Esther Baena

This study models prostate cancer emergence using compartmental stochastic simulations to show how luminal compartment dynamics drive rapid tumor growth, while basal compartment tumors are more aggressive and persistent.

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.

This paper develops bio-fabricated alginate hydrogels to model prostate cancer microenvironments, showing increased cell proliferation and metastatic markers in stiffer, laminin-enriched hydrogels with cancer-associated fibroblasts.

This study identifies RUNX1 as a marker for a castration-resistant luminal lineage in the developing and adult mouse prostate, distinct from NKX3.1+ cells.