Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Translation control of the immune checkpoint in cancer and its therapeutic targeting

Abstract

Cancer cells develop mechanisms to escape immunosurveillance, among which modulating the expression of immune suppressive messenger RNAs is most well-documented. However, how this is molecularly achieved remains largely unresolved. Here, we develop an in vivo mouse model of liver cancer to study oncogene cooperation in immunosurveillance. We show that MYC overexpression (MYCTg) synergizes with KRASG12D to induce an aggressive liver tumor leading to metastasis formation and reduced mouse survival compared with KRASG12D alone. Genome-wide ribosomal footprinting of MYCTg;KRASG12 tumors compared with KRASG12D revealed potential alterations in translation of mRNAs, including programmed-death-ligand 1 (PD-L1). Further analysis revealed that PD-L1 translation is repressed in KRASG12D tumors by functional, non-canonical upstream open reading frames in its 5′ untranslated region, which is bypassed in MYCTg;KRASG12D tumors to evade immune attack. We show that this mechanism of PD-L1 translational upregulation was effectively targeted by a potent, clinical compound that inhibits eIF4E phosphorylation, eFT508, which reverses the aggressive and metastatic characteristics of MYCTg;KRASG12D tumors. Together, these studies reveal how immune-checkpoint proteins are manipulated by distinct oncogenes at the level of mRNA translation, which can be exploited for new immunotherapies.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: MYC and KRAS cooperate to promote liver cancer with metastatic potential and induce marked alterations of immune populations compared with KRAS alone.
Fig. 2: A dichotomy in gene regulation between transcription versus translational control in KRASG12D versus MYCTg;KRASG12D tumors.
Fig. 3: PD-L1 expression is upregulated in MYCTg;KRASG12D cells through a bypass in uORF-mediated translational repression.
Fig. 4: The metastatic potential of MYCTg;KRASG12D tumors is dependent on PD-L1-mediated immune suppression.
Fig. 5: p-eIF4E inhibition by eFT508 reduces PD-L1 abundance and prevents liver cancer progression and metastasis in vivo.

Similar content being viewed by others

Data availability

The sequencing data of the manuscript can be accessed using the following accession number: GSE105147.

References

  1. Chen, D. S. & Mellman, I. Oncology meets immunology: the cancer-immunity cycle. Immunity 39, 1–10 (2013).

    Article  PubMed  Google Scholar 

  2. Casey, S. C. et al. MYC regulates the antitumor immune response through CD47 and PD-L1. Science 352, 227–231 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Marzec, M. et al. Oncogenic kinase NPM/ALK induces through STAT3 expression of immunosuppressive protein CD274 (PD-L1, B7-H1). Proc. Natl Acad. Sci. USA 105, 20852–20857 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Stewart, B. W. & Wild, C. World Cancer Report 2014 (International Agency for Research on Cancer WHO Press, 2014).

  5. Ally, A. et al. Comprehensive and integrative genomic characterization of hepatocellular carcinoma. Cell 169, 1327 (2017).

    Article  Google Scholar 

  6. Schlaeger, C. et al. Etiology-dependent molecular mechanisms in human hepatocarcinogenesis. Hepatology 47, 511–520 (2008).

    Article  CAS  PubMed  Google Scholar 

  7. Marquardt, J. U. et al. Sequential transcriptome analysis of human liver cancer indicates late stage acquisition of malignant traits. J. Hepatol. 60, 346–353 (2014).

    Article  CAS  PubMed  Google Scholar 

  8. Kaposi-Novak, P. et al. Central role of c-Myc during malignant conversion in human hepatocarcinogenesis. Cancer Res. 69, 2775–2782 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. O’Dell, M. R. et al. Kras(G12D) and p53 mutation cause primary intrahepatic cholangiocarcinoma. Cancer Res. 72, 1557–1567 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Saha, S. K. et al. Mutant IDH inhibits HNF-4alpha to block hepatocyte differentiation and promote biliary cancer. Nature 513, 110–114 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Grivennikov, S. I., Greten, F. R. & Karin, M. Immunity, inflammation, and cancer. Cell 140, 883–899 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Sato, E. et al. Intraepithelial CD8+tumor-infiltrating lymphocytes and a high CD8+/regulatory T cell ratio are associated with favorable prognosis in ovarian cancer. Proc. Natl Acad. Sci. USA 102, 18538–18543 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Gao, Q. et al. Intratumoral balance of regulatory and cytotoxic T cells is associated with prognosis of hepatocellular carcinoma after resection. J. Clin. Oncol. 25, 2586–2593 (2007).

