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PD-1 blockade induces responses by inhibiting adaptive immune resistance
Open accessAbstract
Therapies that target the programmed death-1 (PD-1) receptor have shown unprecedented rates of durable clinical responses in patients with various cancer types. One mechanism by which cancer tissues limit the host immune response is via upregulation of PD-1 ligand (PD-L1) and its ligation to PD-1 on antigen-specific CD8+ T cells (termed adaptive immune resistance). Here we show that pre-existing CD8+ T cells distinctly located at the invasive tumour margin are associated with expression of the PD-1/PD-L1 immune inhibitory axis and may predict response to therapy. We analysed samples from 46 patients with metastatic melanoma obtained before and during anti-PD-1 therapy (pembrolizumab) using quantitative immunohistochemistry, quantitative multiplex immunofluorescence, and next-generation sequencing for T-cell antigen receptors (TCRs). In serially sampled tumours, patients responding to treatment showed proliferation of intratumoral CD8+ T cells that directly correlated with radiographic reduction in tumour size. Pre-treatment samples obtained from responding patients showed higher numbers of CD8-, PD-1- and PD-L1-expressing cells at the invasive tumour margin and inside tumours, with close proximity between PD-1 and PD-L1, and a more clonal TCR repertoire. Using multivariate analysis, we established a predictive model based on CD8 expression at the invasive margin and validated the model in an independent cohort of 15 patients. Our findings indicate that tumour regression after therapeutic PD-1 blockade requires pre-existing CD8+ T cells that are negatively regulated by PD-1/PD-L1-mediated adaptive immune resistance.
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“However, both PDL-1 expression and TMB fail to encapsulate various tumor microenvironmental features influencing ICI responses15–17.”
From Predicting the tumor microenvironment composition and immunotherapy response in non-small cell lung cancer from digital histopathology images (2024) · cites this paper as [15]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Pre-treatment CD8+ T cell presence is linked to responses to ICB and anti-PD-1 plus lenvatinib in HCC patients.”
From Contrasting cytotoxic and regulatory T cell responses underlying distinct clinical outcomes to anti-PD-1 plus lenvatinib therapy in cancer (2025) · cites this paper as [4]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“We compared the tumor-associated immune infiltrates via multi-parameter immunohistochemistry (IHC) and observed a higher density of CD8+ T cells in baseline samples of R versus NR (p=0.04), consistent with prior reports (Fig. 4A and fig. S18) (18, 37).”
From Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients (2018) · cites this paper as [37]
In the citing paper
“Additionally, cancer cells can increase immune checkpoint molecules such as PD-L1, resulting in peripheral T cell exhaustion and the inhibition of malignant cell apoptosis [85].”
From Current and Future Trends of Colorectal Cancer Treatment: Exploring Advances in Immunotherapy (2024) · cites this paper as [85]
In the citing paper
“Indeed, as mentioned in the previous section, both PD-1 and CTLA-4 blockades are more effective in tumors that are infiltrated by T cells or that have high mutation rates and are therefore more immunogenic prior to treatment (86–88).”
From Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations (2018) · cites this paper as [88]
In the citing paper
“An increase in CD8+ T cell proliferation within the tumor lesion and an increased frequency of Th9 cells in the patients’ circulation were also associated with treatment response (88, 91, 92).”
From Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations (2018) · cites this paper as [88]
In the citing paper
“Other pre-treatment immunological factors associated with improved treatment responses include high eosinophil and lymphocyte blood counts, an abundance of CD8+ T cells infiltrating the tumor or present at the tumor margin, and increased serum TGF-β levels in melanoma patients treated with anti-PD-1 (88, 91, 92, 109).”
From Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations (2018) · cites this paper as [88]
In the citing paper
“TILs are therefore under active investigation as a biomarker to guide selection of patients for treatment with ICT, although significant variability exists in definitions and thresholds (149, 150).”
From The Next Decade of Immune Checkpoint Therapy (2021) · cites this paper as [149]
In the citing paper
“The presence of CD8+ T cells at tumor margins and within the tumor prior to treatment with checkpoint inhibitors was associated with a stronger response to treatment (Tumeh et al., 2014).”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Tumeh et al., 2014
In the citing paper
“abundance of T cells at the invasive tumor margin prior to treatment was associated with a better response, whereas upon treatment, T cell densities were increased both at the margin and within the tumor parenchyma in responding patients”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Tumeh et al., 2014
In the citing paper
“In metastatic melanoma patients, a higher density of intratumoral CD8+ T cells at baseline was shown to predict favorable response to anti-PD-1 treatment”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Tumeh et al., 2014
In the citing paper
“some studies have found that high TCR diversity in peripheral blood and tumors prior to ICI therapy is predictive of effective treatment, others have pointed to ICI therapy-associated increases in TCR clonality, that is, enrichment of T cells with the same TCRs, as a sign of effective therapy (150, 157-161).”
From Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance (2021) · cites this paper as [150]
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CA-170 – A Potent Small-Molecule PD-L1 Inhibitor or Not?
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Tumor Burden and Immunotherapy: Impact on Immune Infiltration and Therapeutic Outcomes
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Zhang, Y. X., & Chen, L. (2016) · JAMA Oncology · doi:10.1001/jamaoncol.2016.2450 · Cited by 168
Komdeur, F. L., Prins, T. M., van de Wall, S., Plat, A., Wisman, G. B. A., Hollema, H., Daemen, T., Church, D. N., de Bruyn, M., & Nijman, H. W. (2017) · OncoImmunology · doi:10.1080/2162402x.2017.1338230 · Cited by 173
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IFN-gamma-induced PD-L1 expression in melanoma depends on p53 expression
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Toki, M. I., Merritt, C. R., Wong, P. F., Smithy, J. W., Kluger, H. M., Syrigos, K. N., Ong, G. T., Warren, S. E., Beechem, J., & Rimm, D. L. (2019) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-0104 · Cited by 170
“correlate with favorable outcome to immunotherapy treatment (33, 34).”
BackgroundThe immune landscape and response to immune checkpoint blockade therapy in lymphoma
Kline, J. P., Godfrey, J. K., & Ansell, S. M. (2019) · Blood · doi:10.1182/blood.2019000847 · Cited by 166
Lin, Z., Cai, M., Zhang, P., Li, G., Liu, T., Li, X., Cai, K., Nie, X., Wang, J., Liu, J., et al. (2021) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2021-003554 · Cited by 170
Trujillo, J. A., Luke, J. J., Zha, Y., Segal, J. P., Ritterhouse, L. L., Spranger, S., Matijevich, K., & Gajewski, T. F. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0780-0 · Cited by 159
Tumor matrix remodeling and novel immunotherapies: the promise of matrix-derived immune biomarkers
Mushtaq, M. U., Papadas, A., Pagenkopf, A. C., Flietner, E., Morrow, Z. T., Chaudhary, S. G., & Asimakopoulos, F. A. (2018) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-018-0376-0 · Cited by 170
Immune Landscape of Colorectal Cancer Tumor Microenvironment from Different Primary Tumor Location
Zhang, L., Zhao, Y., Dai, Y., Cheng, J., Gong, Z., Feng, Y., Sun, C., Jia, Q., & Zhu, B. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01578 · Cited by 172
PD-L1 expression as predictive biomarker in patients with NSCLC: a pooled analysis
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Myeloid-targeted immunotherapies act in synergy to induce inflammation and antitumor immunity
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“Cell-specific and topological analysis of immune-checkpoint expression in patients has become feasible with the fluorescent multiplex immunohistochemistry (IHC) and automated quantitation technology (29, 30).”
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Therapeutic bispecific T-cell engager antibody targeting the intracellular oncoprotein WT1
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Biomarkers associated with checkpoint inhibitors
Manson, G., Norwood, J., Marabelle, A., Kohrt, H. E. K., & Houot, R. (2016) · Annals of Oncology · doi:10.1093/annonc/mdw181 · Cited by 166
Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer
Herzberg, B., Campo, M. J., & Gainor, J. F. (2016) · The Oncologist · doi:10.1634/theoncologist.2016-0189 · Cited by 165
Cader, F. Z., Schackmann, R. C. J., Hu, X. S., Wienand, K., Redd, R. A., Chapuy, B., Ouyang, J., Paul, N. E., Gjini, E., Lipschitz, M., et al. (2018) · Blood · doi:10.1182/blood-2018-04-843714 · Cited by 166
Chemokines expressed by engineered bacteria recruit and orchestrate antitumor immunity
Savage, T. M., Vincent, R. L., Rae, S. S., Huang, L., Ahn, A., Pu, K., Li, F., Santos, K. D. L., Coker, C., Danino, T., et al. (2023) · Science Advances · doi:10.1126/sciadv.adc9436 · Cited by 168
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Danilova, L., Wang, H., Sunshine, J. C., Kaunitz, G. J., Cottrell, T. R., Xu, H., Esandrio, J., Anders, R. A., Cope, L., Pardoll, D. M., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1607836113 · Cited by 164
Shrimali, R. K., Ahmad, S., Verma, V., Zeng, P., Ananth, S., Gaur, P., Gittelman, R. M., Yusko, E. C., Sanders, C. M., Robins, H. S., et al. (2017) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-17-0292 · Cited by 161
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“Interferon-–responsive gene signature and tumor-infiltrating lymphocytes are associated with favorable responses to ipilimumab The presence of tumor-infiltrating lymphocytes and interferon- (IFN-)–responsive gene signatures have been shown to be predictive of responses to ICB (7, 8, 16, 17).”
