• A Corrigendum to this article was published on 14 December 2016


Macrophages play critical, but opposite, roles in acute and chronic inflammation and cancer1,2,3,4,5. In response to pathogens or injury, inflammatory macrophages express cytokines that stimulate cytotoxic T cells, whereas macrophages in neoplastic and parasitic diseases express anti-inflammatory cytokines that induce immune suppression and may promote resistance to T cell checkpoint inhibitors1,2,3,4,5,6,7. Here we show that macrophage PI 3-kinase γ controls a critical switch between immune stimulation and suppression during inflammation and cancer. PI3Kγ signalling through Akt and mTor inhibits NFκB activation while stimulating C/EBPβ activation, thereby inducing a transcriptional program that promotes immune suppression during inflammation and tumour growth. By contrast, selective inactivation of macrophage PI3Kγ stimulates and prolongs NFκB activation and inhibits C/EBPβ activation, thus promoting an immunostimulatory transcriptional program that restores CD8+ T cell activation and cytotoxicity. PI3Kγ synergizes with checkpoint inhibitor therapy to promote tumour regression and increased survival in mouse models of cancer. In addition, PI3Kγ-directed, anti-inflammatory gene expression can predict survival probability in cancer patients. Our work thus demonstrates that therapeutic targeting of intracellular signalling pathways that regulate the switch between macrophage polarization states can control immune suppression in cancer and other disorders.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. 1.

    & Macrophage plasticity and polarization: in vivo veritas. J. Clin. Invest. 122, 787–795 (2012)

  2. 2.

    & Myeloid cells in tumor inflammation. Vasc. Cell 4, 14 (2012)

  3. 3.

    , & Macrophage biology in development, homeostasis and disease. Nature 496, 445–455 (2013)

  4. 4.

    & Anti-inflammatory therapy in chronic disease: challenges and opportunities. Science 339, 166–172 (2013)

  5. 5.

    & Macrophages and therapeutic resistance in cancer. Cancer Cell 27, 462–472 (2015)

  6. 6.

    & The future of immune checkpoint therapy. Science 348, 56–61 (2015)

  7. 7.

    , & Immune checkpoint blockade: a common denominator approach to cancer therapy. Cancer Cell 27, 450–461 (2015)

  8. 8.

    The Cancer Genome Atlas mRNA expression data for head and neck squamous carcinoma was downloaded from the National Cancer Institute’s Genomic Data Commons Data Portal, The Cancer Genome Atlas: Head and Neck Squamous Cell Carcinoma, (accessed on 12/23/2015)

  9. 9.

    The Cancer Genome Atlas mRNA expression data for lung adenocarcinoma was downloaded from the National Cancer Institute’s Genomic Data Commons Data Portal, The Cancer Genome Atlas: Lung Adenocarcinoma Cell Carcinoma mRNA database, (accessed 04/14/2016). The National Cancer Institute’s (NCI’s) Genomic Data Commons (GDC) is a genomic and transcriptomic data sharing platform

  10. 10.

    , , , & PI3K/AKT signaling pathway and cancer: an updated review. Ann. Med. 46, 372–383 (2014)

  11. 11.

    , & PI3K signalling: the path to discovery and understanding. Nat. Rev. Mol. Cell Biol. 13, 195–203 (2012)

  12. 12.

    et al. Phosphoinositide-3 kinase gamma activity contributes to sepsis and organ damage by altering neutrophil recruitment. Am. J. Respir. Crit. Care Med. 182, 762–773 (2010)

  13. 13.

    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)

  14. 14.

    et al. Bruton tyrosine kinase-dependent immune cell cross-talk drives pancreas cancer. Cancer Discov. 6, 270–285 (2016)

  15. 15.

    et al. PI3-kinase γ promotes Rap1a-mediated activation of myeloid cell integrin α4β1, leading to tumor inflammation and growth. PLoS One 8, e60226 (2013)

  16. 16.

    et al. Macrophage PI3Kγ drives pancreatic ductal adenocarcinoma progression. Cancer Discov. 6, 870–885 (2016)

  17. 17.

    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)

  18. 18.

    & Inflammation meets cancer, with NF-κB as the matchmaker. Nat. Immunol. 12, 715–723 (2011)

  19. 19.

    The role of C/EBP isoforms in the control of inflammatory and native immunity functions. J. Biol. Chem. 273, 29279–29282 (1998)

  20. 20.

    , , & Induction of arginase I transcription by IL-4 requires a composite DNA response element for STAT6 and C/EBPβ. Gene 353, 98–106 (2005)

  21. 21.

    , , & In vitro and in vivo elimination of macrophage tumor cells using liposome-encapsulated dichloromethylene diphosphonate. Virchows Arch. B Cell Pathol. Incl. Mol. Pathol. 54, 241–245 (1988)

  22. 22.

    et al. CSF-1R inhibition alters macrophage polarization and blocks glioma progression. Nat. Med. 19, 1264–1272 (2013)

  23. 23.

    et al. Phosphoinositide-dependent kinase 1 provides negative feedback inhibition to Toll-like receptor-mediated NF-κB activation in macrophages. Mol. Cell. Biol. 30, 4354–4366 (2010)

  24. 24.

    et al. Akt1 and Akt2 protein kinases differentially contribute to macrophage polarization. Proc. Natl Acad. Sci. USA 109, 9517–9522 (2012)

  25. 25.

    et al. The TSC-mTOR pathway regulates macrophage polarization. Nat. Commun. 4, 2834 (2013)

  26. 26.

    et al. Myeloid PTEN deficiency protects livers from ischemia reperfusion injury by facilitating M2 macrophage differentiation. J. Immunol. 192, 5343–5353 (2014)

  27. 27.

    et al. SHIP represses the generation of alternatively activated macrophages. Immunity 23, 361–374 (2005)

  28. 28.

    et al. Suppression of microRNA activity amplifies IFN-γ-induced macrophage activation and promotes anti-tumour immunity. Nat. Cell Biol. 18, 790–802 (2016)

  29. 29.

    , , & Online survival analysis software to assess the prognostic value of biomarkers using transcriptomic data in non-small-cell lung cancer. PLoS One 8, e82241 (2013)

Download references


This work was supported by NIH grants R01CA126820 (J.A.V.), T32HL098062 (M.M.K.), T32CA009523 (S.G.) and T32CA121938 (S.G.), the CAPES Foundation and Ministry of Education of Brazil (C.F.) and by Ralph and Fernanda Whitworth and the Immunotherapy Foundation (J.A.V. and E.E.C.). The authors thank J. Lee and S. Schoenberger for HPV+MEER HNSCC and SSCVII cells.

Author information


  1. Moores Cancer Center, University of California, San Diego, La Jolla, California 92093, USA

    • Megan M. Kaneda
    • , Karen S. Messer
    • , Natacha Ralainirina
    • , Hongying Li
    • , Christopher J. Leem
    • , Sara Gorjestani
    • , Gyunghwi Woo
    • , Abraham V. Nguyen
    • , Camila C. Figueiredo
    • , Philippe Foubert
    • , Michael C. Schmid
    • , Ezra E. W. Cohen
    •  & Judith A. Varner
  2. Division of Biostatistics and Bioinformatics; Department of Family Medicine and Public Health University of California, San Diego, La Jolla, California 92093, USA

    • Karen S. Messer
    •  & Hongying Li
  3. Dep. Biologia Celular, UERJ, Rio de Janeiro, 20550-013, Brazil

    • Camila C. Figueiredo
  4. Infinity Pharmaceuticals, Cambridge, Massachusetts 02139, USA

    • Melissa Pink
    • , David G. Winkler
    • , Matthew Rausch
    • , Vito J. Palombella
    • , Jeffery Kutok
    •  & Karen McGovern
  5. Department of Pediatrics, University of California, San Diego, La Jolla, California 92093, USA

    • Kelly A. Frazer
  6. Institute for Genomic Medicine, University of California, San Diego, La Jolla, California 92093, USA

    • Kelly A. Frazer
  7. Department of Pharmacology, University of California, San Diego, La Jolla, California 92093, USA

    • Xuefeng Wu
    •  & Michael Karin
  8. Center for Computational Biology and Bioinformatics, Institute for Genomic Medicine, University of California, San Diego, La Jolla, California 92093, USA

    • Roman Sasik
  9. Department of Medicine, University of California, San Diego, La Jolla, California 92093, USA

    • Ezra E. W. Cohen
    •  & Judith A. Varner
  10. Department of Pathology, University of California, San Diego, La Jolla, California 92093, USA

    • Judith A. Varner


  1. Search for Megan M. Kaneda in:

  2. Search for Karen S. Messer in:

  3. Search for Natacha Ralainirina in:

  4. Search for Hongying Li in:

  5. Search for Christopher J. Leem in:

  6. Search for Sara Gorjestani in:

  7. Search for Gyunghwi Woo in:

  8. Search for Abraham V. Nguyen in:

  9. Search for Camila C. Figueiredo in:

  10. Search for Philippe Foubert in:

  11. Search for Michael C. Schmid in:

  12. Search for Melissa Pink in:

  13. Search for David G. Winkler in:

  14. Search for Matthew Rausch in:

  15. Search for Vito J. Palombella in:

  16. Search for Jeffery Kutok in:

  17. Search for Karen McGovern in:

  18. Search for Kelly A. Frazer in:

  19. Search for Xuefeng Wu in:

  20. Search for Michael Karin in:

  21. Search for Roman Sasik in:

  22. Search for Ezra E. W. Cohen in:

  23. Search for Judith A. Varner in:


TCGA analysis was performed by H.L. and K.S.M., RNA sequencing by K.A.F., M.M.K., S.G. and R.S., flow cytometry by M.M.K. and N.R., in vitro studies by M.M.K., N.R., S.G., G.W., C.C.F., A.V.N. and M.C.S., and animal studies by M.M.K., N.R., C.L. and P.F. M.P., V.J.P., J.K., K.M., M.R. and D.G.W. provided IPI-549 and carried out experiments for Fig.1c, Extended Data Fig. 8a–b. ML120B was contributed by X.W. and M.K. The project was directed by E.E.W.C., K.S.M. and J.A.V. The manuscript was written by J.A.V. and M.M.K.

Competing interests

M.P., V.J.P., J.K., K.M., M.R. and D.G.W. are former employees of Infinity Pharmaceuticals and J.A.V. received research support from Infinity Pharmaceuticals.

Corresponding author

Correspondence to Judith A. Varner.

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

Supplementary information

PDF files

  1. 1.

    Supplementary Data

    This file contains source data for all gels used in Figure 2 and Extended Data Figures 1 and 6.

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.