The short arm of chromosome 1 (1p), especially the subtelomeric region of 1p36, is a common site for abnormalities in malignant melanoma of the skin. In a recent study nodular melanomas displayed deletions of 1p36 in an augmented percentage of cases. To evaluate the dimension of these deletions and to study their significance for the progression of malignant melanoma we analyzed seven melanoma cell lines, 32 primary tumors, and 32 metastatic tumors by fluorescence in situ hybridization with the DNA probe D1Z2 in 1p36.3 and eight YAC DNA probes hybridizing to 1p36, 1p32, 1p31, and 1p21. All cell lines, 91% of the metastatic tumors and 63% of nodular melanomas showed a deletion of 1p36.3. In the YAC hybridization experiments, the most frequent deletions were found in 1p36 in all cell lines, in 13% of nodular melanoma, and in 44% of metastatic tumors. Deletions in 1p36 were mostly confined to a rather small area near the locus D1Z2. The frequent occurrence of this deletion in melanomas with a high metastatic potential and the abundant accumulation of this deletion in metastasis point to genes located on 1p36, which might be of significance for the metastatic capability of malignant melanoma.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s004280050406 | DOI Listing |
Br J Dermatol
January 2025
Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, the Netherlands.
Background: Patients with haematologic malignancies are at increased risk of developing skin cancer and often experience worse skin cancer-related outcomes. However, there is a lack of nationwide, population-based data with long-term follow-up on the incidence and risks of different skin cancer types across all haematologic malignancies.
Objectives: To assess population-based risk estimates for cutaneous squamous cell carcinoma (CSCC), malignant melanoma (MM), Merkel cell carcinoma (MCC), and basal cell carcinoma (BCC) among patients with haematologic malignancies, stratified by skin cancer type and haematologic malignancy subgroup.
J Eur Acad Dermatol Venereol
January 2025
Pathology Department, IHP Group, Nantes, France.
Background: There is a need to improve risk stratification of primary cutaneous melanomas to better guide adjuvant therapy. Taking into account that haematoxylin and eosin (HE)-stained tumour tissue contains a huge amount of clinically unexploited morphological informations, we developed a weakly-supervised deep-learning approach, SmartProg-MEL, to predict survival outcomes in stages I to III melanoma patients from HE-stained whole slide image (WSI).
Methods: We designed a deep neural network that extracts morphological features from WSI to predict 5-y overall survival (OS), and assign a survival risk score to each patient.
Environ Toxicol
January 2025
C. Yue, W. Lian, Z.
View Article and Find Full Text PDFJ Pathol
January 2025
SIREDO Oncology Center (Care, Innovation and Research for Children and AYA with Cancer), Institut Curie, Université Paris Cité, Paris, France.
Rhabdoid tumours (RT) are an aggressive malignancy affecting <2-year-old infants, characterised by biallelic loss-of-function alterations in SWI/SNF-related BAF chromatin remodelling complex subunit B1 (SMARCB1) in nearly all cases. Germline SMARCB1 alterations are found in ~30% of patients and define the RT Predisposition Syndrome type 1 (RTPS1). Uveal melanoma (UVM), the most common primary intraocular cancer in adults, does not harbour SMARCB1 alterations.
View Article and Find Full Text PDFArch Dermatol Res
January 2025
VA Boston Healthcare System, Boston, MA, USA.
Cases for a disease can be defined broadly using diagnostic codes, or narrowly using gold-standard confirmation that often is not available in large administrative datasets. These different definitions can have significant impacts on the results and conclusions of studies. We conducted this study to assess how using melanoma phecodes versus histologic confirmation for invasive or in situ melanoma impacts the results of a genome-wide association study (GWAS) using the Million Veteran Program.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!