For decades, T-ALL models were based on retroviral overexpression of NOTCH1 in murine hematopoietic stem cells (HSCs). This induces aggressive T-ALL but does not reflect the genetic and clinical heterogeneity of the disease. Large-scale genomic analyses have mapped the detailed landscape of T-ALL driver events over recent years, but how these diverse oncogenic events interact in T-ALL pathogenesis and which vulnerabilities this creates remains incompletely explored. This is in part due to the lack of appropriate mouse models that recapitulate the complex disease biology and are suitable to identify and study potential therapeutic targets and interventions in a more realistic context.
We modeled the genetic heterogeneity of T-ALL through in vivo multiplexing of gain-of-function and loss-of-function oncogenic events known to drive the disease. We developed a novel mouse strain that expresses Cre-recombinase and an inducible Cas9 only in the thymus ( LSL.Cas9 x Lck-cre) along with a lentiviral vector system into which T-ALL specific oncogenes are cloned in antisense flanked by LOX66/71 sites. Gain-of-function events, such as the overexpression of transcriptional regulators ( Tlx1, Tal1, or Lmo2) and signal transducers ( NRAS G12D, PIK3CD E1021K) were induced in developing thymocytes by Cre-mediated inversion together CRISPR-Cas9 editing of recurrent T-ALL loss-of-function drivers. This combinatorial approach allowed to probe more than 2000 possible oncogenic mutational combinations in vivo.
Transplantation of HSCs from LSL.Cas9 x Lck-cre mice transduced with our vector system into sublethally irradiated mice led to T-ALL development with different morphology and disease phenotypes. Developing leukemia harbored reproducible phenotypes, covering very immature CD4-CD8-CD25+CD44+ T-ALL in the Tlx1_NRAS subgroup, in contrast to the classical cortical CD4+CD8+CD3- phenotype (Tlx1_PIK3CD subgroup), as well as mature single-positive CD4+CD3+ or CD8+CD3+ blasts (Tal1_Lmo2 subgroup). We identified Tlx1, Tal1, Lmo2, NRAS G12Dand PIK3CD E1021Kas the main driver of disease phenotype and gene expression profile, whereas the loss-of-function mutations contributed to and accelerated the onset of the disease. Tumor-derived cell lines could be easily established and kept their phenotypic characteristics and mutation patterns.
The resulting T-ALL tumors contained up to eight different disease-relevant genetic alterations, thus recapitulating the genetic complexity in humans and overcoming the long latency for spontaneous mutations in less complex mouse models. Among these, co-evolution of insertions and deletions in Notch1, Cdkn2a, Bcl11b, and Pten were among the most frequently observed mutations in definitive T-ALL, whereas others, e.g., in Dnm2, Phf6, Etv6, and Lef1, occurred more randomly.
While gene editing by CRISPR-Cas9 mostly resulted in frame-shift mutations in both alleles, Bcl11b exhibited a strong haploinsufficient phenotype with exactly one knock-out and one intact allele in each case examined. Following this observation, further suppression of Bcl11b by shRNAs in Bcl11b+/- cell lines derived from our tumor models demonstrated rapid induction of cell death, which was more intense in T-ALL cells compared to non-malignant thymocytes. In addition, re-analysis of CRISPR-based loss-of-function screens of human hematopoietic cell lines retrieved from the Cancer Dependency Map confirmed BCLL11B as a strong selective dependency in human T-ALL.
In summary, we model subgroup-specific T-ALL transformation through conditional and multiplexed in vivo gene editing and oncogene overexpression, thus creating a resource of novel mouse models that recapitulate the genetic and biological heterogeneity of the disease. Using our resource, we identified Bcl11b as a strong and selective context-specific dependency in T-ALL. Although Bcl11b is a transcription factor, our results could serve as an starting point for novel therapies that interfere with Bcl11b function, such as molecular glue degraders or protein interaction inhibitors.
Disclosures
Heuser:Amgen: Consultancy; BergenBio: Research Funding; Abbvie: Consultancy, Research Funding; Servier: Consultancy; Glycostem: Consultancy, Research Funding; PinotBio: Consultancy, Research Funding; Loxo Oncology: Research Funding; Agios: Research Funding; Janssen: Honoraria; Karyopharm: Research Funding; Astellas: Research Funding; Novartis: Honoraria; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Certara: Honoraria; LabDelbert: Consultancy; Pfizer: Consultancy, Honoraria; Sobi: Honoraria.
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