Caroline Hoffmann

OKN4395, a triple EP2/EP4/DP1 antagonist, restores antitumor immunity by reversing prostanoid-driven immunosuppression and synergizes with anti-PD1 therapy.

The paper introduces a machine-learning method to identify recurrent cell-cell communication patterns across tumor samples using spatial transcriptomics and single-cell data, revealing key immune and genetic programs in bladder cancer.

This paper introduces SpaMIL, a spatial transcriptomics-based multiple instance learning framework for patient-level outcome prediction in glioblastoma, achieving high prognostic accuracy.

The paper identifies a prognostic infiltration zone in glioblastoma using histology and spatial transcriptomic integration, revealing specific cell composition associated with long-term survival.

MOSAIC characterizes intra-tumoral heterogeneity using multi-omics spatial and single-cell data across cancer types, revealing insights into drug sensitivity and therapeutic implications.

The paper compares three transcriptomic methods on FFPE tumor samples to assess their ability to detect inter- and intra-patient heterogeneity.