Manuel R. Ramírez

The paper develops an AI algorithm using UMAP to classify bone marrow cells in B-ALL patients, improving disease prognosis and therapy decisions by identifying key subpopulations.

This study identifies the pre-TCR as a target for immunotherapy in T-ALL, showing that anti-pre-TCR antibodies inhibit leukemia-initiating cell activity and tumor progression in xenograft models.

This paper develops and validates a dual-targeting CAR-T cell therapy for T-ALL that targets CCR9 and CD1a, showing improved efficacy and safety compared to single-targeting approaches.

CROCKETA automates multi-omic analysis of scRNA-seq and immune repertoire data, integrating quality control, clustering, and differential expression for human and mouse datasets.

This study shows that engineered CD4+ TIL secreting TCE can induce tumor regression in NSCLC PDX models by redirecting non-tumor dominant T cell clones.