    Article  PubMed  Google Scholar 

  14. Fu, J. L. et al. Increased regulatory T cells correlate with CD8 T-cell impairment and poor survival in hepatocellular carcinoma patients. Gastroenterology 132, 2328–2339 (2007).

    Article  PubMed  Google Scholar 

  15. Fridman, W. H., Pages, F., Sautes-Fridman, C. & Galon, J. The immune contexture in human tumours: impact on clinical outcome. Nat. Rev. Cancer 12, 298–306 (2012).

    Article  CAS  PubMed  Google Scholar 

  16. Tumeh, P. C. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568–571 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Mellman, I., Coukos, G. & Dranoff, G. Cancer immunotherapy comes of age. Nature 480, 480–489 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Joyce, J. A. & Fearon, D. T. T cell exclusion, immune privilege, and the tumor microenvironment. Science 348, 74–80 (2015).

    Article  CAS  PubMed  Google Scholar 

  19. Kortlever, R. M. et al. Myc cooperates with Ras by programming inflammation and immune suppression. Cell 171, 1301–1315 e1314 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. S. & Weissman, J. S. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324, 218–223 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Butte, M. J., Keir, M. E., Phamduy, T. B., Sharpe, A. H. & Freeman, G. J. Programmed death-1 ligand 1 interacts specifically with the B7-1 costimulatory molecule to inhibit T cell responses. Immunity 27, 111–122 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Herbst, R. S. et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 515, 563–567 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Gordon, S. R. et al. PD-1 expression by tumour-associated macrophages inhibits phagocytosis and tumour immunity. Nature 545, 495–499 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Shalapour, S. et al. Immunosuppressive plasma cells impede T-cell-dependent immunogenic chemotherapy. Nature 521, 94–U235 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Khan, A. R. et al. PD-L1hi B cells are critical regulators of humoral immunity. Nat. Commun. 6, 5997 (2015).

    Article  CAS  PubMed  Google Scholar 

  26. Lau, J. et al. Tumour and host cell PD-L1 is required to mediate suppression of anti-tumour immunity in mice. Nat. Commun. 8, 14572 (2017).

    Article  Google Scholar 

  27. Gollwitzer, E. S. et al. Lung microbiota promotes tolerance to allergens in neonates via PD-L1. Nat. Med. 20, 642–647 (2014).

    Article  CAS  PubMed  Google Scholar 

  28. Truitt, M. L. & Ruggero, D. New frontiers in translational control of the cancer genome. Nat. Rev. Cancer 17, 332 (2017).

    Article  CAS  PubMed  Google Scholar 

  29. Sendoel, A. et al. Translation from unconventional 5′ start sites drives tumour initiation. Nature 541, 494–499 (2017).

    Article  Google Scholar 

  30. Stern-Ginossar, N. et al. Decoding human cytomegalovirus. Science 338, 1088–1093 (2012).

    Article  CAS  PubMed  Google Scholar 

  31. Calkhoven, C. F., Muller, C. & Leutz, A. Translational control of C/EBP alpha and C/EBP beta isoform expression. Gene Dev. 14, 1920–1932 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Palam, L. R., Baird, T. D. & Wek, R. C. Phosphorylation of eIF2 facilitates ribosomal bypass of an inhibitory upstream ORF to enhance CHOP translation. J. Biol. Chem. 286, 10939–10949 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Starck, S. R. et al. Translation from the 5′ untranslated region shapes the integrated stress response.Science 351, 3867 (2016).

    Article  Google Scholar 

  34. Sekine, Y. et al. Stress responses. Mutations in a translation initiation factor identify the target of a memory-enhancing compound. Science 348, 1027–1030 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Sidrauski, C., McGeachy A. M. & Ingolia, N. T. & Walter, P. The small molecule ISRIB reverses the effects of eIF2alpha phosphorylation on translation and stress granule assembly. Elife 4, 05033 (2015).

