Tumour ischaemia by interferon-γ resembles physiological blood vessel regression (original) (raw)

Accession codes

Primary accessions

Gene Expression Omnibus

References

1. Blankenstein, T. The role of tumor stroma in the interaction between tumor and immune system. Curr. Opin. Immunol. 17, 180–186 (2005)
   Article CAS PubMed Google Scholar
2. Dighe, A. S., Richards, E., Old, L. J. & Schreiber, R. D. Enhanced in vivo growth and resistance to rejection of tumor cells expressing dominant negative IFNγ receptors. Immunity 1, 447–456 (1994)
   Article CAS PubMed Google Scholar
3. Braumüller, H. et al. T-helper-1-cell cytokines drive cancer into senescence. Nature 494, 361–365 (2013)
   Article PubMed ADS CAS Google Scholar
4. Zhang, B., Karrison, T., Rowley, D. A. & Schreiber, H. IFN-γ - and TNF-dependent bystander eradication of antigen-loss variants in established mouse cancers. J. Clin. Invest. 118, 1398–1404 (2008)
   Article CAS PubMed PubMed Central Google Scholar
5. Listopad, J. J. et al. Fas expression by tumor stroma is required for cancer eradication. Proc. Natl Acad. Sci. USA 110, 2276–2281 (2013)
   Article CAS PubMed ADS PubMed Central Google Scholar
6. Franco, C. A. et al. Dynamic endothelial cell rearrangements drive developmental vessel regression. PLoS Biol. 13, e1002125 (2015)
   Article PubMed PubMed Central CAS Google Scholar
7. Bodnar, R. J., Yates, C. C., Rodgers, M. E., Du, X. & Wells, A. IP-10 induces dissociation of newly formed blood vessels. J. Cell Sci. 122, 2064–2077 (2009)
   Article CAS PubMed PubMed Central Google Scholar
8. Ashkar, A. A., Di Santo, J. P. & Croy, B. A. Interferon γ contributes to initiation of uterine vascular modification, decidual integrity, and uterine natural killer cell maturation during normal murine pregnancy. J. Exp. Med. 192, 259–270 (2000)
   Article CAS PubMed PubMed Central Google Scholar
9. Schreiber, K., Rowley, D. A., Riethmüller, G. & Schreiber, H. Cancer immunotherapy and preclinical studies: why we are not wasting our time with animal experiments. Hematol. Oncol. Clin. North Am. 20, 567–584 (2006)
   Article PubMed Google Scholar
10. Corthay, A. et al. Primary antitumor immune response mediated by CD4+ T cells. Immunity 22, 371–383 (2005)
    Article CAS PubMed Google Scholar
11. Lu, Y. et al. Responsiveness of stromal fibroblasts to IFN-γ blocks tumor growth via angiostasis. J. Immunol. 183, 6413–6421 (2009)
    Article CAS PubMed Google Scholar
12. Qin, Z. & Blankenstein, T. CD4+ T cell-mediated tumor rejection involves inhibition of angiogenesis that is dependent on IFNγ receptor expression by nonhematopoietic cells. Immunity 12, 677–686 (2000)
    Article CAS PubMed Google Scholar
13. Qin, Z. et al. A critical requirement of interferon γ-mediated angiostasis for tumor rejection by CD8+ T cells. Cancer Res. 63, 4095–4100 (2003)
    CAS PubMed Google Scholar
14. Coughlin, C. M. et al. Tumor cell responses to IFNγ affect tumorigenicity and response to IL-12 therapy and antiangiogenesis. Immunity 9, 25–34 (1998)
    Article CAS PubMed Google Scholar
15. Luster, A. D., Unkeless, J. C. & Ravetch, J. V. γ-interferon transcriptionally regulates an early-response gene containing homology to platelet proteins. Nature 315, 672–676 (1985)
    Article CAS PubMed ADS Google Scholar
16. Sgadari, C. et al. Mig, the monokine induced by interferon-γ, promotes tumor necrosis in vivo. Blood 89, 2635–2643 (1997)
    Article CAS PubMed Google Scholar
17. Deng, J. et al. IFNγ-responsiveness of endothelial cells leads to efficient angiostasis in tumours involving down-regulation of Dll4. J. Pathol. 233, 170–182 (2014)
    Article CAS PubMed Google Scholar
18. Tellides, G. et al. Interferon-γ elicits arteriosclerosis in the absence of leukocytes. Nature 403, 207–211 (2000)
    Article CAS PubMed ADS Google Scholar
19. Briesemeister, D. et al. Tumor rejection by local interferon gamma induction in established tumors is associated with blood vessel destruction and necrosis. Int. J. Cancer 128, 371–378 (2011)
    Article CAS PubMed Google Scholar
20. Anders, K. et al. Oncogene-targeting T cells reject large tumors while oncogene inactivation selects escape variants in mouse models of cancer. Cancer Cell 20, 755–767 (2011)
    Article CAS PubMed PubMed Central Google Scholar
21. Mazzieri, R. et al. Targeting the ANG2/TIE2 axis inhibits tumor growth and metastasis by impairing angiogenesis and disabling rebounds of proangiogenic myeloid cells. Cancer Cell 19, 512–526 (2011)
    Article CAS PubMed Google Scholar
