European Journal of Cell Biology 93 (2014) 11–22

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European Journal of Cell Biology journal homepage: www.elsevier.com/locate/ejcb

Mini Review

The role of microRNAs in melanoma夽 Chonglin Luo a,∗ , Claudia E.M. Weber a , Wolfram Osen a , Anja-Katrin Bosserhoff b , Stefan B. Eichmüller a,∗ a b

Translational Immunology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany Institute of Pathology, University of Regensburg, 93053 Regensburg, Germany

a r t i c l e

i n f o

Article history: Received 5 September 2013 Received in revised form 22 January 2014 Accepted 3 February 2014 Keywords: Melanoma MicroRNA Expression profiling Target identification Bioinformatics Oncogene Tumor suppressor Diagnosis Tumor marker Therapy

a b s t r a c t Melanoma is the most dangerous form of skin cancer, being largely resistant to conventional therapies at advanced stages. Understanding the molecular mechanisms behind this disease might be the key for the development of novel therapeutic strategies. MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally control gene expression, thereby regulating various cellular signaling pathways involved in the initiation and progression of different cancer types, including melanoma. In this review, we summarize approaches for the identification of candidate miRNAs and their target genes and review the functions of miRNAs in melanoma. Finally, we highlight the recent progress in pre-clinical use of miRNAs as prognostic markers and therapeutic targets.

Introduction miRNAs represent a large family of short (∼22 nucleotides), endogenous and single-stranded RNA molecules that regulate gene expression post-transcriptionally (Bartel, 2004, 2009). In humans, miRNAs are predicted to target at least 30% of all protein coding genes (Krek et al., 2005). Functional studies show that miRNAs participate in the regulation of mostly every cellular process investigated so far, and that they are involved in many human diseases (Krol et al., 2010). Primary miRNA (pri-miRNA) is transcribed from an independent gene or from an intron of a protein-coding gene by RNA polymerase II (RNAPII) in the nucleus (Winter et al., 2009). A member of RNase III family, Drosha, and a double-stranded RNA binding protein, DGCR8, form a complex that processes the pri-miRNA into a

Abbreviations: EZH2, enhancer of zeste homolog 2; HGF, hepatocyte growth factor; MITF, microphthalmia-associated transcription factor; NHEM, normal human epidermal melanocyte; YB1, Y box binding protein 1. 夽 Parts of this article have been published as doctoral thesis by Dr. Chonglin Luo. ∗ Corresponding authors at: DKFZ, Division of Translational Immunology (D015), INF 280, 69120 Heidelberg, Germany. Tel.: +49 6221423380. E-mail addresses: [email protected] (C. Luo), [email protected] (S.B. Eichmüller). http://dx.doi.org/10.1016/j.ejcb.2014.02.001 0171-9335/© 2014 Elsevier GmbH. All rights reserved.

© 2014 Elsevier GmbH. All rights reserved.

∼70-nucleotide hairpin precursor (pre-miRNA) which is exported to the cytoplasm by Exportin 5 in a Ran-GTP-dependent manner. Some pre-miRNAs are processed directly from short introns (mirtrons), due to splicing and debranching, therefore bypassing the Drosha-DGCR8 step. In either case, pre-miRNA is cleaved by another RNase III enzyme, Dicer, with the assistance of RNA binding protein TRBP to form a ∼70 bp miRNA/miRNA* duplex. In mammals, the 3 arm of some pre-miRNAs with high degree of complementarity along the hairpin stem is cleaved by Argonaute 2 (AGO2) before Dicer-mediated cleavage, thus forming an additional intermediate called AGO2-cleaved precursor miRNA (ac-pre-miRNA), which facilitates subsequent strand dissociation (Diederichs and Haber, 2007). Subsequently, one strand of the miRNA/miRNA* duplex (guide strand) is preferentially integrated into a miRNA-induced silencing complex (miRISC), while the other strand (passenger strand or miRNA*) is released and becomes degraded. Not all miRNA* are mere byproducts and sometimes both strands can be functional. Based on complementarity, the miRNA guides the miRISC to the target mRNA, leading to translational repression, mRNA deadenylation, or mRNA degradation (Winter et al., 2009). In the recent years it has become evident that miRNAs play an important role in cancer (Iorio and Croce, 2012), including melanoma (Kunz, 2013; Voller et al., 2013). This review gives an overview about miRNA expression profiling in melanoma and

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describes the role of miRNAs as tumor suppressors or oncogenes with particular emphasis on melanoma. Furthermore, the potential clinical use of miRNAs as tumor markers and as therapeutic targets is discussed.

Expression profiling of miRNAs miRNA expression profiling has been widely performed to identify miRNAs that are involved in melanoma development and progression (Table 1). The earliest publication concerning miRNAs in melanoma dates back to 2005, when Lu et al. (2005) utilized a bead-based miRNA profiling method to analyze 217 miRNAs derived from 334 samples of various tumor entities and from normal tissues. In this pioneer study, they found that miRNA profiles were suitable to classify tumors with respect to their developmental lineage and differentiation state. In fact, there were only three melanoma tissue samples and two melanoma cell lines, which did not group together in the clustering analysis (Lu et al., 2005). In the next two years, more melanoma cell lines were included in three studies which analyzed miRNA copy number or miRNA expression patterns in panels of different tumor tissues and tumor cell lines (Blower et al., 2007; Gaur et al., 2007; Zhang et al., 2006). In 2007, miRNA profiling studies using the NCI60 panel showed that tumor cell lines clustered in a way that reflected their tissue origin (Blower et al., 2007; Gaur et al., 2007). Comparison of miRNA expression patterns between compound potency patterns suggested that miRNAs might play a role in chemo-resistance (Blower et al., 2007). Mueller et al. (2009) reported the first comprehensive miRNA expression profiling in human normal epidermal melanocytes (NHEMs) and in well-characterized melanoma cell lines derived from primary and metastatic tumors. They identified 91 differentially expressed miRNAs in primary melanoma cell lines compared to melanocytes, as well as 15 differentially expressed miRNAs in metastatic cell lines compared to primary cell lines and melanocytes. In both comparisons, most of the differentially expressed miRNAs were upregulated. Comparison between highly and weakly invasive cell lines revealed 33 differentially expressed miRNAs. Expression of several candidate miRNAs was confirmed by qPCR in these cell lines as well as in tissue samples. Thus, this study identified miRNAs that might be dysregulated at different steps of melanoma progression such as early progression, invasion and metastasis (Mueller et al., 2009). Other research groups working on miRNA profiling in melanoma focused their studies on different aspects, e.g. association with cell growth, differentiation, invasion, and epithelial–mesenchymal transition (EMT) (Jukic et al., 2010) or prognostic value (Segura et al., 2010). In a comprehensive study, miRNA expression profiles for NHEMs and melanoma cell lines were generated using miRNA microarrays and real-time miRNA reverse transcriptionPCR arrays, followed by qPCR validation (Philippidou et al., 2010). Tissue samples including benign nevi, as well as primary and metastatic tumors were also analyzed, in order to compare their miRNA expression pattern with those of the cell lines. Inconsistent results were found between different detection techniques and also between tissue samples and cell lines (Philippidou et al., 2010). Discrepant results between microarray and qPCR analyses or between different microarray platforms may come from the intrinsic technical difficulties within the microarray. Although microarray technology has been successfully utilized to detect and quantify gene expression, it faces unique challenges when dealing with miRNAs compared to its use in mRNA profiling: the short nucleotide sequence of miRNAs limits the options for primer design; mature miRNAs are hard to distinguish from their precursors as well as from their family members that may differ by

