Abstract

Context.—In the current “molecular” era, the advent of technology, such as array-based platforms, systems biology, and genome-wide approaches, has made it possible to examine human cancers, including melanoma, for genetic mutations, deletions, amplification, differentially regulated genes, and epigenetic changes. Advancement in current technologies is such that one can now examine ribonucleic acid (RNA), deoxyribonucleic acid (DNA), and protein directly from the patient's own tumor.

Objective.—To apply these new technologies in advancing molecular diagnostics in melanoma has historically suffered from a major obstacle, namely, the scarcity of fresh frozen, morphologically defined tumor banks, annotated with clinical information. Recently, some of the new platforms have advanced to permit utilization of formalin-fixed, paraffin-embedded (FFPE) tumor specimens as starting material.

Data Sources.—This article reviews the latest technologies applied to FFPE melanoma sections, narrowing its focus on the utility of transcriptional profiling, especially for melastatin; comparative genomic hybridization; BRAF and NRAS mutational analysis; and micro ribonucleic acid profiling.

Conclusion.—New molecular approaches are emerging and are likely to improve the classification of melanocytic neoplasms.

In recent years, the field of molecular oncology has made giant leaps in improving our understanding of the molecules and signaling pathways involved in human cancers. This is especially true since implementation of systems biology and genome-wide approaches, as well as the advent of technology, such as array-based platforms, have made it possible to examine various cancers for genetic mutations, deletions, amplification, differentially regulated genes, and epigenetic changes. As cancer is a disease of the genome, it can arise through a series of genomic alterations, which will ultimately provide selective growth advantage through unchecked, deregulated cellular proliferation. To understand these genetic changes, one must tap into the whole genome and investigate the molecular changes in morphologically and clinically well-defined tumor samples. Advancement in current technologies is such that one can now examine ribonucleic acid (RNA), deoxyribonucleic acid (DNA), and protein directly from cancer specimens. In this rapidly advancing, technology-driven molecular era, the study of melanoma is not excepted, and major discoveries have been made that promise to be of clinical significance in the management of patients with melanoma.

However, the application of such new technologies in the advancing field of molecular diagnostics in melanoma has historically suffered from a major obstacle, namely, the scarcity of fresh frozen, morphologically defined tumor banks, annotated with clinical information. For example, gene expression profiling in melanoma, with DNA microarray chips, has been limited to cultured cells or to a few available fresh frozen primary tumor samples (reviewed in Nambiar et al1). Furthermore, melanoma is a heterogeneous neoplasm in that no single translocation, oncogene, mutated tumor suppressor gene, specific signaling pathway, or gene network has yet to molecularly define what pathologists classify as “melanoma.” In fact, many melanin-synthesizing tumors demonstrating nuclear pleomorphism and “cherry-red macronucleoli” might be composed of many different cancers, currently classified under the rubric of “melanoma.” Although most melanomas can be readily distinguished from melanocytic nevi on histologic examination, there are many types of melanocytic nevi that histologically mimic melanoma and its variants. In addition, there is little consensus among pathologists on the morphologic characteristics of melanoma, leading to an inability to predict the biologic behavior of certain melanocytic tumors, especially those with spitzian differentiation.2 This ambiguity has led some experts to coin the term melanocytic tumor of uncertain biologic potential3 or Spitz tumor of uncertain biologic potential.

Furthermore, for more than 40 years, the prognostication of patients with melanoma showing unambiguous tumor histologic features has relied significantly on the measured depth (Breslow) of the primary tumor.4 Although the American Joint Commission on Cancer (AJCC) histologic parameters (Breslow depth, ulceration, and now also the mitotic activity) prove to be statistically significant in very large clinical cohorts,5,6 the prediction of outcome for the individual patient with melanoma remains difficult. Even though patients with early-stage disease (thin melanoma, Breslow depth <1.0 mm) are thought to have an excellent clinical outcome (>85% survival during a 10-year period)6 and can be treated effectively, 15% of melanoma deaths result from metastases of thin lesions.7 Furthermore, the clinical outcome of patients with melanoma of intermediate thickness (2.0 to 4.0 mm in Breslow depth) is less predictable. Thus, molecular biomarkers, derived directly from the patient's own tumor sample, to improve prognostication for these individuals are urgently needed.

