Please use this identifier to cite or link to this item: doi:10.22028/D291-35712
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Title: 4-miRNA Score Predicts the Individual Metastatic Risk of Renal Cell Carcinoma Patients
Author(s): Heinzelmann, Joana
Arndt, Madeleine
Pleyers, Ramona
Fehlmann, Tobias
Hoelters, Sebastian
Zeuschner, Philip
Vogt, Alexander
Pryalukhin, Alexey
Schaeffeler, Elke
Bohle, Rainer M.
Gajda, Mieczyslaw
Janssen, Martin
Stoeckle, Michael
Junker, Kerstin
Language: English
Title: Annals of Surgical Oncology
Volume: 26
Issue: 11
Pages: 3765–3773
Publisher/Platform: Springer Nature
Year of Publication: 2019
Publikation type: Journal Article
Abstract: Background In order to improve individual prognostication as well as stratification for adjuvant therapy in patients with clinically localized clear cell renal cell carcinoma (ccRCC), reliable prognostic biomarkers are urgently needed. In this study, microRNAs (miRNAs) have emerged as promising candidates. We investigated whether a combination of differently expressed miRNAs in primary tumors can predict the individual metastatic risk. Methods Using two prospectively collected biobanks of academic centers, 108 ccRCCs were selected, including 57 from patients with metastatic disease at diagnosis or during follow-up and 51 without evidence of metastases. Fourteen previously identified candidate miRNAs were tested in 20 representative formalin-fixed and paraffin embedded samples in order to select the best discriminators between metastatic and nonmetastatic ccRCC. These miRNAs were approved in 108 tumor samples. We evaluated the association of altered miRNA expression with the metastatic potential of tumors using quantitative polymerase chain reaction. A prognostic 4-miRNA model has been established using a random forest classifier. Cox regression analyses were performed for correlation of the miRNA model and clinicopathological parameters to metastasis-free and overall survival. Results Nine miRNAs indicated significant expression alterations in the small cohort. These miRNAs were validated in the whole cohort. The established 4-miRNA score (miR-30a-3p/-30c-5p/-139-5p/-144-5p) has been identified as a superior predictor for metastasis-free survival (hazard ratio 12.402; p = 7.0E−05) and overall survival (p = 1.1E−04) compared with clinicopathological parameters, and likewise in the Leibovich score subgroups. Conclusions We identified a 4-miRNA model that was found to be superior to clinicopathological parameters in accurately predicting individual metastatic risk and can support patient selection for risk-stratified follow-up and adjuvant therapy studies.
DOI of the first publication: 10.1245/s10434-019-07578-3
URL of the first publication: https://link.springer.com/article/10.1245/s10434-019-07578-3
Link to this record: hdl:20.500.11880/32577
http://dx.doi.org/10.22028/D291-35712
ISSN: 1534-4681
1068-9265
Date of registration: 11-Mar-2022
Faculty: M - Medizinische Fakultät
Department: M - Medizinische Biometrie, Epidemiologie und medizinische Informatik
M - Pathologie
M - Urologie und Kinderurologie
Professorship: M - Prof. Dr. Rainer M. Bohle
M - Univ.-Prof. Dr. Andreas Keller
M - Prof. Dr. Michael Stöckle
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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