Jan-Niklas May, Jennifer I Moss, Florian Mueller, Susanne K Golombek, Ilaria Biancacci, Larissa Rizzo, Asmaa Said Elshafei, Felix Gremse, Robert Pola, Michal Pechar, Tomáš Etrych, Svea Becker, Christian Trautwein, Roman D Bülow, Peter Boor, Ruth Knuechel, Saskia von Stillfried, Gert Storm, Sanyogitta Puri, Simon T Barry, Volkmar Schulz, Fabian Kiessling, Marianne B Ashford, Twan Lammers
The clinical prospects of cancer nanomedicines depend on effective patient stratification. Here we report the identification of predictive biomarkers of the accumulation of nanomedicines in tumour tissue. By using supervised machine learning on data of the accumulation of nanomedicines in tumour models in mice, we identified the densities of blood vessels and of tumour-associated macrophages as key predictive features. On the basis of these two features, we derived a biomarker score correlating with the concentration of liposomal doxorubicin in tumours and validated it in three syngeneic tumour models in immunocompetent mice and in four cell-line-derived and six patient-derived tumour xenografts in mice...
April 8, 2024: Nature Biomedical Engineering