Expression of RORγt Marks a Pathogenic Regulatory T Cell Subset in Human Colon Cancer
Science Translational Medicine • 12 Dec 2012 • Vol 4, Issue 164 • p. 164ra159 • DOI: 10.1126/scitranslmed.3004566
A Treg Melting Pot
Some things are not what they seem. Like the allegorical wolf in sheep’s clothing, cell populations that may seem homogeneous may actually contain subsets with different functions. Indeed, such hidden subpopulations may result in contradictory findings in different systems. Blatner et al. now find a subset of regulatory T cells (Tregs) in human colon cancer that may explain disparate clinical outcomes between studies.
The authors found preferential expansion in human colon cancer of Tregs that can suppress T cells but are not anti-inflammatory like more classic Tregs. They then looked in a mouse model of hereditary polyposis and found that these cells, which express Foxp3 and RORγt, express the proinflammatory cytokine IL-17 and are directly associated with inflammation and disease progression. The balance between anti-inflammatory Tregs and these “pathogenic” proinflammatory Tregs may play a role in regulating cancer inflammation. Targeting these RORγt+ Tregs may influence disease outcome in colon cancer.
Abstract
The role of regulatory T cells (Tregs) in human colon cancer (CC) remains controversial: high densities of tumor-infiltrating Tregs can correlate with better or worse clinical outcomes depending on the study. In mouse models of cancer, Tregs have been reported to suppress inflammation and protect the host, suppress T cells and protect the tumor, or even have direct cancer-promoting attributes. These different effects may result from the presence of different Treg subsets. We report the preferential expansion of a Treg subset in human CC with potent T cell–suppressive, but compromised anti-inflammatory, properties; these cells are distinguished from Tregs present in healthy donors by their coexpression of Foxp3 and RORγt. Tregs with similar attributes were found to be expanded in mouse models of hereditary polyposis. Indeed, ablation of the RORγt gene in Foxp3+ cells in polyp-prone mice stabilized Treg anti-inflammatory functions, suppressed inflammation, improved polyp-specific immune surveillance, and severely attenuated polyposis. Ablation of interleukin-6 (IL-6), IL-23, IL-17, or tumor necrosis factor–α in polyp-prone mice reduced polyp number but not to the same extent as loss of RORγt. Surprisingly, loss of IL-17A had a dual effect: IL-17A–deficient mice had fewer polyps but continued to have RORγt+ Tregs and developed invasive cancer. Thus, we conclude that RORγt has a central role in determining the balance between protective and pathogenic Tregs in CC and that Treg subtype regulates inflammation, potency of immune surveillance, and severity of disease outcome.
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Supplementary Material
Summary
Materials and Methods
Fig. S1. Flow cytometry gating scheme for Treg fractions.
Fig. S2. Activation state of Treg fractions.
Fig. S3. Example of human RORγt flow cytometry.
Fig. S4. Example of human IL-17 and IL-10 flow cytometry.
Fig. S5. Purity of human Tregs after FACS sorting.
Fig. S6. Cancer stage–dependent expansion of RORγt+Foxp3+ Fr.II Tregs, but not TH17 cells, detected in the PB of CC patients.
Fig. S7. TH17 characteristics and activation state of Tregs.
Fig. S8. Additional invasive polyps.
Fig. S9. Purity of mouse Tregs after FACS sorting and analysis of Treg’s ability to suppress T cells.
Fig. S10. Cytokine and chemokine analysis of tissue lysates.
Fig. S11. Representative image of a developed ELISPOT assay.
Table S1. Patient demographics and tumor characteristics.
Table S2. Statistics for Fig. 1.
Table S3. Statistics for Fig. 2.
Table S4. Statistics for Fig. 3.
Table S5. Statistics for Fig. 4.
Table S6. Statistics for Fig. 6.
Table S7. Statistics for Fig. 7.
Table S8. Statistics for Fig. 8 and fig. S10.
Resources
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Information & Authors
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Published In
Science Translational Medicine
Volume 4 | Issue 164
December 2012
December 2012
Copyright
Copyright © 2012, American Association for the Advancement of Science.
Submission history
Received: 3 July 2012
Accepted: 26 October 2012
Acknowledgments
We thank S. Rosen for his critical comments and support and C. Benoist for his technical assistance and valuable expertise with gene expression analysis. Funding: Supported by the Northwestern University Interdepartmental ImmunoBiology Flow Cytometry Core Facility, The Eisenberg Foundation, Northwestern University Flow Cytometry Facility, and a Cancer Center Support Grant (National Cancer Institute CA060553); NIH grant 1R01CA160436-01, a Zell Family Award, and an anonymous foundation award of the Robert H. Lurie Comprehensive Cancer Center (to K.K.); NIH grants AI089954 and AI091962, a Pew Scholarship, and a Cancer Research Institute Investigator Award (to L.Z.); NIH grant K08AI080836-01 01 (to M.J.A.); and NIH T32 and American Society of Transplantation Basic Science Fellowship Award (to B.S.). Author contributions: N.R.B. designed and performed the experiments, analyzed the data, and wrote the paper. M.F.M. designed the experiments and provided patient samples with clinical data. D.S. performed all statistical analyses. K.L.D., J.D.P., S.H., B.P.S., and M.W.K. conducted the experiments. D.J.B., D.M.M., A.L.H., S.J.S., A.-M.B., A.S., R.K.S., B.S., M.J.A., M.O., L.Z., and Y.I. provided reagents and advice. A.B., P.B., and F.G. gave conceptual and technical advice. K.K. designed the experiments, analyzed the data, and wrote the paper. Competing interests: The authors declare that they have no competing interests. Data and materials availability: The data for this study have been deposited in the Gene Expression Omnibus database (GSE41229).
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