  36. Furic, L. et al. eIF4E phosphorylation promotes tumorigenesis and is associated with prostate cancer progression. Proc. Natl Acad. Sci. USA 107, 14134–14139 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Herdy, B. et al. Translational control of the activation of transcription factor NF-kappaB and production of type I interferon by phosphorylation of the translation factor eIF4E. Nat. Immunol. 13, 543–550 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Ueda, T., Watanabe-Fukunaga, R., Fukuyama, H., Nagata, S. & Fukunaga, R. Mnk2 and Mnk1 are essential for constitutive and inducible phosphorylation of eukaryotic initiation factor 4E but not for cell growth or development. Mol. Cell. Biol. 24, 6539–6549 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Reich, S. H. et al. Structure-based design of pyridone-aminal eFT508 targeting dysregulated translation by selective mitogen-activated protein kinase interacting kinases 1 and 2 (MNK1/2) inhibition. J. Med. Chem. 26, 3516–3540 (2018).

    Article  Google Scholar 

  40. Pulko, V. et al. B7-H1 expressed by activated CD8 T cells is essential for their survival. J. Immunol. 187, 5606–5614 (2011).

    Article  CAS  PubMed  Google Scholar 

  41. Liu, X. et al. B7-H1 antibodies lose antitumor activity due to activation of p38 MAPK that leads to apoptosis of tumor-reactive CD8(+) T cells. Sci. Rep. 6, 36722 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Betts, M. R. et al. Sensitive and viable identification of antigen-specific CD8+T cells by a flow cytometric assay for degranulation. J. Immunol. Methods 281, 65–78 (2003).

    Article  CAS  PubMed  Google Scholar 

  43. Hart, L. S. et al. ER stress-mediated autophagy promotes Myc-dependent transformation and tumor growth. J. Clin. Invest. 122, 4621–4634 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Kataoka, K. et al. Aberrant PD-L1 expression through 3′-UTR disruption in multiple cancers. Nature 534, 402 (2016).

    Article  CAS  PubMed  Google Scholar 

  45. Cerezo, M. et al. Translational control of tumor immune escape via the eIF4F-STAT1-PD-L1 axis in melanoma. Nat. Med. 24, 1877–1886 (2018).

    Article  CAS  PubMed  Google Scholar 

  46. D’Cruz, C. M. et al. c-MYC induces mammary tumorigenesis by means of a preferred pathway involving spontaneous Kras2 mutations. Nat. Med. 7, 235–239 (2001).

    Article  PubMed  Google Scholar 

  47. Ying, H. Q. et al. Oncogenic kras maintains pancreatic tumors through regulation of anabolic glucose metabolism. Cell 149, 656–670 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Sharma, P., Hu-Lieskovan, S., Wargo, J. A. & Ribas, A. Primary, adaptive, and acquired resistance to cancer immunotherapy. Cell 168, 707–723 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Matsuda, T. & Cepko, C. L. Electroporation and RNA interference in the rodent retina in vivo and in vitro. Proc. Natl Acad. Sci. USA 101, 16–22 (2004).

    Article  CAS  PubMed  Google Scholar 

  50. Miyazaki, J. et al. Expression vector system based on the chicken beta-actin promoter directs efficient production of interleukin-5. Gene 79, 269–277 (1989).

    Article  CAS  PubMed  Google Scholar 

  51. Jackson, E. L. et al. Analysis of lung tumor initiation and progression using conditional expression of oncogenic K-ras. Gene Dev. 15, 3243–3248 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Rees, S. et al. Bicistronic vector for the creation of stable mammalian cell lines that predisposes all antibiotic-resistant cells to express recombinant protein. Biotechniques 20, 102–104, 106, 108–110 (1996).

  53. Okada, A., Lansford, R., Weimann, J. M., Fraser, S. E. & McConnell, S. E. Imaging cells in the developing nervous system with retrovirus expressing modified green fluorescent protein. Exp. Neurol. 156, 394–406 (1999).

    Article  CAS  PubMed  Google Scholar 

  54. Hsieh, A. C. et al. The translational landscape of mTOR signalling steers cancer initiation and metastasis. Nature 485, 55–61 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–U354 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Chen, Y., Lun, A. T. & Smyth, G. K. From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline. F1000Res. 5, 1438 (2016).

    PubMed  PubMed Central  Google Scholar 

  59. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Law, C. W., Chen, Y. S., Shi, W. & Smyth, G. K. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Robinson, M. D. & Oshlack, A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 11, R25 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    Article  CAS  PubMed  Google Scholar 

  63. Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Bindea, G. et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25, 1091–1093 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Szklarczyk, D. et al. STRINGv10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 43, D447–D452 (2015).

