A Novel Platform to Test In Vivo Single Gene Dependencies in t(8,21) and t(15,17) AML Confirms Zeb2 as Leukemia Target

Simple SummaryMouse models are extensively used to study human diseases, including cancer. They are particularly useful to evaluate the role of specific genes in the tumorigenic process. The platform we present allows to effectively induce in vivo silencing of any potential candidate gene in two acute myeloid leukemia mouse models, with the scope of furthering the understanding of this gene's role in the biology of leukemia.The increased usage of high-throughput technologies in cancer research, including genetic and drug screens, generates large sets of candidate targets that need to be functionally validated for their roles in tumor development. Thus, reliable and robust in vivo model systems are needed to perform reverse genetic experiments. Ideally, these models should allow for a conditional silencing of the target and an unambiguous identification of engineered cancer cells. Here, we present a platform consisting of: (i) t(8;21) and t(15;17) driven acute myeloid leukemia (AML) transgenic mice with constitutive expression of green fluorescent protein (GFP) and inducible expression of Cre recombinase, and (ii) REX, a modified pSico lentiviral vector for inducible shRNA expression and red fluorescent protein (RFP) as a selection marker. In this system, leukemic cells from transgenic mice are transduced with REX, flow sorted, and transplanted into syngeneic hosts. Gene interference is induced in established tumors by tamoxifen treatment. Dual-color cell fluorescence guides the in vivo identification of shRNA interfered AML cells, monitoring engraftment and disease progression. We tested the platform by inducing knockdown of Zeb2, a gene upregulated by AML1-ETO and PML-RAR alpha oncogenes in pre-leukemic hematopoietic stem cell compartment, and observed a significant delay in leukemia onset. This proves the power and utility of the platform and confirms Zeb2 contribution to the pathogenesis of AML.