Faculty Bibliography

Despite major advances in the treatment of metastatic melanoma, treatment failure is still inevitable in most cases. Manipulation of key epigenetic regulators, including inhibition of Bromodomain and extra-terminal domain (BET) family members impairs cell proliferation in vitro and tumor growth in vivo in different cancers, including melanoma. Here, we investigated the effect of combining the BET inhibitor JQ1 with the BRAF inhibitor Vemurafenib in in vitro and in vivo models of BRAF-mutant melanoma. We performed cytotoxicity and apoptosis assays, and a xenograft mouse model to determine the in vitro and in vivo efficacy of JQ1 in combination with Vemurafenib against BRAF-mutant melanoma cell lines. Further, to investigate the molecular mechanisms underlying the effects of combined treatment, we conducted antibody arrays of in vitro drug-treated cell lines and RNA sequencing of drug-treated xenograft tumors. The combination of JQ1 and Vemurafenib acted synergistically in BRAF-mutant cell lines, resulting in marked apoptosis in vitro, with upregulation of proapoptotic proteins. In vivo, combination treatment suppressed tumor growth and significantly improved survival compared to either drug alone. RNA sequencing of tumor tissues revealed almost four thousand genes that were uniquely modulated by the combination, with several anti-apoptotic genes significantly down-regulated. Collectively, our data provide a rationale for combined BET and BRAF inhibition as a novel strategy for the treatment of melanoma.

The American Joint Committee on Cancer staging system for cutaneous melanoma is based on primary tumor thickness and the presence of ulceration, mitoses, lymph node spread, and distant metastases as determinants of prognosis. Although this cutaneous melanoma staging system has evolved over time to more accurately reflect patient prognosis, improvements are still needed, because current understanding of the particular factors (genetic mutation, expression alteration, host response, etc) that are critical for predicting patient outcomes is incomplete. Given the clinical and biologic heterogeneity of primary melanomas, new prognostic tools are needed to more precisely identify patients who are most likely to develop advanced disease. Such tools would affect clinical surveillance strategies and aid in patient selection for adjuvant therapy. The authors reviewed the literature on prognostic molecular and immunologic markers in primary cutaneous melanoma, their associations with clinicopathologic and survival outcomes, and their potential for incorporation into current staging models. Overall, the studies considered in this review did not define prognostic markers that could be readily incorporated into the current staging system. Therefore, efforts should be continued in these and other directions to maximize the likelihood of identifying clinically useful prognostic biomarkers for cutaneous melanoma. Cancer 2015. (c) 2015 American Cancer Society.

PURPOSE: Brain metastasis is the major cause of mortality among melanoma patients. A molecular prognostic test that can reliably stratify patients at initial melanoma diagnosis by risk of developing brain metastasis may inform the clinical management of these patients. EXPERIMENTAL DESIGN: We performed a retrospective, cohort-based study analyzing genome-wide and targeted microRNA expression profiling of primary melanoma tumors of three patient cohorts (n= 92, n= 119, n= 45) with extensive clinical follow up. We used Cox regression analysis to establish a microRNA-based signature that improves the ability of the current clinicopathologic staging system to predict the development of brain metastasis. RESULTS: Our analyses identified a 4-microRNA (miR-150-5p, miR-15b-5p, miR-16-5p, and miR-374b-3p) prognostic signature that, in combination with stage, distinguished primary melanomas that metastasized to the brain from non-recurrent and non-brain-metastatic primary tumors (training cohort: C-index=81.4%, validation cohort: C-index=67.4%, independent cohort: C-index=76.9%). Corresponding Kaplan-Meier curves of high- vs. low-risk patients displayed a clear separation in brain-metastasis-free and overall survival (training: p<0.001, p<0.001, validation: p=0.033, p=0.007, independent: p=0.021, p=0.022, respectively). Finally, of the microRNA in the prognostic model, we found that the expression of a key lymphocyte miRNA, miR-150-5p, which is less abundant in primary melanomas metastatic to brain, correlated with presence of CD45+ tumor infiltrating lymphocytes. CONCLUSIONS: A prognostic assay based on the described miRNA expression signature combined with the currently used staging criteria may improve accuracy of primary melanoma patient prognoses and aid clinical management of patients, including selection for adjuvant treatment or clinical trials of adjuvant therapies.

