A multimarker prognostic assay for primary cutaneous melanoma

Relationship of Histopathologic Parameters and Gene Expression Profiling in Malignant Melanoma

BACKGROUND

Histopathologic characteristics (HC) are a mainstay in melanoma prognosis; gene expression profiling (GEP) has emerged as a potential additional independent value.

OBJECTIVE

To elucidate HC predictive of groups obtained via GEP of malignant melanoma.

METHODS

A retrospective study analyzing HC of 265 melanomas submitted for GEP over the course of 8 years. GEP was conducted as a part of regular clinicopathologic workup through Castle Biosciences Decision Dx®.

RESULTS

Of the 265 cases, the major HC found to have an association with reported gene expression profiles were melanoma histology subtype, depth of invasion, and presence of ulcer.

LIMITATIONS

This study is limited by its cross-sectional nature. Causation and long-term related outcomes of the use of GEP versus American Joint Committee on Cancer histopathologic staging cannot be ascertained by this design.

CONCLUSIONS

An association, but no definitive prediction, exists between histopathologic categories of depth of invasion, melanoma subtype, and presence or absence of ulcer and gene expression profiles. GEP adds valuable data to the evaluation of malignant melanomas that cannot be definitively predicted by conventional models. The findings add to needed groundwork for comparison of traditional markers and molecular genotyping and begins to build a robust predictive model for better outcomes in patients with malignant melanoma.

CDCA3 is a prognostic biomarker for cutaneous melanoma and is connected with immune infiltration

Introduction

Dysregulation of cell cycle progression (CCP) is a trait that distinguishes cancer from other diseases. In several cancer types, CCP-related genes serve as the primary risk factor for prognosis, but their role in cutaneous melanoma remains unclear.

Methods

Data from cutaneous melanoma patients were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Using a Wilcoxon test, the level of CCP-related gene expression in cutaneous melanoma patient tissues was compared to that in normal skin tissues. Logistic analysis was then utilized to calculate the connection between the CCP-related genes and clinicopathological variables. The important functions of the CCP-related genes were further investigated using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and single-sample Gene Set Enrichment Analysis (ssGSEA). Univariate and multivariate Cox analyses and Kaplan-Meier analysis were used to estimate the association between CCP-related genes and prognosis. In addition, using Cox multivariate analysis, a nomogram was constructed to forecast the influence of CCP-related genes on survival rates.

Results

High expression of CCP-related genes was associated with TNM stage, age, pathological grade, and Breslow depth (P < 0.05). Multivariate analysis demonstrated that CCP-related genes were an independent factor in overall survival and disease-specific survival. High levels of gene expression originating from CCP were shown by GSEA to trigger DNA replication, the G1-S specific transcription factor, the mitotic spindle checkpoint, and the cell cycle. There was a negative association between CCP-related genes and the abundance of innate immune cells. Finally, we revealed that knockdown of cell division cycle-associated gene 3 (CDCA3) significantly suppressed the proliferation and migration ability of cutaneous melanoma cells.

Conclusion

According to this study, CCP-related genes could serve as potential biomarkers to assess the prognosis of cutaneous melanoma patients and are crucial immune response regulators.

An Integrated Platform for Skin Cancer Heterogenous and Multilayered Data Management

Electronic health record (EHR) systems improve health care services by allowing the combination of health data with clinical decision support features and clinical image analyses. This study presents a modular and distributed platform that is able to integrate and accommodate heterogeneous, multidimensional (omics, histological images and clinical) data for the multi-angled portrayal and management of skin cancer patients. The proposed design offers a layered analytical framework as an expansion of current EHR systems, which can integrate high-volume molecular -omics data, imaging data, as well as relevant clinical observations. We present a case study in the field of dermatology, where we attempt to combine the multilayered information for the early detection and characterization of melanoma. The specific architecture aspires to lower the barrier for the introduction of personalized therapeutic approaches, towards precision medicine. The paper describes the technical issues of implementation, along with an initial evaluation of the system and discussion.

Computational Drug Repositioning Identifies Statins as Modifiers of Prognostic Genetic Expression Signatures and Metastatic Behavior in Melanoma

Despite advances in melanoma treatment, more than 70% of patients with distant metastasis die within 5 years. Proactive treatment of early melanoma to prevent metastasis could save lives and reduce overall healthcare costs. Currently, there are no treatments specifically designed to prevent early melanoma from progressing to metastasis. We used the Connectivity Map to conduct an in silico drug screen and identified 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitors (statins) as a drug class that might prevent melanoma metastasis. To confirm the in vitro effect of statins, RNA sequencing was completed on A375 cells after treatment with fluvastatin to describe changes in the melanoma transcriptome. Statins induced differential expression in genes associated with metastasis and are used in commercially available prognostic tests for melanoma metastasis. Finally, we completed a chart review of 475 patients with melanoma. Patients taking statins were less likely to have metastasis at the time of melanoma diagnosis in both univariate and multivariate analyses (24.7% taking statins vs. 37.6% not taking statins, absolute risk reduction = 12.9%, P = 0.038). These findings suggest that statins might be useful as a treatment to prevent melanoma metastasis. Prospective trials are required to verify our findings and to determine the mechanism of metastasis prevention.

Aberrant RNA Splicing Events Driven by Mutations of RNA-Binding Proteins as Indicators for Skin Cutaneous Melanoma Prognosis

The worldwide incidence of skin cutaneous melanoma (SKCM) is increasing at a more rapid rate than other tumors. Aberrant alternative splicing (AS) is found to be common in cancer; however, how this process contributes to cancer prognosis still remains largely unknown. Mutations in RNA-binding proteins (RBPs) may trigger great changes in the splicing process. In this study, we comprehensively analyzed DNA and RNA sequencing data and clinical information of SKCM patients, together with widespread changes in splicing patterns induced by RBP mutations. We screened mRNA expression-related and prognosis-related mutations in RBPs and investigated the potential affections of RBP mutations on splicing patterns. Mutations in 853 RBPs were demonstrated to be correlated with splicing aberrations (p < 0.01). Functional enrichment analysis revealed that these alternative splicing events (ASEs) may participate in tumor progress by regulating the modification process, cell-cycle checkpoint, metabolic pathways, MAPK signaling, PI3K-Akt signaling, and other important pathways in cancer. We also constructed a prediction model based on overall survival-related AS events (OS-ASEs) affected by RBP mutations, which exhibited a good predict efficiency with the area under the curve of 0.989. Our work highlights the importance of RBP mutations in splicing alterations and provides effective biomarkers for prediction of prognosis of SKCM.

