaft

Search
Browse
Statistics
Feeds

Circular RNAs and their linear transcripts as diagnostic and prognostic tissue biomarkers in prostate cancer after prostatectomy in combination with clinicopathological factors

[img]
Preview
PDF (Original Article) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB
[img] Other (Supplementary Material)
5MB

Item Type:Article
Title:Circular RNAs and their linear transcripts as diagnostic and prognostic tissue biomarkers in prostate cancer after prostatectomy in combination with clinicopathological factors
Creators Name:Rochow, H. and Jung, M. and Weickmann, S. and Ralla, B. and Stephan, C. and Elezkurtaj, S. and Kilic, E. and Zhao, Z. and Jung, K. and Fendler, A. and Franz, A.
Abstract:As new biomarkers, circular RNAs (circRNAs) have been largely unexplored in prostate cancer (PCa). Using an integrative approach, we aimed to evaluate the potential of circRNAs and their linear transcripts (linRNAs) to act as (i) diagnostic biomarkers for differentiation between normal and tumor tissue and (ii) prognostic biomarkers for the prediction of biochemical recurrence (BCR) after radical prostatectomy. In a first step, eight circRNAs (circATXN10, circCRIM1, circCSNK1G3, circGUCY1A2, circLPP, circNEAT1, circRHOBTB3, and circSTIL) were identified as differentially expressed via a genome-wide circRNA-based microarray analysis of six PCa samples. Additional bioinformatics and literature data were applied for this selection process. In total, 115 malignant PCa and 79 adjacent normal tissue samples were examined using robust RT-qPCR assays specifically established for the circRNAs and their linear counterparts. Their diagnostic and prognostic potential was evaluated using receiver operating characteristic curves, Cox regressions, decision curve analyses, and C-statistic calculations of prognostic indices. The combination of circATXN10 and linSTIL showed a high discriminative ability between malignant and adjacent normal tissue PCa. The combination of linGUCY1A2, linNEAT1, and linSTIL proved to be the best predictive RNA-signature for BCR. The combination of this RNA signature with five established reference models based on only clinicopathological factors resulted in an improved predictive accuracy for BCR in these models. This is an encouraging study for PCa to evaluate circRNAs and their linRNAs in an integrative approach, and the results showed their clinical potential in combination with standard clinicopathological variables.
Keywords:Prostate Cancer, Microarray, Identification, Validation and Differential Expression of Circular RNAs, Circular RNAs and Linear Counterparts, Biochemical Recurrence, Diagnostic and Prognostic Tissue Biomarkers, Improved Predictive Accuracy by RNA Signature
Source:International Journal of Molecular Sciences
ISSN:1422-0067
Publisher:MDPI
Volume:21
Number:21
Page Range:E7812
Date:22 October 2020
Official Publication:https://doi.org/10.3390/ijms21217812
PubMed:View item in PubMed

Repository Staff Only: item control page

Downloads

Downloads per month over past year

Open Access
MDC Library