Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells (original) (raw)

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Acknowledgements

We would like to thank the Flow Cytometry and Integrated Genomics Operation Core Facilities at MSKCC. Swim Across America, Ludwig Institute for Cancer Research, Parker Institute for Cancer Immunotherapy, Center for Experimental Therapeutics at MSKCC (ETC), and the Breast Cancer Research Foundation supported this work. The work was also supported in part by the MSKCC Core Grant (P30 CA008748). O.D.H. was supported by J. Houtard foundation, Nuovo Soldati Foundation and Wallonie-Bruxelles International. We would also like to thank Y. Senbabaoglu for his help in bioinformatics data analysis, A. Bossert for his contribution as part of the GME program as well as J. Gladstone and K. Walsh for their contributions while working as co-op students in the laboratory.

Author information

Author notes

  1. Jedd D. Wolchok and Taha Merghoub: These authors jointly supervised this work.

Authors and Affiliations

  1. Memorial Sloan Kettering Cancer Center, Parker Institute for Cancer Immunotherapy and Swim Across America/Ludwig Collaborative Laboratory, New York, 10065, New York, USA
    Olivier De Henau, Luis Felipe Campesato, Cailian Liu, Daniel Hirschhorn Cymerman, Sadna Budhu, Arnab Ghosh, Jedd D. Wolchok & Taha Merghoub
  2. Infinity Pharmaceuticals, Inc., Cambridge, 02139, Massachusetts, USA
    Matthew Rausch, David Winkler, Melissa Pink, Jeremy Tchaicha, Mark Douglas, Thomas Tibbitts, Sujata Sharma, Jennifer Proctor, Nicole Kosmider, Kerry White, Howard Stern, John Soglia, Julian Adams, Vito J. Palombella, Karen McGovern & Jeffery L. Kutok
  3. Weill Cornell Medical and Graduate Schools, New York, 10065, New York, USA
    Jedd D. Wolchok

Authors

  1. Olivier De Henau
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  2. Matthew Rausch
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  3. David Winkler
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  4. Luis Felipe Campesato
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  5. Cailian Liu
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  6. Daniel Hirschhorn Cymerman
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  7. Sadna Budhu
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  8. Arnab Ghosh
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  9. Melissa Pink
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  10. Jeremy Tchaicha
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  11. Mark Douglas
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  12. Thomas Tibbitts
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  13. Sujata Sharma
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  14. Jennifer Proctor
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  15. Nicole Kosmider
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  16. Kerry White
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  17. Howard Stern
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  18. John Soglia
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  19. Julian Adams
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  20. Vito J. Palombella
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  21. Karen McGovern
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  22. Jeffery L. Kutok
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  23. Jedd D. Wolchok
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  24. Taha Merghoub
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Contributions

O.D.H., T.M., J.D.W., K.M., J.L.K, V.J.P. and J.A. developed the concepts and discussed experiments. O.D.H., T.M., J.D.W., K.M. and J.L.K. wrote the manuscript. O.D.H., M.R., D.W., L.F.C., D.H.C., S.B., A.G., M.P., J.P. and N.K. performed and analysed animal model experiments, flow cytometry experiments and functional assays. C.L. provided technical assistance; S.S. and K.W. performed assays in human samples. M.D., T.T. and H.S. performed transcriptomic analysis. J.T. and J.S. performed pharmacodynamics and pharmacokinetics studies.

Corresponding authors

Correspondence toJedd D. Wolchok or Taha Merghoub.

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Competing interests

All authors with affiliation to Infinity Pharmaceuticals, Inc. were employees and shareholders at Infinity Pharmaceuticals, Inc. at the time of the study. All other authors have no competing interests.

Additional information

Reviewer Information Nature thanks F. Balkwill, M. De Palma and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Effect of suppressive myeloid TILs in response to checkpoint blockade.

a, Individual tumour growth of subcutaneous (4T1) or intradermal (B16, B16-GMCSF) implants in anti-PD-1-, anti-CTLA4- or control-treated mice (n = 10). b, In vitro suppressive activity of tumour-infiltrating CD11b+ cells purified from spleen of 4T1, B16, B16-GMCSF tumour-bearing mice. Representative histograms of CD8+ T cell proliferation at corresponding CD11b+ to CD8+ T cell ratio (left panel) and quantification of CD8+ T cell proliferation (right panel) (n = 3), mean ± s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 (non-parametric Mann–Whitney _U_-test).

Extended Data Figure 2 Effect of selective PI3Kγ inhibition on tumour growth and myeloid TILs.

a, Binding affinities (_K_d) and cellular IC50 inhibition of pAKT by IPI-549 for class I PI3K isoforms (left table). Percentage of inhibition of expression on bone-marrow-derived macrophages polarized with M-CSF and IL-4, (right panel). b, Percentage of tumour growth inhibition in LLC, MC38, 4T1, CT26, B16-GMCSF tumour-bearing mice treated with IPI-549 (table). c, Quantification of CD11b, CD206, NOS2 and PD-L1 expression in CD11b+ tumour-infiltrating leukocytes from IPI-549- versus vehicle-treated CT26 tumour-bearing mice. d, RNA-seq of co-stimulatory and checkpoint molecules on whole tumours from CT26 tumour-bearing mice treated for 6 or 9 days with IPI-549 compared to vehicle. e, Mean tumour volume of subcutaneous LLC-Brei implants in IPI-549- versus vehicle-treated mice without or after CD11b+ cell depletion. Data represent analysis of 5–10 mice per group, mean ± s.e.m. *P < 0.05, ***P < 0.001 (non-parametric Mann–Whitney _U_-test).

Extended Data Figure 3 Effect of selective PI3Kγ inhibition on subsets of CD11b myeloid cells.

a, Representative flow cytometry analysis and quantification of Ly6C, MHC class II expression in CD11b+Ly6G− cells infiltrating 4T1 tumours. b, mRNA expression of selected M1 and M2 markers in sorted Ly6ClowMHCIIlow (TAM-M2) compared to Ly6ClowMHCIIhigh (TAM-M1) population from 4T1 tumour, data were relative to GAPDH expression and normalized versus the mean of TAM-M1 population. Mean ± s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 (non-parametric Mann–Whitney _U_-test).

Extended Data Figure 4 Effect of selective PI3Kγ inhibition on suppressive PBMC derived human myeloid cells.

a, Inhibition of CXCL-12 activation of PI3Kγ in monocytes as measured by pAKT (S473) in human whole blood. b, Representative histograms and quantification of human CD8+ T cell proliferation after 72 h of co-culture with or without autologous myeloid-derived suppressor cells generated from the T-cell-depleted PBMCs ± IPI-549.

Extended Data Figure 5 Effect of selective PI3Kγ inhibition on function of tumour specific T cell responses.

a, Quantification of KI67, and CTLA4 expression in CD8+ T cells in TILs of 4T1 or B16-GMCSF tumours at IPI-549 compared to vehicle treatment days 7 and 14. b, Mean tumour volume of subcutaneous 4T1 tumour in IPI-549- versus vehicle-treated BALB/c NU/NU mice (n = 10). c, Mean tumour volume of subcutaneous CT-26 tumour in IPI-549- versus vehicle-treated BALB/c mice with or without CD8+ T cell depletion by anti-CD8 antibody (n = 10). d, Quantification and representative pictures of CT26 tumour-specific immune responses in PBMCs from CT26 tumour-bearing mice treated with IPI-549 in comparison to vehicle by ELISPOT. PBMCs were collected from tumour-bearing animals after 10 days of vehicle or IPI-549 treatment and restimulated overnight with irradiated CT26 or 4T1 stimulator cells.

Extended Data Figure 6 Effect of selective PI3Kγ inhibition on the differentiation of T cells in tumours.

a, Representative flow cytometry analysis and quantification of CD62L and CD44 expression in CD8+ and CD4+ T cell infiltrates in tumour, lymph node (LN) and spleen of 4T1 tumour-bearing mice treated with IPI-549 compared to vehicle. Data represent analyses of five mice per group, mean ± s.e.m. NS, not significant (non-parametric Mann–Whitney _U_-test).

Extended Data Figure 7 Effect of combination of a selective PI3Kγ inhibitor with checkpoint blockade on various tumours.

a, Survival to 2,000 mm3 tumour volume of LLC Brei tumour in IPI-549- or vehicle-treated mice in combination with or without anti-CTLA4 (vehicle and IPI-549 groups, n = 14; anti-CTLA4, n = 13; IPI-549 and anti-CTLA4 combination, n = 10). b, Mean tumour volume of CT26 tumour in IPI-549- or vehicle-treated mice in combination with or without anti-PD-L1 (n = 15 for all groups except vehicle, n = 13).

Extended Data Figure 8 Effect of combination of a selective PI3Kγ inhibitor with checkpoint blockade on TILs.

a, Mean tumour volume of subcutaneous 4T1 tumour-bearing mice treated with IPI-549, vehicle or anti-PD-1 in combination with IPI-549 or vehicle (n = 10). b, Representative flow cytometry analysis of CD206 and MHCII labelling in CD11b+ F4/80+ cell populations in the different treatment groups of 4T1 tumour-bearing mice. c, Quantification of CD11b+F4/80+, M1/M2 ratio, CD8+/Treg in TILs and granzyme B expression in CD8+ T cells from 4T1 tumours in the different treatment groups. d, Quantification of CD11b+F4/80+, M1/M2 ratio, CD8+/Treg in TILs and granzyme B expression in CD8+ T cells from B16-GMCSF tumours in the different treatment groups, mean ± s.e.m. *P < 0.05, **P < 0.01 (non-parametric Mann–Whitney _U_-test).

Extended Data Figure 9 Effect of combination of a selective PI3Kγ inhibitor with checkpoint blockade on acquisition of anti-tumour memory.

a, Tumour re-challenge at 100 days (from first tumour implant) following primary tumour complete response in B16-GMCSF tumour-bearing mice treated with vehicle (blue) or IPI-549 (red) in combination with both anti-PD1 and anti-CTLA4. b, CT26 tumour-bearing mice with complete responses in the anti-PD-1 treatment group and the IPI-549 plus anti-PD-1 combination treatment group were re-challenged with CT26 tumour implant. Additional mice with complete responses from the IPI-549 plus anti-PD-1 combination were implanted with 4T1 tumours. There was a low or no tumour take with CT26 re-challenge, while all 4T1 tumours grew, indicating specific anti-tumour memory.

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De Henau, O., Rausch, M., Winkler, D. et al. Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells.Nature 539, 443–447 (2016). https://doi.org/10.1038/nature20554

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