BET inhibitor suppresses melanoma progression via the noncanonical NF-κB/SPP1 pathway

Background: Bromodomain and extra-terminal domain (BET) inhibitors have shown profound efficacy against hematologic malignancies and solid tumors in preclinical studies. However, the underlying molecular mechanism in melanoma is not well understood. Here we identified secreted phosphoprotein 1 (SPP1) as a melanoma driver and a crucial target of BET inhibitors in melanoma. Methods: Bioinformatics analysis and meta-analysis were used to evaluate the SPP1 expression in normal tissues, primary melanoma, and metastatic melanoma. Real-time PCR (RT-PCR) and Western blotting were employed to quantify SPP1 expression in melanoma cells and tissues. Cell proliferation, wound healing, and Transwell assays were carried out to evaluate the effects of SPP1 and BET inhibitors in melanoma cells in vitro. A xenograft mouse model was used to investigate the effect of SPP1 and BET inhibitors on melanoma in vivo. Chromatin immunoprecipitation (ChIP) assay was performed to evaluate the regulatory mechanism of BET inhibitors on SPP1. Results: SPP1 was identified as a melanoma driver by bioinformatics analysis, and meta-analysis determined it to be a diagnostic and prognostic biomarker for melanoma. SPP1 overexpression was associated with poor melanoma prognosis, and silencing SPP1 suppressed melanoma cell proliferation, migration, and invasion. Through a pilot drug screen, we identified BET inhibitors as ideal therapeutic agents that suppressed SPP1 expression. Also, SPP1 overexpression could partially reverse the suppressive effect of BET inhibitors on melanoma. We further demonstrated that bromodomain-containing 4 (BRD4) regulated SPP1 expression. Notably, BRD4 did not bind directly to the SPP1 promoter but regulated SPP1 expression through NFKB2. Silencing of NFKB2 resembled the phenotype of BET inhibitors treatment and SPP1 silencing in melanoma. Conclusion: Our findings highlight SPP1 as an essential target of BET inhibitors and provide a novel mechanism by which BET inhibitors suppress melanoma progression via the noncanonical NF-κB/SPP1 pathway.

Risk prediction in cutaneous melanoma patients from their clinico-pathological features: superiority of clinical data over gene expression data

Risk assessment in cutaneous melanoma (CM) patients is one of the major challenges in the effective treatment of CM patients. Traditionally, clinico-pathological features such as Breslow thickness, American Joint Committee on Cancer (AJCC) tumor staging, etc. are utilized for this purpose. However, due to advancements in technology, most of the upcoming risk prediction methods are gene-expression profile (GEP) based. In this study, we have tried to develop new GEP and clinico-pathological features-based biomarkers and assessed their prognostic strength in contrast to existing prognostic methods. We developed risk prediction models using the expression of the genes associated with different cancer-related pathways and got a maximum hazard ratio (HR) of 2.52 with p-value ~10-8 for the apoptotic pathway. Another model, based on combination of apoptotic and notch pathway genes boosted the HR to 2.57. Next, we developed models based on individual clinical features and got a maximum HR of 2.45 with p-value ~10-6 for Breslow thickness. We also developed models using the best features of clinical as well as gene-expression data and obtained a maximum HR of 3.19 with p-value ~10-9. Finally, we developed a new ensemble method using clinical variables only and got a maximum HR of 6.40 with p-value ~10-15. Based on this method, a web-based service and an android application named 'CMcrpred' is available at (https://webs.iiitd.edu.in/raghava/cmcrpred/) and Google Play Store respectively to facilitate scientific community. This study reveals that our new ensemble method based on only clinico-pathological features overperforms methods based on GEP based profiles as well as currently used AJCC staging. It also highlights the need to explore the full potential of clinical variables for prognostication of cancer patients.

Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model

PURPOSE

To develop and validate an integrated model for discriminating tumor recurrence from radiation necrosis in glioma patients.

METHODS

Data from 160 pathologically confirmed glioma patients were analyzed. The diagnostic model was developed in a primary cohort (n = 112). Textural features were extracted from postoperative ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET), ¹¹C-methionine (¹¹C-MET) PET, and magnetic resonance images. The least absolute shrinkage and selection operator regression model was used for feature selection and radiomics signature building. Multivariable logistic regression analysis was used to develop a model for predicting tumor recurrence. The radiomics signature, quantitative PET parameters, and clinical risk factors were incorporated in the model. The clinical value of the model was then assessed in an independent validation cohort using the remaining 48 glioma patients.

RESULTS

The integrated model consisting of 15 selected features was significantly associated with postoperative tumor recurrence (p < 0.001 for both primary and validation cohorts). Predictors contained in the individualized diagnosis model included the radiomics signature, the mean of tumor-background ratio (TBR) of ¹⁸F-FDG, maximum of TBR of ¹¹C-MET PET, and patient age. The integrated model demonstrated good discrimination, with an area under the curve (AUC) of 0.988, with a 95% confidence interval (CI) of 0.975-1.000. Application in the validation cohort showed good differentiation (AUC of 0.914 and 95% CI of 0.881-0.945). Decision curve analysis showed that the integrated diagnosis model was clinically useful.

CONCLUSIONS

Our developed model could be used to assist the postoperative individualized diagnosis of tumor recurrence in patients with gliomas.

Immunohistochemical analysis of Bcl-2, nuclear S100A4, MITF and Ki67 for risk stratification of early-stage melanoma - A combined IHC score for melanoma risk stratification

BACKGROUND AND OBJECTIVES

Overall survival (OS) in patients with early-stage malignant melanoma differs. To date, there are no established prognostic markers. We aimed to contribute to a better understanding of potential prognostic immunohistochemical markers for risk stratification.

PATIENTS AND METHODS

161 surgically resected early-stage malignant melanomas (stage pT1 and pT2) were analyzed for expression of 20 different proteins using immunohistochemistry. The results were correlated with OS. The cohort was randomly split into a discovery and a validation cohort.

RESULTS

High Bcl-2 expression, high nuclear S100A4 expression as well as a Ki67 proliferation index of ≥ 20 % were associated with shorter OS. Strong MITF immunoreactivity was a predictor for favorable prognosis. A combination of these four markers resulted in a multi-marker score with significant prognostic value in multivariate survival analysis (HR: 3.704; 95 % CI 1.484 to 9.246; p = 0.005). Furthermore, the score was able to differentiate a low-risk group with excellent OS rates (five-year survival rate: 100 %), an intermediate-risk group (five-year survival rate: 81.8 %) and a high-risk group (five-year survival rate: 52.6 %). The prognostic value was confirmed within the validation cohort.