Background: Manipulation of key epigenetic regulators in melanoma proliferation is emerging as a new therapeutic strategy. Bromodomain-containing proteins such as the extraterminal domain (BET) family are components of transcription factor complexes and determinants of epigenetic memory. We investigated the expression of BRD4, a BET family member in melanoma cell lines and tissues, and the effects of its inhibition with the small molecule compounds MS436 and MS417 in in vitro and in vivo models of melanoma. Methods: BRD2 and BRD4 expression were analyzed by immunohistochemistry. We tested the effects of pharmacological or RNAi-mediated inhibition of BRD4 in melanoma cells using crystal violet-based assays for proliferation/colony formation and flow-cytometry for cell cycle analysis. The molecular effects of BRD4 suppression were examined using RNA sequencing, Real-Time quantitative PCR and western blots for p27, p21, MYC, ERK1 and SKP2. In the in vivo xenograft experiments NOD/SCID/IL2R-/-mice were injected with melanoma cells and treated with MS417. Statistical significance was determined by unpaired t-test (GraphPad). Results: BRD4 was found significantly upregulated in primary and metastatic melanoma tissues compared to melanocytes and nevi (p<0.001). Treatment with BET inhibitors impaired melanoma cell proliferation in vitro and tumor growth and metastatic behavior in vivo, effects that were mostly recapitulated by individual silencing of BRD4. Rapidly after BET displacement, key cell cycle genes (SKP2, ERK1 and c-MYC) were downregulated concomitantly with the accumulation of CDK inhibitors (p21, p27), followed by melanoma cell cycle arrest. BET inhibitor efficacy was not influenced by BRAF or NRAS mutational status. Conclusions: Our results demonstrate for the first time a role for BRD4 in melanoma maintenance and support the role of BET proteins as novel targets in melanoma. Further investigation in the clinical setting is warranted

Background: Estimating the risk of recurrence in patients with melanoma is extremely challenging. Standard of care is AJCC staging system, but the accuracy and robustness of this method is still under development. We conducted a proof of concept study exploring the use of machine-learned Bayesian Belief Networks (ml-BBNs) using a miRNA profiled cohort of melanoma patients with extended follow up to create Bayesian Biological Systems Models (BBSMs). We sought to determine if ml-BBNs could describe the biological system and if we could use the model to identify new cases with higher risk of recurrence. Methods: Our study cohort consisted of 89 patients (42 of which recurred) with a median follow up time of 118 months, that were examined for 869 miRNAs. Prior to modeling we segmented the data into training data (72 cases/80%) and testing data (17 cases/20%) at random. We recursively trained ml-BBNs on the training set, using all miRNAs. We used the directed graph structure of the ml-BBNs to identify miRNAs that consistently had more connectivity and goodness of fit as determined by Bayesian Information Criteria (BIC) scoring. MiRNAs that were in the top 50 BIC-scoring nodes across all models were selected for use to train the recurrence BBSMs. To compensate for a small number, bootstrapping was used to increase the sample to 100 records. We then compared our test set cases to our recurrence model, and used a similarity scoring algorithm to evaluate the similarity of values in each test instance to our biological models. For comparison we also trained an ml-BBN using clinical data from the same cohort. We then evaluated the scores against known recurrence outcome using Receiver Operating Characteristic (ROC) curve analysis. Results: BIC-scoring analysis selected 35 miRNAs for use in BBSM modeling. Area Under the Curve (AUC) for detection of recurrence is 0.76 in the training set and 0.62 in the testing set, while the clinical data yielded an AUC of 0.5 in this cohort. Conclusions: Our data suggest !