To obtain meaningful “molecular” data that promise to improve classification and/or prognostication for melanoma, an extensive primary tumor bank, coupled with morphologically characterized melanomas with relevant clinical follow-up, is needed. Accumulating evidence shows that informative molecular data could be mined from formalin-fixed, paraffin-embedded (FFPE) material, thereby alleviating the need for fresh frozen primary melanoma samples. Being able to tap into archival material provides several advantages: (1) a vast archive of biopsy and excision specimens, processed for histologic diagnosis (ie, FFPE material), exists in many departments of pathology worldwide, (2) these specimens represent a unique source of morphologically defined and disease-specific samples, and (3) in certain cases, the archived specimens have been saved for up to 20 years, which enables retrospective studies with the clinical outcome. It is important to recognize that many alterations in genetic and cell-signaling pathways have been implicated in melanoma, with the following suggested as susceptibility gene(s): CDKN2A (cyclin-dependent kinase inhibitor 2A); CDK4 (cyclin-dependent kinase 4); MC1R (melanocortin 1 receptor); MITF (microphthalmia-associated transcription factor); BCL2; PTEN (phosphatase and tensin homolog); CDKN2A (p14ARF gene product); TP53 (tumor protein p53); AKT; c-KIT; and RAS and BRAF (involved in mitogen-activated protein kinase pathway).8,9 Although such a vast body of knowledge exists in the English literature, this article reviews the latest technologies applied to FFPE melanoma sections and narrows its focus on the utility of transcriptional profiling, especially for melastatin (MLSN-1); comparative genomic hybridization (CGH); BRAF and NRAS mutational analysis; and micro ribonucleic acid (miRNA) profiling.

MELASTATIN EXPRESSION HAS PROGNOSTIC UTILITY FOR PATIENTS WITH MELANOMA

Solid cancers demonstrate changes in gene expression that may provide an identifiable “molecular signature,” possibly associated with a specific cancer type,10 a predictable clinical outcome,10,11 or a biologic response to a specific drug therapy.12 The specific gene expression changes, either upregulated or down-regulated pattern of specific genes, can be studied by comparing the RNA extracted from tumor (eg, melanoma) to that extracted from normal counterpart tissue (eg, skin) or from a benign proliferation (melanocytic nevus). Transcriptional profiling of tumor specimens takes advantage of a technique in which hundreds of molecules of complementary DNA (cDNA) are spotted on a glass slide (reviewed in Nambiar et al1). This microarray technology allows for hybridization of messenger RNA (mRNA) prepared from the tumor samples. This hybridization permits the identification of genes whose expression is differentially regulated in human fresh frozen melanoma13,14 or cultured cells.15,16 Unfortunately, this technology is typically limited to fresh frozen samples or cultured cells, as most mRNA molecules in FFPE material are either degraded or covalently linked to proteins.

Nevertheless, the use of mouse or human melanoma cell lines in transcriptional profiling has yielded some very promising results. A similar but older technology, differential cDNA display, has identified a novel gene—melastatin-1 (MLSN1, TPRM1)—in a B16 metastatic mouse model that is also differentially expressed in human melanocytic neoplasms.17 These investigators showed that MLSN-1 is highly expressed in melanocytic nevi, but it is absent from melanoma metastases. In a subset of cutaneous melanomas examined, the expression of MLSN-1 inversely correlated with tumor thickness. These observations suggested that MLSN-1 may be an indicator of aggressive clinical behavior.17 Most importantly, loss of MLSN1 mRNA, as detected by in situ hybridization on FFPE tumor sections, is predictive of a statistically significant decrease in disease-free survival, as reported in a study of 150 patients with melanoma.18 The importance of MLSN-1 in melanoma progression is further evidenced by the fact that microphthalmia-associated transcription factor, an essential melanocyte transcription factor and a specific melanocytic marker, regulates the expression of MLSN-1, also known as TRPM1, in a series of melanoma cells lines.19 More recently, independent investigators20 confirmed the prognostic utility of loss of MLSN-1 expression in a cohort of 30 patients with melanoma (AJCC stage I and II) who had negative sentinel lymph node biopsy results but developed recurrent melanoma. This study used a chromogenic in situ hybridization technique instead of a traditional 35S-radiolabeled probe,17 enabling the detection of the mRNA signal with light microscopy and eliminating the need for bright-field microscopy. However, a study is needed to compare both detection methods side by side to assess sensitivity and specificity, if MLSN-1 expression is to be used routinely in clinical specimens. Overall, the results indicate that detecting MLSN1 mRNA in FFPE tumor sections may serve as an ancillary test to accurately predict early-stage melanoma in patients at risk for metastatic disease.

