GENOMIC, CELLULAR AND DEVELOPMENTAL RECONSTRUCTION.. (INFANTLEUKEMIA)
GENOMIC, CELLULAR AND DEVELOPMENTAL RECONSTRUCTION OFINFANT MLL-AF4+ ACUTE LYMPHOBLASTIC LEUKEMIA
(INFANTLEUKEMIA)
End date: Jan 1, 2016
PROJECT
FINISHED
Infant cancer is very distinct to adult cancer and it is progressively seen as a developmental disease. An intriguing infant cancer is the t(4;11) acute lymphoblastic leukemia (ALL) characterized by the hallmark rearrangement MLL-AF4 (MA4), and associated with dismal prognosis. The 100% concordance in twins and its prenatal onset suggest an extremely rapid disease progression. Many key issues remain elusive: Is MA4 leukemogenic? Which are other relevant oncogenic drivers? Which is the nature of the cell transformed by MA4? Which is the leukemia-initiating cell (LIC)? Does this ALL follow a hierarchical or stochastic cancer model? How to explain therapy resistance and CNS involvement? To what extent do genetics vs epigenetics contribute this ALL?These questions remain a challenge due to: 1) the absence of prospective studies on diagnostic/remission-matched samples, 2) the lack of models which faithfully reproduce the disease and 3) a surprising genomic stability of this ALL.I hypothesize that a Multilayer-Omics to function approach in patient blasts and early human hematopoietic stem/progenitor cells (HSPC) is required to fully scrutinize the biology underlying this life-threatening leukemia. I will perform genome-wide studies on the mutational landscape, DNA and H3K79 methylation profiles, and transcriptome on a uniquely available, large cohort of diagnostic/remission-matched samples. Omics data integration will provide unprecedented information about oncogenic drivers which must be analyzed in ground-breaking functional assays using patient blasts and early HSPCs carrying a CRISPR/Cas9-mediated locus/allele-specific t(4;11). Serial xenografts combined with exome-seq in paired diagnostic samples and xenografts will identify the LIC and determine whether variegated genetics may underlie clonal functional heterogeneity. This project will provide a precise understanding and a disease model for MA4+ ALL, offering a platform for new treatment strategies.
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