Andreas Lösch

fastMHN enables pan-cancer tumor evolution analysis by approximating complex progression models, identifying a progression group linked to STK11 mutations across multiple cancer types.

This study introduces metMHN, a model to infer metastatic progression from cross-sectional cancer genomics data, identifying TP53 and EGFR as key mediators and highlighting copy number alterations in post-seeding adaptation.

This paper extends cancer progression models to account for observation bias by modeling how genetic events affect tumor detection, improving the accuracy of inferred causal interactions.