22. Schietinger, A. et al. Longitudinal confocal microscopy imaging of solid tumor destruction following adoptive T cell transfer. OncoImmunology 2, e26677 (2013)
    Article PubMed PubMed Central Google Scholar
23. Hock, H. et al. Mechanisms of rejection induced by tumor cell-targeted gene transfer of interleukin 2, interleukin 4, interleukin 7, tumor necrosis factor, or interferon γ. Proc. Natl Acad. Sci. USA 90, 2774–2778 (1993)
    Article CAS PubMed ADS PubMed Central Google Scholar
24. Augustin, H. G., Braun, K., Telemenakis, I., Modlich, U. & Kuhn, W. Ovarian angiogenesis. Phenotypic characterization of endothelial cells in a physiological model of blood vessel growth and regression. Am. J. Pathol. 147, 339–351 (1995)
    CAS PubMed PubMed Central Google Scholar
25. Modlich, U., Kaup, F. J. & Augustin, H. G. Cyclic angiogenesis and blood vessel regression in the ovary: blood vessel regression during luteolysis involves endothelial cell detachment and vessel occlusion. Lab. Invest. 74, 771–780 (1996)
    CAS PubMed Google Scholar
26. Guo, S. et al. IRF4 is a novel mediator for neuronal survival in ischaemic stroke. Cell Death Differ. 21, 888–903 (2014)
    Article CAS PubMed PubMed Central Google Scholar
27. Rothstein, J. L. & Schreiber, H. Synergy between tumor necrosis factor and bacterial products causes hemorrhagic necrosis and lethal shock in normal mice. Proc. Natl Acad. Sci. USA 85, 607–611 (1988)
    Article CAS PubMed ADS PubMed Central Google Scholar
28. Johansson, A., Hamzah, J., Payne, C. J. & Ganss, R. Tumor-targeted TNFα stabilizes tumor vessels and enhances active immunotherapy. Proc. Natl Acad. Sci. USA 109, 7841–7846 (2012)
    Article CAS PubMed ADS PubMed Central Google Scholar
29. Refaeli, Y., Van Parijs, L., Alexander, S. I. & Abbas, A. K. Interferon γ is required for activation-induced death of T lymphocytes. J. Exp. Med. 196, 999–1005 (2002)
    Article CAS PubMed PubMed Central Google Scholar
30. Hemmi, S. et al. Cloning of murine interferon gamma receptor cDNA: expression in human cells mediates high-affinity binding but is not sufficient to confer sensitivity to murine interferon gamma. Proc. Natl Acad. Sci. USA 86, 9901–9905 (1989)
    Article CAS PubMed ADS PubMed Central Google Scholar
31. Sakai, K., Mitani, K. & Miyazaki, J. Efficient regulation of gene expression by adenovirus vector-mediated delivery of the CRE recombinase. Biochem. Biophys. Res. Commun. 217, 393–401 (1995)
    Article CAS PubMed Google Scholar
32. Staveley-O’Carroll, K. et al. In vivo ligation of CD40 enhances priming against the endogenous tumor antigen and promotes CD8+ T cell effector function in SV40 T antigen transgenic mice. J. Immunol. 171, 697–707 (2003)
    Article PubMed Google Scholar
33. Bhowmick, N. A. et al. TGF-β signaling in fibroblasts modulates the oncogenic potential of adjacent epithelia. Science 303, 848–851 (2004)
    Article CAS PubMed ADS Google Scholar
34. Clausen, B. E., Burkhardt, C., Reith, W., Renkawitz, R. & Förster, I. Conditional gene targeting in macrophages and granulocytes using LysMcre mice. Transgenic Res. 8, 265–277 (1999)
    Article CAS PubMed Google Scholar
35. Claxton, S. et al. Efficient, inducible Cre-recombinase activation in vascular endothelium. Genesis 46, 74–80 (2008)
    Article CAS PubMed Google Scholar
36. Luche, H., Weber, O., Nageswara Rao, T., Blum, C. & Fehling, H. J. Faithful activation of an extra-bright red fluorescent protein in “knock-in” Cre-reporter mice ideally suited for lineage tracing studies. Eur. J. Immunol. 37, 43–53 (2007)
    Article CAS PubMed Google Scholar
37. Mittrücker, H. W. et al. Requirement for the transcription factor LSIRF/IRF4 for mature B and T lymphocyte function. Science 275, 540–543 (1997)
    Article PubMed Google Scholar
38. Willimsky, G. & Blankenstein, T. Sporadic immunogenic tumours avoid destruction by inducing T-cell tolerance. Nature 437, 141–146 (2005)
    Article CAS PubMed ADS Google Scholar
39. Textor, A. et al. Preventing tumor escape by targeting a post-proteasomal trimming independent epitope. J. Exp. Med. 213, 2333–2348 (2016)
    Article CAS PubMed PubMed Central Google Scholar
40. Li, L. P., Schlag, P. M. & Blankenstein, T. Transient expression of SV 40 large T antigen by Cre/LoxP-mediated site-specific deletion in primary human tumor cells. Hum. Gene Ther. 8, 1695–1700 (1997)
    Article CAS PubMed Google Scholar
41. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012)
    Article CAS PubMed Google Scholar

Download references

Acknowledgements

We thank R. Naumann, S. Jähne, T. Schüler, A. Sporbert, M. Richter, M. Schreiber, I. Gavvovidis, B. Purfürst and S. Fillatreau for support. This work was supported by the DFG through SFB-TR36 (to T.K., W.U. and T.B.), the Einstein Stiftung Berlin (to H.S. and T.B.) and the NIH (RO1-CA37156 and RO1-CA22677 to H.S.). M.Lo. was supported by Rhön-Klinikum-AG.

Author information

Author notes

1. Christian Idel
   Present address: Department for Otorhinolaryngology, University of Luebeck, 23562, Luebeck, Germany

Authors and Affiliations

1. Institute of Immunology, Charité Campus Buch, Berlin, 13125, Germany
   Thomas Kammertoens, Christian Friese, Dana Briesemeister, Michael Rothe, Matthias Leisegang, Ana Textor, Hans Schreiber & Thomas Blankenstein
2. Max Delbrück Center for Molecular Medicine, Berlin, 13125, Germany
   Thomas Kammertoens, Christian Friese, Dana Briesemeister, Michael Rothe, Anna Szymborska, Giannino Patone, Severine Kunz, Daniel Sommermeyer, Boris Engels, Matthias Leisegang, Ana Textor, Wolfgang Uckert, Norbert Hübner, Holger Gerhardt, Dieter Beule & Thomas Blankenstein
3. Department of Radiation and Cellular Oncology, Ludwig Center for Metastasis Research, The University of Chicago, Chicago, 60637, Illinois, USA
   Ainhoa Arina & Ralph Weichselbaum
4. Department of Pathology, The University of Chicago, Chicago, 60637, Illinois, USA
   Christian Idel & Hans Schreiber
5. Berlin Institute of Health, Berlin, 10117, Germany
   Andranik Ivanov, Matthias Leisegang, Wolfgang Uckert, Holger Gerhardt, Dieter Beule, Hans Schreiber & Thomas Blankenstein
6. Charité - Universitätsmedizin, Berlin, 10117, Germany
   Andranik Ivanov & Norbert Hübner
7. Institute of Immunology, University Clinics Ulm, Ulm, 89081, Germany
   Hans Joerg Fehling
8. Institute of Ophthalmology, University College London, London, EC1V 9EL, UK
   Marcus Fruttiger
9. Institute for Medical Microbiology, University of Marburg, Marburg, 35032, Germany
   Michael Lohoff
10. Beckman Research Institute at the Comprehensive Cancer Center City of Hope, Los Angeles, California, 91010-3000, USA
    Andreas Herrmann & Hua Yu
11. DZHK (German Center for Cardiovascular Research), partner site Berlin, Berlin, 13347, Germany
    Norbert Hübner & Holger Gerhardt

Authors

1. Thomas Kammertoens
   You can also search for this author inPubMed Google Scholar
2. Christian Friese
   You can also search for this author inPubMed Google Scholar
3. Ainhoa Arina
   You can also search for this author inPubMed Google Scholar
4. Christian Idel
   You can also search for this author inPubMed Google Scholar
5. Dana Briesemeister
   You can also search for this author inPubMed Google Scholar
6. Michael Rothe
   You can also search for this author inPubMed Google Scholar
7. Andranik Ivanov
   You can also search for this author inPubMed Google Scholar
8. Anna Szymborska
   You can also search for this author inPubMed Google Scholar
9. Giannino Patone
   You can also search for this author inPubMed Google Scholar
10. Severine Kunz
    You can also search for this author inPubMed Google Scholar
11. Daniel Sommermeyer
    You can also search for this author inPubMed Google Scholar
12. Boris Engels
    You can also search for this author inPubMed Google Scholar
13. Matthias Leisegang
    You can also search for this author inPubMed Google Scholar
14. Ana Textor
    You can also search for this author inPubMed Google Scholar
15. Hans Joerg Fehling
    You can also search for this author inPubMed Google Scholar
16. Marcus Fruttiger
    You can also search for this author inPubMed Google Scholar
17. Michael Lohoff
    You can also search for this author inPubMed Google Scholar
18. Andreas Herrmann
    You can also search for this author inPubMed Google Scholar
19. Hua Yu
    You can also search for this author inPubMed Google Scholar
20. Ralph Weichselbaum
    You can also search for this author inPubMed Google Scholar
21. Wolfgang Uckert
    You can also search for this author inPubMed Google Scholar
22. Norbert Hübner
    You can also search for this author inPubMed Google Scholar
23. Holger Gerhardt
    You can also search for this author inPubMed Google Scholar
24. Dieter Beule
    You can also search for this author inPubMed Google Scholar
25. Hans Schreiber
    You can also search for this author inPubMed Google Scholar
26. Thomas Blankenstein
    You can also search for this author inPubMed Google Scholar

Contributions

T.K. and C.F. planned and performed most experiments. A.A., C.I., R.W. and H.S. generated and analysed imaging experiments. D.Br. established MCA313 cells. M.R. contributed ATT experiments. M.Le. contributed T cell experiments and performed retroviral gene transfer. S.K. generated and analysed transmission electron microscopy data. A.T. established 16.113-999 cells. G.P. and N.H. performed gene expression analysis. A.I. and D.Be. performed bioinformatics analysis. A.S. and H.G. advised and contributed HUVEC-experiments. D.S., B.E. and W.U. generated constructs. A.H. and H.Y. performed two-photon and VE-cadherin microscopy. H.J.F., M.F. and M.Lo. provided mice. T.B. and T.K. conceived the project, analysed data and wrote the manuscript. All authors revised the manuscript.

Corresponding author

Correspondence toThomas Blankenstein.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks T. Curiel, M. De Palma and S. Turley for their contribution to the peer review of this work.

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

Extended data figures and tables

Extended Data Figure 1 Release of IFNγ in established tumours leads to necrosis, blood vessel reduction and tumour regression.

a–h, MCA313IFNγ-IND tumours (a–c), 16.113 tumours (d, h) and 16.113-999IFNγ-IND tumours (e–g). a, Without IFNγ induction, MCA313IFNγ-IND tumours grow progressively (1st panel). Dox-induced IFNγ expression in established MCA313IFNγ-IND tumours (2nd panel) leads to tumour regression in wild-type but not IFNγR− mice (3rd, 4th panel). Differences in tumour growth between ‘no dox’ and ‘dox’ groups in wild-type mice are statistically significant on days 19 (*), 23 (**) and 25 (***). IFNγ induction in wild-type mice at 642 ± 236 mm3 (the two crosses indicate mice that reached a humane endpoint and were taken out of the experiment) and in IFNγR− mice at 608 ± 130 mm3. No difference in tumour growth and IFNγ-induced tumour regression of MCA313IFNγ-IND tumours between Rag− and Rag-competent hosts (5th panel Rag−, n = 5; 6th panel wild type, n = 6). Dox administration at 1,304 ± 290 mm3 on day 15. b, c, MCA313IFNγ-IND tumours without and 120 h after dox. b, c, Macroscopic image (b; scale bars, 0.5 cm) and H&E staining (c) (1st row), N and dotted line indicate necrotic area (2nd row), immunohistology using anti-CD31 monoclonal antibody (scale bars, 100 μm). For H&E staining, three animals per group with 4 to 5 areas were compared and differences are statistically significant (***). d, T-cell-mediated rejection of 16.113 tumours. Mice (same as depicted in Fig. 1c) were subcutaneously injected with 106 16.113 cells. On day 57, 107 TCR transgenic T cells specific for SV40 large T antigen, epitope I (TCR-I), expressed by 16.113 tumour cells, were transferred when tumour size was 489 ± 253 mm3. Combined data from two experiments is shown (n = 16). e–g, Induction of IFNγ in established carcinomas leads to tumour regression and blood vessel reduction. e, Dox-dependent IFNγ expression by 16.113-999IFNγ-IND cells in vitro, analysed by ELISA (mean values from two experiments are shown). f, g, Dox-induced IFNγ expression in established 16.113-999IFNγ-IND tumours grown in Rag− mice leads to tumour regression (f) and blood vessel reduction (g). The relative number of tumour endothelial cells (CD31+CD146+) without and 120 h after IFNγ induction in tumours was determined from 107 tumour cells by flow cytometry. h, IFNγ released during T-cell-mediated rejection of 16.113 tumours contributes to blood vessel reduction. Tumours were established as in d, and either not treated, treated with 106 TCR-I-transduced T cells from either wild-type or IFNγ− mice. On day 5 after ATT, the relative number of tumour endothelial cells (CD31+CD146+) was determined as in g. *P < 0.05, **P < 0.01 and ***P < 0.001.The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Extended Data Figure 2 Mice with conditional IFNγR expression.

a, Schematic representation of transgenes combined to generate mice with conditional IFNγR expression. b, c, Functional IFNγR expression in PIGΔIFNγR fibroblasts upon Cre-mediated excision of the stop cassette. b, Immortalized tail fibroblasts from PIGΔIFNγR mice were transfected with pBabe-puro-Cre plasmid, selected for puromycin resistance and analysed for GFP and IFNγR (CD119) expression by flow cytometry. Wild-type fibroblasts served as control. One representative out of two experiments is shown. c, IFNγ induces MHC-I upregulation in Cre-transfected fibroblasts from PIGΔIFNγR mice. Flow cytometry of MHC-I expression by fibroblasts from PIGΔIFNγR mice with (right panel) or without Cre-transfection (middle panel) (same fibroblasts as shown in b) that were cultured without (dotted line) or with 1 ng ml−1 IFNγ for 48 h (black line). Fibroblasts from wild-type mice served as control (left panel). One representative out of two experiments is shown. d, e, Cre-mediated recombination induces GFP expression in tumour stroma cells of PIGCMV-Cre, shown by immunohistology. MCA313IFNγ-IND tumours from PIGCMV-Cre (d) and PIGΔIFNγR (e) mice. GFP signals were amplified by anti-GFP antibody and are shown in green, staining with antibodies as indicated in red, overlay in yellow and Hoechst staining in blue. Scale bars, 50 μm. The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Extended Data Figure 3 GFP (IFNγR) expression in myeloid cells or fibroblasts of MCA313IFNγ-IND tumours in indicated mice and IFNγ signalling in T cells fails to contribute to tumour endothelial cell reduction.

a, PIGLys-Cre mice; b, c, PIGFSP-Cre. a, c, Immunohistology. GFP signals were amplified by anti-GFP antibody and are shown in green, staining with antibodies as indicated in red, overlay in yellow and Hoechst staining in blue. Scale bars, 50 μm. b, Flow cytometry for GFP expression of primary tail fibroblasts from PIGΔIFNγR (n = 6) and PIGFSP-Cre (n = 5) mice after 7 days of culture (mean 25.5% ± s.d. 12.8%). d, Rag− (n = 6) or Rag−IFNγR− mice (n = 5) were reconstituted with 2 × 107 splenocytes from wild-type mice. Two weeks after T cell transfer, MCA313IFNγ-IND cells were injected and IFNγ was induced when tumours were established (846 ± 263 mm3). 5 days after IFNγ induction, endothelial cells from 107 tumour cells were analysed by flow cytometry. **P < 0.01. The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Extended Data Figure 4 Cre-mediated recombination in MCA313IFNγ-IND tumour endothelial cells of PDGFB-CreER-IRES-GFP × Rosa26-RFP mice and confounding effects of endogenous IFNγ.

a, Tumour sections of mice, treated with tamoxifen (upper left) or not (lower left), were stained with anti-CD31 antibodies (white). RFP expression (red) indicates tamoxifen-dependent recombination, GFP signals were amplified by anti-GFP antibody and are shown in green, indicating PDGFB promoter activity, overlay in yellow, Hoechst in blue. Panels to the right show single colours of the upper left panel. Scale bars, 50 μm. b, Flow cytometry of tumour-derived endothelial cells, gated on CD31+CD146+ cells, of tamoxifen-treated (right panel) or non-treated mice (left panel) reveals recombination (RFP+ cells). For the tamoxifen-treated group, one representative out of four experiments is shown (mean 75.4 ± s.d. 8.8% RFP+ cells). c, In PIGPDGFB-Cre mice treated with tamoxifen, GFP expression (reflecting both PDGFB-promoter-dependent Cre expression and excision of the stop cassette in PIGΔIFNγR mice) was detected in endothelial cells in MCA313IFNγ-IND tumours. c, GFP expression in endothelial cells of MCA313IFNγ-IND tumours of PIGPDGFB-Cre mice. Mice received tamoxifen starting 3 days before cancer cell injection. Scale bars, 50 μm. d, Tumour regression following dox application (dox was given at a size of 509 ± 119 mm3 ; n = 5 no dox, and n = 6 with dox). e, Necrosis is visible in tumours before and is increased 120 h after dox-mediated IFNγ induction. d, e, MCA313IFNγ-IND tumours grew slower than in wild-type mice even without IFNγ induction (d) and became necrotic (e), presumably because of low-level constitutive IFNγ present in the mice and primarily IFNγR-expressing endothelial cells being able to consume it. Scale bars, 0.5 cm. d, IFNγ induction in established MCA313IFNγ-IND tumours in PIGPDGFB-Cre mice induced tumour regression, and reduction of endothelial cells (f, g). f, Reduced blood vessel density in MCA313IFNγ-IND tumours of PIGPDGFB-Cre mice 120 h after dox-mediated IFNγ induction. Tamoxifen treatment and immunohistology as in c. Scale bars, 100 μm. g, Reduced numbers of CD31+CD146+ cells in MCA313IFNγ-IND tumours 120 h after dox application. Endothelial cells from 107 tumour cells were analysed by flow cytometry (n = 3 no dox, n = 4 with dox). The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Extended Data Figure 5 In PIGPDGFB-Cre-ΔIFNγ mice, IFNγR is expressed in MCA313IFNγ-IND tumour endothelial cells and wound healing is impaired.

a, GFP is expressed in MCA313IFNγ-IND tumour endothelial cells. Scale bars, 50 μm. b, CD119 (1st column) and GFP (2nd column) expression in tumour endothelial cells from PIGPDGFB-Cre-ΔIFNγ mice treated (1st row, green histograms) or not treated with tamoxifen (2nd row, dotted line), PDGFB-CreER-IRES-GFPΔIFNγR treated with tamoxifen (3rd row, blue histograms) and PIGΔIFNγR treated with tamoxifen (4th row, red histogram) confirms that only after tamoxifen application in PIGPDGFB-Cre-ΔIFNγ mice both GFP and CD119 are induced. c, As very few CD11b+ (7.5%) and NK1.1+ (4.2%) cells in the tumour stroma of PIGPDGFB-Cre-ΔIFNγ were GFP+ (Supplementary Table 1b), nitric oxide production by tumour-derived CD11b+ cells as read-out for IFNγ responsiveness was analysed. 4 × 105 purified CD11b+ cells of MCA313IFNγ-IND tumours from mice as indicated were exposed to 250 U ml−1 IFNγ for 24 h, supernatants were mixed with Griess reagent and absorbance measured at 540 nm (dotted line shows detection limit) mean ± s.d. d–f, Tumours progressing after prolonged IFNγ exposure are largely necrotic but still produce IFNγ. d, H&E staining of a tumour section (from mice depicted in Fig. 2i) after around 50 days of IFNγ exposure. One representative of four mice is shown. e, Tumour of a mouse without dox (small central necrosis, one representative of two mice). Necrotic areas are encircled (dotted line). Scale bars, 2 mm. f, Progressing tumours still produce IFNγ. Tumours were re-isolated after IFNγ induction from wild type (n = 1, day 116), PIGCMV-Cre (n = 3, day 92–116) and PIGPDGFB-Cre (n = 3, day 65–66). Re-isolated tumour cells were cultured in 500 ng ml−1 dox for 48 h. Supernatants were analysed by IFNγ ELISA, mean ± s.d. g, h, Impaired wound healing in PIGPDGFB-Cre-ΔIFNγ mice. In the indicated mice bearing MCA313IFNγ-IND tumours (approximately 50 mm3), a wound of 5 mm diameter was instilled. g, Wild type (n = 3), IFNγR− (n = 3) and mice with endothelial-specific IFNγR expression (n = 6) were dox-treated (circles) or left untreated (squares); wild-type (n = 3) and IFNγR− (n = 2) and mice with endothelial-specific IFNγR expression (n = 4). Wound healing was recorded. Differences in mice with endothelial-specific IFNγR became significant at day 6 (*) and were highly significant at day 18 (***). h, Representative pictures (wild type, day 14; IFNγR−, day 14; PIGPDGFB-Cre-ΔIFNγ, day 21). *P < 0.05, **P < 0.01 and ***P < 0.001. The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Extended Data Figure 6 Induction of IFNγ–GFP fusion protein induces regression of established J558LIFNγ–GFP-IND tumours and blood vessels.

a, 106 J558LIFNγ–GFP-IND cells were injected into Rag− mice that were untreated (left panel) or treated with dox (right panel) when tumours reached a size of 461 ± 230 mm3. The crosses indicate mice that reached a humane endpoint and were taken out of the experiment (n = 10). b, Window chamber imaging of a J558LIFNγ–GFP-IND tumour at low magnification. The same procedure as described in Fig. 3c. Two weeks established J558LIFNγ-GFP-IND tumour was imaged for 6 days. Blue, cancer cells; green, IFNγ–GFP fusion protein and right vascular network. One representative of three experiments is shown. c, d, Quantification of histological analysis for CD31 and cleaved caspase 3 (CC3) staining, respectively. Each dot represents one field of view analysed by ImageJ. e, Representative CD31 and CC3 staining before and 120 h after dox. f, Quantification of ERG+ nuclei from immunohistology. g, Representative ERG staining before and 120 h after dox. Scale bars, 100 μm. Three tumours with 4–6 fields of view were analysed. ***P < 0.001. The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Extended Data Figure 7 Induction of TNF–GFP fusion protein induces regression of established J558LTNF–GFP-IND tumours and bursting of blood vessels.

a, 106 J558LTNF–GFP-IND cells were injected into Rag− mice that were left untreated (left panel) or treated with dox (right panel) when tumours had a size of 611 ± 201 mm3. Tumours eventually relapsed owing to selection of TNF–GFP loss variants (data not shown) (n = 9 no dox; n = 10 with dox). b, Window chamber imaging of a J558LTNF–GFP-IND tumour at lower magnification. The same procedure as described in Fig. 3c. Two-week-established J558LTNF–GFP-IND tumour was imaged for 2 days. Blue, cancer cells; green, TNF–GFP fusion protein and right vascular network. One representative out of four experiments is shown. c, d, Quantification of histological analysis for CD31 and cleaved caspase 3 (CC3) staining, respectively. Each dot represents one field of view analysed by ImageJ. e, Representative CD31 and CC3 staining before and 120 h after dox. f, Quantification of ERG+ nuclei from immunohistology. g, Representative ERG staining without and 120 h after dox. Scale bars, 100 μm. Three tumours with 4–6 fields of view were analysed. **P < 0.01 and ***P < 0.001. The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Extended Data Figure 8 Erythrocyte extravasation after induction of TNF–GFP but not IFNγ–GFP.

a, J558LIFNγ-GFP-IND or J558LTNF–GFP-IND tumours were established for two weeks and mice were dox-treated for 48 h or left untreated. Then, tumour sections were stained with H&E. In the upper row light microscopy and in the lower row eosin fluorescence signals were captured. Shown are representative sections from tumours treated with dox for 48 h. Scale bars, 100 μm. b, Quantification of erythrocytes in high magnification fields (HMF) using the ImageJ program. Number of analysed HMF: no dox IFNγ–GFP, 69 HMF, three tumours; 48 h IFNγ–GFP, 97 HMF, four tumours; no dox TNF–GFP, 130 HMF, three tumours; 48 h TNF–GFP: 92 HMF, four tumours. Groups were compared by unpaired _t_-test. ***P < 0.001; ns, not significant. The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Extended Data Figure 9 Activated but not normal vessels regress upon IFNγ exposure and regression is accelerated in _Irf4_− mice; IFNγ derived from T cells induces similar changes in gene expression as IFNγ from tumours.

a, No changes in blood vessel density in spleen and kidney after IFNγ induction. Anti-CD31 staining of kidney and spleen sections after IFNγ induction in MCA313IFNγ-IND tumours grown in wild-type mice (n = 2). Scale bars, 50 μm. b, Results of gene expression analysis as number of IFNγ-induced genes (log2 fold change) in tumour endothelial cells of J558LIFNγ-GFP-IND tumours (n = 3) and kidney endothelial cells (n = 3). After IFNγ induction, there are more genes differentially regulated in kidney than in tumour endothelial cells. c, Venn diagram showing the overlap between significantly differentially expressed genes (adjusted P value < 0.05) in endothelial cells of J558LIFNγ–GFP-IND, MCA313IFNγ-IND tumours (dox-treated versus untreated) and 16.113 tumours after treatment with IFNγ− versus wild-type TCR-I T cells. d, Scatter plots of data from Venn diagram displaying changes of all genes presented (that is, genes significantly differentially expressed in any of three comparisons). Endothelial cells from all three tumour types revealed strong similarity in regulated genes (Pearson correlation coefficients are calculated using all 410 genes). The union of 410 genes that were significantly differentially regulated in any of the three comparisons showed a correlation of approximately 0.8 across all 3 groups. Colours of dots match the colours of the numbers in the Venn diagram. The overlapping 10 genes (red dots) are highly deregulated in all three comparisons. e, Representative images of untreated or IFNγ-treated (10 ng ml−1 for 96 h) HUVECs, stained with phalloidin (green) and antibody against VE-cadherin (red). f, IRF4 is induced in mouse endothelial (SEND.1) cells 48 h after IFNγ (5 U ml−1) treatment. Cells were stained with anti-IRF4 monoclonal antibody, using transcription factor staining kit, and analysed by flow cytometry (grey, isotype control; dotted line, without IFNγ; black line, IFNγ). g, Endothelial cells from 107 MCA313IFNγ-IND cells grown in heterozygous _Irf4_WT/− or _Irf4_−/− mice that were treated with dox or left untreated. CD31+CD146+ cells were analysed by flow cytometry. h–j, Immunohistology of MCA313IFNγ-IND tumours grown in heterozygous _Irf4_WT/− or _Irf4_− mice, either treated or not with dox and stained for ERG (h), CD31 and CC3 (i, j). *P < 0.05, **P < 0.01 and ***P < 0.001. The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Extended Data Figure 10 IFNγ-mediated blood vessel regression in MCA313IFNγ-IND tumours of PIGPDGFB-Cre-ΔIFNγ mice.

a–c, Non-apoptotic vessel regression in MCA313IFNγ-IND tumours. a, Representative staining for ERG and CC3. Scale bar, 100 μm. b, c, ERG+ nuclei (b) and ERG+CC3+ cells (c). d, f, Quantification of histological analysis for CD31 (d) and CC3 (f). e, Representative staining of CD31 and CC3. g, Quantification of histological analysis for collagen IV (Col4). h, Representative staining of CD31 and collagen IV staining at 48 h at higher magnification. i, Representative staining of CD31 and collagen IV. White arrows indicate collagen IV staining not associated with CD31 staining (h, i). Scale bars, 100 μm. j, Quantification of histological analysis for NG2. k, Representative staining of CD31 and NG2. Each dot shows one field of view analysed by ImageJ (d, f, g, j). l, Ratio of co-localization of NG2 and CD31. m, VE-cadherin, CD31 and DAPI staining without and 24 h after IFNγ induction. n, Electron microscopy analysis of blood vessels from MCA313IFNγ-IND tumours grown in PIGPDGFB-Cre-ΔIFNγ mice. Electron micrographs show non-occluded vessel (left) and occluded vessel (right). Lumen of capillaries (asterisks), erythrocytes (Er), endothelial cells (En) and macrophages (M) are labelled. Scale bar, 5 μm. o, Three tumours (for each two specimens) and in total 32 vessels without dox and 38 vessels after 48 h after dox were analysed by electron microscopy for vessel occlusion (bar diagram). **P < 0.01 and ***P < 0.001. The number of mice, replications and sample size for each experiment are shown in Supplementary Table 3.

Source data

Supplementary information

Supplementary Data

This file contains Supplementary Tables 1-3. Supplementary Table 1 shows the percentage of recombination in the respective transgenic mice as the percentage of GFP positive cells in different a) PBMC and b) tumour stroma subpopulations. Subpopulations of cells were identified with specific antibodies and analysed by flowcytometry. Supplementary Table 2 shows the differentially expressed genes in endothelial cells of J558LIFNγ-GFP-IND tumours, MCA313IFNγ-IND tumours (dox-treated vs. untreated) and of 16.113 tumours after treatment with IFNγdel versus WT T cells. Tumour endothelial cells were isolated by fluorescence-activated cell sorting. RNA was isolated and cDNA was synthesized. cDNA was hybridized to Affymetrix MOGENE 2.0 ST arrays. GeneChips were scanned, image data was normalized and quality controlled using Affymetrix software. Bioinformatics analysis of the gene expression data was performed. Shown are relative expression (log fold change) and adjusted p-values. Supplementary Table 3 shows the number of mice included in experiments, replications of experiments, centre value- and error bar information for each experiment. (PDF 2588 kb)

J558LIFNγ-GFP-IND tumours without induction of the IFNγ-GFP fusion protein

In vivo multiphoton microscopy of J558LIFNγ-GFP-IND tumours engrafted in Ragdel mice without induction of the IFNγ-GFP fusion protein. Blue signals show second harmonic generation and visualise the extracellular matrix. Green signals show the IFNγ-GFP fusion protein. Collected single plane images were assembled to a 3D stack in silico. (MP4 1218 kb)

J558LIFNγ-GFP-IND tumours 24 h after induction of the IFNγ-GFP fusion protein

In vivo multiphoton microscopy of J558LIFNγ-GFP-IND tumours engrafted in Ragdel mice treated for 24 h with dox, inducing the IFNγ-GFP fusion protein. Blue signals show second harmonic generation and visualise the extracellular matrix. Green signals show the IFNγ-GFP fusion protein. Collected single plane images were assembled to a 3D stack in silico. (MP4 1220 kb)

Ceasing blood flow inducing tumour ischemia with progressing vessel regression after induction of the IFNγ-GFP fusion protein in J558LIFNγ-GFP-IND tumours

Shown is longitudinal microscopy of the same area over time of J558LIFNγ-GFP-IND tumours growing behind glass window chambers in mice. For visualization of the tumour vasculature and blood flow, mice were injected with DiD-labelled red blood cells. (MP4 2629 kb)

Red blood cells extravasation and haemorrhagic tumour necrosis after induction of the TNF-GFP fusion protein in J558LIFNγ-GFP-IND tumours

Shown is longitudinal microscopy of the same area over time of J558LIFNγ-GFP-IND tumours growing behind glass window chambers in mice. For visualization of the tumour vasculature and blood flow, mice were injected with DiD-labelled red blood cells. (MP4 2084 kb)

HUVECS exposed to IFNγ

Representative images of F-actin dynamics in a monolayer of HUVECs mock-treated (left panel) or exposed to 10 ng/ml of IFNγ for 96 hours (right panel). (MP4 8878 kb)

PowerPoint slides

Source data

Rights and permissions

About this article

Cite this article

Kammertoens, T., Friese, C., Arina, A. et al. Tumour ischaemia by interferon-γ resembles physiological blood vessel regression.Nature 545, 98–102 (2017). https://doi.org/10.1038/nature22311

Download citation

• Received: 02 February 2016
• Accepted: 30 March 2017
• Published: 26 April 2017
• Issue Date: 04 May 2017
• DOI: https://doi.org/10.1038/nature22311