Nevi and Melanomas

The primary objective of this study is to create a highly multidimensional and multicentric database for melanoma that encompasses cohorts of children, adolescent and young adults. This database will be used to perform survival analysis and evaluate sentinel lymph node (SLNB) positivity in CAYA. The secondary objectives to be met are the following: * Adaptation and optimization of algorithms: work on optimizing existing precision medicine algorithms, which are currently being used in adult patient care, for their application within pediatric and young adult populations. * Implementation of transfer learning: given the limitations associated with pediatric and young adult data, the investigators intend to utilize transfer learning techniques. The study will employ a sequential waterfall methodology, whereby machine learning models trained on adult patient data will be fine-tuned using the more limited data from younger cohorts. * Integration of expert medical opinion: to integrate physician's scientific domain knowledge into the decision support system. This will be facilitated through the comprehensive examination of existing literature, as well as the evaluation of variable risk contributions within each patient group. * AI-based prognostic models: to develop artificial intelligence-based models for the quantitative prognosis of melanoma across the three age groups: adults, young adults, and children.

The primary objective is to evaluate the possibility of using minimally and non-invasive technologies (skin patch and breath analyzer) based on the detection of volatile organic compounds (VOCs) for the early identification of metastases. The secondary objective is to evaluate the usability of these technologies in the follow up of high-risk melanoma patients.

The primary objective of this study is to identify the molecular identity profiles of all cellular states that characterize the progression from benign nevi to malignant melanoma in CAYA patients with L/GCMN. The secondary objectives are: * To longitudinally characterize the cell-free DNA (cfDNA) from CAYA patients. * To improve the early diagnosis and treatments for intermediate conditions such as L/GCMN through evidence-based interpretation of personal risk from endogenous or exogenous sources. * To test pre-clinical strategies to best model and improve patient response.