Ultraviolet radiation (UVR) has been recognized as a potential trigger for the transformation of benign melanocytic nevi into melanoma. However, the mechanisms governing the formation and progression of melanocytic nevi remain poorly understood. This lack of understanding is partly due to the difficulty in isolating and culturing nevus tissues in vitro, resulting in a dearth of robust ex vivo models for nevi. Therefore, the establishment of a reliable melanocytic nevus model is imperative. Such a model is essential for elucidating nevus pathogenesis and facilitating the development of effective therapeutic interventions. Therefore, we have sought to establish an ex vivo nevus explant model to study UVR stimulation. And the structural integrity and tissue activity of the ex vivo nevi explant model was evaluated. We then observed melanogenesis and proliferation activity of the explants after UVR stimulation. There was less blister formation after Day 3 in nevi explants under our modified medium conditions. The nevi explant was able to maintain almost the same morphological structure and tissue activity as in vivo tissue within 24 h. Following UVR stimulation, we observed increased melanogenesis and proliferation activity in nevi explants. Nevi explants could serve as an ex vivo model for UVR-induced nevi stimulation research.

In humans, germline TP53 mutations predispose carriers to a wide spectrum of cancers, which is known as Li-Fraumeni syndrome (LFS). To date, the association of melanomas with LFS remains unestablished. No melanomas have been reported in any P53-modified mouse models either. In this study, we show that targeted disruption of P53 at the DNA-binding domain in Xenopus tropicalis recapitulates LFS, with the formation of soft-tissue sarcomas and pancreatic ductal adenocarcinoma. Interestingly, 19% of the 14-month-old tp53Δ7/Δ7 homozygotes and 18% of tp53+/Δ7 heterozygotes spontaneously developed small nevi and non-invasive melanomas. Large invasive melanomas were also observed in other older homozygous mutants, with about 7.9% penetrance. Our data suggest that more dermatologic investigation of LFS patients should be able to settle the association of melanoma with LFS in epidemiology. Our model is also valuable for further investigation of the molecular mechanism underlying melanoma progression upon germline alteration of the tp53 locus.

BACKGROUND: Basal cell carcinoma (BCC) is the most common cutaneous malignancy. Occasionally, it may have an appearance similar to that of some benign pigmented skin lesions. Therefore, additional information is needed to differentiate these lesions.
METHODS: A diagnostic accuracy study was performed from February 2018 to April 2019. All lesions underwent ultrasound examination with 50 and 20 MHz probes. The high-frequency ultrasound (HFUS) images were evaluated independently by 2 experienced doctors for the presence of predefined features, including the depth, shape, margin, anechoic area, hyperechoic spots, epidermal interrupted echo, mushroom sign, flat-bottom sign, and superficial hyperechoic focus (SHEF).
RESULTS: A total of 54 BCCs, 51 melanocytic nevi and 55 seborrheic keratoses (SK), were included. BCCs often involved the subcutaneous tissue (11/54, 20.4%; P < .001) and had an irregular shape (26/54, 48.1%; P < .001) and ill-defined borders (26/54, 48.1%; P < .001), while most benign pigmented lesions had a regular shape (101/106, 95.3%; P < .001) and well-defined borders (95/106, 89.6%; P < .001). BCCs occasionally showed anechoic areas (10/54, 18.5%; P < .001) and epidermal interrupted echo (18/54, 33.3%; P < .001). Moreover, hyperechoic spots could be found in BCCs (43/54, 79.6%), nevi (27/51, 52.9%), and SK (30, 54.5%) (P = .001), with mean number of 7.3, 5.5, and 8.0, respectively. The mushroom signs were all present in melanocytic nevi (18/51, 35.3%), while the flat-bottom sign (43/55, 78.2%; P < .001) and SHEF (40/55, 72.7%; P < .001) presented mainly in SKs.
CONCLUSIONS: Based on the typical features, HFUS could improve the accuracy of BCC identification and should be considered when dermatologists are unsure about the lesion type.

As an analytic tool in medicine, deep learning has gained great attention and opened new ways for disease diagnosis. Recent studies validate the effectiveness of deep learning algorithms for binary classification of skin lesions (i.e., melanomas and nevi classes) with dermoscopic images. Nonetheless, those binary classification methods cannot be applied to the general clinical situation of skin cancer screening in which multi-class classification must be taken into account. The main objective of this research is to develop, implement, and calibrate an advanced deep learning model in the context of automated multi-class classification of skin lesions. The proposed Deep Convolutional Neural Network (DCNN) model is carefully designed with several layers, and multiple filter sizes, but fewer filters and parameters to improve efficacy and performance. Dermoscopic images are acquired from the International Skin Imaging Collaboration databases (ISIC-17, ISIC-18, and ISIC-19) for experiments. The experimental results of the proposed DCNN approach are presented in terms of precision, sensitivity, specificity, and other metrics. Specifically, it attains 94 % precision, 93 % sensitivity, and 91 % specificity in ISIC-17. It is demonstrated by the experimental results that this proposed DCNN approach outperforms state-of-the-art algorithms, exhibiting 0.964 area under the receiver operating characteristics (AUROC) in ISIC-17 for the classification of skin lesions and can be used to assist dermatologists in classifying skin lesions. As a result, this proposed approach provides a novel and feasible way for automating and expediting the skin lesion classification task as well as saving effort, time, and human life.

