Abstract
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, p21 WAF1 nuclear compartment AQUA score of more than 12.98, p16 INK4A ln(non-nuclear/nuclear AQUA score ratio) of ≤ - 0.083, β-catenin total AQUA score of more than 38.68, and fibronectin total AQUA score of ≤ 57.93. Primary tumors that met at least four of these five conditions were considered a low-risk group, and those that met three or fewer conditions formed a high-risk group (log-rank P < .0001). Multivariable proportional hazards analysis adjusting for clinicopathologic parameters shows that the high-risk group has significantly reduced survival on both the discovery (hazard ratio = 2.84; 95% CI, 1.46 to 5.49; P = .002) and validation (hazard ratio = 2.72; 95% CI, 1.12 to 6.58; P = .027) cohorts. 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. © 2009 by American Society of Clinical Oncology.
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CITATION STYLE
Gould Rothberg, B. E., Berger, A. J., Molinaro, A. M., Subtil, A., Krauthammer, M. O., Camp, R. L., … Rimm, D. L. (2009). Melanoma prognostic model using tissue microarrays and genetic algorithms. Journal of Clinical Oncology, 27(34), 5772–5780. https://doi.org/10.1200/JCO.2009.22.8239
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