Melanoma incidence and associated mortality continue to increase worldwide. The lack of treatments with durable responses for stage IV melanoma may be due, at least in part, to an incomplete understanding of the molecular mechanisms that regulate tumor initiation and/or progression to metastasis. Recent evidence supports miRNA dysregulation in melanoma impacting several well-known pathways such as the PI3K/AKT or RAS/MAPK pathways, but also underexplored cellular processes like protein glycosylation and immune modulation. There is also increasing evidence that miRNA can improve patient prognostic classification over the classical staging system and provide new therapeutic opportunities. The integration of this recently acquired knowledge with known molecular alterations in protein coding genes characteristic of these tumors (i.e., BRAF and NRAS mutations, CDKN2A inactivation) is critical for a complete understanding of melanoma pathogenesis. Here, we compile the evidence of the functional roles of miRNAs in melanomagenesis and progression, and of their clinical utility as biomarkers, prognostic tools and potential therapeutic targets. Characterization of miRNA alterations in melanoma may provide new angles for therapeutic intervention, help to decipher mechanisms of drug resistance, and improve patient classification for disease surveillance and clinical benefit.

We examined the microRNA signature that distinguishes the most common melanoma histological subtypes, superficial spreading melanoma (SSM) and nodular melanoma (NM). We also investigated the mechanisms underlying the differential expression of histology-specific microRNAs. MicroRNA array performed on a training cohort of 82 primary melanoma tumors (26 SSM, 56 NM), and nine congenital nevi (CN) revealed 134 microRNAs differentially expressed between SSM and NM (P<0.05). Out of 134 microRNAs, 126 remained significant after controlling for thickness and 31 were expressed at a lower level in SSM compared with both NM and CN. For seven microRNAs (let-7g, miR-15a, miR-16, miR-138, miR-181a, miR-191, and miR-933), the downregulation was associated with selective genomic loss in SSM cell lines and primary tumors, but not in NM cell lines and primary tumors. The lower expression level of six out of seven microRNAs in SSM compared with NM was confirmed by real-time PCR on a subset of cases in the training cohort and validated in an independent cohort of 97 melanoma cases (38 SSM, 59 NM). Our data support a molecular classification in which SSM and NM are two molecularly distinct phenotypes. Therapeutic strategies that take into account subtype-specific alterations might improve the outcome of melanoma patients.

Background: We hypothesize that BRAF mutations result in microRNA (miRNA) alterations which contribute to orchestrating the mutant BRAF's oncogenic effects in melanoma. Our study is the first to examine the association between the BRAF mutation status in primary melanomas and the expression of miRNAs that target known tumor suppressors. Methods: 84 prospectively accrued melanoma patients at New York University Langone Medical Center were studied. DNA and total RNA were extracted from consecutive sections of formalin-fixed paraffin-embedded primary tissues. BRAF mutation status was determined by DNA sequencing. RNA was hybridized to miRCURY miRNA microarrays containing 1314 probes. Normalized miRNA data were analyzed using the t-test (p<0.05) to identify differentially expressed miRNAs between BRAFmut vs. BRAFwt cases. Those with an average fold change (FC) > 2 were selected for predicted (TargetScan, PicTar) and validated (miRWalk) gene target analysis, and overlapping genes targeted by 2 miRNAs were analyzed using pathway-mapping algorithms (KEGG, BioCarta, PANTHER). Results: 48 (57%) primaries were BRAFwt and 36 (43%) were BRAFmut (26 V600E, 4 V600K, 1 V600R, 1 V600D, 4 other). 30 miRNAs met the criteria for statistically significant differential expression and FC thresholding: let-7i, miR-23c, -26a/b, -27b, -34a, -98, -126*, -141, -148a, -181b, -195, -199a-3p, -199a/b-5p, -200a/b/c, -203, -205, -455-3p, -491-3p, -606, -641, -646, -1297, -4301; miRPlus-C1070, -C1110, -G1246-3p (average FC: 2.3-3.5, all increased in BRAFmut vs. BRAFwt). Predicted and validated target gene analysis revealed 317 genes, of which 110 (35%) were convergent targets of 2 miRNAs. Pathway analyses of the predicted, validated, and convergent target genes pointed to the potential impact of BRAFmut-associated miRNAs on known tumor suppressors FAS, PTEN, and TNF and the p53 pathway. Conclusions: Differentially expressed miRNAs in BRAFmut vs. BRAFwt primaries target genes with known roles in melanoma biology and/or treatmen!