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http://dx.doi.org/10.1016/j.ijwd.2018.10.020 | DOI Listing |
Vet Clin Pathol
September 2024
Research Institute, Green Vet, Yongin-si, Korea.
A feline cutaneous melanocytic tumor in a 1-year-old cat is reported. The cytologic, histologic, and immunohistochemical characteristics of the pediatric feline cutaneous melanocytoma are included. A solitary, black-colored nodule on the head was histologically diagnosed as the epithelioid type of melanocytoma.
View Article and Find Full Text PDFPigment Cell Melanoma Res
July 2024
Department of Dermatology, Eberhard Karls University of Tübingen, Tübingen, Germany.
Cancer Cell Int
February 2024
Department of Biological Sciences, National Sun Yat-Sen University, Kaohsiung, 804, Taiwan.
The incidence of melanoma, the most lethal form of skin cancer, has increased due to ultraviolet exposure. The treatment of advanced melanoma, particularly metastatic cases, remains challenging with poor outcomes. Targeted therapies involving BRAF/MEK inhibitors and immunotherapy based on anti-PD1/anti-CTLA4 antibodies have achieved long-term survival rates of approximately 50% for patients with advanced melanoma.
View Article and Find Full Text PDFNeoplasia
February 2023
Department of Medical Biotechnology, Faculty of Biophysics, Biochemistry and Biotechnology, Jagiellonian University, 30-387 Krakow, Poland. Electronic address:
Slow-cycling cancer cells (SCC) contribute to the aggressiveness of many cancers, and their invasiveness and chemoresistance pose a great therapeutic challenge. However, in melanoma, their tumor-initiating abilities are not fully understood. In this study, we used the syngeneic transplantation assay to investigate the tumor-initiating properties of melanoma SCC in the physiologically relevant in vivo settings.
View Article and Find Full Text PDFFront Oncol
April 2021
Department of Dermatology, China-Japan Union Hospital of Jilin University, Changchun, China.
Background: Currently there is no effective prognostic indicator for melanoma, the deadliest skin cancer. Thus, we aimed to develop and validate a nomogram predictive model for predicting survival of melanoma.
Methods: Four hundred forty-nine melanoma cases with RNA sequencing (RNA-seq) data from TCGA were randomly divided into the training set I (n = 224) and validation set I (n = 225), 210 melanoma cases with RNA-seq data from Lund cohort of Lund University (available in GSE65904) were used as an external test set.
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