Gene expression risk signatures maintain prognostic power in multiple myeloma despite microarray probe set translation

Niels Emil Hermansen, Rehannah Borup, Mette Klarskov Andersen, Annette Juul Vangsted, Nielsaage Tøffner Clausen, Dan Lennart Kristensen, Finn Cilius Nielsen, Peter Gimsing

Publikation: Bidrag til tidsskriftArtikelForskningpeer review

Abstrakt

Gene expression profiling signatures have proven superior to the International Staging System and cytogenetic markers in multiple myeloma prognostication. But the current gene expression risk signatures are all based on 3'-end microarrays and a common standard remains disputed. We hypothesized that upon translation to a whole-transcript microarray one of nine gene expression risk signatures would outperform other prognostic factors. We studied CD138 positive bone marrow plasma cells in a prospective, consecutive cohort of 59 newly diagnosed high-dose candidates and 67 previously high-dose treated patients with progressive disease. Median follow-up was 66 months (range 42-87). Samples with del(17p13), t(4;14), or t(14;16) were cytogenetic high-risk. We used Affymetrix Human Gene 1.0 ST microarrays for gene expression profiling. Six independent gene expression risk signatures and three meta-signatures developed for other microarrays were translated by probeset match and applied to our results. In multivariate Cox regression analysis for progression-free survival and overall survival, none of the translated risk signatures were prognostically supreme. But various gene expression risk signatures or combinations hereof were significantly correlated with survival, primarily in combination with cytogenetic high-risk markers among newly diagnosed patients, and in combination with International Staging System stage III among patients with progressive disease. In summary, we found gene expression risk signatures to maintain significant prognostic power in multiple myeloma at the time of both diagnosis and progressive disease despite translation. We suggest probeset matching for risk signature translation across microarrays as part of the efforts towards a common gene expression risk standard. (ClicinalTrials.gov identifier: NCT00639054)
OriginalsprogDansk
Sider (fra-til)298-307
Antal sider10
TidsskriftInternational Journal of Laboratory Hematology
Vol/bind38
Udgave nummer3
DOI
StatusUdgivet - 2016

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