CONCLUSIONS

Combined immunohistochemical analysis of Bcl-2, nuclear S100A4, Ki67 and MITF could contribute to better risk stratification of early-stage malignant melanoma patients.

Biomarkers Predictive of Survival and Response to Immune Checkpoint Inhibitors in Melanoma

Immunotherapy has revolutionized the treatment of melanoma. Targeting of the immune checkpoints cytotoxic T-lymphocyte-associated protein 4 and programmed cell death protein 1 has led to improved survival in a subset of patients. Unfortunately, the use of immune checkpoint inhibitors is associated with significant side effects and many patients do not respond to treatment. Thus, there is an urgent need both for prognostic biomarkers to estimate risk and for predictive biomarkers to determine which patients are likely to respond to therapy. In this review, prognostic and predictive biomarkers that are an active area of research are outlined. Of note, certain transcriptomic signatures are already used in the clinic, albeit not routinely, to prognosticate patients. In the predictive setting, programmed cell death protein ligand 1 expression has been shown to correlate with benefit but is not precise enough to be used as an exclusionary biomarker. Future investigation will need to focus on biomarkers that are easily reproducible, cost effective, and accurate. The use of readily available clinical material, such as serum or hematoxylin and eosin-stained images, may offer one such path forward.

Identification of gene expression levels in primary melanoma associated with clinically meaningful characteristics

Factors influencing melanoma survival include sex, age, clinical stage, lymph node involvement, as well as Breslow thickness, presence of tumor-infiltrating lymphocytes based on histological analysis of primary melanoma, mitotic rate, and ulceration. Identification of genes whose expression in primary tumors is associated with these key tumor/patient characteristics can shed light on molecular mechanisms of melanoma survival. Here, we show results from a gene expression analysis of formalin-fixed paraffin-embedded primary melanomas with extensive clinical annotation. The Cancer Genome Atlas data on primary melanomas were used for validation of nominally significant associations. We identified five genes that were significantly associated with the presence of tumor-infiltrating lymphocytes in the joint analysis after adjustment for multiple testing: IL1R2, PPL, PLA2G3, RASAL1, and SGK2. We also identified two genes significantly associated with melanoma metastasis to the regional lymph nodes (PIK3CG and IL2RA), and two genes significantly associated with sex (KDM5C and KDM6A). We found that LEF1 was significantly associated with Breslow thickness and CCNA2 and UBE2T with mitosis. RAD50 was the gene most significantly associated with survival, with a higher level of expression associated with worse survival.

Identification of risk in cutaneous melanoma patients: Prognostic and predictive markers

New therapeutic modalities for melanoma promise benefit in selected individuals. Efficacy appears greater in patients with lower tumor burden, suggesting an important role for risk-stratified surveillance. Robust predictive markers might permit optimization of agent to patient, while low-risk prognostic markers might guide more conservative management. This review evaluates protein, gene, and multiplexed marker panels that may contribute to better risk assessment and improved management of patients with cutaneous melanoma.

Predictive genetic profiles for regional lymph node metastasis in primary cutaneous melanoma: a case-matched pilot study

Melanoma confers an estimated lifetime risk of one in 50 for 2016. Clinicopathologic staging and sentinel lymph node biopsy (SLNB) have been the standard of care for T2 and T3 lesions. Molecular biomarkers identified in the primary lesion suggestive of metastatic potential may offer a more conclusive prognosis of these lesions. Our purpose was to investigate molecular mutations in primary melanoma that were predictive for micrometastasis as defined by a positive sentinel lymph node (SLN) in a case-controlled manner: nine patients with negative SLN and nine with positive SLN. The two cohorts were statistically identical as shown by a t-test for age (P=0.17), race (P=0.18), Breslow depth (P=0.14), Clark level (P=0.33), host response (P=0.17), ulceration (P=0.50), satellite nodules (P=0.17), lymphovascular invasion (P=0.50), and mitotic activity (P=0.09). While no single gene was significantly associated with SLN status, multivariate analysis using classification and regression tree assessment revealed two unique gene profiles that completely represented regional metastases in our cohort as defined by a positive SLN: PIK3CA (+) NRAS (-) and PIK3CA (-) ERBB4 (-) TP53 (+) SMAD4 (-). These profiles were identified in 89% of the patients with positive SLN; none of these profiles were identified in the SLN-negative cohort. We identified two unique gene profiles associated with positive SLN that do not overlap other studies and highlight the genetic complexity that portends the metastatic phenotype in cutaneous melanoma.

Review of diagnostic, prognostic, and predictive biomarkers in melanoma

Melanoma is an aggressive cutaneous malignancy with rapidly rising incidence. Diagnosis of controversial melanocytic lesions, correct prognostication of patients, selection of appropriate adjuvant and systemic therapies, and prediction of response to a given therapy remain very real challenges. Despite these challenges, multiple high throughput, nucleic-acid based biomarkers have been developed that can be assayed from histologic tissue specimens. FISH, CGH, Decision-Dx, and other multi-marker assays have been combined to improve overall predictability. This review discusses some of the most promising nucleic acid based assays that can be obtained from tissue specimens to assist with diagnosis, prognostication, and prediction of treatment response.

Emerging Biomarkers in Cutaneous Melanoma

Earlier identification of aggressive melanoma remains a goal in the field of melanoma research. With new targeted and immune therapies that have revolutionized the care of patients with melanoma, the ability to predict progression and monitor or predict response to therapy has become the new focus of research into biomarkers in melanoma. In this review, promising biomarkers are highlighted. These biomarkers have been used to diagnose melanoma as well as predict progression to advanced disease and response to therapy. The biomarkers take various forms, including protein expression at the level of tissue, genetic mutations of cancer cells, and detection of circulating DNA. First, a brief description is provided about the conventional tissue markers used to stage melanoma, including tumor depth. Next, protein biomarkers, which provide both diagnostic and prognostic information, are described. This is followed by a discussion of important genetic mutations, microRNA, and epigenetic modifications that can provide therapeutic and prognostic material. Finally, emerging serologic biomarkers are reviewed, including circulating melanoma cells and exosomes. Overall the goal is to identify biomarkers that aid in the earlier identification and improved treatment of aggressive melanoma.

RAC3 influences the chemoresistance of colon cancer cells through autophagy and apoptosis inhibition

Background

RAC3 coactivator overexpression has been implicated in tumorigenesis, contributing to inhibition of apoptosis and autophagy. Both mechanisms are involved in resistance to treatment with chemotherapeutic agents. The aim of this study was to investigate its role in chemoresistance of colorectal cancer.

Methods

The sensitivity to 5-fluorouracil and oxaliplatin in colon cancer cells HT-29, HCT 116 and Lovo cell lines, expressing high or low natural levels of RAC3, was investigated using viability assays.

Results

In HCT 116 cells, we found that although 5-fluorouracil was a poor inducer of apoptosis, autophagy was strongly induced, while oxaliplatin has shown a similar ability to induce both of them. However, in HCT 116 cells expressing a short hairpin RNA for RAC3, we found an increased sensitivity to both drugs if it is compared with control cells. 5-Fluorouracil and oxaliplatin treatment lead to an enhanced caspase 3-dependent apoptosis and produce an increase of autophagy. In addition, both process have shown to be trigged faster than in control cells, starting earlier after stimulation.

Conclusions

Our results suggest that RAC3 expression levels influence the sensitivity to chemotherapeutic drugs. Therefore, the knowledge of RAC3 expression levels in tumoral samples could be an important contribution to design new improved therapeutic strategies in the future.

Prospective Validation of Molecular Prognostic Markers in Cutaneous Melanoma: A Correlative Analysis of E1690

Purpose: To validate the prognostic impact of combined expression levels of three markers (SPP1, RGS1, and NCOA3) in melanoma specimens from patients enrolled in the E1690 clinical trial of high-dose or low-dose IFNα-2b versus observation.Experimental Design: Tissue was available from 248 patients. Marker expression was determined by digital imaging of immunohistochemically stained slides. The prognostic impact of each marker was first assessed by recording its expression value relative to the median. A multimarker index was then developed to combine marker expression levels by counting for each patient the number of markers with high expression. The impact of the multimarker index on relapse-free survival (RFS) and overall survival (OS) was assessed using Kaplan-Meier analysis, and both univariate and multivariate Cox regression analyses.Results: By Kaplan-Meier analysis, high multimarker expression scores were significantly predictive of RFS (P < 0.001) and OS (P < 0.001). Stepwise multivariate Cox regression analysis with backward elimination that included routine clinical and histologic prognostic factors revealed high multimarker expression scores and tumor thickness as the only factors significantly and independently predicting RFS and OS. Stepwise multivariate Cox regression analyses that also included treatment type and number of positive lymph nodes generated identical results for both RFS and OS. In the molecularly defined low-risk subgroup, patients treated with high-dose IFN had a significantly improved RFS compared with patients in the other two subgroups (P < 0.05).Conclusions: These results validate the independent impact of combined expression levels of SPP1, RGS1, and NCOA3 on survival of melanoma in a prospectively collected cohort. Clin Cancer Res; 23(22); 6888-92. ©2017 AACR.

Recent advances in melanoma research via "omics" platforms

Melanoma has a high mortality rate and metastatic melanoma is highly resistant to conventional therapies. "Omics" fields such as proteomics and microRNA and exosome studies have provided new knowledge to complement the information generated by genomic studies. This work aimed to review the current status of biomarker discovery for melanoma through multi-"omics" platforms. A few sets of novel microRNAs and proteins are described, some of them with important implications in suppressing melanoma at different stages. Upregulation of genes involved in angiogenesis, immunosuppressive factors, modification of stroma, capture of melanoma cells in lymph nodes and factors responsible for tumour cell recruitment have been identified in exosomes, among molecules with other functions. A remarkable series of proteins involved in epithelial-mesenchymal/mesenchymal-epithelial transitions, inflammation, motility, proliferation and progression processes, centrosome amplification, aneuploidy, inhibition of CD8+ effector T-cells, and metastasis in general were identified. Genomic and protein-protein interactions or metabolome levels were not analysed. Proteomics tools such as Orbitrap shotgun mass spectrometry or deep mining proteomic analysis utilizing high-resolution reversed phase nanoseparation in combination with mass spectrometry are also discussed. The application of these tools together with bioinformatics approaches applied to the clinical setting will enable the implementation of personalized medicine in the near future.

Clinical and biological determinants of melanoma progression: Should all be considered for clinical management?

Cutaneous melanoma is a heterogeneous disease affecting the regulation of multiple genes and proteins that contribute to melanoma progression. Survival for patients with locally invasive disease varies greatly, even within tumour stages based on current prognostic criteria. This has prompted investigations into the value of additional clinical or biological parameters predicting survival. In particular, the improved knowledge of tumour biology has fed the hope that the outcome may be predicted at the molecular level. The prognostic value of numerous potential biomarkers has therefore been evaluated in protein and gene expression studies, and genomic associations with melanoma prognosis are beginning to emerge. These potential biomarkers interrogate key tumour and host processes important for tumour development and progression, such as proliferation, invasion and migration through epithelial mesenchymal transition or the host immune or vascular responses. This research may allow more individualised information on prognosis if the challenges regarding the quality and validation of studies are overcome.

Clinical utilities and biological characteristics of melanoma sentinel lymph nodes

An estimated 73870 people will be diagnosed with melanoma in the United States in 2015, resulting in 9940 deaths. The majority of patients with cutaneous melanomas are cured with wide local excision. However, current evidence supports the use of sentinel lymph node biopsy (SLNB) given the 15%-20% of patients who harbor regional node metastasis. More importantly, the presence or absence of nodal micrometastases has been found to be the most important prognostic factor in early-stage melanoma, particularly in intermediate thickness melanoma. This review examines the development of SLNB for melanoma as a means to determine a patient’s nodal status, the efficacy of SLNB in patients with melanoma, and the biology of melanoma metastatic to sentinel lymph nodes. Prospective randomized trials have guided the development of practice guidelines for use of SLNB for melanoma and have shown the prognostic value of SLNB. Given the rapidly advancing molecular and surgical technologies, the technical aspects of diagnosis, identification, and management of regional lymph nodes in melanoma continues to evolve and to improve. Additionally, there is ongoing research examining both the role of SLNB for specific clinical scenarios and the ways to identify patients who may benefit from completion lymphadenectomy for a positive SLN. Until further data provides sufficient evidence to alter national consensus-based guidelines, SLNB with completion lymphadenectomy remains the standard of care for clinically node-negative patients found to have a positive SLN.

Prognostic and predictive biomarkers in melanoma: an update

Malignant melanoma is one of the most aggressive cancers. Several new therapeutic strategies that focus on immuno- and/or targeted therapy have been developed, which have entered clinical trials or already been approved. This review provides an update on prognostic and predictive biomarkers in melanoma that may be used to improve the clinical management of patients. Prognostic markers include conventional histopathological characteristics, chromosomal aberrations, gene expression patterns and miRNA profiles. There is a trend towards multi-marker assays and whole-genome molecular screening methods to determine the prognosis of individual patients. Predictive biomarkers, including targeted components of signal transduction, developmental or transcriptional pathways, can be used to determine patient response towards a particular treatment or combination thereof. The rapid evolution of sequencing technologies and multi-marker screening will change the spectrum of patients who become candidates for therapeutic agents, and in addition create new ethical and regulatory challenges.

Revisiting determinants of prognosis in cutaneous melanoma

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

miR-137 Targets p160 Steroid Receptor Coactivators SRC1, SRC2, and SRC3 and Inhibits Cell Proliferation

The p160 family of steroid receptor coactivators (SRCs) are pleiotropic transcription factor coactivators and "master regulators" of gene expression that promote cancer cell proliferation, survival, metabolism, migration, invasion, and metastasis. Cancers with high p160 SRC expression exhibit poor clinical outcomes and resistance to therapy, highlighting the SRCs as critical oncogenic drivers and, thus, therapeutic targets. microRNAs are important epigenetic regulators of protein expression. To examine the regulation of p160 SRCs by microRNAs, we used and combined 4 prediction algorithms to identify microRNAs that could target SRC1, SRC2, and SRC3 expression. For validation of these predictions, we assessed p160 SRC protein expression and cell viability after transfection of corresponding microRNA mimetics in breast cancer, uveal melanoma, and prostate cancer (PC) cell lines. Transfection of selected microRNA mimetics into breast cancer, uveal melanoma, and PC cells depleted SRC protein expression levels and exerted potent antiproliferative activity in these cell types. In particular, microRNA-137 (miR-137) depleted expression of SRC1, SRC2, and very potently, SRC3. The latter effect can be attributed to the presence of 3 miR-137 recognition sequences within the SRC3 3'-untranslated region. Using reverse phase protein array analysis, we identified a network of proteins, in addition to SRC3, that were modulated by miR-137 in PC cells. We also found that miR-137 and its host gene are epigenetically silenced in human cancer specimens and cell lines. These results support the development and testing of microRNA-based therapies (in particular based on restoring miR-137 levels) for targeting the oncogenic family of p160 SRCs in cancer.

SNPs at miR-155 binding sites of TYRP1 explain discrepancy between mRNA and protein and refine TYRP1 prognostic value in melanoma

Background:

We previously demonstrated an inverse correlation between tyrosinase-related protein 1 (TYRP1) mRNA expression in melanoma metastases and patient survival. However, TYRP1 protein was not detected in half of tissues expressing mRNA and did not correlate with survival. Based on a study reporting that 3′ untranslated region (UTR) of TYRP1 mRNA contains two miR-155-5p (named miR-155) binding sites exhibiting single-nucleotide polymorphisms (SNPs) that promote (matched miRNA–mRNA interaction) mRNA decay or not (mismatched), we aimed to investigate the role of miR-155 in the regulation of TYRP1 mRNA expression and protein translation accounting for these SNPs.

Methods:

The effect of miR-155 on TYRP1 mRNA/protein expression was evaluated in two melanoma cell lines harbouring matched or mismatched miR-155–TYRP1 mRNA interaction after transfection with pre-miR-155. In parallel, 192 skin and lymph node melanoma metastases were examined for TYRP1 mRNA/protein, miR-155 and SNPs and correlated with patient survival. TYRP1 mRNA, SNPs at its 3′UTR and miR-155 were analysed by RT–qPCR, whereas TYRP1 protein was evaluated by western blot in cell lines and by immunohistochemistry in metastatic tissues.

Results:

The miR-155 induced a dose-dependent TYRP1 mRNA decay and hampered its translation into protein in the line with the ‘match' genotype. In melanoma metastases, TYRP1 mRNA inversely correlated with miR-155 expression but not with TYRP1 protein in the ‘match' group, whereas it positively correlated with protein but not with miR-155 in the ‘mismatch' group. Consequently, in the latter group, TYRP1 protein inversely correlated with survival.

Conclusion:

Polymorphisms in 3′UTR of TYRP1 mRNA can affect TYRP1 mRNA regulation by miR-155 and its subsequent translation into protein. These SNPs can render TYRP1 mRNA and protein expression nonsusceptible to miR-155 activity and disclose a prognostic value for TYRP1 protein in a subgroup of melanoma patients. These data support the interest in the prognostic value of melanogenic markers and propose TYRP1 to refine prognosis in patients with advanced disease.

Stage-specific prognostic biomarkers in melanoma

The melanoma staging system proposed by the American Joint Committee on Cancer (AJCC) (which classifies melanoma patients into four clinical stages) is currently the most widely used tool for melanoma prognostication, and clinical management decision making by clinicians. However, multiple studies have shown that melanomas within specific AJCC Stages can exhibit varying progression and clinical outcomes. Thus, additional information, such as that provided by biomarkers is needed to assist in identifying the patients at risk of disease progression. Having previously found six independent prognostic biomarkers in melanoma, including BRAF, MMP2, p27, Dicer, Fbw7 and Tip60, our group has gone on to investigate if these markers are useful in risk stratification of melanoma patients in individual AJCC stages. First, we performed Kaplan-Meier survival and Cox proportional multivariate analyses comparing prognostication power of these markers in 254 melanoma patients for whom the expression levels were known, identifying the best performing markers as candidates for stage-specific melanoma markers. We then verified the results by incorporating an additional independent cohort (87 patients) and in a combined cohort (341 patients). Our data indicate that BRAF and MMP2 are optimal prognostic biomarkers for AJCC Stages I and II, respectively (P = 0.010, 0.000, Log-rank test); whereas p27 emerged as a good marker for AJCC Stages III/IV (0.018, 0.046, respectively, log-rank test). Thus, our study has identified stage-specific biomarkers in melanoma, a finding which may assist clinicians in designing improved personalized therapeutic modalities.

Molecular markers in melanoma

The last few years have witnessed the dawn of the molecular era in melanoma treatment. With the advent of successful therapy targeting mutant BRAF, melanoma is leading the field of cancer research in the molecular approach to therapy of advanced disease. Attempting to keep pace with advances in therapy are advances in the molecular assessment of melanoma progression, facilitated by the availability of genome-wide approaches to interrogate the malignant phenotype. At the DNA level, this has included approaches such as comparative genomic hybridization. At the RNA level, this has consisted of gene expression profiling using various assay methodologies. In certain instances, markers identified using these platforms have been further examined and developed using fluorescence in situ hybridization and immunohistochemical analysis. In this article, we will review recent progress in the development of novel molecular markers for melanoma that are nearing clinical application. We will review developments in the molecular classification of melanoma, in the molecular diagnosis of melanoma, and in the molecular assessment of melanoma prognosis.

Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma

PURPOSE

The development of a genetic signature for the identification of high-risk cutaneous melanoma tumors would provide a valuable prognostic tool with value for stage I and II patients who represent a remarkably heterogeneous group with a 3% to 55% chance of disease progression and death 5 years from diagnosis.

EXPERIMENTAL DESIGN

A prognostic 28-gene signature was identified by analysis of microarray expression data. Primary cutaneous melanoma tumor tissue was evaluated by RT-PCR for expression of the signature, and radial basis machine (RBM) modeling was performed to predict risk of metastasis.

RESULTS

RBM analysis of cutaneous melanoma tumor gene expression reports low risk (class 1) or high risk (class 2) of metastasis. Metastatic risk was predicted with high accuracy in development (ROC = 0.93) and validation (ROC = 0.91) cohorts of primary cutaneous melanoma tumor tissue. Kaplan-Meier analysis indicated that the 5-year disease-free survival (DFS) rates in the development set were 100% and 38% for predicted classes 1 and 2 cases, respectively (P < 0.0001). DFS rates for the validation set were 97% and 31% for predicted classes 1 and 2 cases, respectively (P < 0.0001). Gene expression profile (GEP), American Joint Committee on Cancer stage, Breslow thickness, ulceration, and age were independent predictors of metastatic risk according to Cox regression analysis.

CONCLUSIONS

The GEP signature accurately predicts metastasis risk in a multicenter cohort of primary cutaneous melanoma tumors. Preliminary Cox regression analysis indicates that the signature is an independent predictor of metastasis risk in the cohort presented.

Development and validation of a gene profile predicting benefit of postmastectomy radiotherapy in patients with high-risk breast cancer: a study of gene expression in the DBCG82bc cohort

PURPOSE

To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT).

EXPERIMENTAL DESIGN

The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients.

RESULTS

Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients.

CONCLUSIONS

A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT.

A novel hypoxia-associated subset of FN1 high MITF low melanoma cells: identification, characterization, and prognostic value

In many human cancers, the epithelial-to-mesenchymal transition has an important role in the induction of cancer stem-like cells, and hence, in the causation of intratumoral heterogeneity. This process, also referred to as mesenchymal mimicry, is, however, only poorly understood in melanoma and histological correlation is still lacking. In an immunohistochemical analysis of a large prospective series of 220 primary and metastatic melanomas for the well-known epithelial-to-mesenchymal transition marker FN1, we observed melanoma cells with high FN1 expression in metastases with ischemic necrosis, but rarely or not at all in samples lacking evidence of hypoxia. In a blinded, retrospective series of 82 melanoma metastases with 10-year follow-up, the presence of clusters of these FN1(high) melanoma cells correlated significantly with shortened melanoma-specific survival, highlighting the prognostic value of their presence. We describe in detail the unique light- and electron-microscopic features of these FN1(high) melanoma cells, enabling their identification in routinely hematoxylin-and-eosin-stained sections. In addition, by laser microdissection and subsequent gene expression analysis and immunohistochemistry, we highlight their distinctive, molecular phenotype that includes expression of various markers of the epithelial-to-mesenchymal transition (eg, ZEB1) and of melanoma stem-like cells (eg, NGFR), and lack of immunoreactivity for the melanocytic marker MITF. This phenotype could be reproduced in vitro by culturing melanoma cells under hypoxic conditions. Functionally, the hypoxic microenvironment was shown to induce a more migratory and invasive cell type. In conclusion, we identified a novel clinically relevant FN1(high)MITF(low) cell type in melanoma associated with ischemic necrosis, and propose that these cells reside at the crossroad of the epithelial-to-mesenchymal transition and stem-like cell induction, plausibly triggered by the hypoxic environment.

Diagnostic and prognostic biomarkers in melanoma

Melanoma is a lethal melanocytic neoplasm. Unfortunately, the histological diagnosis can be difficult at times. Distinguishing ambiguous melanocytic neoplasms that are benign nevi from those that represent true melanoma is important both for treatment and prognosis. Diagnostic biomarkers currently used to assist in the diagnosis of melanoma are usually specific only for melanocytic neoplasms and not necessarily for their ability to metastasize. Traditional prognostic biomarkers include depth of invasion and mitotic count. Newer diagnostic and prognostic biomarkers utilize immunohistochemical staining as well as ribonucleic acid, micro-ribonucleic acid, and deoxyribonucleic acid assays and fluorescence in situ hybridization. Improved diagnostic and prognostic biomarkers are of increasing importance in the treatment of melanoma with the development of newer and more targeted therapies. Herein, the authors review many of the common as well as newer diagnostic and prognostic biomarkers used in melanoma.

Tissue prognostic biomarkers in primary cutaneous melanoma

Cutaneous melanoma (CM) causes the greatest number of skin cancer-related deaths worldwide. Predicting CM prognosis is important to determine the need for further investigation, counseling of patients, to guide appropriate management (particularly the need for postoperative adjuvant therapy), and for assignment of risk status in groups of patients entering clinical trials. Since recurrence rate is largely independent from stages defined by morphological and morphometric criteria, there is a strong need for identification of additional robust prognostic factors to support decision-making processes. Most data on prognostic biomarkers in melanoma have been evaluated in tumor tissue samples by conventional morphology and immunohistochemistry (IHC) as well as DNA and RNA analyses. In the present review, we critically summarize main high-quality studies investigating IHC-based protein biomarkers of melanoma outcome according to Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)-derived criteria. Pathways have been classified and conveyed in the "biologic road" previously described by Hanahan and Weinberg. Data derived from genomic and transcriptomic technologies have been critically reviewed to better understand if any of investigated proteins or gene signatures should be incorporated into clinical practice or still remain a field of melanoma research. Despite a wide body of research, no molecular prognostic biomarker has yet been translated into clinical practice. Conventional tissue biomarkers, such as Breslow thickness, ulceration, mitotic rate and lymph node positivity, remain the backbone prognostic indicators in melanoma.

Immunohistochemical diagnostic and prognostic markers for melanoma

Recent studies in our laboratory have identified novel molecular diagnostic and prognostic markers based on analyses in large cohorts of melanoma patients. These markers were initially derived from gene expression profiling analyses of distinct stages of melanoma progression. Immunohistochemical analyses confirmed the differential expression of these markers, and immunohistochemistry-based multimarker assays were developed to assess melanoma diagnosis and prognosis at the molecular level. In this chapter we review the development of these assays and the methodologies used to assess marker expression in both nevi and primary melanomas.

