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Novel Multiple Markers to Distinguish Melanoma from Dysplastic Nevi

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  • Guohong Zhang
  • Gang Li

Abstract

Background: Distinguishing melanoma from dysplastic nevi can be challenging. Objective: To assess which putative molecular biomarkers can be optimally combined to aid in the clinical diagnosis of melanoma from dysplastic nevi. Methods: Immunohistochemical expressions of 12 promising biomarkers (pAkt, Bim, BRG1, BRMS1, CTHRC1, Cul1, ING4, MCL1, NQO1, SKP2, SNF5 and SOX4) were studied in 122 melanomas and 33 dysplastic nevi on tissue microarrays. The expression difference between melanoma and dysplastic nevi was performed by univariate and multiple logistic regression analysis, diagnostic accuracy of single marker and optimal combinations were performed by receiver operating characteristic (ROC) curve and artificial neural network (ANN) analysis. Classification and regression tree (CART) was used to examine markers simultaneous optimizing the accuracy of melanoma. Ten-fold cross-validation was analyzed for estimating generalization error for classification. Results: Four (Bim, BRG1, Cul1 and ING4) of 12 markers were significantly differentially expressed in melanoma compared with dysplastic nevi by both univariate and multiple logistic regression analysis (p

Suggested Citation

  • Guohong Zhang & Gang Li, 2012. "Novel Multiple Markers to Distinguish Melanoma from Dysplastic Nevi," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-9, September.
    • Handle: RePEc:plo:pone00:0045037
    DOI: 10.1371/journal.pone.0045037
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