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Molecular stratification of metastatic melanoma using gene expression profiling : Prediction of survival outcome and benefit from molecular targeted therapy

Authors :
Sofia K. Gruvberger-Saal
Katja Harbst
Christian Ingvar
Linda Werner-Hartman
Anders Kvist
Kari Nielsen
Erik Fredlund
Henrik Ekedahl
Frida Rosengren
Åke Borg
Helena Cirenajwis
Håkan Olsson
Lao H. Saal
Hensin Tsao
Ana Carneiro
Martin Lauss
Göran Jönsson
Lotta Lundgren
Jillian Howlin
Markus Ringnér
Johan Staaf
Karin Jirström
Pär-Ola Bendahl
Jens Enoksson
Therese Törngren
Source :
Oncotarget, ResearcherID, Oncotarget; 6(14), pp 12297-12309 (2015)
Publication Year :
2015
Publisher :
Impact Journals LLC, 2015.

Abstract

Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.

Details

Language :
English
ISSN :
19492553
Volume :
6
Issue :
14
Database :
OpenAIRE
Journal :
Oncotarget
Accession number :
edsair.doi.dedup.....6d2b44dfa515b9ed118c6317b63512c8