Current status of diagnostic and prognostic markers in melanoma

Melanoma is the most life-threatening common form of skin cancer. While most cutaneous melanomas are cured by surgical resection, a minority will relapse locally, regionally, or distantly. Biomarkers have represented a focal point for research aimed at improving diagnostic accuracy as well as providing prognostic information that may help to guide therapeutic decisions. While systemic melanoma therapies were of extremely limited utility for patients with advanced disease in the past, two drugs have been approved the FDA within the past several years, and it is possible that they may provide even greater impact if employed earlier in the disease process. To optimally employ these therapies, prognostic biomarkers may offer significant value. This article reviews methodologies for both discovery and routine testing of melanoma biomarkers. It also focuses on specific commonly used markers, as well as approaches to studying their applications to specific clinical settings. As the armamentarium of melanoma drugs grows, it is hoped that specific biomarkers will aid in guiding the use of these agents for patients in the clinic.

Construction and analysis of multiparameter prognostic models for melanoma outcome

The outcome of Stage II melanoma is uncertain. Despite that 10-year melanoma-specific survival can approach 50 % following curative-intent wide local excision and negative sentinel lymph node biopsy, the adverse risk-benefit ratio of interferon-based adjuvant regimens precludes their use in most patients. The discovery and translation of protein-based prognostic biomarkers into the clinic offers the promise for residual risk stratification of Stage II melanoma patients beyond conventional clinicopathologic criteria to identify an additional subset of patients who, based upon tumor molecular profiles, might also derive benefit from adjuvant regimens. Despite incorporation of Ki-67 assays into clinical practice, systematic review of REMARK-compliant, immunostain-based prognostic biomarker assays in melanoma suggests that residual risk of recurrence might be best explained by a composite score derived from a small panel of proteins representing independent features of melanoma biology. Reflecting this trend, to date, five such multiparameter melanoma prognostic models have been published. Here, we review these five models and provide detailed protocols for discovering and validating multiparameter models including: appropriate cohort recruitment strategies, comprehensive laboratory protocols supporting fully quantitative chromogenic or fluorescent immunostaining platforms, statistical approaches to create composite prognostic indices recommended steps for model validation in independent cohorts.

Plasma osteopontin concentrations in patients with cutaneous melanoma

An effective circulating tumour marker is needed for melanoma especially with the advent of targeted therapies. Gene expression studies examining primary melanomas have shown that increased expression of osteopontin (SPP1) is associated with poor prognosis. Studies subsequently reported higher blood levels in melanoma patients with metastatic disease than those without. This study was designed to determine whether osteopontin plasma concentrations in disease-free patients after initial treatment predict survival. An enzyme-linked immunosorbent assay (ELISA) was used to measure osteopontin levels in stored plasma samples (N=215) from participants in the Leeds Melanoma Cohort. AJCC stage at sampling was statistically significant associated with osteopontin levels (p=0.03). Participants with untreated stage IV disease at sampling (n=10) had higher median osteopontin levels compared to those with treated stage I-III disease (n=158) (p<0.001) confirming previous findings. There was a trend for increased risk of death with increasing osteopontin levels but this was not statistically significant. If a level of 103.14 ng/ml (95th centile of healthy controls) was taken as the upper end of the normal range then 2.5% of patients with treated stage I-III (4/110), 17.6% of patients with untreated stage III (3/17) and 30% of patients with untreated stage IV disease (3/10) had higher levels. These findings suggest that plasma osteopontin levels warrant investigation as a tumour marker in a larger study in which the significance of change in levels over time should be studied in relation to detectable disease recurrence.

Prognostic impact of PHIP copy number in melanoma: linkage to ulceration

Ulceration is an important prognostic factor in melanoma whose biologic basis is poorly understood. Here we assessed the prognostic impact of pleckstrin homology domain-interacting protein (PHIP) copy number and its relationship to ulceration. PHIP copy number was determined using fluorescence in situ hybridization (FISH) in a tissue microarray cohort of 238 melanomas. Elevated PHIP copy number was associated with significantly reduced DMFS (P = 0.01) and DSS (P = 0.009) by Kaplan-Meier analyses. PHIP FISH scores were independently predictive of DMFS (P = 0.03) and DSS (P = 0.03). Increased PHIP copy number was an independent predictor of ulceration status (P = 0.04). The combined impact of increased PHIP copy number and tumor vascularity on ulceration status was highly significant (P< 0.0001). Stable suppression of PHIP in human melanoma cells resulted in significantly reduced glycolytic activity in vitro, with lower expression of LDH5, HIF1A, and VEGF, and was accompanied by reduced microvessel density in vivo. These results provide further support for PHIP as a molecular prognostic marker of melanoma, and reveal a significant linkage between PHIP levels and ulceration. Moreover, they suggest that ulceration may be driven by increased glycolysis and angiogenesis.

Future perspectives in melanoma research. Meeting report from the "Melanoma Bridge. Napoli, December 2nd-4th 2012"

Recent insights into the genetic and somatic aberrations have initiated a new era of rapidly evolving targeted and immune-based treatments for melanoma. After decades of unsuccessful attempts to finding a more effective cure in the treatment of melanoma now we have several drugs active in melanoma. The possibility to use these drugs in combination to improve responses to overcome the resistance, to potentiate the action of immune system with the new immunomodulating antibodies, and identification of biomarkers that can predict the response to a particular therapy represent new concepts and approaches in the clinical management of melanoma. The third "Melanoma Research: "A bridge from Naples to the World" meeting, shortened as "Bridge Melanoma Meeting" took place in Naples, December 2 to 4th, 2012. The four topics of discussion at this meeting were: advances in molecular profiling and novel biomarkers, combination therapies, novel concepts toward integrating biomarkers and therapies into contemporary clinical management of patients with melanoma across the entire spectrum of disease stage, and the knowledge gained from the biology of tumor microenvironment across different tumors as a bridge to impact on prognosis and response to therapy in melanoma. This international congress gathered more than 30 international faculty members who in an interactive atmosphere which stimulated discussion and exchange of their experience regarding the most recent advances in research and clinical management of melanoma patients.