A more recent study21 has shown that a multimarker assay, composed of 5 proteins overexpressed in melanoma, can distinguish malignant melanomas from benign nevi. This set of 5 markers (ARPC2, FN1, RGS1, SPP1, and WNT2) was selected on the basis of the following criteria: (1) the markers were discovered to be differentially expressed in a few fresh frozen primary melanomas13 and (2) commercially available antibodies were available for testing. The investigators21 analyzed the immunohistochemical expression of these 5 proteins in 693 melanocytic tumors, which included tissue microarrays and tissue sections of melanoma arising in a nevus, dysplastic nevi, Spitz nevi, and misdiagnosed melanocytic tumors. Although these 5 proteins are products of independent genes present in separate pathways, the intensity and the pattern of protein expression of each marker in tumor samples was used in FFPE samples to develop a diagnostic algorithm. When applied to a training set, the algorithm achieved a specificity of 95% and a sensitivity of 91%. An independent group22 used a similar gene expression analysis platform of a custom DNA microarray, that is, directly from laser-captured microdissected FFPE samples: 62 primary melanomas (superficial spreading, desmoplastic, nodular, acral-lentiginous, and metastatic) and 58 nevi (common acquired and congenital type, excluding Spitz nevi). Unsupervised hierarchic clustering identified 2 distinct lesional groups that closely correlated with the histologic classification of melanomas and nevi. Although 36 differentially expressed genes were identified in this analysis, only 3 genes (FABP7, PCNA, and L1CAM) were validated by using quantitative polymerase chain reaction (PCR).22 

A promising approach to RNA profiling with FFPE specimens has been provided by using a novel platform.23,24 This approach uses cDNA-mediated annealing, selection, extension, and ligation assay as a gene expression solution designed to generate profiles from partially degraded RNA from FFPE specimens. Overall, these studies demonstrate that gene-specific signatures based on expression profiling can indeed distinguish histologically diagnosed melanoma from nevus. These diagnostic schemas need to be further validated by testing a large number of melanocytic tumors with ambiguous histologic features.

CAN ARRAY COMPARATIVE GENOMIC HYBRIDIZATION DIFFERENTIATE MELANOMA FROM SPITZ NEVUS?

Most solid cancers display structural alterations of chromosomes, where loss in genomic stability and integrity can manifest as specific genomic deletion, amplification, translocation, or point mutation that can potentially serve as a specific biomarker for a specific cancer type. In melanoma, genomic instability is a frequent occurrence, as 95% of primary lesions show some physical distortion in the chromosomal structure, either as gains or losses of chromosomal pieces.25,26 These DNA aberrations manifest as DNA copy-number changes. Comparative genomic hybridization (CGH) is a powerful research tool allowing for detection of copy-number changes at the genome level.27 Although cytogenetic analysis has been often used to identify chromosomal defects and aberrations, the use of CGH in solid tumors has been revolutionary, as CGH does not require cultured tumor cells and can be performed on FFPE samples (reviewed in Bauer and Bastian28). Array CGH (aCGH), a variation on conventional CGH technology, allows for a more accurate quantification of DNA copy number and reliable detection of single-copy deletions or duplications,29 thereby significantly improving the resolution.

