MicroRNAs induced in melanoma treated with combination targeted therapy of Temsirolimus and Bevacizumab

Abstract

Background: Targeted therapies directed at commonly overexpressed pathways in melanoma have clinical activity in numerous trials. Little is known about how these therapies influence microRNA (miRNA) expression, particularly with combination regimens. Knowledge of miRNAs altered with treatment may contribute to understanding mechanisms of therapeutic effects, as well as mechanisms of tumor escape from therapy. We analyzed miRNA expression in metastatic melanoma tissue samples treated with a novel combination regimen of Temsirolimus and Bevacizumab. Given the preliminary clinical activity observed with this combination regimen, we hypothesized that we would see significant changes in miRNA expression with combination treatment.

Methods: Using microarray analysis we analyzed miRNA expression levels in melanoma samples from a Cancer Therapy Evaluation Program-sponsored phase II trial of combination Temsirolimus and Bevacizumab in advanced melanoma, which elicited clinical benefit in a subset of patients. Pre-treatment and post-treatment miRNA levels were compared using paired t-tests between sample groups (patients), using a p-value < 0.01 for significance.

Results: microRNA expression remained unchanged with Temsirolimus alone; however, expression of 15 microRNAs was significantly upregulated (1.4 to 2.5-fold) with combination treatment, compared to pre-treatment levels. Interestingly, twelve of these fifteen miRNAs possess tumor suppressor capabilities. We identified 15 putative oncogenes as potential targets of the 12 tumor suppressor miRNAs, based on published experimental evidence. For 15 of 25 miRNA-target mRNA pairings, changes in gene expression from pre-treatment to post-combination treatment samples were inversely correlated with changes in miRNA expression, supporting a functional effect of those miRNA changes. Clustering analyses based on selected miRNAs suggest preliminary signatures characteristic of clinical response to combination treatment and of tumor BRAF mutational status.

Conclusions: To our knowledge, this is the first study analyzing miRNA expression in pre-treatment and post-treatment human metastatic melanoma tissue samples. This preliminary investigation suggests miRNAs that may be involved in the mechanism of action of combination Temsirolimus and Bevacizumab in metastatic melanoma, possibly through inhibition of oncogenic pathways, and provides the preliminary basis for further functional studies of these miRNAs.

Figures

Figure 1

Unsupervised clustering analysis of miRNA expression. The heat map illustrates the result of the two-way hierarchical clustering of miRNAs and samples. Each row represents one miRNA and each column represents one sample, including pre-treatment, post-Temsirolimus alone, or post-combination treatment samples from patients #1 through 12. Samples resubmitted for quality assurance purposes are marked by a shaded oval enclosing the duplicate samples. The color scale illustrates the relative expression level (log median ratio, LMR) of a miRNA across all samples: red color represents an expression level above the mean, blue color represents expression lower than the mean. Clustering was performed on all samples and on the 50 miRNAs with the highest standard deviation across the sample set.

Figure 2

Significant differential expression of miRNA with treatment. Volcano plots were generated to facilitate identification of significantly differentially expressed miRNAs with Temsirolimus alone (A) and with combination treatment (B). The plot shows fold-change (dLMR) on the x-axis and –log10 (p-value) on the y-axis. Criteria used to identify significantly differentially expressed miRNAs included 1) two-tailed t-test p-value < 0.01 and 2) absolute delta-log median ratio (dLMR) value > 0.5. miRNA marked by solid red circles are putative tumor suppressors.

Figure 3

Inverse correlation between changes in miR-let-7b and proposed target LIN28B mRNA. miR-let-7b fold change (2^dLMR) with combination treatment is plotted against log10 of the percent change in LIN28B mRNA with combination treatment (post-treatment expression/pre-treatment expression) for each patient for whom both pre-treatment and post-combination treatment samples were available. The slope and intercept of the linear trendline were -1.75 and 3.7, respectively.

Figure 4

Clustering analysis of miRNA expression according to clinical outcome and BRAF tumor status. The heat map illustrates the result of the two-way hierarchical clustering of pre-selected miRNAs and samples. The color scale illustrates the relative expression level or changes in expression level across all samples: red color represents an expression level above the mean and blue color represents expression lower than the mean. Patients #5, 7, and 8 had progressive disease (PD), patient #6 and 9 had partial responses (PR), and the remaining patients had stable disease (SD). (A) Clustering was performed with pre-treatment expression values (LMRs) for miRNAs with t-test p-value < 0.01 and effect size > 0.5. (B) Clustering was performed with changes in miRNA expression (dLMRs) with combination treatment for miRNAs whose t-test p-value < 0.04 and effect size > 0.5. (C) Clustering was performed with pre-treatment expression values (LMRs) for miRNAs whose t-test p-value < 0.02 and effect size > 0.5, using p-values obtained from two-tailed t-tests comparing the average expression level for patients with BRAF mutant melanomas (in orange) with those who had wild-type BRAF melanomas.