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Melanoma Biomarkers

Cutaneous malignant melanoma remains the leading cause of skin cancer death in industrialized countries. Melanoma is diagnosed in more than 50,000 new patients in the US annually. Melanoma progression is well defined in its clinical and histo- pathological aspects (Breslow’s index, tumor size, ulceration, or vascular invasion), which also give hints to prognosis of the patient. Use of molecular biomarkers should therefore give additional information which cannot be determined by routine histopathology. There is a critical unmet need for new predictive and prognostic biomarkers for melanoma, particularly ones that can identify those tumors that are likely to result in progression (metastasis) and death. A classification of biomarkers of melanoma is shown in Table 13.11.

Several molecules influencing invasiveness and metastatic dissemination of melanoma have been identified. Expression of these molecules has been studied in primary melanoma and correlated with prognosis. Moreover, several tumor suppressors and oncogenes have been shown to be involved in melanoma pathogenesis, including CDKN2A, PTEN, TP53, RAS and MYC, but have not been related to melanoma subtypes or validated as prognostic markers. In the past, an increase in the number of positive tumor cells for Ki67, cyclin A, cyclin D, MMP-2, integrins beta1 and beta3 or osteonectin, as well as the decrease in p16, p27, and Melan A were considered as factors of poor prognosis in melanoma. However, only a small subset of these proteins has a prognostic value independent of tumor thickness. Development of high-throughput technologies fornanalyzing global molecular profiles of cancer is discovering previously unknown candidate genes involved in melanoma, such as Wnt-5A and B-raf.

YKL-40 is a growth factor for connective tissue cells and stimulates migration of endothelial cells. Cancer cells, macrophages, and neutrophils secrete YKL-40.

Table 13.11 Classification of biomarkers of melanoma

Genes

B-raf

Oncogenes: CDKN2A, MYC, RAS Tumor suppressors: PTEN, TP53 Wnt-5A

Protein biomarkers

Cell cycle associated proteins: Cyclin A, B, C, D Matrix metalloproteinases (MMP)-1 and —9 Melan A

Melanoma-inhibiting activity (MIA)

Melastatin

p16

p27

S100B

Methylation biomarkers

MicroRNA biomarkers

Suppressed natural killer (NK) cell function

NKG2D CD 158a CD 158b

Serum biomarkers

Lactic dehydrogenase (LDH)

Melanoma cell adhesion molecules: soluble intracellular adhesion molecule 1 (sICAM-1) Melanoma-inhibiting activity (MIA)

Melanocyte lineage/differentiation antigens: S100B TA90-immune complex (TA90IC)

YKL-40

Imaging biomarkers

DCE-MRI

© Jain PharmaBiotech

Elevated serum YKL-40 is an independent prognostic factor for poor survival in patients with metastatic melanoma.

The first unbiased systematic effort to determine methylation biomarkers in melanoma by mapping chemical modifications of DNA in the melanoma genome has revealed several novel genes regulated by promoter methylation that were not described in cancer cells before (Koga et al. 2009). Discovery of new meth- ylation biomarkers will help develop more effective treatment strategies to fight this disease.

Currently, no biomarker to improve risk stratification is part of recommended clinical practice. Although numerous biomarkers candidates have been identified, their relevance to melanoma progression, clinical outcome and the selection of optimal treatment strategies still needs to be established. A more accurate, therapeutically predictive classification of human melanomas and selection of patient populations that would profit from therapeutic interventions are among the major challenges expected to be addressed in the future. Biomarker identification and validation will provide a rapidly changing molecular view of melanoma, a strategy that is necessary for developing truly stratified or personalized prevention or management.

 
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