This technology has been extensively applied to melanocytic tumors to elucidate the copy-number changes in hopes of genetically differentiating between a melanoma and a melanocytic nevus.25 For example, a CGH study of 17 Spitz nevi30 demonstrated no chromosomal aberrations in 13 cases but showed a gain in short arm of chromosome 11 (11p) in 3 cases and a gain of 7q21qter in 1 case. Although no specific gene probes are available yet to make a distinction between spitzoid melanoma and Spitz nevus, the many deletions and gains of chromosomes that are frequently found in melanoma are absent from Spitz nevi.30,31 Another study of 3 Spitz nevi and 2 spitzoid melanomas, using aCGH, showed that 1 Spitz nevus had a gain of 11p, while the other 2 Spitz nevi exhibited no significant chromosomal aberrations.31 In this study, a comparison of the entire spectrum of chromosomal defects between melanoma and Spitz nevi showed that Spitz nevi had many and frequent occurrences of amplifications and deletions, as previously described in melanoma. Another aCGH study32 showed no chromosomal changes in 5 of 10 cases and an isolated gain of 11p in 3 cases. In a larger study of 102 unequivocal melanomas and 125 unequivocal Spitz nevi,33 “consumption of the epidermis” was demonstrated to be an additional diagnostic criterion for melanoma, with this microscopic finding present in 86% of melanomas but only 9.6% of Spitz nevi. When aCGH was applied to a set of 61 histologically ambiguous melanocytic tumors (melanoma versus Spitz nevus) in this study, the analysis found multiple aberrations suggestive of melanoma in 19 cases (31%) and no aberrations or an isolated gain of 11p, as characteristic for Spitz nevus, in 42 cases (69%). Consumption of the epidermis was found in only 6 of 42 (14%) of the ambiguous cases in which aCGH suggested a benign process and 14 of 19 (74%) of the ambiguous cases in which aCGH suggested melanoma (P < .001). Overall, these results suggest that the 11p amplification can be a defining aberration for Spitz nevus; however, this is an infrequent finding, for example, 17% in 1 study.30 Furthermore the gain of 11p needs to be examined in other controversial melanocytic tumors, such as pigmented epithelioid melanocytoma (PEM), formerly known as animal-type melanoma.3436 For example, the biopsy specimen in the right postauricular region of an 11-year-old girl consisted of a black-brown nodule (Figure 1, A) that showed histologic features compatible with PEM: heavily pigmented, wedge-shaped tumor (Figure 1, B) composed of long spindle cells with fine dendritic processes and large epithelioid cells, some lightly melanized and others heavily melanized, with round to oval nuclei and numerous darkly pigmented melanophages (Figure 1, C and D). The excision revealed a 3.7-mm thick PEM, level IV, nonulcerated, with 2 mitoses per mm2, and areas suggestive of lymphovascular invasion (Figure 1, E and F). Given these findings, the patient underwent a modified sentinel lymph node (SLN) sampling of the right clavicular nodes (Figure 2, A). Histologic analysis showed extensive, multifocal, subcapsular, and parenchymal deposits with prominent pigment-synthesizing tumor cells in 1 of 7 nodes (Figure 2, A). Immunohistochemical stains for S100 (Figure 2, B), HMB-45 (Figure 2, C), and Melan-A (Figure 2, D and F) strongly highlight the tumor cells (Figure 2, B through D and F). The morphology of these nodal tumor cells (Figure 2, E) was identical to that of the primary tumor (Figure 1, D). Comparative genomic hybridization data for this tumor demonstrated gain of chromosome 11p, compatible with a Spitz nevus. However, Spitz nevi are typically amelanotic or exhibit lightly melanized cytoplasm. In addition, the clinical behavior of this lesion is also compatible with PEM, showing nodal metastasis with a benign clinical course, as attested by this patient's good health 3 years after local excision and SLN sampling. Currently, the utility of CGH analysis in differentiating Spitz nevus from melanoma consists in examining the entire chromosomal spectrum for aberrations. Even though there are no gene-specific probes for making this distinction, it is likely that such probes may be further defined for use in fluorescence in situ hybridization (FISH) in the near future and may be made commercially available.

Figure 1

Clinicopathologic correlations of a prominent pigment-synthesizing tumor. A, An 11-year-old girl presented with a heavily pigmented nodule with satellite lesions in the right postauricular area. B, A biopsy revealed a deeply invasive melanocytic tumor, extending to the tissue edge. C and D, A closer examination showed 3 cell types with distinct morphology: long spindle cells with fine dendritic processes and large, epithelioid cells, some lightly melanized with others heavily melanized, with round to oval nuclei and numerous darkly pigmented melanophages. These features are histologically compatible with a pigmented epithelioid melanocytoma. E and F, Both the biopsy and the complete local excision specimens showed areas highly suggestive of lymphovascular invasion (hematoxylin-eosin, original magnifications ×20 [B], ×100 [C and E], and ×400 [D and F]).

Figure 1

Clinicopathologic correlations of a prominent pigment-synthesizing tumor. A, An 11-year-old girl presented with a heavily pigmented nodule with satellite lesions in the right postauricular area. B, A biopsy revealed a deeply invasive melanocytic tumor, extending to the tissue edge. C and D, A closer examination showed 3 cell types with distinct morphology: long spindle cells with fine dendritic processes and large, epithelioid cells, some lightly melanized with others heavily melanized, with round to oval nuclei and numerous darkly pigmented melanophages. These features are histologically compatible with a pigmented epithelioid melanocytoma. E and F, Both the biopsy and the complete local excision specimens showed areas highly suggestive of lymphovascular invasion (hematoxylin-eosin, original magnifications ×20 [B], ×100 [C and E], and ×400 [D and F]).

Figure 2

Sentinel lymph node (SLN) biopsy with extensive metastatic foci. A, A modified SLN sampling of the right clavicular nodes of the patient in Figure 1 showed extensive, multifocal, subcapsular, and parenchymal deposits with prominent pigment-synthesizing tumor cells in 1 of 7 nodes. Immunohistochemical stains for S100 (B), HMB-45 (C), and Melan-A (D and F) strongly highlight the tumor cells. E, Histologic analysis showed morphology similar to that of the primary tumor (Figure 1, D) (hematoxylin-eosin, original magnifications ×20 [A] and ×400 [E]; original magnifications ×20 [B through D] and ×400 [F]).

