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Targeting VLA4 integrin and CXCR2 mobilizes serially repopulating hematopoietic stem cells
Darja Karpova, … , Daniel C. Link, John F. DiPersio
Darja Karpova, … , Daniel C. Link, John F. DiPersio
Published May 14, 2019
Citation Information: J Clin Invest. 2019;129(7):2745-2759. https://doi.org/10.1172/JCI124738.
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Research Article

Targeting VLA4 integrin and CXCR2 mobilizes serially repopulating hematopoietic stem cells

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Abstract

Mobilized peripheral blood has become the primary source of hematopoietic stem and progenitor cells (HSPCs) for stem cell transplantation, with a 5-day course of granulocyte colony-stimulating factor (G-CSF) as the most common regimen used for HSPC mobilization. The CXCR4 inhibitor plerixafor is a more rapid mobilizer, yet not potent enough when used as a single agent, thus emphasizing the need for faster acting agents with more predictable mobilization responses and fewer side effects. We sought to improve hematopoietic stem cell transplantation by developing a new mobilization strategy in mice through combined targeting of the chemokine receptor CXCR2 and the very late antigen 4 (VLA4) integrin. Rapid and synergistic mobilization of HSPCs along with an enhanced recruitment of true HSCs was achieved when a CXCR2 agonist was coadministered in conjunction with a VLA4 inhibitor. Mechanistic studies revealed involvement of CXCR2 expressed on BM stroma in addition to stimulation of the receptor on granulocytes in the regulation of HSPC localization and egress. Given the rapid kinetics and potency of HSPC mobilization achieved by the VLA4 inhibitor and CXCR2 agonist combination in mice compared with currently approved HSPC mobilization methods, the combination represents an exciting potential strategy for clinical development in the future.

Authors

Darja Karpova, Michael P. Rettig, Julie Ritchey, Daniel Cancilla, Stephanie Christ, Leah Gehrs, Ezhilarasi Chendamarai, Moses O. Evbuomwan, Matthew Holt, Jingzhu Zhang, Grazia Abou-Ezzi, Hamza Celik, Eliza Wiercinska, Wei Yang, Feng Gao, Linda G. Eissenberg, Richard F. Heier, Stacy D. Arnett, Marvin J. Meyers, Michael J. Prinsen, David W. Griggs, Andreas Trumpp, Peter G. Ruminski, Dwight M. Morrow, Halvard B. Bonig, Daniel C. Link, John F. DiPersio

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Figure 1

Targeting VLA4 and CXCR2 to mobilize HSPCs.

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Targeting VLA4 and CXCR2 to mobilize HSPCs.
(A–B) DBA2/J mice were treat...
(A–B) DBA2/J mice were treated with the VLA4 inhibitor firategrast (100 mg/kg, i.v.), the CXCR2 ligand tGro-β (2.5 mg/kg, s.c.) or both agents immediately after each other. Blood was analyzed for WBCs (A) and CFU-Cs (B). Data are mean ± SEM, n = 5. ***P < 0.001, **P < 0.01, compared with firategrast alone/compared with tGro-β alone. (C) Molecular structures. (D) G2-ALL cells were treated in duplicate with the VLA4 inhibitors shown in C. Percent inhibition of VCAM1 binding as compared with untreated samples. Data are mean ± SEM of a single experiment representative of 3 experiments. (E) DBA2/J mice were injected with tGro-β (2.5 mg/kg, s.c.), a VLA4 antagonist (3 mg/kg, i.v., for BIO5192, CWHM-823, and -842; 100 mg/kg, i.v., for firategrast), or their combination. Controls received vehicle only. Numbers of circulating CFU-Cs and LSK cells were analyzed 0.5 hours after the injection(s). Data are mean ± SEM, n = 8–10. ***P < 0.001, **P < 0.01, *P < 0.01, compared with tGro-β alone/VLA4 antagonist alone. (F) HSPC mobilization in CXCR2-KO mice using the CXCR2 ligands CXCL1, CXCL2 (tGro-β), and CXCL8 and the VLA4 antagonist CWHM-823 as well as their combinations was compared with that in WT BALB/cJ. Blood CFU-C numbers were analyzed at baseline, 15 minutes after injection of CXCR2 ligands (s.c., 1 mg/kg CXCL1 and CXCL8, 2 mg/kg tGro-β), 1 hour after injection of CWHM-823 (s.c., 3 mg/kg), and 30 minutes after the combined treatment (s.c. injection of each ligand together with CWHM-823 at same doses as single treatments). Data are mean ± SEM, n = 4–26 in mobilized groups, n = 51–78 in baseline groups. ***P < 0.001, compared with CXCR2 agonist alone/compared with CWHM-823 alone. Statistical comparisons were made using linear mixed models in A and B and ANOVA in all others, followed by step-down Bonferroni’s adjustment for multiple comparisons.

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