Yu-Hsuan Fu

The paper uses a state-transition model to study transcriptome dynamics in AML, finding delayed miRNA responses and linking the Dlk1-Dio3 locus to treatment-induced desynchronization.

Combining 177Lu-PSMA-617 radioligand therapy with PSCA-CAR T cells improves tumor control and survival in prostate cancer models by overcoming antigen heterogeneity and reshaping the immunosuppressive tumor microenvironment.

The paper shows that clinically relevant leukemia phenotypes emerge at the macrostate level from single cell data, revealing how disease states aggregate from noisy single cell transcriptomes.

This study develops a computational model of the AML bone marrow microenvironment and shows that combining TKIs with miR-126 inhibition can overcome treatment resistance by disrupting the protective vascular niche.

The paper uses transcriptome-based state-transition models to predict CML disease progression and treatment response using time-sequential blood samples from mice.