Figure 2

Sentinel lymph node (SLN) biopsy with extensive metastatic foci. A, A modified SLN sampling of the right clavicular nodes of the patient in Figure 1 showed extensive, multifocal, subcapsular, and parenchymal deposits with prominent pigment-synthesizing tumor cells in 1 of 7 nodes. Immunohistochemical stains for S100 (B), HMB-45 (C), and Melan-A (D and F) strongly highlight the tumor cells. E, Histologic analysis showed morphology similar to that of the primary tumor (Figure 1, D) (hematoxylin-eosin, original magnifications ×20 [A] and ×400 [E]; original magnifications ×20 [B through D] and ×400 [F]).

ARRAY CGH IDENTIFIES DISTINCT GENETIC PATHWAYS IN MELANOMAS

In addition to the extensive application of aCGH analyses in Spitz nevi and ambiguous melanocytic tumors, this technique has also been applied to unequivocal melanomas to elucidate the genetic events occurring during melanomagenesis. In a landmark study,37 the genomic DNA from 126 FFPE melanoma specimens was subjected to aCGH analysis and sequenced for the mutational status of BRAF and NRAS, 2 important genes encoding 2 proteins in the mitogen-activated protein kinase pathway in melanoma. Mutated genes in this cellular proliferation pathway will render the cell insensitive to the regulatory control of growth signals, promoting proliferation. The genome-wide assessment showed that the differences in the DNA copy number, based on aCGH, correctly classified melanomas into 4 groups, with 70% accuracy.37 These groups were not those of the conventional World Health Organization classification of melanoma, but rather were based on anatomic location and ultraviolet-light exposure, as follows: mucosal, acral, skin with chronic sun damage, and skin without chronic sun damage. Surprisingly, the mucosal and acral melanomas (at locations that are relatively shielded from the sun) had higher numbers of amplicons (pieces of genomic DNA naturally formed as a result of genetic aberrations) than the melanomas from skin, with and without sun damage. Furthermore, among the 4 groups of tumors, melanomas not linked to chronic sun damage had the most frequent occurrence of BRAF mutations and frequent losses of chromosome 10; on the other hand, melanomas associated with chronic sun damage had infrequent BRAF mutations and frequent CCND1 (cyclin D1 amplification),37 a gene encoding a downstream protein from BRAF in the mitogen-activated protein kinase pathway. Overall, these findings show that distinct genetic pathways may play an important role in the development of different melanomas, as dictated by anatomic location and amount of sun exposure. Discovering specific genetic mutations in the various melanoma histologic subtypes would not only improve the classification of this extremely heterogeneous group of cancers but also provide novel drug targets. For example, oncogenic mutations in KIT, an essential gene for melanocyte survival and development,38,39 were found in 39% of mucosal and 36% of acral melanomas.40 The KIT mutations found in these melanomas also exist in other cancer types that are imatinib mesylate (STI-571)–responsive, for example, gastrointestinal stromal tumor. Therefore, imatinib may provide a therapeutic benefit to patients with mucosal or acral melanomas bearing such mutations.40,41 

The culmination of numerous aCGH studies and cytogenetic analyses in melanoma, absent for melanocytic nevi, have led to recurrent patterns of chromosomal aberrations: loss in 6q, 8p, 9p, and 10q as well as copy-number increase in 1q, 6p, 7, 8q, 17q, and 20q.25,4246 Based on the previous results, a recent study47 established a panel of 4 FISH probes targeting 6p25 (RREB1), 6 centromere, 6q23 (MYB), and 11q13 (CCND1) and suitable for the analysis of FFPE specimens. Using a complex protocol based on nuclear counts of the 4 combined, multicolored FISH probes, investigators established a discriminatory algorithm from a training set of 301 melanocytic nevi and melanomas. This algorithm was validated with an independent set of 169 unequivocal melanocytic nevi and unequivocal melanomas and was then applied to 27 cases of equivocal melanocytic lesions; the FISH test successfully segregated these 27 cases according to the metastasis-free survival of patients (follow-up range, 12–159 months).47 In an independent study,48 other investigators applied the same set of commercially available FISH probes to 40 FFPE unambiguous melanocytic tumor specimens: 20 melanocytic nevi (unspecified subtypes), 10 primary melanomas, and 10 metastatic melanomas. Their results showed that the 4-color FISH assay accurately distinguished melanoma from nevus, with a sensitivity of 90% and a specificity of 95%. Should the use of such algorithms be validated by other investigators, simplified, and made readily and commercially available to diagnostic dermatopathology laboratories, the specific combination of these FISH probes or of other probe set combinations could provide an ancillary histologic diagnostic tool to aid in the diagnosis of ambiguous melanocytic tumors, for which the diagnostic discrepancies could vary widely.49,50 

IS THERE PROGNOSTIC OR DIAGNOSTIC INFORMATION ASSOCIATED WITH BRAF AND NRAS MUTATIONAL STATUS?

