Periodic Reporting for period 2 - MELCAYA (Novel health care strategies for melanoma in children, adolescents and young adults)
Periodo di rendicontazione: 2024-06-01 al 2025-11-30
Melanoma in children, adolescents and young adults (CAYA) remains under-studied, with limited tailored guidance, fragmented expertise and unequal access to specialised care, contributing to diagnostic uncertainty and delayed pathways. During the reporting period, MELCAYA strengthened the scientific and technical basis for improved prevention, diagnosis and prognosis in CAYA melanoma by expanding interoperable datasets and biospecimen collections, progressing multi-omics and tissue profiling in congenital melanocytic nevi (CMN) and related lesions, consolidating a pan-European digital pathology consultation workflow and advancing AI/ML and non-invasive technologies for early detection and risk stratification. In parallel, the project developed adoption-oriented evaluation approaches and patient-generated evidence to support future implementation and equity-focused policy uptake.
WP1 quantified CAYA melanoma incidence, sex differences and survival using EUROCARE-6 and ECIS-derived registry data, compiling historical registry information for pan-European analyses. Harmonized REDCap datasets/codebooks now include >500 cases, enabling hypothesis-driven epidemiological sub-studies. Exposome modelling was operationalized by stratifying Europe into latitudinal climatic zones and integrating environmental layers to support regression-based risk estimation. Genetics reached sequencing scale: from 465 selected germline samples, 323 were selected for WGS, passed initial QC and entered bioinformatic processing, supporting preliminary variant analyses and CAYA-oriented genetic risk modelling. WP2 advanced harmonized molecular workflows in L/GCMN. CNV profiling across 16 lesions from 14 patients (aCGH, shallow WGS, methylation-derived CNV) showed concordance for broad events while improving detection of focal/segmental CNVs and highlighting the need to update interpretation criteria beyond legacy CGH. Visium-based spatial transcriptomics expanded, generating and integrating 14 L/GCMN datasets and supporting identification of lesion-specific melanocytic states relevant to transformation biology.
WP3 consolidated the pathology network and curated case base: multicenter expert review continued under standardized QC and cutting/handling procedures and a HALO Link second-opinion workflow was advanced and documented, capturing implementation lessons (WSI variability, tissue scarcity) that inform standards for scalable cross-border pathology support. WP4 consolidated and analyzed the most extensive real-world anti-PD-1 dataset in pediatric melanoma (106 patients ≤18 years, stage III–IV) in a GDPR-compliant database with peer-reviewed dissemination. Results indicate adjuvant outcomes and safety comparable to adults, similar outcomes/safety across age strata including <12 years, and apparently lower survival in advanced disease versus adult series, addressing a key evidence gap due to rarity. WP5 progressed AI-based diagnostic support through scaled imaging acquisition/governance and explainable AI, combining Grad-CAM attribution with a pathologist-oriented strategy that decomposes WSIs into interpretable tissue/structure components and extracts human-aligned quantitative descriptors (e.g. melanocyte/nest metrics). WP6 advanced ML models for prognosis/survival and sentinel lymph node positivity prediction through retrospective validation and integration. Non-invasive technologies moved beyond prototyping: breath-analysis workflows were optimized (including simulated breath generation and sensor improvements) and the disposable sensing patch progressed through sensor configuration and device-readiness work, with clinical translation prepared through technical set-up and study preparation.
WP7 finalized an HTA framework for digital health/AI in rare diseases (scoping review, HTA/KOL interviews, proof-testing with MELCAYA technologies) and a transferability tool. ELSI work defined policy priorities (training, over/underdiagnosis balance, autonomy, equitable access, responsible AI), and a Delphi instrument (34 statements) was prepared across awareness/early recognition, governance, assessment/reimbursement and health system organization. WP8 supported technical integration via harmonization exchange and infrastructure-alignment planning to position outputs for long-term accessibility via UNCAN.eu. WP9 strengthened patient-generated evidence through SenseMaker self-ethnography. Training was completed and a pilot survey on access-related burden was designed and tested with patient advocates, improving usability/data quality.
WP3 consolidated the pathology network and curated case base: multicenter expert review continued under standardized QC and cutting/handling procedures and a HALO Link second-opinion workflow was advanced and documented, capturing implementation lessons (WSI variability, tissue scarcity) that inform standards for scalable cross-border pathology support. WP4 consolidated and analyzed the most extensive real-world anti-PD-1 dataset in pediatric melanoma (106 patients ≤18 years, stage III–IV) in a GDPR-compliant database with peer-reviewed dissemination. Results indicate adjuvant outcomes and safety comparable to adults, similar outcomes/safety across age strata including <12 years, and apparently lower survival in advanced disease versus adult series, addressing a key evidence gap due to rarity. WP5 progressed AI-based diagnostic support through scaled imaging acquisition/governance and explainable AI, combining Grad-CAM attribution with a pathologist-oriented strategy that decomposes WSIs into interpretable tissue/structure components and extracts human-aligned quantitative descriptors (e.g. melanocyte/nest metrics). WP6 advanced ML models for prognosis/survival and sentinel lymph node positivity prediction through retrospective validation and integration. Non-invasive technologies moved beyond prototyping: breath-analysis workflows were optimized (including simulated breath generation and sensor improvements) and the disposable sensing patch progressed through sensor configuration and device-readiness work, with clinical translation prepared through technical set-up and study preparation.
WP7 finalized an HTA framework for digital health/AI in rare diseases (scoping review, HTA/KOL interviews, proof-testing with MELCAYA technologies) and a transferability tool. ELSI work defined policy priorities (training, over/underdiagnosis balance, autonomy, equitable access, responsible AI), and a Delphi instrument (34 statements) was prepared across awareness/early recognition, governance, assessment/reimbursement and health system organization. WP8 supported technical integration via harmonization exchange and infrastructure-alignment planning to position outputs for long-term accessibility via UNCAN.eu. WP9 strengthened patient-generated evidence through SenseMaker self-ethnography. Training was completed and a pilot survey on access-related burden was designed and tested with patient advocates, improving usability/data quality.
MELCAYA advanced beyond the state of the art by combining rare-disease-scale harmonized resources with deployable digital workflows and adoption frameworks tailored to CAYA constraints. Key results include: (i) integrated CAYA risk databases (registry, exposome, WGS) enabling CAYA-specific risk stratification, (ii) CMN molecular diagnostics and spatial biology clarifying transformation trajectories and limitations of legacy CNV interpretation criteria, (iii) functioning multi-country digital pathology consultation model enabling expert second opinions and informing real-world standardization needs, (iv) the largest real-world evidence base on anti-PD-1 therapy in pediatric melanoma, (v) explainability-first AI pipelines and clinically oriented prognostic/staging tools and (vi) a rare-disease-adapted HTA/ELSI framework paired with patient-generated system intelligence. Key needs for further uptake include prospective multi-center validation, standards and regulatory alignment (WSI/metadata quality, reproducible pipelines, AI/medical device requirements), sustained governance and UNCAN integration for discoverability/reuse and implementation pathways that address patient-reported barriers to reduce inequalities in early diagnosis and access to expertise.