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Single Cell T Cell Receptor Sequencing: Techniques and Future Challenges
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Shi, T., Song, X., Wang, Y., Liu, F., & Wei, J. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.00683 · Cited by 168
“Currently it remains difficult to make OVs reach every primary and metastatic tumor site to achieve the desired effects; also ICIs are most effective in patients with preexisting T cell infiltrations, which are found mostly within the primary tumor lesion (69).”
BackgroundImmune-related adverse events in various organs caused by immune checkpoint inhibitors
Okiyama, N., & Tanaka, R. (2022) · Allergology International · doi:10.1016/j.alit.2022.01.001 · Cited by 170
Advances in immunotherapy for melanoma
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Molecular Subtype Not Immune Response Drives Outcomes in Endometrial Carcinoma
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PAK4 inhibition improves PD-1 blockade immunotherapy
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“Our work shows that: (1) PAK4 expression is enriched in non-responding tumor biopsies with low immune cell infiltration; (2) genetic and pharmacologic PAK4 inhibition improve response to PD-1 blockade in vivo; and (3) this provides a novel therapeutic strategy that may improve the efficacy of immune checkpoint inhibit…”
Self-citationBioinspired and Biomimetic Delivery Platforms for Cancer Vaccines
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Control of CD8 T-Cell Infiltration into Tumors by Vasculature and Microenvironment
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PD-L1 Expression in Melanoma: A Quantitative Immunohistochemical Antibody Comparison
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Enhancing Tumor T Cell Infiltration to Enable Cancer Immunotherapy
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“Moreover, systemic inflammation as reflected by serum CRP has been suggested to correlate with low levels of CD4+ T-cells, which play a key role in ICI mediated antitumor immune response [128].”
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Metadata
- Authors
- Tumeh, P. C., Harview, C. L., Yearley, J. H., Shintaku, I. P., Taylor, E. J. M., Robert, L., Chmielowski, B., Spasic, M., Henry, G., Ciobanu, V., West, A. N., Carmona, M., Kivork, C., Seja, E., Cherry, G., Gutierrez, A. J., Grogan, T. R., Mateus, C., Tomasic, G., Glaspy, J. A., Emerson, R. O., Robins, H., Pierce, R. H., Elashoff, D. A., Robert, C., & Ribas, A.
- Affiliations
- University of California, Los Angeles (US)
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- Inserm (FR)
- Adaptive Biotechnologies (United States) (US)
- Fred Hutch Cancer Center (US)
- Corresponding author
- Tumeh, Paul C.
- Ribas, Antoni
- ORCID
- Venue
- Nature
- Published
- 2014-11-26
- Volume
- 515
- Issue
- 7528
- Pages
- 568-571
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4246418
- OpenAlex
- W2039123767
- Semantic Scholar
- 2c96ca62d538ff43fce01bc848fc018f6ae2b4a0
- Cited by
- 6,609
- References
- 24
- Citations by year
- 2026: 280 · 2025: 398 · 2024: 491 · 2023: 588 · 2022: 695 · 2021: 768 · 2020: 800 · 2019: 610 · 2018: 593 · 2017: 566 · 2016: 488 · 2015: 303 · 2014: 12
- FWCI
- 220.45
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- American Association for Cancer Research (SU2C-AACR-DT1012)
- Cancer Research Institute (SU2C-AACR-DT1012, CA16042)
- Melanoma Research Alliance (SU2C-AACR-DT1012)
- Adaptive Biotechnologies
- Institut Gustave-Roussy
- Sociedad Española de Oncología Médica
- National Institutes of Health (UL1TR000124, 5u54ca119347-03, P30 CA- 16042, SU2C-AACR-DT1012, CA16042)
- Stand Up To Cancer (SU2C-AACR-DT1012))
- National Cancer Institute (U54-CA119347, P01CA168585, P30-CA16042, R01CA170689, P30CA016042)
- National Institute of Allergy and Infectious Diseases (K08AI091663)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- pembrolizumab, adaptive immune resistance, CD8+ T cells, PD-L1, PD-1/PD-L1 axis, metastatic melanoma, tumor-infiltrating lymphocytes, T cell receptor repertoire, predictive biomarkers, tumor regression, immune checkpoint inhibitors
- MeSH terms
- Aged, Aged, 80 and over, Female, Humans, Immunotherapy, Male, Melanoma, Middle Aged, Models, Biological, Biomarkers, Gene Expression Regulation, Neoplastic, Multivariate Analysis, Treatment Outcome, CD8-Positive T-Lymphocytes, Cell Proliferation, Adaptive Immunity, Programmed Cell Death 1 Receptor
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