Gene signature combinations improve prognostic stratification of multiple myeloma patients

W. J. Chng, T. H. Chung, Shaji K Kumar, S. Usmani, N. Munshi, H. Avet-Loiseau, H. Goldschmidt, B. Durie, P. Sonneveld

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Multiple myeloma (MM) is a plasma cell neoplasm with significant molecular heterogeneity. Gene expression profiling (GEP) has contributed significantly to our understanding of the underlying biology and has led to several prognostic gene signatures. However, the best way to apply these GEP signatures in clinical practice is unclear. In this study, we investigated the integration of proven prognostic signatures for improved patient risk stratification. Three publicly available MM GEP data sets that encompass newly diagnosed as well as relapsed patients were analyzed using standardized estimation of nine prognostic MM signature indices and simulations of signature index combinations. Cox regression analysis was used to assess the performance of simulated combination indices. Taking the average of multiple GEP signature indices was a simple but highly effective way of integrating multiple GEP signatures. Furthermore, although adding more signatures in general improved performance substantially, we identified a core signature combination, EMC92+HZDCD, as the top-performing prognostic signature combination across all data sets. In this study, we provided a rationale for gene signature integration and a practical strategy to choose an optimal risk score estimation in the presence of multiple prognostic signatures.Leukemia advance online publication, 15 January 2016; doi:10.1038/leu.2015.341.

Original languageEnglish (US)
JournalLeukemia
DOIs
StateAccepted/In press - Dec 16 2015

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Gene Expression Profiling
Multiple Myeloma
Transcriptome
Genes
Plasma Cell Neoplasms
Publications
Leukemia
Regression Analysis
Datasets

ASJC Scopus subject areas

  • Hematology
  • Cancer Research
  • Anesthesiology and Pain Medicine

Cite this

Chng, W. J., Chung, T. H., Kumar, S. K., Usmani, S., Munshi, N., Avet-Loiseau, H., ... Sonneveld, P. (Accepted/In press). Gene signature combinations improve prognostic stratification of multiple myeloma patients. Leukemia. https://doi.org/10.1038/leu.2015.341

Gene signature combinations improve prognostic stratification of multiple myeloma patients. / Chng, W. J.; Chung, T. H.; Kumar, Shaji K; Usmani, S.; Munshi, N.; Avet-Loiseau, H.; Goldschmidt, H.; Durie, B.; Sonneveld, P.

In: Leukemia, 16.12.2015.

Research output: Contribution to journalArticle

Chng, WJ, Chung, TH, Kumar, SK, Usmani, S, Munshi, N, Avet-Loiseau, H, Goldschmidt, H, Durie, B & Sonneveld, P 2015, 'Gene signature combinations improve prognostic stratification of multiple myeloma patients', Leukemia. https://doi.org/10.1038/leu.2015.341
Chng, W. J. ; Chung, T. H. ; Kumar, Shaji K ; Usmani, S. ; Munshi, N. ; Avet-Loiseau, H. ; Goldschmidt, H. ; Durie, B. ; Sonneveld, P. / Gene signature combinations improve prognostic stratification of multiple myeloma patients. In: Leukemia. 2015.
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