    Article  CAS  PubMed  Google Scholar 

  66. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Liu, F., Song, Y. & Liu, D. Hydrodynamics-based transfection in animals by systemic administration of plasmid DNA. Gene Ther. 6, 1258–1266 (1999).

    Article  CAS  PubMed  Google Scholar 

  68. Kozak, M. Primer extension analysis of eukaryotic ribosome-mRNA complexes. Nucleic Acids Res. 26, 4853–4859 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Ran, F. A. et al. Genome engineering using the CRISPR-Cas9 system. Nat. Protoc. 8, 2281–2308 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to thank members of the Ruggero laboratory for discussion and critical reading of the manuscript. We thank C. Her for his help with the mouse HCC cell line generation protocol, D. Wang for the help with hydrodynamic transfection, and K. Fujii and D. Simsek for advice and technique assistance. We thank B. Tiano for the contribution in developing and characterizing the MYC transgenic mice. This work was supported by the Damon Runyon Postdoctoral Fellowship (Y.X.), AACR-Incyte Corporation Fellowship In Basic Cancer Research (grant no. 17-40-46-JIN) (H.Y.J), Life Science Foundation Postdoctoral Fellowship (S.Z.), Department of Defense Physician training award (H.G.N), the Campini Foundation, The Leukemia and Lymphoma Foundation Career Development Grant and UCSF Department of Pediatrics K12 (grant no. 5K12HDO72222-05) (C.M.F.), American Cancer Society Postdoctoral Fellowship and Conquer Cancer Foundation Young Investigator Award (J.D.G), Pew Scholars Award (M.B.), NIH grant no. 1R01HD086634 (M.B.), NIH grants (nos. R01CA140456, R01CA154916, and R01CA184624) (D.R.). M.B. is a New York Stem Cell Foundation Robertson Investigator. D.R. is a Leukemia and Lymphoma Society Scholar.

Author information

Authors and Affiliations

Authors

Contributions

D.R. conceived and supervised the project. Y.X. and M.P. designed and performed most experiments with the help of the other authors. H.Y.J. contributed to the immune profiling analyses, luciferase reporter assays, hydrodynamic tail vein injection and flow cytometry analyses. C.M.F. performed the immune profiling. Y.W., E.D., and A.G. contributed to western blots, cloning, qPCR, CRISPR cell line generation, and intrahepatic HCC graft implantation. J.T.C. developed the MYC transgenic mice and helped C.R.S. with the ribosome profiling and RNA sequencing. L.S. helped with the ribosome-profiling sample preparation. S.A. helped with genome alignment. M.B. and Z.S. performed the bioinformatics analyses related to ribosome profiling and RNA-Seq. H.G.N. and L.X. performed immunofluorescence staining. H.G.N., S.E.U., and J.D.G. provided pathology support and provided human HCC primary samples. K.R.W., S.H.R., and S.T.W. developed and/or supported the development of eFT508. Y.X. and D.R. wrote the manuscript with contributions from M.B., H.Y.J., and C.M.F.

Corresponding author

Correspondence to Davide Ruggero.

Ethics declarations

Competing interests

C.R.S., S.H.R. and K.R.W. are employees and shareholders of eFFECTOR Therapeutics, Inc. S.T.W. is the President and CEO of eFFECTOR Therapeutics, Inc. D.R. is a shareholder of eFFECTOR Therapeutics, Inc., and a member of its scientific advisory board.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–15

Reporting Summary

Supplementary Table 1

The transcriptional and translational profiles of gene expression in wild-type (WT) and KRAS-G12D liver tumors

Supplementary Table 2

The transcriptional and translational profiles of gene expression in KRAS-G12D and MYC-Tg;KRAS-G12D liver tumors

Supplementary Table 3

Enriched gene ontology categories (biological processes) among 339 transcripts that are translationally induced comparing MYCTg;KRAS-G12D to KRAS-G12D

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, Y., Poggio, M., Jin, H.Y. et al. Translation control of the immune checkpoint in cancer and its therapeutic targeting. Nat Med 25, 301–311 (2019). https://doi.org/10.1038/s41591-018-0321-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41591-018-0321-2

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing