Cesar Augusto Santa-Maria

This study introduces a bi-level graph model to identify prognostic tumor microenvironment patterns in breast cancer, validated across multiple cohorts.

The paper uses virtual patient models to evaluate biomarkers for predicting response to PD-1 blockade in TNBC, finding that early on-treatment biomarkers and blood-based markers offer better performance.

The paper identifies spatial and compositional biomarkers in the tumor microenvironment of triple-negative breast cancer that predict clinical outcomes using imaging mass cytometry and deep learning.

This paper introduces SpaceMarkers, a method to infer molecular changes from cell-cell interactions in spatial transcriptomics data, applied to tumor-immune interactions in metastasis and immunotherapy.