The discovery of frequent mutations in BRAF5153 and mutations in neuroblastoma RAS viral (v-ras) (NRAS) and HRAS represents a major breakthrough in the genetics of melanoma. The RAS family includes 3 proto-oncogenes: KRAS, HRAS, and NRAS. These RAS genes have GTP/GDP binding and GTPase activity, and their normal function is the normal control of cell growth. Mutations that change amino acid residues 12, 13, or 61 activate the potential of NRAS to transform cultured cells; these mutations are implicated in a variety of human tumors, including melanoma. The RAS gene family acts as a molecular on/off switch; when it is turned on (or mutated) it recruits and activates proteins necessary for the propagation of the receptor's signal, such as c-Raf and lipid kinase phosphoinositide-3 kinase. When mutated, the RAS protein is “stuck” in the “on” position, leading to continuous and unregulated cell growth. In general, activating mutations in RAS do not occur with as high a frequency in melanoma as they do in other malignancies, thereby limiting their discriminatory power. Of the RAS family members, mutations in NRAS occur most frequently in melanocytes, with rates approaching 56% in congenital nevi,54 33% in primary melanomas, and 26% in metastatic melanomas.55 In an effort to assist with the more accurate classification of notoriously difficult-to-classify spitzoid melanocytic lesions, investigators sequenced the PCR-amplified genomic DNA from 96 FFPE tumor samples by using primer sets designed to look for hotspot mutations in BRAF, NRAS, and HRAS.56 These lesions included Spitz nevus (n  =  14), atypical Spitz nevus (n  =  16), suspected spitzoid melanoma (n  =  23), primary spitzoid melanoma (n  =  36), and spitzoid melanoma metastasis (n  =  7). A significant aspect of this study is the relatively long-term clinical follow-up of affected patients: Spitz nevi, 6 to 16 years; suspected spitzoid melanomas, 4 to 10 years; and primary spitzoid melanomas, 4 to12 years. The results showed that neither the 14 Spitz nevi nor the 16 atypical Spitz nevi had mutations in any of the 3 genes. In contrast, 86% of spitzoid melanomas and 86% of spitzoid melanoma metastases exhibited mutations in either BRAF or NRAS. However, only 35% of the suspected spitzoid melanomas showed mutations in either BRAF or NRAS. HRAS mutations were less frequent: Spitz nevi, 29%; atypical Spitz nevi, 14%; and suspected spitzoid melanomas, 7%, with no such mutations in the spitzoid melanomas. Overall, these results show that BRAF or NRAS status can discriminate between histologically classifiable Spitz nevus and spitzoid melanoma; however, given the low frequency of such mutations in more ambiguous spitzoid lesions, this discriminatory power is limited.

Using a similar methodology, other investigators57 analyzed congenital melanocytic nevi (n  =  32), proliferating nodules in congenital melanocytic nevi (n  =  10), and congenital pattern nevi (n  =  28) for mutations in BRAF and NRAS. The important aspect of this work is that the history of the presence of congenital melanocytic nevi at birth was confirmed and that the mutation status of these lesions was compared to that of melanocytic nevi with histologic features similar to congenital nevi, namely, congenital pattern nevi. The results demonstrated that 81% of congenital melanocytic nevi harbored mutations in NRAS, but none in BRAF, while 71% of congenital pattern nevi harbored mutations in BRAF, but only 25% had mutations in NRAS. Similar to congenital melanocytic nevi, 70% of proliferating nodules in congenital melanocytic nevi harbored mutations in NRAS, but none in BRAF. Given the high frequency of mutations, with an inverse mutational ratio, the combination of NRAS and BRAF status can be used to discriminate between histologically identical truly congenital melanocytic nevi and congenital pattern nevi. Although not directly shown in the former study, NRAS and BRAF mutational analysis could perhaps be used to discriminate proliferating nodules from melanoma in congenital melanocytic nevi.

