Recent clinical trials using immunotherapy have demonstrated its potential to control cancer by disinhibiting the immune system. Immune checkpoint blocking (ICB) antibodies against cytotoxic-T-lymphocyte-associated protein 4 or programmed cell death protein 1/programmed death-ligand 1 have displayed durable clinical responses in various cancers1. Although these new immunotherapies have had a notable effect on cancer treatment, multiple mechanisms of immune resistance exist in tumours. Among the key mechanisms, myeloid cells have a major role in limiting effective tumour immunity2,3,4. Growing evidence suggests that high infiltration of immune-suppressive myeloid cells correlates with poor prognosis and ICB resistance5,6. These observations suggest a need for a precision medicine approach in which the design of the immunotherapeutic combination is modified on the basis of the tumour immune landscape to overcome such resistance mechanisms. Here we employ a pre-clinical mouse model system and show that resistance to ICB is directly mediated by the suppressive activity of infiltrating myeloid cells in various tumours. Furthermore, selective pharmacologic targeting of the gamma isoform of phosphoinositide 3-kinase (PI3Kγ), highly expressed in myeloid cells, restores sensitivity to ICB. We demonstrate that targeting PI3Kγ with a selective inhibitor, currently being evaluated in a phase 1 clinical trial (NCT02637531), can reshape the tumour immune microenvironment and promote cytotoxic-T-cell-mediated tumour regression without targeting cancer cells directly. Our results introduce opportunities for new combination strategies using a selective small molecule PI3Kγ inhibitor, such as IPI-549, to overcome resistance to ICB in patients with high levels of suppressive myeloid cell infiltration in tumours.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. 1.

    , , & The future of cancer treatment: immunomodulation, CARs and combination immunotherapy. Nat. Rev. Clin. Oncol. 13, 273–290 (2016)

  2. 2.

    , & Neutralizing tumor-promoting chronic inflammation: a magic bullet? Science 339, 286–291 (2013)

  3. 3.

    , & Innate and adaptive immune cells in the tumor microenvironment. Nat. Immunol. 14, 1014–1022 (2013)

  4. 4.

    & Myeloid cells in the tumor microenvironment: modulation of tumor angiogenesis and tumor inflammation. J. Oncol. 2010, 201026 (2010)

  5. 5.

    , & Myeloid-derived suppressor cells in cancer: therapeutic, predictive, and prognostic implications. Semin. Oncol. 41, 174–184 (2014)

  6. 6.

    et al. Myeloid cells and related chronic inflammatory factors as novel predictive markers in melanoma treatment with Ipilimumab. Clin. Cancer Res. 21, 5453–5459 (2015)

  7. 7.

    , , & Cancer-associated myeloid regulatory cells. Front. Immunol. 7, 113 (2016)

  8. 8.

    et al. Disruption of CXCR2-mediated MDSC tumor trafficking enhances anti-PD1 efficacy. Sci. Transl. Med . 6, 237ra67 (2014)

  9. 9.

    et al. Frequencies of circulating MDSC correlate with clinical outcome of melanoma patients treated with ipilimumab. Cancer Immunol. Immunother. 63, 247–257 (2014)

  10. 10.

    et al. Immunological correlates of treatment and response in stage IV malignant melanoma patients treated with Ipilimumab. OncoImmunology 5, e1100788 (2015)

  11. 11.

    , , , & Targeting myeloid-derived suppressor cells with colony stimulating factor-1 receptor blockade can reverse immune resistance to immunotherapy in indoleamine 2,3-dioxygenase-expressing tumors. EBioMedicine 6, 50–58 (2016)

  12. 12.

    , , & Tumor-induced myeloid deviation: when myeloid-derived suppressor cells meet tumor-associated macrophages. J. Clin. Invest . 125, 3365–3376 (2015)

  13. 13.

    Mechanisms and functional significance of tumour-induced dendritic-cell defects. Nat. Rev. Immunol. 4, 941–952 (2004)

  14. 14.

    et al. Monocytic CCR2+ myeloid-derived suppressor cells promote immune escape by limiting activated CD8 T-cell infiltration into the tumor microenvironment. Cancer Res. 72, 876–886 (2012)

  15. 15.

    et al. PI3Kγ is a molecular switch that controls immune suppression. Nature (2016)

  16. 16.

    et al. Central role for G protein-coupled phosphoinositide 3-kinase γ in inflammation. Science 287, 1049–1053 (2000)

  17. 17.

    Roles of PLC-β2 and -β3 and PI3Kγ in chemoattractant-mediated signal transduction. Science 287, 1046–1049 (2000)

  18. 18.

    et al. Receptor tyrosine kinases and TLR/IL1Rs unexpectedly activate myeloid cell PI3kγ, a single convergent point promoting tumor inflammation and progression. Cancer Cell 19, 715–727 (2011)

  19. 19.

    et al. Discovery of a selective phosphoinositide-3-kinase (PI3K)-γ inhibitor (IPI-549) as an immuno-oncology clinical candidate. ACS Med. Chem. Lett . 7, 862–867 (2016)

  20. 20.

    et al. Tumor hypoxia does not drive differentiation of tumor-associated macrophages but rather fine-tunes the M2-like macrophage population. Cancer Res. 74, 24–30 (2014)

  21. 21.

    et al. Different tumor microenvironments contain functionally distinct subsets of macrophages derived from Ly6C(high) monocytes. Cancer Res. 70, 5728–5739 (2010)

  22. 22.

    et al. Combined Nivolumab and Ipilimumab or monotherapy in untreated melanoma. N. Engl. J. Med. 373, 23–34 (2015)

  23. 23.

    et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity 39, 782–795 (2013)

  24. 24.

    et al. Tumour regression and autoimmunity after reversal of a functionally tolerant state of self-reactive CD8+ T cells. J. Exp. Med. 198, 569–580 (2003)

  25. 25.

    et al. PI3K-δ and PI3K-γ inhibition by IPI-145 abrogates immune responses and suppresses activity in autoimmune and inflammatory disease models. Chem. Biol. 20, 1364–1374 (2013)

Download references


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

    • Jedd D. Wolchok
    •  & Taha Merghoub

    These authors jointly supervised this work.


  1. Memorial Sloan Kettering Cancer Center, Parker Institute for Cancer Immunotherapy and Swim Across America/Ludwig Collaborative Laboratory, New York, New York 10065, 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, Massachusetts 02139, 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, New York 10065, USA

    • Jedd D. Wolchok


  1. Search for Olivier De Henau in:

  2. Search for Matthew Rausch in:

  3. Search for David Winkler in:

  4. Search for Luis Felipe Campesato in:

  5. Search for Cailian Liu in:

  6. Search for Daniel Hirschhorn Cymerman in:

  7. Search for Sadna Budhu in:

  8. Search for Arnab Ghosh in:

  9. Search for Melissa Pink in:

  10. Search for Jeremy Tchaicha in:

  11. Search for Mark Douglas in:

  12. Search for Thomas Tibbitts in:

  13. Search for Sujata Sharma in:

  14. Search for Jennifer Proctor in:

  15. Search for Nicole Kosmider in:

  16. Search for Kerry White in:

  17. Search for Howard Stern in:

  18. Search for John Soglia in:

  19. Search for Julian Adams in:

  20. Search for Vito J. Palombella in:

  21. Search for Karen McGovern in:

  22. Search for Jeffery L. Kutok in:

  23. Search for Jedd D. Wolchok in:

  24. Search for Taha Merghoub in:


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.

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.

Corresponding authors

Correspondence to Jedd D. Wolchok or Taha Merghoub.

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

About this article

Publication history







By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.