The “3D-Leuko-TAD” project aims to improve treatments for acute leukemias (acute lymphoblastic and myeloid leukemia) by focusing on how changes in tridimensional structures impact the development of the disease. Acute leukemias are serious diseases and often difficult to cure, especially in cases of relapse. Recent research has shown that leukemia can be influenced from disruptions in the way DNA loop organized structures, called “Topologically Associating Domains (TADs)” work. These disruptions can increase or alter the activity of genes like FLT3, which could drive cancer growth.

The project team will collect samples from adult and pediatric patients and use advanced lab techniques, such as Micro-C, to analyze the 3D organization of DNA in leukemia cells. By focusing on the role of FLT3 and its surrounding regions, through in vitro and in vivo studies, researchers hope to understand why some patients respond to specific treatments, while others do not. Additionally, the project will use machine learning to analyze this complex data, to integrate multi-omic, epigenetic and 3D genome data, aiming to identify patterns that could predict disease progression and treatment outcomes.

One key goal is to develop personalized treatments based on each patient’s genomic profile. The project will thus also identify new biomarkers, biological indicators that help track the disease’s progress, which can lead to targeted, more effective therapies for acute leukemias, especially for those patients who have not benefited from current treatments.