The aim of this study is to investigate a type of skin cancer, also known as melanoma, in children, adolescents, and young adults, who will be referred to as CAYA patients in this project. The need for this study arises because this disease, in CAYA patients, is still poorly understood due to its rarity in individuals under 30 years old. This often leads to difficulties in assessing its severity and, consequently, in deciding on the necessary treatments to ensure the patient's recovery. The goal of this study is to examine melanoma in CAYA patients in order to gather the information needed to provide better diagnoses for affected patients and, as a result, select appropriate treatments to fight the disease and promote the patient's full recovery. Additionally, the data collected will be used to create a Pan-European online platform that will allow doctors across the European Union to consult the obtained data and collaborate on particularly complex melanoma cases, always with the aim of ensuring the patient's full recovery in the shortest possible time.

The Mol-Mel study will focus on different tasks and for each task different investigations will be carried out:

• Standardization and tissue quality control: The quality of the samples will then be determined using hematoxylin & eosin (HE)-staining. If any quality issue is detected feedback will be sent to the clinical center responsible for providing the sample
• Histopathology & computational pathology: Melanoma samples will undergo a central pathology review and analysis of conventional prognostic staging parameters. Diagnostically challenging neoplasms will be included in an "inter-observer agreement" carried out by different pathologist.Melanoma samples will also be charactered by single and multi-plex IHC in whole sections and tissue microarrays (TMA), and subjected to automated digital quantification. Spatial proteomics by automated ultra-high content imaging/MACSima Imaging Cyclic Staining (MICS) technology enables simultaneous analysis of hundreds of marker antigens on a single sample. Hundreds of antigens for single sample will be analysed via "Automated ultra-high content imaging/MACSima Imaging Cyclic Staining" (MICS) that will be performed on the novel automated ultra-high content imaging platform MACSimaTM (Miltenyi Biotec).
• Comprehensive somatic, transcriptional and DNA methylation landscape and data integration: DNA and RNA will be extracted by FFPE melanoma samples and characterized using whole-exome sequencing (WES), single nucleotide polymorphism (SNP) and RNA sequencing (RNAseq) arrays on matched tumor/normal pairs of samples. Then recurrent somatic aberrations, DNA methylation subclasses and patterns of tumor evolution will be characterized.
• Pan-European digital second opinion platform: this last task will focus on creating a pan-european second opinion platofrom in order to facilitate standardization of melanoma diagnosis and to share knowledge about biomarkers, algorithms and subtype classification.

Inclusion Criteria:

• adolescent and childhood patients (< 20 years) or young adults (< 30 years)
• histologically confirmed diagnosis of melanoma or intermediate/ambiguous melanocytic neoplasm (i.e., melanocytomas, SAMPUS, IAMPUS and MELTUMP according to WHO classification)

Exclusion criteria:

• adult patients (> 30 years of age)
• patients without histologically confirmed diagnosis of melanoma or intermediate/ambiguous melanocytic neoplasm

The study will focus on CAYA (< 30 y.o) patients with histologically confirmed melanoma or intermediate/ambiguous melanocytic neoplasm (i.e.,melanocytomas, SAMPUS, IAMPUS and MELTUMP according to WHO classification).The population include patients of both genders.

Informations about the patients will be shared with other collaborators for the sharing of histological and clinical data in order to reach a consensus diagnosis between collaborating pathologists. Each collected sample will receive a identification code which will allow the results of the automated process to be saved and compared with those noted by the pathological anatomy medical staff. The code is assigned through pseudonymisation techniques (reversible de-identification), so that it cannot be directly traced back to the interested parties.

Up to 32 months from enrollment

The data will be managed by the main investigator of the study: Prof Daniela Massi, according to the recent European regulations in force of the GDPR and the Provision containing the requirements relating to the processing of particular categories of data, pursuant to art. 21, paragraph 1 of Legislative Decree 10 August 2018, n. 101 (GU no. 176 of 29 July 2019).

Other collaborators can only access histopathological and clinical data of the patients.