Currently, the most important signaling molecule in melanoma that is downstream of RAS is BRAF. RAF, a cytosolic serine/threonine-specific protein kinase downstream of RAS, activates the MAPK (mitogen-activated protein kinase) extracellular signal–regulated kinase (also known as MEK), which in turn activates ERK and ultimately influences cell growth. Sixty-six percent of melanomas harbor BRAF somatic missense mutations,53 of which 80% consist of a single base substitution resulting in the protein sequence variation V600E (valine at residue 600 replaced by glutamic acid).52 This activating mutation renders BRAF constitutively active and increases its kinase activity.53 The same mutation pattern is seen in most melanocytic nevi (82%).58 Although the discriminating power of BRAF mutation status is limited in the distinction of a melanoma from a melanocytic nevus, it may identify a distinct melanoma histologic subtype with a predictable clinical outcome. A recent study59 assessed a panel of distinct histologic features and correlated them with BRAF and NRAS mutation status in 302 FFPE primary cutaneous melanoma samples. In this study, melanomas harboring BRAF mutations showed distinct histologic features: increased pagetoid migration, nesting of intraepidermal melanocytes, epidermal acanthosis, and sharper circumscription of the surrounding skin. In the BRAF-mutated melanomas, the tumor cells exhibited large, round, and more pigmented cytoplasm. In contrast, melanomas harboring NRAS mutations did not reveal any specific histologic features. BRAF mutation status was significantly correlated with age in the subset of patients aged 55 years or less who had melanoma and was used as a predictable factor of BRAF status in the study's cohort. Using an age factor of 55 years or less and a prediction tree, as a surrogate for BRAF mutation analysis (not actual DNA analysis), the researchers59 predicted that 69% of patients in an independent cohort of 4785 would have a BRAF mutation. Surprisingly, this group showed a significantly improved 10-year survival, despite that they had more frequent metastasis to regional lymph nodes, versus those patients who were predicted to have no BRAF mutation status. Thus far, this is the only study indirectly demonstrating survival advantage with BRAF mutation, as several other studies51,6062 did not reveal any significant survival differences for patients harboring melanomas with or without BRAF mutation. In a recent study,63 69 frozen primary cutaneous melanomas were analyzed for BRAF and NRAS mutation status; 46% of melanomas harbored a BRAF mutation, most of which resulted in the protein sequence variation V600E. In this study, similar to most other studies, there was no significant association between BRAF mutation status and distant metastasis-free survival. A significant advantage of this study was the correlation between transcriptional profiling data (oligonucleotide microarray expression) and BRAF and NRAS mutation status.63 This combined analysis revealed 17 genes, previously implicated in cutaneous melanoma progression or pigmentation driven by the microphthalmia-associated transcription factor, that demonstrated the gene expression sequel of BRAF mutation.

Overall, NRAS and BRAF mutations are mutually exclusive in most tested melanomas; all cohorts, except for 1, demonstrated no survival advantage, whether BRAF mutation was present or absent. The combined NRAS and BRAF mutational analysis can differentiate between a Spitz nevus and spitzoid melanoma, but not an ambiguous spitzoid lesion. NRAS and BRAF mutational analysis can discriminate between truly congenital melanocytic nevus and melanocytic nevus with congenital pattern.

CAN PROFILING OF SMALL RNAs MAKE A BIG IMPROVEMENT IN PROGNOSTICATION OF PATIENTS WITH MELANOMA?

Although FFPE tumor specimens are widely available, the use of these samples as the starting material for gene expression profiling experiments has significant limitations. Formalin fixation results in covalent modification of ribonucleic acids by addition of a mono-methylol group to the bases, cross-linkage of nucleic acid to proteins, and strand breakage, thereby making RNA extraction and quantification difficult.6468 Even though it is possible to measure mRNA levels in FFPE specimens,65,6972 extensive degradation occurs (often resulting in fragments <300 bases in length), making gene expression analysis difficult. In contrast to mRNAs, miRNAs and other small RNAs are thought to be more stable in FFPE specimens.7377 miRNAs are endogenous, noncoding RNAs, approximately 22 nucleotides in length; they are a class of small RNAs that play important regulatory roles in animals and plants by pairing to the mRNAs of target genes and specifying mRNA cleavage or repression of protein synthesis.78,79 Evidence is emerging that particular miRNAs may function as tumor suppressors and oncogenes,7982 suggesting that abnormal expression of certain miRNAs may play a role in human cancer pathogenesis. Accumulating evidence shows that changes in miRNA levels may accompany dysregulated growth and apoptosis in some cancers. For example, reductions in expression of miR-15a and miR-16, let-7a, and miR-143 and miR-145 have been reported in chronic lymphocytic leukemia,83 lung cancer,84 and colorectal neoplasia,85 respectively. Furthermore, miRNAs are amenable to profiling in the search for prognostic biomarkers,81,83,84,86,87 which can be identified by using microarray hybridization74,77,88 or size-fractionated cDNA library sequencing.75,89,90 The latter approach provides an opportunity to identify novel miRNAs87 or other small RNAs and to profile the expression of known miRNAs. Further evidence shows that small RNAs are stable in FFPE specimens73,91 for up to 10 years.75 

