Multimodal AI and tumour microenvironment integration predicts metastasis in cutaneous melanoma.

ABSTRACT: 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 biom

SUBMITTER: Andrew TW 

PROVIDER: S-EPMC12627701 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature