Structural and functional consequences of the STAT5BN642H driver mutation

Hyper-activated STAT5B variants are high value oncology targets for pharmacologic intervention. STAT5BN642H, a frequently-occurring oncogenic driver mutation, promotes aggressive T-cell leukemia/lymphoma in patient carriers, although the molecular origins remain unclear. Herein, we emphasize the aggressive nature of STAT5BN642H in driving T-cell neoplasia upon hematopoietic expression in transgenic mice, revealing evidence of multiple T-cell subset organ infiltration. Notably, we demonstrate STAT5BN642H-driven transformation of γδ T-cells in in vivo syngeneic transplant models, comparable to STAT5BN642H patient γδ T-cell entities. Importantly, we present human STAT5B and STAT5BN642H crystal structures, which propose alternative mutation-mediated SH2 domain conformations. Our biophysical data suggests STAT5BN642H can adopt a hyper-activated and hyper-inactivated state with resistance to dephosphorylation. MD simulations support sustained interchain cross-domain interactions in STAT5BN642H, conferring kinetic stability to the mutant anti-parallel dimer. This study provides a molecular explanation for the STAT5BN642H activating potential, and insights into pre-clinical models for targeted intervention of hyper-activated STAT5B.


Statistics
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Life sciences study design
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Sample size
Experimental design and number of mice assessed were based on prior experience with similar models and provided sufficient statistical power to discern significant differences.
Data exclusions No data were excluded from analyses.

Replication
All experiments were performed independently at least twice (as indicated in figure legends), with the exception of the in vivo transplant experiment which was only performed once, as a proof-of-principle experiment, for ethical reasons adhering to the 3R principle. All data obtained were found to be reproducible.
Randomization Randomization was not applicable to this study, as no treatment groups were required and all samples/mice were treated equally in all experiments.

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Blinding was not possible for mice processing, due to disease severity.

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Materials
Mycoplasma contamination 32D and Ba/F3 cells tested negative for mycoplasma contamination during routine checks.
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Animals and other organisms
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Laboratory animals
Transgenic mice expressing either hSTAT5B or hSTAT5B N642H under the control of the Vav1 promoter were generated and bred on a C57BL/6N background (Charles River Laboratories), as previously described (

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The study did not involve wild animals.

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The study did not involved samples collected from the field.

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Flow Cytometry
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Sample preparation
For FACS of lymph nodes, single cell suspensions were made by mincing the tissue through a 70 μm cell strainer. Cells were stained for FACS analysis with primary antibodies for 30 minutes in the dark. Cells were washed 2x in cold PBS and samples were acquired. For organ infiltration analyses, whole body perfusion with phosphate-buffered saline (PBS) was performed on hSTAT5B N642H or WT mice, and organs were then collected and minced through a 70 μm cell strainer. Leukocytes were isolated using 40% and 78% Percoll gradients and were then stained for FACS analysis with primary antibodies for 30 minutes in the dark. Cells were washed 2x in cold PBS and samples were acquired. Counting beads were added before acquisition in order to quantify absolute cell numbers.

Instrument
All FACS analyses were performed on a FACSCanto II instrument (BD Biosciences).

Software
Acquisition of FACS data was performed using FACSDiva software (BD Biosciences). Further analyses were performed using FlowJo 10 software.
Cell population abundance For transplant experiments, purity of the sorted gamma delta T-cell populations was determined by re-analysing sorted cells by FACS using identical gating strategies, and purity was found to be >90%.

Gating strategy
All FACS gates were kept identical for comparisons between all samples within a defined group of analyses (e.g. for each organ analysed). The starting cell populations were gated on the lymphocyte population from the FSC/SSC plot. These cells were then gated on single cells by doublet discrimination using both FSC-A/FSC-H and SSC-A/SSC-H. Single cells were gated on live cells based on negativity of a live/dead stain. Live cells were gated on CD3+ staining, and were then plotted against TCRgd and TCRB to gate on the respective single positive populations. Both the TCRgd+ and TCRB+ cells were then plotted against CD4 and CD8 to gate on and quantify single positive or double negative populations. Gates were determined and set based on plots obtained from unstained negative control samples.
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