In profiling miRNA expression in melanocytic tumors, most studies have applied microarray hybridization technology to cultured cells or fresh frozen tumors; however, we recently devised a reproducible, robust methodology that released sufficient amounts of high-quality total RNA from various FFPE specimens optimized for small-RNA sequencing and discovery of novel small RNAs.75 We examined a variety of organs (colon, liver, thyroid, uterus, lymph node, and skin) commonly available to most surgical pathologists. To demonstrate the feasibility of sequencing directly from archived specimens, we chose normal skin, primary cutaneous melanoma (4.0 mm, level IV), negative sentinel lymph node (SLN), and positive SLN from a 52-year-old man who had been diagnosed with melanoma on the scalp 10 years earlier. These specimens were chosen from the same patient to reduce individual genetic variation, while simultaneously keeping the focus on changes in expression pattern of small RNAs associated with melanoma progression, that is, from normal skin to primary tumor to metastatic melanoma. We discovered 17 novel and 53 known miRNAs differentially regulated in these samples, which were verified by Northern blot analysis and quantitative reverse transcriptase–polymerase chain reaction (qRT-PCR). Interestingly, some specific miRNA families were associated with melanoma progression; for example, the let-7 family, the most abundant miRNAs, demonstrated a down-regulation trend except for let-7e and let-7i, which exhibited an upregulation trend from skin to tumor and negative to positive SLN. Given the abundance of let-7a, we verified the down-regulation trend by using qRT-PCR; we also verified the upregulation trend of let-7e and let-7i by using qRT-PCR. Our finding is corroborated by a recent study,92 which also demonstrated down-regulation of let-7 family members in primary cutaneous melanoma when compared to benign nevi. Moreover, let-7a negatively regulates integrin β3, involved in melanoma progression and invasion in cultured melanoma cells.93 Importantly, chromatin structure analyses have identified 9 miRNAs regulated by the microphthalmia-associated transcription factor, whose oncogenic gene amplification occurs in 10% to 20% of human melanomas94; of these miRNAs, many belong to the let-7 family, namely, let-7i, let-7a, let-7f, and let 7-d.95 Together, the let-7 family members may play a significant role in melanoma progression.

Overall, results show that it is feasible to profile small RNAs in FFPE specimens by sequencing. This approach provides at least 2 advantages: (1) discovery of new small RNAs and (2) profiling of previously identified miRNAs present at low abundance. Our current methodology, coupled with high-throughput sequencing technology such as the 454 method,96 can provide a more robust strategy for obtaining an accurate expression profile for novel and/or previously characterized small RNAs. An integrated approach in which miRNA expression profiling is combined with clinicopathologic parameters and long-term clinical follow-up could facilitate the discovery of “oncomirs” as biomarkers in melanoma progression and provide new means to better estimate the prognosis for the individual patient.

SUMMARY

The field of oncology has made giant leaps in identifying the molecular players involved in melanoma. Some of these players include altered gene expression patterns, the presence of activated mutations in oncogenes, or loss of function in tumor suppressor genes; however, it is unclear whether they are indeed the cause or the effect of melanomagenesis. It is likely that the use of multimarker assays including (1) immunostaining for a defined panel of antibodies, (2) qRT-PCR analysis of a panel of genes, and (3) four-color FISH probe panel will provide a higher certainty for the diagnosis of melanocytic tumors with ambiguous morphology. As applied to FFPE melanoma samples, these new techniques could prove diagnostically useful, provided that they are validated in large cohorts with clinical follow-up to demonstrate the disease specificity and sensitivity associated with each diagnostic ancillary test. Investigating small RNAs, including miRNAs, may make a big impact in improving melanoma prognostication by providing a series of biomarkers associated with a specific clinical behavior, for example, early metastasis to SLN. This miRNA-based “metastatic signature” could successfully segregate patients with melanoma to small subgroups with a more predictable outcome. When the expression profiling of such miRNAs is established in the melanoma biopsy specimen of an individual patient, the use of RNA interference technology could then be offered as a novel, tailored treatment strategy for that individual.

Acknowledgments

I thank Susan M. Swetter, MD, Department of Dermatology, Stanford University Medical Center, Stanford, California, for the clinical pictures, follow-up, and helpful discussions; and Boris Bastian, MD, Department of Dermatology, University of California San Francisco, for the comparative genomic hybridization analysis.

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Author notes

From the Departments of Dermatology and Genetics and Developmental Biology, University of Connecticut Health Center, Farmington, Connecticut.

The author has no relevant financial interest in the products or companies described in this article.