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Prognostic value of cross-omics screening for kidney clear cell renal cancer survival


Dimitrieva, Slavica; Schlapbach, Ralph; Rehrauer, Hubert (2016). Prognostic value of cross-omics screening for kidney clear cell renal cancer survival. Biology Direct, 11(1):68.

Abstract

BACKGROUND Kidney renal clear cell carcinoma (KIRC) is a type of cancer that is resistant to chemotherapy and radiotherapy and has limited treatment possibilities. Large-scale molecular profiling of KIRC tumors offers a great potential to uncover the genetic and epigenetic changes underlying this disease and to improve the clinical management of KIRC patients. However, in practice the clinicians and researchers typically focus on single-platform molecular data or on a small set of genes. Using molecular and clinical data of over 500 patients, we have systematically studied which type of molecular data is the most informative in predicting the clinical outcome of KIRC patients, as a standalone platform and integrated with clinical data. RESULTS We applied different computational approaches to preselect on survival-predictive genomic markers and evaluated the usability of mRNA/miRNA/protein expression data, copy number variation (CNV) data and DNA methylation data in predicting survival of KIRC patients. Our analyses show that expression and methylation data have statistically significant predictive powers compared to a random guess, but do not perform better than predictions on clinical data alone. However, the integration of molecular data with clinical variables resulted in improved predictions. We present a set of survival associated genomic loci that could potentially be employed as clinically useful biomarkers. CONCLUSIONS Our study evaluates the survival prediction of different large-scale molecular data of KIRC patients and describes the prognostic relevance of such data over clinical-variable-only models. It also demonstrates the survival prognostic importance of methylation alterations in KIRC tumors and points to the potential of epigenetic modulators in KIRC treatment. REVIEWERS An extended abstract of this research paper was selected for the CAMDA Satellite Meeting to ISMB 2015 by the CAMDA Programme Committee. The full research paper then underwent one round of Open Peer Review under a responsible CAMDA Programme Committee member, Djork-Arné Clevert, PhD (Bayer AG, Germany). Open Peer Review was provided by Martin Otava, PhD (Janssen Pharmaceutica, Belgium) and Hendrik Luuk, PhD (The Centre for Disease Models and Biomedical Imaging, University of Tartu, Estonia). The Reviewer comments section shows the full reviews and author responses.

Abstract

BACKGROUND Kidney renal clear cell carcinoma (KIRC) is a type of cancer that is resistant to chemotherapy and radiotherapy and has limited treatment possibilities. Large-scale molecular profiling of KIRC tumors offers a great potential to uncover the genetic and epigenetic changes underlying this disease and to improve the clinical management of KIRC patients. However, in practice the clinicians and researchers typically focus on single-platform molecular data or on a small set of genes. Using molecular and clinical data of over 500 patients, we have systematically studied which type of molecular data is the most informative in predicting the clinical outcome of KIRC patients, as a standalone platform and integrated with clinical data. RESULTS We applied different computational approaches to preselect on survival-predictive genomic markers and evaluated the usability of mRNA/miRNA/protein expression data, copy number variation (CNV) data and DNA methylation data in predicting survival of KIRC patients. Our analyses show that expression and methylation data have statistically significant predictive powers compared to a random guess, but do not perform better than predictions on clinical data alone. However, the integration of molecular data with clinical variables resulted in improved predictions. We present a set of survival associated genomic loci that could potentially be employed as clinically useful biomarkers. CONCLUSIONS Our study evaluates the survival prediction of different large-scale molecular data of KIRC patients and describes the prognostic relevance of such data over clinical-variable-only models. It also demonstrates the survival prognostic importance of methylation alterations in KIRC tumors and points to the potential of epigenetic modulators in KIRC treatment. REVIEWERS An extended abstract of this research paper was selected for the CAMDA Satellite Meeting to ISMB 2015 by the CAMDA Programme Committee. The full research paper then underwent one round of Open Peer Review under a responsible CAMDA Programme Committee member, Djork-Arné Clevert, PhD (Bayer AG, Germany). Open Peer Review was provided by Martin Otava, PhD (Janssen Pharmaceutica, Belgium) and Hendrik Luuk, PhD (The Centre for Disease Models and Biomedical Imaging, University of Tartu, Estonia). The Reviewer comments section shows the full reviews and author responses.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Functional Genomics Center Zurich
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:20 December 2016
Deposited On:26 Jan 2018 11:44
Last Modified:02 Feb 2018 11:38
Publisher:BioMed Central
ISSN:1745-6150
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/s13062-016-0170-1
PubMed ID:27993167

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