Abstract

BackgroundDistinguishing melanoma from dysplastic nevi can be challenging.ObjectiveTo assess which putative molecular biomarkers can be optimally combined to aid in the clinical diagnosis of melanoma from dysplastic nevi.MethodsImmunohistochemical 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.ResultsFour (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 < 0.01). These four combined markers achieved 94.3% sensitivity, 81.8% specificity and attained 84.3% area under the ROC curve (AUC) and the ANN classified accuracy with training of 83.2% and testing of 81.2% for distinguishing melanoma from dysplastic nevi. The classification trees identified ING4, Cul1 and BRG1 were the most important classification parameters in ranking top-performing biomarkers with cross-validation error of 0.03.ConclusionsThe multiple biomarkers ING4, Cul1, BRG1 and Bim described here can aid in the discrimination of melanoma from dysplastic nevi and provide a new insight to help clinicians recognize melanoma.

Highlights

  • Malignant melanoma is one of the most aggressive malignancies in humans with an estimated total of 48,000 fatalities worldwide per year, and the incidence of melanoma continues to rise [1]

  • The multiple biomarkers ING4, Cul1, BRG1 and Bim described here can aid in the discrimination of melanoma from dysplastic nevi and provide a new insight to help clinicians recognize melanoma

  • Since melanoma is very resistant to conventional chemotherapy with only 14 percent of patients with metastatic melanoma survive for 5 years [2], it accounts for almost 75% of deaths related to skin cancer

Read more

Summary

Introduction

Malignant melanoma is one of the most aggressive malignancies in humans with an estimated total of 48,000 fatalities worldwide per year, and the incidence of melanoma continues to rise [1]. Since melanoma is very resistant to conventional chemotherapy with only 14 percent of patients with metastatic melanoma survive for 5 years [2], it accounts for almost 75% of deaths related to skin cancer. Distinguishing malignant melanoma from dysplastic nevi remained problematic due to the wide variation in morphologic features. Dysplastic nevi often have some clinical and histologic features that overlap with melanoma, such as an irregular border, the asymmetric distribution of pigmentation, cytologic atypia and dermal inflammatory response [5,6,7]. The clinical picture, dermatoscopy and molecular or genetic testing often cannot distinguish a histological dysplastic nevus from a melanoma [8]. Distinguishing melanoma from dysplastic nevi can be challenging

Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.