The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Combination Therapy with Anti–CTLA-4 and Anti–PD-1 Leads to Distinct Immunologic Changes In Vivo
Open accessAbstract
Combination therapy concurrently targeting PD-1 and CTLA-4 immune checkpoints leads to remarkable antitumor effects. Although both PD-1 and CTLA-4 dampen the T cell activation, the in vivo effects of these drugs in humans remain to be clearly defined. To better understand biologic effects of therapy, we analyzed blood/tumor tissue from 45 patients undergoing single or combination immune checkpoint blockade. We show that blockade of CTLA-4, PD-1, or combination of the two leads to distinct genomic and functional signatures in vivo in purified human T cells and monocytes. Therapy-induced changes are more prominent in T cells than in monocytes and involve largely nonoverlapping changes in coding genes, including alternatively spliced transcripts and noncoding RNAs. Pathway analysis revealed that CTLA-4 blockade induces a proliferative signature predominantly in a subset of transitional memory T cells, whereas PD-1 blockade instead leads to changes in genes implicated in cytolysis and NK cell function. Combination blockade leads to nonoverlapping changes in gene expression, including proliferation-associated and chemokine genes. These therapies also have differential effects on plasma levels of CXCL10, soluble IL-2R, and IL-1α. Importantly, PD-1 receptor occupancy following anti–PD-1 therapy may be incomplete in the tumor T cells even in the setting of complete receptor occupancy in circulating T cells. These data demonstrate that, despite shared property of checkpoint blockade, Abs against PD-1, CTLA-4 alone, or in combination have distinct immunologic effects in vivo. Improved understanding of pharmacodynamic effects of these agents in patients will support rational development of immune-based combinations against cancer.
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Citations
Cites
Improved Survival with Ipilimumab in Patients with Metastatic Melanoma
Hodi, F. S., O'Day, S. J., McDermott, D. F., Weber, R. W., Sosman, J. A., Haanen, J. B., Gonzalez, R., Robert, C., Schadendorf, D., Hassel, J. C., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1003466 · Cited by 15,155
Self-citationThe blockade of immune checkpoints in cancer immunotherapy
Pardoll, D. M. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3239 · Cited by 13,838
Safety, activity, and immune correlates of anti–PD-1 antibody in cancer
Topalian, S. L., Hodi, F. S., Brahmer, J. R., Gettinger, S. N., Smith, D. C., McDermott, D. F., Powderly, J. D., Carvajal, R. D., Sosman, J. A., Atkins, M. B., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200690 · Cited by 12,628
Self-citationSafety and activity of anti-PD-L1 antibody in patients with advanced cancer
Brahmer, J. R., Tykodi, S. S., Chow, L. Q. M., Hwu, W.-J., Topalian, S. L., Hwu, P., Drake, C. G., Camacho, L. H., Kauh, J., Odunsi, K., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200694 · Cited by 7,945
Nivolumab plus Ipilimumab in Advanced Melanoma
Wolchok, J. D., Kluger, H., Callahan, M. K., Postow, M. A., Rizvi, N. A., Lesokhin, A. M., Segal, N. H., Ariyan, C. E., Gordon, R.-A., Reed, K., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1302369 · Cited by 4,230
Self-citationLymphoproliferative Disorders with Early Lethality in Mice Deficient in Ctla-4
Waterhouse, P., Penninger, J. M., Timms, E., Wakeham, A., Shahinian, A., Lee, K. P., Thompson, C. B., Griesser, H., & Mak, T. W. (1995) · Science · doi:10.1126/science.270.5238.985 · Cited by 2,766
CD28 and CTLA-4 have opposing effects on the response of T cells to stimulation.
Krummel, M. F., & Allison, J. P. (1995) · The Journal of experimental medicine · doi:10.1084/jem.182.2.459 · Cited by 2,245 · cited 3×
“A ntigen-specific T cell activation is regulated by a balance of costimulatory and coinhibitory signals, such as those mediated by inhibitory receptors CTLA-4 and PD-1 (1).”
BackgroundInfluentialTopalian, S. L., Sznol, M., McDermott, D. F., Kluger, H. M., Carvajal, R. D., Sharfman, W. H., Brahmer, J. R., Lawrence, D. P., Atkins, M. B., Powderly, J. D., et al. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2013.53.0105 · Cited by 2,222
Self-citationBenson, D. M., Bakan, C. E., Mishra, A., Hofmeister, C. C., Efebera, Y., Becknell, B., Baiocchi, R. A., Zhang, J., Yu, J., Smith, M. K., et al. (2010) · Blood · doi:10.1182/blood-2010-02-271874 · Cited by 807
Cited by
Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy
Sharma, P., Hu-Lieskovan, S., Wargo, J. A., & Ribas, A. (2017) · Cell · doi:10.1016/j.cell.2017.01.017 · Cited by 5,588
Fundamental Mechanisms of Immune Checkpoint Blockade Therapy
Wei, S. C., Duffy, C. R., & Allison, J. P. (2018) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-0367 · Cited by 3,088
Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab
Riaz, N., Havel, J. J., Makarov, V., Desrichard, A., Urba, W. J., Sims, J. S., Hodi, F. S., Martín-Algarra, S., Mandal, R., Sharfman, W. H., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.028 · Cited by 2,401
CTLA-4 and PD-1 Pathways: Similarities, Differences, and Implications of Their Inhibition
Buchbinder, E. I., & Desai, A. (2016) · American Journal of Clinical Oncology · doi:10.1097/coc.0000000000000239 · Cited by 2,360
CXCL9, CXCL10, CXCL11/CXCR3 axis for immune activation - a target for novel cancer therapy
Tokunaga, R., Zhang, W., Naseem, M., Puccini, A., Berger, M. D., Soni, S., McSkane, M., Baba, H., & Lenz, H.-J. (2018) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2017.11.007 · Cited by 1,627
Metadata
- Authors
- Das, R., Verma, R., Sznol, M., Boddupalli, C. S., Gettinger, S. N., Kluger, H., Callahan, M., Wolchok, J. D., Halaban, R., Dhodapkar, M. V., & Dhodapkar, K. M.
- Venue
- The Journal of Immunology
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-02-01
- Volume
- 194
- Issue
- 3
- Pages
- 950-959
- ISSN
- 0022-1767 (ISSN-L)
- 1550-6606
- OpenAlex
- W1849671624
- Cited by
- 461
- References
- 9
- FWCI
- 14.51
- Type
- journal article
- Language
- en
- Open access
- green
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