A patient-centered methodology that improves the accuracy of prognostic predictions in cancer

Individualized approaches to prognosis are crucial to effective management of cancer patients. We developed a methodology to assign individualized 5-year disease-specific death probabilities to 1,222 patients with melanoma and to 1,225 patients with breast cancer. For each cancer, three risk subgroups were identified by stratifying patients according to initial stage, and prediction probabilities were generated based on the factors most closely related to 5-year disease-specific death. Separate subgroup probabilities were merged to form a single composite index, and its predictive efficacy was assessed by several measures, including the area (AUC) under its receiver operating characteristic (ROC) curve. The patient-centered methodology achieved an AUC of 0.867 in the prediction of 5-year disease-specific death, compared with 0.787 using the AJCC staging classification alone. When applied to breast cancer patients, it achieved an AUC of 0.907, compared with 0.802 using the AJCC staging classification alone. A prognostic algorithm produced from a randomly selected training subsample of 800 melanoma patients preserved 92.5% of its prognostic efficacy (as measured by AUC) when the same algorithm was applied to a validation subsample containing the remaining patients. Finally, the tailored prognostic approach enhanced the identification of high-risk candidates for adjuvant therapy in melanoma. These results describe a novel patient-centered prognostic methodology with improved predictive efficacy when compared with AJCC stage alone in two distinct malignancies drawn from two separate populations.

Tumor profiling using protein biomarker panels in malignant melanoma: application of tissue microarrays and beyond

Despite advances in our knowledge of the disease, malignant melanoma remains an unpredictable entity. The revolution in molecular biological techniques, such as DNA sequencing and gene-expression profiling, has uncovered many potential protein targets and biomarkers relevant to melanoma progression. Successful clinical application would be aided significantly by downstream proteomic validation of those candidate markers using a combination of immunohistochemistry and tissue microarrays. Yet, research in this context seems to lag behind the output of genomic data relating to melanoma. In this article, we look at the strengths and pitfalls of tissue microarrays in malignant melanoma. We will show how tissue microarrays have become a vital step in the transition from molecular techniques to useful clinical assays and interventions and look at likely future developments for advances in this field.

An attempt at a molecular prediction of metastasis in patients with primary cutaneous melanoma

Background

Current prognostic clinical and morphological parameters are insufficient to accurately predict metastasis in individual melanoma patients. Several studies have described gene expression signatures to predict survival or metastasis of primary melanoma patients, however the reproducibility among these studies is disappointingly low.

Methodology/Principal Findings

We followed extended REMARK/Gould Rothberg criteria to identify gene sets predictive for metastasis in patients with primary cutaneous melanoma. For class comparison, gene expression data from 116 patients with clinical stage I/II (no metastasis) and 72 with III/IV primary melanoma (with metastasis) at time of first diagnosis were used. Significance analysis of microarrays identified the top 50 differentially expressed genes. In an independent data set from a second cohort of 28 primary melanoma patients, these genes were analyzed by multivariate Cox regression analysis and leave-one-out cross validation for association with development of metastatic disease. In a multivariate Cox regression analysis, expression of the genes Ena/vasodilator-stimulated phosphoprotein-like (EVL) and CD24 antigen gave the best predictive value (p = 0.001; p = 0.017, respectively). A multivariate Cox proportional hazards model revealed these genes as a potential independent predictor, which may possibly add (both p = 0.01) to the predictive value of the most important morphological indicator, Breslow depth.

Conclusion/Significance

Combination of molecular with morphological information may potentially enable an improved prediction of metastasis in primary melanoma patients. A strength of the gene expression set is the small number of genes, which should allow easy reevaluation in independent data sets and adequately designed clinical trials.

Molecular diagnostic strategies: a role in the practice of dermatology

Molecular diagnostic strategies are gaining wider acceptance and use in dermatology and dermatopathology as more practitioners in this field develop an understanding of the principles and applications of genomic technologies. Molecular testing is facilitating more accurate diagnosis, staging, and prognostication, in addition to guiding the selection of appropriate treatment, monitoring of therapy, and identification of novel therapeutic targets, for a wide variety of skin diseases.

Progression of cutaneous melanoma: implications for treatment

The survival rates of melanoma, like any type of cancer, become worse with advancing stage. Spectrum theory is most consistent with the progression of melanoma from the primary site to the in-transit locations, regional or sentinel lymph nodes and beyond to the distant sites. Therefore, early diagnosis and surgical treatment before its spread is the most effective treatment. Recently, new approaches have revolutionized the diagnosis and treatment of melanoma. Genomic profiling and sequencing will form the basis for molecular taxonomy for more accurate subgrouping of melanoma patients in the future. New insights of molecular mechanisms of metastasis are summarized in this review article. Sentinel lymph node biopsy has become a standard of care for staging primary melanoma without the need for a more morbid complete regional lymph node dissection. With recent developments in molecular biology and genomics, novel molecular targeted therapy is being developed through clinical trials.

Immunoexpression analysis and prognostic value of BLCAP in breast cancer

Bladder Cancer Associated Protein (BLCAP, formerly Bc10), was identified by our laboratory as being down-regulated in bladder cancer with progression. BLCAP is ubiquitously expressed in different tissues, and several studies have found differential expression of BLCAP in various cancer types, such as cervical and renal cancer, as well as human tongue carcinoma and osteosarcoma. Here we report the first study of the expression patterns of BLCAP in breast tissue. We analyzed by immunohistochemistry tissue sections of normal and malignant specimens collected from 123 clinical high-risk breast cancer patients within the Danish Center for Translational Breast Cancer Research (DCTB) prospective study dataset. The staining pattern, the distribution of the immunostaining, and its intensity were studied in detail. We observed weak immunoreactivity for BLCAP in mammary epithelial cells, almost exclusively localizing to the cytoplasm and found that levels of expression of BLCAP were generally higher in malignant cells as compared to normal cells. Quantitative IHC analysis of BLCAP expression in breast tissues confirmed this differential BLCAP expression in tumor cells, and we could establish, in a 62-patient sample matched cohort, that immunostaining intensity for BLCAP was increased in tumors relative to normal tissue, in more than 45% of the cases examined, indicating that BLCAP may be of value as a marker for breast cancer. We also analyzed BLCAP expression and prognostic value using a set of tissue microarrays comprising an independent cohort of 2,197 breast cancer patients for which we had follow-up clinical information.

Melanoma molecular classes and prognosis in the postgenomic era

Gene expression profiling is a powerful method to classify human tumours on the basis of biological aggressiveness, response to therapy, and outcome for the patient, but its application in melanoma lags behind that of other cancers. From more than 100 articles available on the topic, we selected 14 focusing on patients' outcome. We review and briefly discuss salient findings, and list ten reasons why melanoma molecular classes are not yet used in clinical diagnosis and prognosis. The available evidence suggests that we are on the verge of creating a framework for the use of melanoma molecular classes in prognosis, but so far there is little consensus to put together informative diagnostic and prognostic gene sets.