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

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.

Keywords: BRAF; BRAF inhibitor; gene expression; melanoma; mutation.

Figure 1. Gene expression phenotypes in melanoma

A) Heatmap of 299 genes (rows) included in the classification of 214 melanoma tumors (columns). Tumor descriptions are shown in the color bars including phenotype classification and tumor type. B) Network analysis identified five clusters of genes reflecting biological mechanisms of relevance in melanoma and named thereafter. Each dot (pink) represents a gene that is connected by lines (blue) representing correlations between the genes. C) Immunohistochemical staining of MITF, Ki67, CD3 were performed in 59 tumors. Three representative tumors of the gene expression phenotypes are shown in the figure. Sections were also stained with hematoxylin/eosin (HE) to see structural patterns in the tissues.

Figure 2. Analysis of the mutational landscape in melanoma tumors

A) Genetic events such as mutations, homozygous deletions and focal amplifications in cancer genes within the context of the gene expression phenotypes. Tumors are ordered according to the gene expression phenotypes and the genes of interest. The mutation frequency plot corresponds to the number of somatically acquired mutations observed in the 1697 investigated cancer-associated genes in each melanoma tumor. B) Mutations in genes involved in the MAPK pathway. Tumors are ordered according to mutations in BRAF, NRAS, NF1, KIT, KRAS and CCND1. C). Genetic events in genes involved in the CDKN2A-RB1 pathway. Tumors are ordered according to genetic events in CDKN2A, CDK4, CCND1 and RB1.

Figure 3. Survival analysis of metastatic melanomas stratified by gene expression phenotype using the Kaplan-Meier estimator to determine

A) Distant metastasis free survival (DMFS) and B) and disease specific survival (DSS). C) Metastatic tumors from the TCGA data were stratified and Kaplan-Meier analysis was performed. D) Pigmentation-classified tumors were stratified by the cell cycle module (low or high). Survival differences between low and high groups were estimated using Kaplan-Meier analysis. P-values have been calculated using the log-rank test.

Figure 4. Gene expression phenotypes and prediction of clinical benefit from molecular targeted therapies

A) Melanoma tumors from patients treated with BRAFi [16] or B) BRAFi/MEKi [17] were classified into the gene expression phenotypes and further analyzed for objective response (RECIST response, %) (4A, upper panel; 4B left panel) and phenotype distribution in pre-treatment and post-relapse biopsies (4A, lower panel; 4B, middle and right panel). C) Gene expression phenotype distribution in patients treated with MAGE-A3 vaccine [14]. The fraction of patients with clinical and no benefit is indicated for each phenotype.