Independent replication of a melanoma subtype gene signature and evaluation of its prognostic value and biological correlates in a population cohort.

Jérémie Nsengimana,Joost J Van Den Oord,Antje Sucker,Christy Walker,Pascal Wolter,D Timothy Bishop,Julia Newton-Bishop,Dirk Schadendorf,Göran B Jönsson,Rosalyn Jewell,Poulam Patel,Jon Laye,Anastasia Filia

doi:10.18632/oncotarget.3549

Abstract

Development and validation of robust molecular biomarkers has so far been limited in melanoma research. In this paper we used a large population-based cohort to replicate two published gene signatures for melanoma classification. We assessed the signatures prognostic value and explored their biological significance by correlating them with factors known to be associated with survival (vitamin D) or etiological routes (nevi, sun sensitivity and telomere length). Genomewide microarray gene expressions were profiled in 300 archived tumors (224 primaries, 76 secondaries). The two gene signatures classified up to 96% of our samples and showed strong correlation with melanoma specific survival (P=3 x 10(-4)), Breslow thickness (P=5 x 10(-10)), ulceration (P=9.x10-8) and mitotic rate (P=3 x 10(-7)), adding prognostic value over AJCC stage (adjusted hazard ratio 1.79, 95%CI 1.13-2.83), as previously reported. Furthermore, molecular subtypes were associated with season-adjusted serum vitamin D at diagnosis (P=0.04) and genetically predicted telomere length (P=0.03). Specifically, molecular high-grade tumors were more frequent in patients with lower vitamin D levels whereas high immune tumors came from patients with predicted shorter telomeres. Our data confirm the utility of molecular biomarkers in melanoma prognostic estimation using tiny archived specimens and shed light on biological mechanisms likely to impact on cancer initiation and progression.

Highlights

Considerable efforts have been devoted to improving estimation of cancer prognosis with varying levels of successes
We tested the association between this signature and characteristics of the melanoma patients that we have previously reported to be related to melanoma susceptibility pathways, namely telomere length predicted from inherited genetic variation [13], number of melanocytic nevi [14, 15] and sun sensitivity score [16], to test the hypothesis that different “routes” to melanoma [17] may determine the nature of the tumor
We aimed to classify these samples using gene signature centroids developed in the Swedish cohort of primary tumors assayed on an earlier version of DASL array (HT8 v3) and that had been filtered during quality control (QC) to retain 8932 best performing probes [11]

Summary

Introduction

Considerable efforts have been devoted to improving estimation of cancer prognosis with varying levels of successes. The American Joint Committee on Cancer (AJCC) proposed a staging system based on data from 31,000 melanoma patients [1]. This powerful tool uses histopathological features such as www.impactjournals.com/oncotarget. A review of published melanoma biomarker reports highlighted a paucity of sufficiently powered and well-designed gene expression studies. The few that were compliant with REMARK (REporting recommendations for MARKer prognostic studies [7]) showed the ability of expression signatures to reproducibly predict melanoma prognosis, the most advanced tumors [8, 9]. It was suggested that elucidation of the translational value of these gene signatures requires more research using larger datasets with well-annotated risk factors [8]

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