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Multimodal AI and tumour microenvironment integration predicts metastasis in cutaneous melanoma

Title: Multimodal AI and tumour microenvironment integration predicts metastasis in cutaneous melanoma
Authors: Andrew TW; Combalia M; Hernandez C; Grant S; Paragh G; Puig S; Mc Arthur G; Richardson G; Sloan P; Shalhout SZ; Plummer R; Lovat PE
Source: Nature Communications, December 2025
Publisher Information: Nature Research
Publication Year: 2025
Collection: Newcastle University Library ePrints Service
Description: © The Author(s) 2025.Accurate prognostication is essential to guide clinical management in localised cutaneous melanoma (CM), the form of skin cancer with the highest mortality. While the tumour microenvironment (TME) plays a key role in disease progression, current staging systems rely on limited tumour features and exclude key clinicopathological prognostic features. Here we show that MelanoMAP, a multimodal AI model integrating TME-derived digital biomarkers and clinicopathological features from over 3,500 histology slides, improves prognostication of localised CM. MelanoMAP achieved a C-index of 0.82, a 24% improvement over traditional AJCC staging (0.66) and consistently outperformed clinicopathological-only models across six international patient cohorts. SHAP analysis identified TME-derived digital biomarkers, alongside traditional clinicopathological factors including age, mitotic count, and Breslow depth, were critical determinants of metastatic risk. MelanoMAP establishes a potential foundation for precision oncology in CM, demonstrating how AI-driven digital biomarkers can advance personalised prognostication and inform clinical-decision making.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: unknown
Relation: https://eprints.ncl.ac.uk/309045; https://eprints.ncl.ac.uk/fulltext.aspx?url=309045/97277E17-1E16-4B31-9401-CA435B56DF20.pdf&pub_id=309045
Availability: https://eprints.ncl.ac.uk/309045
Rights: https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.FB2843C1
Database: BASE