only a single nucleotide; mature miRNAs often have quite different melting temperatures (Tm ) making it difficult to determine the hybridization conditions suitable to cover the entire array for hundreds of miRNAs (Git et al., 2010). Git et al. (2010) compared the performances of six miRNA microarray platforms by analyzing three biological samples comprised of normal breast tissue, the luminal breast cancer cell line MCF7, and a breast progenitor cancer cell line PMC42. Among these samples, the overlap of differentially expressed miRNAs identified by the six platforms was very low and fold changes of differentially expressed miRNAs obtained from microarray data were compressed compared to those obtained from qPCR data (Git et al., 2010). Pradervand et al. (2010) analyzed differential miRNA expression in RNA samples from human brain and heart using Agilent, Illumina and Affymetrix microarrays, as well as qPCR (Applied Biosystems), and deep sequencing (Illumina). The qPCR and deep sequencing results were highly correlated (r = 0.9). The Agilent platform showed the best correlation with qPCR (r = 0.9) and deep sequencing (r = 0.83), and also the least fold change compression (Pradervand et al., 2010). The two most recent miRNA profiling studies in melanoma were carried out using Agilent microarray platform followed by Taqman qPCR validation (Couts et al., 2013; Sand et al., 2013). Comparing the miRNA expression levels between primary melanocytes and BRAF V600E-positive melanoma cell lines, or between melanoma cells treated with and without an MKK1/2 inhibitor, a network of more than 20 miRNAs was found to be dysregulated by aberrant B-Raf/MKK/ERK signaling in melanoma cells (Couts et al., 2013). Analysis of the expression levels of 1205 miRNAs in clinical samples from primary melanoma, metastases, and benign melanocytic nevi identified 19 novel miRNA candidates being dysregulated in cutaneous melanoma (Sand et al., 2013). Although microarray approaches are widely used in miRNA expression profiling, they are limited to the analysis of known miRNA species. Deep sequencing is a promising alternative technology as it is able to identify and quantify also novel miRNAs. Stark and co-workers deep sequenced 12 small RNA libraries from melanoblasts, melanocytes, congenital nevus as well as from acral, mucosal, cutaneous and uveal melanoma cells, and identified 539 known mature miRNAs along with 279 predicted novel miRNAs (Stark et al., 2010). Some of the potentially novel miRNAs were likely to be specific for the melanocytic lineage and might become interesting candidates in melanoma research (Stark et al., 2010). In a recent study, deep sequencing was performed on tissues or cell lines from primary and metastatic melanoma, normal skin, nevi and NHEM, which identified 698 known mature miRNAs and 429 putative novel miRNAs (Kozubek et al., 2013). A top-40 list of the known miRNAs was able to classify different disease groups and control groups. Three putative miRNAs were differentially expressed among the disease groups (Kozubek et al., 2013). These studies demonstrate that deep sequencing is a robust technology for miRNA expression analysis in melanoma.

Regulation of miRNA expression miRNA expression can be influenced by different mechanisms, such as regulation of transcription, epigenetic regulation, alterations within the miRNA biogenesis machinery, and chromosomal abnormalities (Iorio et al., 2010) (Table 2). Expression of miR-21 can be induced by AP-1 (c-Jun/c-Fos heterodimer) transcription factor which in turn inhibits expression of PTEN and PDCD4 (Talotta et al., 2009). Dysregulation of miR-21 was reported in melanoma and an increased copy number of miR-21 has been described in 12 out of 45 melanoma cell lines (Grignol et al., 2011). Furthermore, miR-21 was found to be upregulated in several highly invasive melanoma cell lines (Mueller et al., 2009).

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In 2007, reports from several research groups showed that members of miR-34 family are direct transcriptional targets of the tumor suppressor protein p53, for the first time connecting the p53 pathway to the miRNA network (Chang et al., 2007; He et al., 2007; Raver-Shapira et al., 2007; Tarasov et al., 2007). A substantial

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number of miR-34 targets has been identified and many of them are regulators of the cell cycle or of apoptosis, proliferation, migration and invasion, including c-MYC, E2F3, BCL2, CDK4, CDK6 and c-Met (Hermeking, 2010). Furthermore, miR-34 expression can be inactivated by promoter hypermethylation in various types of

Table 1 miRNA profiling focused on melanoma cell lines or tissues. Specimen

Number of melanoma samples

Number of NHEM or nevi

Number of miRNAs

Platforms

Main results

References

Various tumors

3 tissues, 2 cell lines 45 cell lines

None

217 283

NCBI 60 panel

8 cell lines

None

241

TaqMan microRNA assay

NCBI 60 panel

8 cell lines

None

321

Homemade miRNA microarray

Melanoma cell lines and NHEM

7 cell lines incl. 3 primary, various k.o cell lines

Pooled NHEMs from two donors

470

Agilent miRNA microarray and qPCR

FFPE melanoma tissues and nevi

Melanoma tissues from 10 old adults and 10 young adults;

6 nevi

666

Taqman microRNA low density array

FFPE melanoma tissues

59 melanoma metastases

None

911

miRdicator array platform, qPCR

Melanoma cell lines, NHEM, FFPE melanoma tissues and nevi

9 cell lines, 7 primary tumor, 10 metastases

1 NHEM, 3 pools of nevi (2 different donors each)

88 cancer-related miRNAs

RT2 miRNA PCR array, qPCR

FFPE melanoma tissues

8 melanoma metastases

8 nevi

470

Agilent miRNA microarray, qPCR

Too few melanoma samples High protion of miRNA genes were located in regions that exhibited DNA copy number abnormalities Tumor cell lines clustered based on their tissue of origin; miRNA expression levels correlated with cell proliferation indices; Tumor cell lines clustered based on their tissue of origin; miRNA expression patterns correlated with compound potency patterns, suggesting the involvement of miRNAs in chemoresistence 91 miRNAs differentially expressed in melanoma vs. NHEM; 13 miRNAs differentially expressed in primary tumor vs. metastases; 33 miRNAs associated with invasiveness Compared miRNA expression pattern between melanoma samples of old and young adults, as well as between melanoma and nevi Identified a signature of 18 miRNAs that correlated with post-recurrence survival Inconsistent results between different platforms and between cell lines and tissues 31 miRNAs differentially expressed (13 upand 18 down-regulated) in metastatic melanomas compared to benign nevi

Lu et al. (2005)

None

Bead-based miRNA profiling method Array comparative genomic hybridization

Ovarian cancer, breast cancer and melanoma

Zhang et al. (2006)

Gaur et al. (2007)

Blower et al. (2007)

Mueller et al. (2009)

Jukic et al. (2010)

Segura et al. (2010)

Philippidou et al. (2010)

Chen et al. (2010a)

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Table 1 (Continued) Specimen

Number of melanoma samples

Number of NHEM or nevi

Cell lines

9 melanoma cell lines (acral, mucosal, cutaneous and uveal melanoma)

1 cell line each of melanoblast, NHEM, nevus

Melanoma cell lines and NHEMs,

6 melanoma cell lines (B-Raf mutated) treated in the presence and absence of an MKK1/2 inhibitor 9 tissues from primary cutaneous melanoma, 4 tissues from metastases

2 NHEM cell lines

470

Dharmacon microRNA expression profiling platform, qPCR

8 nevi

1205

Agilent miRNA microarray, qPCR

Tissues from acrolentiginous melanoma (1), primary cutaneous melanoma (5), and metastases (6) 3 cell lines each from primary cutaneous melanoma and metastases

4 samples from normal skin, 2 nevi, 1 normal lymphnode, 3 cell lines of NHEM

Frozen melanoma tissues and nevi

FFPE and fresh frozen melanoma tissues, melanoma cell lines, normal skin, nevi, and NHEM

Number of miRNAs

cancer (Lodygin et al., 2008). Recently, Perera’s group undertook efforts to identify epigenetically regulated miRNAs in melanoma (Mazar et al., 2011a,b; Perera and Ray, 2012). By treating melanoma cells with the DNA methyltransferase inhibitor 5-aza-2 -deoxycytidine, this group could define a list of upregulated miRNAs with miR-375 and miR-34b being among the ones with the strongest effects. Further analysis showed that the CpG islands up-stream of miR-375 and miR-34b genes were unmethylated or poorly methylated in keratinocytes and melanocytes, whereas methylation of these CpG islands was increased in melanoma cell lines. Both, miR-375 and miR-34b were able to inhibit invasion and migration of melanoma cell lines in vitro. The authors suggested that miR-375 and miR-34b might be silenced by DNA hypermethylation, thereby impairing their tumor suppressive functions during melanoma progression. Alterations in the miRNA biogenesis machinery can also cause dysregulation of miRNA expression in cancer. The All1 fusion proteins (All1/Af4 and All1/Af9) mediate Drosha recruitment to miRNA loci to enhance the expression of the corresponding miRNAs (e.g. miR-191) in ALL-1-associated leukemias (Nakamura et al., 2007). In a human colon cancer cell line, p53 in association with DEAD-box RNA helicase p68 interacted with Drosha and facilitated the expression of several miRNAs with growth-inhibitory function (Suzuki et al., 2009). Several studies have reported the dysregulation of miRNA biogenesis factors in melanoma. Alternative processing-deficient Drosha splice variants were identified in human melanoma cell lines but they did not affect general miRNA expression in the cell lines tested (Grund et al., 2012). Expression of Dicer and Drosha was found to be reduced during progression of human melanoma (Jafarnejad et al., 2013a,b). In a more recent study, the enzyme adenosine deaminase acting on RNA (ADAR1)

Platforms

Main results

References

Deep-sequencing (Illumina Genome Analyzer II)

Identifed 539 known mature miRNAs along with 279 predicted novel miRNAs. Some of the potentially novel miRNAs were likely to be specific for the melanocytic lineage Identified a network of >20 miRNAs deregulated by B-Raf/MKK/ERK in melanoma cells 19 previously unidentified miRNAs were found to be dysregulated in cutaneous melanoma patient samples Identified 698 known mature miRNAs and 429 putative novel miRNAs; a top-40 list from the known miRNAs was able to properly classify normal from cancer

Stark et al. (2010)

Deep-sequencing (Illumina Genome Analyzer II), qPCR

Couts et al. (2013)

Sand et al. (2013)

Kozubek et al. (2013)

was shown to control the expression of more than 100 miRNAs in melanoma by the regulation of Dicer expression and by the interaction with the DGCR8-Drosha complex (Nemlich et al., 2013). In a genome-wide analysis of various cancer types including melanoma, high percentages of genomic loci containing miRNA genes showed DNA copy number alterations, which correlated with the corresponding miRNA expression levels (Zhang et al., 2006). As a good example, miR-182 encoded within the chromosomal 7q31–34 region frequently amplified in melanoma, was highly expressed in melanoma and promoted melanoma metastasis (Segura et al., 2009). miRNA as tumor suppressor The first study that links miRNA to cancer showed frequent downregulation or deletion of miR-15a and miR-16 in most chronic lymphocytic leukemia (CLL) patients (Calin et al., 2002). Since then, miRNA expression profiling and functional studies on miRNAs in cancer have been growing exponentially, demonstrating that miRNAs are important players in cancer development and progression. Cancer cells display dysregulated miRNA expression profiles compared to their normal counterparts. Studies have shown that miRNAs can act as either tumor suppressors (Table 3) or oncogenes (Table 4), depending on their downstream target genes (EsquelaKerscher and Slack, 2006). The first functional study of an individual miRNA in melanoma was reported by Bemis et al. (2008). They demonstrated that miR-137 downregulates microphthalmia-associated transcription factor (MITF) by binding to the specific target site in the 3 UTR of the MITF-encoding mRNA. Moreover, they found that miR-137 expression was decreased by ␣-MSH, suggesting that miR-137 might be

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Table 2 Specific regulation of miRNA expression levels. Regulated miRNA

Regulator/mode of action

Effect

Reported for tumor entity

References

miR-137

Variable nucleotide tandem repeat located just 5 to the pre-miR-137 sequence AP-1 (c-Jun/c-Fos heterodimer)

Alters the processing of miR-137

Melanoma

Bemis et al. (2008)

Upregulation

Talotta et al. (2009)

miR-34 family members

P53

Upregulation

Increased levels have been detected in melanoma Various

miR-34 miR-221

Hypermethylation Human polynucleotide phosphorylase (by enzymatic degradation) Hypermethylation

Downregulation Degradation

Various Melanoma

Downregulation

Melanoma

DNA methylation and histone deacetylation p53 Protein kinase C ␣ blocks the nuclear release of pri-microRNA 15a by direct binding Activation of STAT1

Downregulation

Uveal melanoma

Upregulation Downregulation

Melanoma Various

Jin et al. (2011) von Brandenstein et al. (2011)

Upregulation

Melanoma

Downregulation

Melanoma

Reinsbach et al. (2012), Schmitt et al. (2012) Asangani et al. (2012)

Up- or downregulation

Melanoma

Nemlich et al. (2013)

Upregulation

Melanoma

Downregulation Downregulation

Uveal melanoma Melanoma

Bell et al. (2014), Levy et al. (2010) Chen et al. (2013) Jiang et al. (2013)

Upregulation Downregulation

Melanoma Melanoma

Errico et al. (2013) Dar et al. (2013)

miR-21

miR-34b and miR-375 miR-137 miR-149* miR-15a

miR-29 miR-31

Various miRNAs

miR-211 miR-124a miR-768-3p miR-221&222 miR-18b

DNA methylation and EZH2-mediated histone methylation Adenosine deaminase acting on RNA 1 (ADAR1) affect the biogenesis of miRNAs MITF Hypermethylation Activation of MEK/ERK pathway HOXB7/PBX2 dimer Hypermethylation

Chang et al. (2007), He et al. (2007), Raver-Shapira et al. (2007), Tarasov et al. (2007) Lodygin et al. (2008) Das et al. (2010)

Mazar et al. (2011a,b), Perera and Ray (2012) Chen et al. (2011c)

Table 3 miRNAs validated for tumor-suppressor function in melanoma. miRNA

Activity

Approved targets

References

miR-137

Inhibits proliferation, invasion

c-Met, YBX-1, MITF, EZH2, CDC42

miR-101

Inhibits proliferation, invasion

MITF, EZH2

let-7 family

Inhibits cell cycle progression, anchorage-independnet growth

miR-26a

Inhibits tumor growth and metastasis

miR-200 family

EMT induction, downregulated during melanomagenesis, inhibits invasion

Ras, c-Myc, cyclin A, cyclin D1, cyclin D3, CDK4, integrin ß3, Dicer, HMGA2 Lin28B and Zcchc11; upregulates let-7 BIM-1, ZEB2

miR-211

Inhibits invasion, migration and anchorage dependent colony formation

NUAK1

miR-196a

Inhibits invasion, reduced melanoma tumorigenicity

HOX-C8, HOX-B7

miR-126/126*

Reduced tumor growth, decreased metastatic potential Regulates apoptosis, innate immunity, inflammation and hematopoietic differentiation

ADAM9, MMP7

Bemis et al. (2008), Deng et al. (2011), Luo et al. (2013b) Luo et al. (2013a), Smits et al. (2010) Dangi-Garimella et al. (2009), Muller and Bosserhoff (2008), Schultz et al. (2008) Couts et al. (2013), Fu et al. (2013) Liu et al. (2012), van Kempen et al. (2012), Xu et al. (2012) Bell et al. (2014), Levy et al. (2010), Mazar et al. (2010), Xu et al. (2012) Braig et al. (2010), Mueller and Bosserhoff (2011) Felli et al. (2013), Mueller et al. (2009) Kappelmann et al. (2013)

miR-125b (miR-125a)

c-Jun (protein)

Tumor-suppressor function is defined as reduced expression of a given miRNA in tumor cells and an increased proliferation or tumor growth upon knock down of the respective miRNA.

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Table 4 miRNAs validated for oncogenic function in melanoma. miRNA

Activity

Approved targets

References

miR-221/222

Promotes tumor growth, progression, cell cycle regulation, AKT pathway activation

c-KIT,CDKN1B, p27Kip1 , c-FOS, ETS-1

miR-155

Associated with malignancy (in vivo), reduced cell proliferation, enhanced apoptosis (in vitro), increased IL-8 production

SKI, FOXO3

miR-21

Upregulation correlates with malignancy, supresses IFN induced-apoptosis

PTEN, BAX, Akt,

miR-182 miR-30b/30d

Upregulation correlates with malignancy Enhances invasion, immunosuppression during metastasis

miR-214

Induced cell migration, invasion and extravasation

FOXO3, MITF GALNT7, GALNT1, SEMA3, CELSR3, TWF1, CASP2 TFAP2C, AP-2␥, PTEN

Errico et al. (2013), Felicetti et al. (2008), Mattia et al. (2011) Grignol et al. (2011), Levati et al. (2009, 2011), Philippidou et al. (2010) Grignol et al. (2011), Levati et al., (2009), Philippidou et al. (2010) Segura et al. (2009) Gaziel-Sovran et al. (2011) Bar-Eli (2011), Penna et al. (2011, 2013)

Oncogenic miRNAs are defined as miRNAs promoting proliferation or tumor growth.

involved in the sun tanning response. Subsequently, miR-137 was identified as a tumor suppressor in a variety of cancers including brain tumors, colorectal cancer, head and neck cancer, gastric cancer and melanoma (Chen et al., 2011b; Deng et al., 2011; Langevin et al., 2011; Liu et al., 2011; Silber et al., 2008). In line with these earlier reports, a recent study correlates miR-137 expression with melanoma patients’ clinical outcome indicating a shorter survival time for stage IV melanoma patients with reduced miR-137 expression (Luo et al., 2013b). We identified two novel targets (c-Met and YB1) of miR-137 and confirmed two previously known targets, namely EZH2 and MITF in melanoma cells showing that miR137 might interfere with multiple crucial pathways of melanoma development and progression (Fig. 1). Furthermore, miR-137 was demonstrated to inhibit migration, invasion and proliferation of melanoma cells through multiple targets, strongly emphasizing the tumor suppressive role of miR-137 in melanoma. Further preclinical studies are needed to evaluate whether miR-137 may be of therapeutic value in the treatment of melanoma. Another notable tumor suppressive miRNA is miR-101. Varambally et al. (2008) reported that a decreased miR-101 copy number in the genome caused a reduction of miR-101 expression during prostate cancer progression, paralleled by an increase of EZH2 expression. miR-101 could directly target EZH2 leading to the inhibition of cell proliferation, invasion and tumor growth. The regulation of EZH2 by miR-101 was confirmed in different tumor entities, including gastric cancer (Wang et al., 2010), glioblastoma (Smits et al., 2010), non-small cell lung cancer (NSCLC) (Zhang et al., 2011), and melanoma, as shown in our recent study (Luo et al., 2013a). Notably, we identified MITF as a direct target of miR-101 in melanoma cells. The functional assays showed that miR-101 could

Fig. 1. Example of small signaling network regulated by miR-101 and miR-137 in melanoma. Note that such networks will increase to high levels of complexity once more miRNAs are included.

suppress melanoma cell invasion and proliferation. Thus, miR-101 and miR-137 share two target genes (MITF and EZH2; Fig. 1). Studies on the possible interplay between them might help to understand the modulation of these important target genes in melanoma. The let-7 family has been found to act as tumor suppressor through targeting of oncogenes, such as RAS and c-Myc in various cancer types (Ventura and Jacks, 2009). Schultz et al. (2008) identified 72 differentially expressed miRNAs by miRNA expression profiling in benign melanocytic nevi and primary melanomas and reported several let-7 family members to be down regulated in primary melanoma. Among them, let-7b expression was significantly reduced in melanoma compared to nevi, suggesting a role of let-7b in the transition from nevi to primary melanomas (Johnson et al., 2005). In another study, Muller and Bosserhoff (2008) found let-7a downregulated in melanoma cell lines compared to melanocytes, whereas integrin ␤3 showed an opposite expression pattern. Recently, miR-26a was described to inhibit tumor growth and metastasis formation and upregulate let-7 (Couts et al., 2013; Fu et al., 2013). These studies demonstrated that loss of let7 family members may contribute to melanoma development and progression through the activation of various oncogenic processes including signaling pathways acting on proliferation, migration and invasion. A number of other tumor suppressive miRNAs has been shown to play essential roles in cancer, such as miR-200c which targets zinc finger E-box binding homeobox 1 (ZEB1) and facilitates EMT in various cancers (Burk et al., 2008). In melanoma, miRNAs of the miR-200 family, namely miR-200a, miR-200b, miR-200c and miR-141 as well as additional miRNAs not belonging to that family like miR-205, miR-203 and miR-211 were shown to be downregulated during melanomagenesis and are therefore suggested as tumor suppressors (Xu et al., 2012). Furthermore, miR-141 showed an additional decrease in melanoma metastases compared to primary melanoma (Xu et al., 2012). Members of the miR-200 family are described to play distinct roles in melanoma progression and malignancy (Elson-Schwab et al., 2010). However, further analysis is needed to confirm their specific role in cancer progression. It should be noted that results of miRNA analyses performed on formalin fixed and paraffin embedded (FFPE) tissue sections should be taken with care, as the composition of different cell types varies substantially between nevi and primary or metastatic melanoma tissues the miRNA content. Microdissection can improve the purity but will not completely avoid differences in the number of infiltrating cells. At least the attribute “tumor suppressor” should only be given after functional validation. For example, overexpression of miR-200c was reported to result in a significant decrease of

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proliferation, migration and drug resistance in melanoma caused by miR-200c mediated down regulation of BIM-1 (Liu et al., 2012). In most of the above-mentioned studies, miRNA expression profiling analyses were performed first to screen for dysregulated miRNA candidates, followed by target identification and functional study. In order to obtain candidate miRNAs relevant for defined functions, functional screenings using miRNA libraries have been applied to various types of cancer including lung (Cheng et al., 2005), breast (Ovcharenko et al., 2007), colorectal (Lam et al., 2010), pancreas (Izumiya et al., 2010), and to melanoma (Levy et al., 2010). Levy et al. (2010) performed a miRNA library screening in the A375M melanoma cell line using a matrigel invasion assay, and they found that cell invasion was reduced most significantly by overexpression of miR-211. Since miR-211 represents an intronic miRNA in the TRPM1 gene which is downregulated in metastatic melanoma, this miRNA has been considered as a melanoma tumor suppressor. Further experiments of the group showed a decreased expression of miR-211 along with its host gene TRPM1. Increased expression of miR-211, but not TRPM1, reduced the migration and invasion of highly invasive melanoma cells with low levels of miR211 and TRPM1. This study proposed that miR-211 acts as a tumor suppressor whose expression might be blocked via suppression of the TRPM1 locus during melanoma progression (Levy et al., 2010). This notion was further confirmed by another study in the same month (Mazar et al., 2010). The investigation of miRNAs in melanoma progression unravels the complexity of the miRNA network. miR-196a was found able to control several melanoma-associated genes by direct regulation of the homeobox proteins, HOX-C8 and HOX-B7 (Mueller and Bosserhoff, 2011). Down regulation of miR-196a resulted in elevated HOX-C8 expression levels and therefore in a more aggressive dedifferentiated phenotype via activation of several tumorigenic signaling pathways. The presented results show that elevated miR196a levels inhibit melanoma cell invasion in vitro and reduce melanoma tumorigenicity in vivo (Mueller and Bosserhoff, 2011). The mechanism involving this complex process was already clarified earlier by the same group. This study indicated an inverse correlation between HOX-B7 mRNA levels and miR-196a expression, finally resulting in an enhanced expression of bone morphogenetic protein 4 (BMP4), thus directly connecting low miR-196a expression to high BMP4 levels and in conclusion to an increased migratory capacity of these melanoma cells (Braig et al., 2010). miR-126 and its complement miR-126* are encoded by intron seven of the egfl7 gene in all vertebrates (Fish et al., 2008; Wang et al., 2008). The known secreted inhibitor of smooth muscle cell migration EGFL7 is suggested to be a regulator of blood vessel formation (Soncin et al., 2003). miR-126 was reported to be lost in breast cancer tissue and its retroviral restoration in primary breast cancer cells led to tumor growth inhibition and decreased metastatic potential (Tavazoie et al., 2008). A strong down regulation of miR-126 in cancerous versus non-cancerous tissue has been reported for several malignancies, including lung (Cho et al., 2009; Yanaihara et al., 2006), cervix (Wang et al., 2008), stomach (Feng et al., 2010), prostate and bladder (Saito et al., 2009), as well as melanoma (Felli et al., 2013; Mueller et al., 2009). In accordance, loss of its complement miRNA, miR-126*, was observed in various cancer cell lines of the colon (Guo et al., 2008), lung (Yanaihara et al., 2006) and prostate (Musiyenko et al., 2008). The restored expression of miR-126/miR-126* in melanoma cells showed a decrease of neoplastic behavior of these cells in vivo and in vitro. Conversely, tumor progression could be observed after loss of miR-126/miR126* in melanoma cells (Felli et al., 2013). Overall, miR-126/126* have been reported to influence cancer progression via signaling pathways that control tumor progression, migration, invasion and survival (Meister and Schmidt, 2010). Moreover, miR-126/miR126* might support cancer progression through signaling pathways

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regulating inflammatory processes and angiogenesis (Fish et al., 2008; Nicoli et al., 2010). However, the detailed mechanisms and possible additional functions of miR-126/126* still have to be further investigated. Recently, regulation of protein expression by miRNAs was also observed on translational level in melanoma (Kappelmann et al., 2013). For example, miR-125b was found to be strongly down regulated in this tumor entity. In fact, this miRNA was shown to influence c-Jun protein expression on the level of translation but not on mRNA level. Further, the binding site of miR-125b in cJun was located in the protein encoding sequence suggesting that potential regulation of gene expression on translational level by miRNAs might have been missed until today as most prediction programs focus on the 3 UTR of mRNAs.

miRNA as oncogene The potential of a single oncogene to drive malignant progression despite the complex process of cancer development was termed “oncogene addiction” (Hanahan and Weinberg, 2011; Weinstein and Joe, 2008). Specific targeting of such driving forces should lead to significant treatment responses. miR-221 and miR-222 are clustered on the X chromosome and are likely to be transcribed as a common precursor (Felicetti et al., 2008). They were found to be overexpressed in different cancers including pancreatic cancer (Lee et al., 2007), papillary thyroid carcinoma (He et al., 2005), glioblastoma (le Sage et al., 2007), and prostate cancer (Galardi et al., 2007). miR-221/211 were reported to target c-KIT in papillary thyroid carcinoma (He et al., 2005) and in erythroleukemic cells (Felli et al., 2005). Expression of the receptor tyrosine kinase c-KIT was found to decrease with melanoma progression (Montone et al., 1997; Shen et al., 2003). Based on these previous findings, Felicetti et al. (2008) analyzed the expression of miR-221/222 and c-KIT in melanocytes and melanoma cell lines including primary vertical growth phase and metastatic melanomas. They found that miR-221/222 expression increased with tumor progression and reversely correlated with c-KIT expression. The authors identified the promyelocytic leukemia zinc finger (PLZF) transcription factor as a repressor of miR-221/222 by binding to the regulatory region of their genes. Thus, the same group proposed that downregulation of PLZF in melanoma cells unblocks miR-221/222 which in turn represses the expression of cyclin-dependent kinase inhibitor 1B (CDKN1B) and c-KIT, leading to increased proliferation and inhibited differentiation, respectively. Further in vivo experiments showed that overexpression of miR-221/222 promoted tumor growth while inhibition of miR-221/222 by respective antagomirs suppressed tumor growth (Felicetti et al., 2008). Mendell (2008) described a miR-17–92 cluster whose members are known to act as oncogenes promoting cell proliferation, apoptosis resistance, and induction of tumor angiogenesis. The miR-17–92 cluster is upregulated in both, hematopoietic malignancies and solid tumors (Hayashita et al., 2005; Ota et al., 2004; Volinia et al., 2006). In a human B-cell line, overexpression of cMyc induced the expression of the miR-17–92 cluster that in turn inhibited the expression of E2F1, which is also a target of c-Myc and induces apoptosis at high level (O’Donnell et al., 2005). Thus, c-Myc promotes E2F1 transcription and in parallel limits the translation of E2F1, allowing a tightly controlled proliferative signaling (O’Donnell et al., 2005). The expression profiles of several miRNAs indicate a correlation between miRNA expression and increased malignant phenotype. To distinguish between benign melanocytes, melanocytic lesions and metastatic melanoma, comprehensive studies were performed which identified miR-155 and miR-21 as being upregulated in

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correlation with malignancy (Grignol et al., 2011; Philippidou et al., 2010; Segura et al., 2010; Xu et al., 2012). In contrast, the observed decrease of miR-155 expression in a panel of cultured melanoma cell lines suggested a differential role of miR-155 in vitro (Levati et al., 2009). This decrease correlated with reduced cell proliferation and enhanced apoptosis, possibly mediated via miR155 induced SKI (transcriptional coregulator over expressed in melanoma) gene silencing (Levati et al., 2011). Furthermore, miR155 can play a role in the development of B-cell lymphomas, as it was shown that blockage of the pre-B cell to B cell differentiation step led to the development of lymphoblastic leukemia in miR-155 transgenic mice, “underlining” the oncogenic potential of miR-155 (Garzon et al., 2009; Vasilatou et al., 2010). A recent study reported miR-21 to be highly increased in primary melanoma compared to benign nevi (Satzger et al., 2012). In addition they could show that miR-21 downregulation resulted in apoptosis induction in several melanoma cell lines (Satzger et al., 2012). miR-182 located at chromosomal region (7q31–34) is frequently amplified in melanoma and was found to be upregulated in melanoma cell lines and tissues (Segura et al., 2009). Accordingly, expression of miR-182 correlated with melanoma progression and malignancy in tissue microarrays of benign melanocytic nevi, as well as in primary and metastatic melanomas. Two recent studies underlined the relevance of this miRNA in melanoma progression (Huynh et al., 2011; Segura et al., 2009), showing that miR-182 overexpression can facilitate anchorage-independent growth and increased lung metastasis formation in the murine B16F10 melanoma system. Silencing of miR-182 led to apoptosis in melanoma cells and diminished their invasive capacity in vitro (Segura et al., 2009). Different putative targets of miR-182 are currently under investigation, namely FOXO3 (FKHRL1), FOXO1 (FKHR), MITF, CDKN2C (p181INK4C), CASP2 and FAS. So far, only MITF and FOXO3 were shown to be direct targets of miR-182; in fact, this interaction is thought to enhance the invasive potential of melanoma cells triggered by miR-182 overexpression (Segura et al., 2009). Upregulated miR-30b/30d expression was described to correlate with melanoma stage, metastatic potential and reduced overall survival (Gaziel-Sovran et al., 2011). miR-30b/30d are directly targeting GalNAc transferase encoding mRNAs leading to increased IL-10 secretion and thus to reduced immune cell activation. These effects are reported to promote formation of a metastatic phenotype after ectopic miR-30b/30d expression (Gaziel-Sovran et al., 2011). Similar oncogenic effects could also be observed for miR214, one of the so called “melano-miRs” (Bar-Eli, 2011), reported to directly target the AP-2 transcription factors (TFAP2) during melanoma progression leading to an increased metastatic phenotype through control of the activated leukocyte cell adhesion molecule (ALCAM) expression in a dual way (Penna et al., 2013). Both proteins are reported to be members of a signaling pathway regulating melanoma cell migration and invasion. ALCAM can be upregulated either via miR-214 over expression targeting miR-148b post-transcriptionally or transcriptionally via TFAP2. Several prometastatic functions, e.g. cell migration, invasion and extravasation were influenced via differential expression of miR214, miR-148b, TFAP2 and ALCAM in melanoma (Penna et al., 2013).

