Kimmo Porkka

This study identifies SRSF2 and U2AF1 mutations as biomarkers of sensitivity to ATR-CHK1 pathway inhibitors and RUNX1 mutations as a mechanism of resistance in MDS/AML.

This study identifies SPATS2L as a mediator of growth and survival in RUNX1-mutant blast-phase CML through stress granule formation, suggesting it as a therapeutic target.

The paper develops a machine learning model to identify patient-specific multi-targeting therapies using single-cell transcriptomic data for hematological cancers and solid tumors.

This study identifies two genome-wide significant susceptibility loci for acute myeloid leukemia through a meta-analysis of GWAS data.

This paper develops a computational-experimental approach to design patient-specific drug combinations for AML that are synergistic and minimally toxic.

This study uses deep learning to analyze bone marrow histopathology in MDS patients, linking morphological features to genetic and clinical outcomes.