Cyclin D1 and D3 expression in melanocytic skin lesions

Cyclins, cyclin-dependent kinases, as well as proteins cooperating with them are responsible for cell cycle regulation which is crucial for normal development, injury repair, and tumorigenesis. D-type cyclins regulate G1 cell cycle progression by enhancing the activities of cyclin-dependent kinases, and their expression is frequently altered in tumors. Disturbances in cyclin expression were also reported in melanocytic skin lesions. The objective of the study was to evaluate the expression of cyclins D1 and D3 in common, dysplastic, and malignant melanocytic skin lesions. Forty-eight melanocytic skin lesions including common nevi (10), dysplastic nevi (24), and melanomas (14) were diagnosed by dermoscopy and excised. Expression of cyclin D1 and D3 was detected by immunohistochemistry and quantified as percentage of immunostained cell nuclei in each sample. In normal skin, expression of cyclins D1 and D3 was not detected. The mean percentage of cyclin D1-positive nuclei was 7.75% for melanoma samples, 5% for dysplastic nevi samples, and 0.34% for common nevi samples. For cyclin D3, the respective values were 17.8, 6.4, and 1.8%. Statistically significant differences in cyclin D1 expression were observed between melanomas and common nevi as well as between dysplastic and common nevi (p = 0.0001), but not between melanomas and dysplastic nevi. Cyclin D3 expression revealed significant differences between all investigated lesion types (p = 0.0000). The mean cyclin D1 and D3 scores of melanomas with Breslow thickness <1 mm and >1 mm were not significantly different. G1/S abnormalities are crucial for the progression of malignant melanoma, and enhanced cyclin D1 and D3 expression leading to increased melanocyte proliferation is observed in both melanoma and dysplastic nevi. In histopathologically ambiguous cases, lower cyclin D3 expression in dysplastic nevi can be a diagnostic marker for that lesion type

Computational Methods for Pigmented Skin Lesion Classification in Images: Review and Future Trends

Skin cancer is considered as one of the most common types of cancer in several countries, and its incidence rate has increased in recent years. Melanoma cases have caused an increasing number of deaths worldwide, since this type of skin cancer is the most aggressive compared to other types. Computational methods have been developed to assist dermatologists in early diagnosis of skin cancer. An overview of the main and current computational methods that have been proposed for pattern analysis and pigmented skin lesion classification is addressed in this review. In addition, a discussion about the application of such methods, as well as future trends, is also provided. Several methods for feature extraction from both macroscopic and dermoscopic images and models for feature selection are introduced and discussed. Furthermore, classification algorithms and evaluation procedures are described, and performance results for lesion classification and pattern analysis are given

Dermoscopy in general dermatology

Dermoscopy improves the diagnostic accuracy in the clinical evaluation of pigmented skin lesions, but it is also useful for the assessment of vascular structures that are not visible to the naked eye. As a consequence, dermoscopy has been employed more and more for the differential diagnosis of nonpigmented skin disorders, including tumors but also inflammatory and infectious diseases. This article provides a review of the dermoscopic features seen in various nonpigmented tumoral and nontumoral skin lesions as well as the dermoscopic criteria used for monitoring skin reactions to various treatments. Copyright (c) 2006 S. Karger AG, Basel