miRNAs as prognostic markers in melanoma miRNAs are important regulators of many cellular processes affecting the aggressiveness of melanoma. In addition, they are known to be dysregulated in different cancer types, as for example let-7 in lung (Takamizawa et al., 2004) and miR-126 in breast cancer (Tavazoie et al., 2008) correlating with malignancy and cancer aggressiveness. This indicates their potential relevance as biomarkers for cancer diagnosis and prognosis, as well as for

optimal therapy design and evaluation of the clinical responses (Bader et al., 2010). Their evaluation as prognostic as well as diagnostic tools is a rapidly developing field of cancer research at the moment (Cortez et al., 2010) Recent reports show miRNA detection not only in tissue samples, but demonstrate that miRNAs stay remarkably stable also in body fluids like blood, plasma and serum (Bartels and Tsongalis, 2009; Mitchell et al., 2008). For example, miR-155 and miR-150 were found upregulated in blood samples of chronic lymphocytic leukemia patients (Bartels and Tsongalis, 2009). However, whether these tumor-associated changes in the miRNA profile of the blood were actually caused by the tumor cells themselves or by other cell types such as immune cells, remains at current an open question. Currently, two different physical sources, tissue and body fluids, are used to determine differences in miRNA expression profiles between tumor and healthy tissue. Reports indicate measurable changes in miRNA expression levels in blood samples of cancer patients, including melanoma patients, for a panel of different miRNAs (Leidinger et al., 2010; Sita-Lumsden et al., 2013). In one report, where 35 blood samples of melanoma patients were screened for changes in miRNA expression levels, 21 miRNAs could be found to be down regulated and 30 miRNAs were up regulated with a high accuracy of 97%, in comparison to the control group. Despite distinct changes of miRNA expression levels in cancer patients, the source of the miRNAs in the blood remains elusive in this case (Leidinger et al., 2010). Contradictory reports about the suitability of miR-221 as prognostic marker in melanoma indicate the importance to determine the source of miRNAs in the blood (Kanemaru et al., 2011). Specific prognostic miRNA-expression patterns could be identified upon analysis of 59 formalin-fixed paraffin-embedded (FFPE) melanoma metastatic samples using miRNA arrays containing 911 probes (Segura et al., 2010). The authors identified a signature of 18 miRNAs whose overexpression was significantly correlated with longer post-recurrence survival (>18 months), and a signature of six miRNAs with prognostic value for stage III melanoma patients (Segura et al., 2010). High miR-15b expression in FFPE primary melanoma samples could be associated with poor overall and recurrence free survival (Satzger et al., 2010). In cell culture experiments, decreased miR-15b expression was also associated with reduced tumor cell proliferation and increased apoptosis. This indicates a prognostic potential of miR-15b to predict poor recurrence free and overall survival for melanoma patients (Satzger et al., 2010). Interestingly, in the aforementioned study by Segura et al. (2010), high miR-193b levels were associated with longer post-recurrence survival. In addition, two different studies found miR-193 acting as a tumor suppressor, able to downregulate expression of CCND1 and MCL1 (Chen et al., 2010a, 2011a). Contradictory, high expression of miR-193b was reported to be associated with poor patient survival in a data set composed of 16 samples derived from regional lymph node metastases (Caramuta et al., 2010). These discrepancies need to be solved by further investigations with independent samples cohorts and upon identification of more miR-193b associated targets. Overall, several miRNAs, e.g. miR-221, miR-155, miR-455 and miR-15b (Satzger et al., 2010) among others, either individually or in combination, might become relevant biomarkers and might serve as prognostic tools to indicate melanoma progression (Kunz, 2013).

The therapeutic potential of miRNAs The identification of molecular pathways involved in melanoma has provided opportunities for the development of targeted antimelanoma therapies (Gray-Schopfer et al., 2007). A number of

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regulatory proteins such as kinases as well as anti-apoptotic proteins or integrins (e.g. RAF, RAS, BCL2, PI3K and integrins) have been selected as targets in preclinical research, some of them showing encouraging results in clinical trials (Bedikian et al., 2006; Eisen et al., 2006; End et al., 2001; Tucker, 2006; Yaguchi et al., 2006). As increasing evidence shows that miRNAs are regulators of key signaling pathways in cancer, attention has been drawn to the development of miRNA based cancer therapy (Bader et al., 2010). Since miRNAs can act as either tumor suppressors or as oncomirs, reintroduction of tumor suppressive miRNAs or inhibition of oncogenic miRNAs using antagomirs (Bader et al., 2010; Wu, 2010) could be considered as principal strategies for miRNA-based anti-tumor therapy approaches. Several preclinical studies have been carried out to explore the feasibility of such approaches in the treatment of cancer including melanoma. In a preliminary in vivo study, inhibited tumor growth was observed after injection of antagomirs against miR-221/222 into xenografted melanomas in athymic nude mice (Felicetti et al., 2008). In another study, intraperitoneal injection of anti-miR-182 oligonucleotides was applied in a spleen-to-liver melanoma metastasis mouse model, resulting in lower liver metastases formation compared with the control (Huynh et al., 2011). Moreover, miR-182 levels were decreased and previously known targets of miR-182 were upregulated in the metastatic lesion of the anti-miR-182 treated mice (Huynh et al., 2011). For specific delivery of siRNA and miRNAs, Chen et al. (2010b) developed liposome-polycation-hyaluronic acid nanoparticles tagged with a tumor-targeting single-chain antibody fragment (scFv). Using this system, the authors delivered a cocktail of siRNAs (against cMyc, MDM2 and VEGF), miR-34a, or a combination of siRNAs and miR-34a into lung metastases of the B16F10 melanoma mouse model. Their results demonstrated that the targeted nanoparticles enhanced uptake of siRNA and miRNA into B16F10 lung metastasis resulting in inhibited tumor growth (Chen et al., 2010b). In a recent study, a genome-scale lentiviral human miRNA expression library was applied to the melanoma cell line A375 to screen systematically for miRNAs capable of decreasing cell viability (Poell et al., 2012). A number of miRNAs, including miR-16, miR-497, miR-141, miR-96, miR-182, miR-184 and miR-203, showed long-term (>1 month) suppressive effects on melanoma cell proliferation in vitro. Importantly, ectopic expression of miR-16 and miR-203 led to longterm (>1 month) inhibition of cell growth in vivo (Poell et al., 2012). These studies hold promise for miRNA-based melanoma therapies in future.