UNASSIGNED: Melanoma is a highly invasive malignant skin tumor. While melanoma may share some similarities with that of melanocytic nevi, there also exist a number of distinct differences between these conditions. An analysis of these differences may provide a means to more effectively evaluate the etiology and pathogenesis of melanoma. In particular, differences in aberrant methylation expression may prove to represent a critical distinction.
UNASSIGNED: Data from gene expression datasets (GSE3189 and GSE46517) and gene methylation datasets (GSE86355 and GSE120878) were downloaded from the GEO database. GEO2R was used to obtain differentially expressed genes (DEGs) and differentially methylation genes (DMGs). Function and pathway enrichment of selected genes were performed using the DAVID database. A protein-protein interaction (PPI) network was constructed by STRING while its visualization was achieved with use of cytoscape. Primary melanoma samples from TCGA were used to identify significant survival genes.
UNASSIGNED: There was a total of 199 genes in the hypermethylation-low expression group, while 136 genes in the hypomethylation-high expression group were identified. The former were enriched in the biological processes of transcription regulation, RNA metabolism and regulation of cell proliferation. The later were highly involved in cell cycle regulation. 13 genes were screened out after survival analysis and included: ISG20, DTL, TRPV2, PLOD3, KIF3C, DLGAP4, PI4K2A, WIPI1, SHANK2, SLC16A10, GSTA4O, LFML2A and TMEM47.
UNASSIGNED: These findings reveal some of the methylated differentially expressed genes and pathways that exist between melonoma and melanocytic nevi. Moreover, we have identified some critical genes that may help to improve the diagnosis and treatment of melanoma.

Melanoma is the most deadly type of skin cancer. This study aimed at uncovering the molecular mechanisms underlying melanoma progression. This study used the microarray dataset GSE46517, downloaded from the Gene Expression Omnibus database, including eight normal tissue samples, nine nevus tissue samples, 31 primary melanoma samples, and 73 metastatic melanoma tissue samples. Differentially expressed genes (DEGs) in nevus, primary melanoma, and metastatic melanoma were identified, with which a reactome functional interaction (FI) network was constructed, and pathway enrichment analysis of the network modules was performed. The common DEGs in primary and metastatic melanoma were identified by venn diagram analysis, followed by Gene ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and a protein-protein interaction (PPI) network. The study identified 130 DEGs in nevus, 539 DEGs in primary melanoma, and 1170 DEGs in metastatic melanoma. The reactome FI network modules 10, 14, and 15 were significantly enriched in the transforming growth factor (TGF)-β signaling pathway. EDNRB, MITF, and LEF1 were the common upregulated DEGs in nevus, primary, and metastatic melanoma, and they were significantly enriched in the melanogenesis pathway. In the PPI network with the common DEGs in primary and metastatic melanoma, EGFR, ERBB2, CD8A, and MMP9 were the hub genes. EDNRB, MITF, LEF1, EGFR, ERBB2, CD8A, MMP9, melanogenesis pathway, and TGF-β signaling pathway might be involved in the molecular mechanism of melanoma. These genes may be recommended as promising molecular targets for development of melanoma therapeutics.

Recent studies have demonstrated that cathepsin K seems to be a powerful marker in identifying the microphthalmia associated transcription factor (MITF) family tumors such as renal perivascular epithelioid cell neoplasms (PEComas), alveolar soft part sarcoma, and translocation-associated renal cell carcinomas. However, the expression of cathepsin K in melanocytic lesions has not been well characterized. Our aim was to investigate the expression of cathepsin K in a wide histological spectrum of melanocytic lesions and to evaluate its potential diagnostic and molecular target therapy usefulness in comparison with other commonly used markers. 143 consecutive melanocytic lesions were selected for study including 56 primary malignant melanomas, 62 metastatic melanomas, and 25 benign nevi (16 intradermal melanocytic nevi and 9 compound melanocytic nevi). 107 of the 118 (91%) primary and metastatic melanomas displayed a high percentage of cells with moderately to strongly positive reactions for cathepsin K (mean 82%; range 0-95%). MITF, HMB45, Melan-A, and S100 were expressed in 85, 76, 78 and 96% of cases, respectively, with various percentages of positive cells (mean, 63, 49, 55 and 86%; range 0-90, 0-80, 0-90 and 0-95%). Among the benign nevi, cathepsin K, MITF, HMB45, Melan-A, and S100 were expressed in 88, 80, 36, 68 and 100% of cases, respectively. Cathepsin K appears to be consistently and strongly expressed in melanocytic lesions and valuable in distinguishing malignant melanomas from the majority of human cancers.