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JCO Early Release, published online ahead of print Nov 2 2009
Received February 26, 2009 Melanoma Prognostic Model Using Tissue Microarrays and Genetic Algorithms
From the Departments of Pathology, Medicine, Dermatology, and Surgery, Yale University School of Medicine; Department of Biostatistics, Yale School of Public Health, New Haven, CT. * To whom correspondence should be addressed. E-mail: david.rimm{at}yale.edu
Purpose: As a result of the questionable risk-to-benefit ratio of adjuvant therapies, stage II melanoma is currently managed by observation because available clinicopathologic parameters cannot identify the 20% to 60% of such patients likely to develop metastatic disease. Here, we propose a multimarker molecular prognostic assay that can help triage patients at increased risk of recurrence. Methods: Protein expression for 38 candidates relevant to melanoma oncogenesis was evaluated using the automated quantitative analysis (AQUA) method for immunofluorescence-based immunohistochemistry in formalin-fixed, paraffin-embedded specimens from a cohort of 192 primary melanomas collected during 1959 to 1994. The prognostic assay was built using a genetic algorithm and validated on an independent cohort of 246 serial primary melanomas collected from 1997 to 2004. Results: Multiple iterations of the genetic algorithm yielded a consistent five-marker solution. A favorable prognosis was predicted by ATF2 ln(non-nuclear/nuclear AQUA score ratio) of more than –0.052, p21WAF1 nuclear compartment AQUA score of more than 12.98, p16INK4A ln(non-nuclear/nuclear AQUA score ratio) of Conclusion: This multimarker prognostic assay, an independent determinant of melanoma survival, might be beneficial in improving the selection of stage II patients for adjuvant therapy.
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Copyright © 2009 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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