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RSS FeedsIJMS, Vol. 20, Pages 6277: Optimized Xenograft Protocol for Chronic Lymphocytic Leukemia Results in High Engraftment Efficiency for All CLL Subgroups (International Journal of Molecular Sciences)

 
 

13 december 2019 05:02:34

 
IJMS, Vol. 20, Pages 6277: Optimized Xenograft Protocol for Chronic Lymphocytic Leukemia Results in High Engraftment Efficiency for All CLL Subgroups (International Journal of Molecular Sciences)
 


Preclinical drug development for human chronic lymphocytic leukemia (CLL) requires robust xenograft models recapitulating the entire spectrum of the disease, including all prognostic subgroups. Current CLL xenograft models are hampered by inefficient engraftment of good prognostic CLLs, overgrowth with co-transplanted T cells, and the need for allogeneic humanization or irradiation. Therefore, we aimed to establish an effective and reproducible xenograft protocol which allows engraftment of all CLL subtypes without the need of humanization or irradiation. Unmanipulated NOD.Cg-PrkdcscidIl2rgtm1Sug/JicTac (NOG) mice in contrast to C.Cg-Rag2tm1Fwa-/-Il2rgtm1Sug/JicTac (BRG) mice allowed engraftment of all tested CLL subgroups with 100% success rate, if CLL cells were fresh, injected simultaneously intra-peritoneally and intravenously, and co-transferred with low fractions of autologous T cells (2%–4%). CLL transplanted NOG mice (24 different patients) developed CLL pseudofollicles in the spleen, which increased over 4–6 weeks, and were then limited by the expanding autologous T cells. Ibrutinib treatment studies were performed to validate our model, and recapitulated treatment responses seen in patients. In conclusion, we developed an easy-to-use CLL xenograft protocol which allows reliable engraftment for all CLL subgroups without humanization or irradiation of mice. This protocol can be widely used to study CLL biology and to explore novel drug candidates.


 
243 viewsCategory: Biochemistry, Biophysics, Molecular Biology
 
IJMS, Vol. 20, Pages 6278: Combined De Novo Transcriptome and Metabolome Analysis of Common Bean Response to Fusarium oxysporum f. sp. phaseoli Infection (International Journal of Molecular Sciences)
IJMS, Vol. 20, Pages 6276: A Deep Learning Model for Cell Growth Inhibition IC50 Prediction and Its Application for Gastric Cancer Patients (International Journal of Molecular Sciences)
 
 
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