Improved risk stratification in myeloma using a microRNA-based classifier

Wu, Ping, Agnelli, Luca, Walker, Brian A, Todoerti, Katia, Lionetti, Marta, Johnson, David C, Kaiser, Martin, Mirabella, Fabio, Wardell, Christopher, Gregory, Walter M, Davies, Faith E, Brewer, Daniel ORCID: https://orcid.org/0000-0003-4753-9794, Neri, Antonino and Morgan, Gareth J (2013) Improved risk stratification in myeloma using a microRNA-based classifier. British Journal of Haematology, 162 (3). pp. 348-59. ISSN 0007-1048

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Abstract

Multiple myeloma (MM) is a heterogeneous disease. International Staging System/fluorescence hybridization (ISS/FISH)-based model and gene expression profiles (GEP) are effective approaches to define clinical outcome, although yet to be improved. The discovery of a class of small non-coding RNAs (micro RNAs, miRNAs) has revealed a new level of biological complexity underlying the regulation of gene expression. In this work, 163 presenting samples from MM patients were analysed by global miRNA profiling, and distinct miRNA expression characteristics in molecular subgroups with prognostic relevance (4p16, MAF and 11q13 translocations) were identified. Furthermore we developed an "outcome classifier", based on the expression of two miRNAs (MIR17 and MIR886-5p), which is able to stratify patients into three risk groups (median OS 19.4, 40.6 and 65.3 months, P = 0.001). The miRNA-based classifier significantly improved the predictive power of the ISS/FISH approach (P = 0.0004), and was independent of GEP-derived prognostic signatures (P

Item Type:	Article
Additional Information:	© 2013 John Wiley & Sons Ltd.
Uncontrolled Keywords:	aged,chromosome aberrations,gene expression profiling,gene expression regulation, neoplastic,humans,in situ hybridization, fluorescence,kaplan-meier estimate,micrornas,middle aged,multiple myeloma,prognosis,rna, neoplasm,risk assessment,tumor markers, biological
Faculty \ School:	Faculty of Science > School of Biological Sciences
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Groups > Cancer Studies Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health
Depositing User:	Pure Connector
Date Deposited:	06 Jan 2014 14:14
Last Modified:	19 Oct 2023 01:15
URI:	https://ueaeprints.uea.ac.uk/id/eprint/47021
DOI:	10.1111/bjh.12394

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