Acute leukemias affect all age groups, show a rapid disease progression, and have a marked negative impact on normal blood formation. The prognosis for older patients is very poor, while most children and young adults affected survive. However, there are subgroups of the latter who show low survival rates due to e.g. treatment resistance and relapse. Moreover, not all patient groups can tolerate the high-intensity treatment protocols required for remission, which are also associated with several long-term complications. There is therefore an urgent need to develop new treatment strategies for patients with these diseases. T-cell lymphoblastic leukemia (T-ALL) is an aggressive subtype of acute leukemia that is caused by genetic and epigenetic alterations that perturb normal T-cell development. Recent whole-exome and RNA-seq analyses of large T-ALL cohorts have identified mutations and dysregulated expression of oncogenic transcription factors as the major drivers of T-ALL pathogenesis. Though, the mechanisms of activation for these oncogenic transcription factors are largely unknown. Here, we will use an integrated analysis of Hi-C, RNA-seq and CTCF ChIP–seq datasets to study if the 3D organization of the genome plays are role in their activation. The human genome is hierarchically organized by multi-scaled structural units, including compartments, topologically associated domains (TADs), and loops, which can be identified by Hi-C. These features, which have important implications for gene regulation, will be studied in primary leukemia and normal control samples with focus on transcription factor genes, using the resources provided by NAISS. Our study has the potential to uncover new mechanisms of activation for oncogenic drivers and may identify novel targets for therapy.