"Melanoma is notorious for its high tendency to metastasize and its refractoriness to treatment thereafter. Metastasis is believed to occur mostly through the lymphatic system, and the status of sentinel lymph nodes is currently recognized as the best prognostic indicator. Unfortunately, the lymphatic metastatic process is still poorly understood and the occurrence of sentinel node metastases (micrometastases) may be underestimated. We performed genome-wide gene expression analyses of melanoma lymph node micrometastases and macrometastases, and of primary melanomas and benign naevi, to characterize the early metastatic cells molecularly and to disclose the best diagnostic markers and rational targets for therapy. Significance analysis of microarrays identified 22 over- and five under-expressed genes with >= four-fold changes in the micrometastases. Of these genes, MLANA, TYR, MIA, ERBB3, PRAME, and SPP1 were tested as potential markers by RT-PCR and immunobistochernistry. In a prospective study of 160 patients, our graded MLANA and TYR RT-PCR analyses disclosed clinically significant metastases, as assessed by disease recurrence, better than histological and immunohistochernical examinations. These results strongly suggest the clinical implementation of quantifiable RT-PCR assays to confirm and complement the pathological examination of sentinel node metastases. Furthermore, SPP1 and PRAME proved valuable as melanoma-specific markers capable of differentiating melanoma cells from benign naevi in the sentinel lymph nodes. Importantly, these two genes may also prove to be ideal targets for drug development and therapy. Most molecular traits of the micrometastases were already present in the primary tumours, suggesting that micrometastasis to sentinel lymph nodes is a fairly non-selective process. Copyright (c) 2007 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd."
|Journal||Journal of Pathology|
|Number of pages||10|
|Publication status||Published - 2007|
|MoE publication type||A1 Journal article-refereed|
Fields of Science
- 113 Computer and information sciences