Conclusion In the last decade, miRNAs have been increasingly acknowledged for their pivotal role in cancer development, more recently also in the field of melanoma. Large scale expression profiling is still hampered by technical challenges, thus qPCR has remained the obligatory gold standard for the validation of microarray data. The impact of deep sequencing in profiling experiments will be seen in the next years. miRNA targets can be identified by bioinformatic prediction algorithms in silico, or by mRNA and protein expression analyses and immunoprecipitation experiments. The validation of putative targets still depends on the performance of laborious experiments including reporter assays and site specific mutagenesis of the miRNA binding sites to confirm the predictions obtained from bioinformatic analysis. To date, an increasing number of miRNAs has been found to be dysregulated in melanoma. Their expression can be affected by transcription factors, epigenetic mechanisms, and alterations within the biogenesis machinery. In melanoma, miRNA genes are often located in chromosomal regions (like the 7q31–34 region)

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with altered DNA copy numbers, resulting in aberrant miRNA expression levels. As described for other tumors, certain miRNAs can function in melanoma as tumor suppressors (e.g. let-7, miR-137, miR-101, miR196a) or as oncogenes (e.g. miR-155, miR-221/222, miR-182). Elucidation of the function of miRNAs in melanoma will eventually lead to the identification of new prognostic markers, as shown for miR-15b, whose expression measured in FFPE samples correlated with poor overall and recurrence free survival. miRNAs add another level of complexity to the signaling networks in normal and malignant cells. The fact, that one individual miRNA may regulate a whole plethora of targets emphasizes the manifold effects to be expected if a given miRNA is dysregulated. At the same time, however, it also opens the chance to identify individual master switches, modulating entire cellular protein expression or signaling programs. Consequently, miRNAs have been recognized as attractive therapeutic targets also in melanoma, which in future need to be tested in preclinical models. Conflict of interest The authors state that there is no conflict of interest. Acknowledgment A.K.B. and S.B.E. were supported by the German Cancer Aid (Melanoma Research Network). References Asangani, I.A., Harms, P.W., Dodson, L., Pandhi, M., Kunju, L.P., Maher, C.A., Fullen, D.R., Johnson, T.M., Giordano, T.J., Palanisamy, N., Chinnaiyan, A.M., 2012. Genetic and epigenetic loss of microRNA-31 leads to feed-forward expression of EZH2 in melanoma. Oncotarget 3, 1011–1025. Bader, A.G., Brown, D., Winkler, M., 2010. The promise of microRNA replacement therapy. Cancer Res. 70, 7027–7030. Bar-Eli, M., 2011. Searching for the ‘melano-miRs’: miR-214 drives melanoma metastasis. EMBO J. 30, 1880–1881. Bartel, D.P., 2004. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–297. Bartel, D.P., 2009. MicroRNAs: target recognition and regulatory functions. Cell 136, 215–233. Bartels, C.L., Tsongalis, G.J., 2009. MicroRNAs: novel biomarkers for human cancer. Clin. Chem. 55, 623–631. Bedikian, A.Y., Millward, M., Pehamberger, H., Conry, R., Gore, M., Trefzer, U., Pavlick, A.C., DeConti, R., Hersh, E.M., Hersey, P., Kirkwood, J.M., Haluska, F.G., 2006. Bcl-2 antisense (oblimersen sodium) plus dacarbazine in patients with advanced melanoma: the Oblimersen Melanoma Study Group. J. Clin. Oncol. 24, 4738–4745. Bell, R.E., Khaled, M., Netanely, D., Schubert, S., Golan, T., Buxbaum, A., Janas, M.M., Postolsky, B., Goldberg, M.S., Shamir, R., Levy, C., 2014. Transcription factor/microRNA axis blocks melanoma invasion program by miR-211 targeting NUAK1. J. Invest. Dermatol. 134, 441–451. Bemis, L.T., Chen, R., Amato, C.M., Classen, E.H., Robinson, S.E., Coffey, D.G., Erickson, P.F., Shellman, Y.G., Robinson, W.A., 2008. MicroRNA-137 targets microphthalmia-associated transcription factor in melanoma cell lines. Cancer Res. 68, 1362–1368. Blower, P.E., Verducci, J.S., Lin, S., Zhou, J., Chung, J.H., Dai, Z., Liu, C.G., Reinhold, W., Lorenzi, P.L., Kaldjian, E.P., Croce, C.M., Weinstein, J.N., Sadee, W., 2007. MicroRNA expression profiles for the NCI-60 cancer cell panel. Mol. Cancer Ther. 6, 1483–1491. Braig, S., Mueller, D.W., Rothhammer, T., Bosserhoff, A.K., 2010. MicroRNA miR-196a is a central regulator of HOX-B7 and BMP4 expression in malignant melanoma. Cell. Mol. Life Sci. 67, 3535–3548. Burk, U., Schubert, J., Wellner, U., Schmalhofer, O., Vincan, E., Spaderna, S., Brabletz, T., 2008. A reciprocal repression between ZEB1 and members of the miR-200 family promotes EMT and invasion in cancer cells. EMBO Rep. 9, 582–589. Calin, G.A., Dumitru, C.D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., Aldler, H., Rattan, S., Keating, M., Rai, K., Rassenti, L., Kipps, T., Negrini, M., Bullrich, F., Croce, C.M., 2002. Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. U.S.A. 99, 15524–15529. Caramuta, S., Egyhazi, S., Rodolfo, M., Witten, D., Hansson, J., Larsson, C., Lui, W.O., 2010. MicroRNA expression profiles associated with mutational status and survival in malignant melanoma. J. Invest. Dermatol. 130, 2062–2070. Chang, T.C., Wentzel, E.A., Kent, O.A., Ramachandran, K., Mullendore, M., Lee, K.H., Feldmann, G., Yamakuchi, M., Ferlito, M., Lowenstein, C.J., Arking, D.E., Beer,

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