This article appears in the following Annals of Oncology issue: Melanoma: Perspectives of the Global Melanoma Task Force [View the issue table of contents]
Articles |
Biomarkers in melanoma
1 First Department of Medicine, Medical School, University of Athens, Greece
2 Department of Surgical Oncology, Erasmus University Medical Center–Daniel den Hoed Cancer Center, Rotterdam, The Netherlands
3 Department of Dermatology, University of Kiel, Kiel, Germany
4 Immunology and Oncology Unit, Calvary Mater Newcastle Hospital, New South Wales, Australia
5 Department of Dermatology, Elbe-Klinikum Buxtehude, Buxtehude, Germany
6 Department of Dermatology, University Hospital Essen, Essen, Germany
7 Department of Pathology, Sir Mortimer B. Davis Jewish General Hospital and McGill University, Montreal, Canada
8 Department of Dermatology, University of Zürich Hospital, Zürich, Switzerland
* Correspondence to: Helen Gogas, Assistant Professor of Medical Oncology, First Department of Medicine, University of Athens Medical School, 24 Karneadou STR, Athens, 10675, Greece; Tel: +30-6944681159; Fax: +30-2107781517; E-mail: hgogas{at}hol.gr
Biomarkers are tumour- or host-related factors that correlate with tumour biological behaviour and patient prognosis. High-throughput analytical techniques—DNA and RNA microarrays—have identified numerous possible biomarkers, but their relevance to melanoma progression, clinical outcome and the selection of optimal treatment strategies still needs to be established. The review discusses a possible molecular basis for predictive tissue biomarkers such as melanoma thickness, ulceration and mitotic activity, and provides a list of promising new biomarkers identified from tissue microarrays that needs confirmation by independent, prospectively collected clinical data sets. In addition, common predictive serum biomarkers—lactate dehydrogenase, S100B and melanoma-inhibiting activity—as well as selected investigational serum biomarkers such as TA90IC and YKL-40 are also reviewed. 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.
Key words: biomarkers, melanoma, LDH, MIA, S100