The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
Wanchoo, R., Karam, S., Uppal, N. N., Barta, V. S., Deray, G., Devoe, C., Launay‐Vacher, V., Jhaveri, K. D., & on behalf of Cancer and Kidney International Network Workgroup on Immune Checkpoint Inhibitors (2017) · American Journal of Nephrology · doi:10.1159/000455014 · Cited by 15,320
The 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
Safety 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
Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome
Galon, J., Costes, A., Sanchez-Cabo, F., Kirilovsky, A., Mlecnik, B., Lagorce-Pagès, C., Tosolini, M., Camus, M., Berger, A., Wind, P., et al. (2006) · Science · doi:10.1126/science.1129139 · Cited by 6,516
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
Safety and Tumor Responses with Lambrolizumab (Anti–PD-1) in Melanoma
Hamid, O., Robert, C., DAUD, A. I., Hodi, F. S., Hwu, W., Kefford, R. F., Wolchok, J. D., Hersey, P., Joseph, R. W., Weber, J. S., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1305133 · Cited by 3,427
Self-citationIntratumoral T Cells, Recurrence, and Survival in Epithelial Ovarian Cancer
Zhang, L., Conejo-Garcia, J. R., Katsaros, D., Gimotty, P. A., Massobrio, M., Regnani, G., Makrigiannakis, A., Gray, H., Schlienger, K., Liebman, M. N., et al. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa020177 · Cited by 3,397
Wolchok, J. D., Hoos, A., O'Day, S. J., Weber, J. S., Hamid, O., Lebbé, C., Maio, M., Binder, M., Bohnsack, O., Nichol, G. M., et al. (2009) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-09-1624 · Cited by 3,214
Taube, J. M., Klein, A., Brahmer, J. R., Xu, H., Pan, X., Kim, J. H., Chen, L., Pardoll, D. M., Topalian, S. L., & Anders, R. A. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-3271 · Cited by 2,324
Topalian, 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
Effector Memory T Cells, Early Metastasis, and Survival in Colorectal Cancer
Pagès, F., Berger, A., Camus, M., Sanchez-Cabo, F., Costes, A., Molidor, R., Mlecnik, B., Kirilovsky, A., Nilsson, M., Damotte, D., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa051424 · Cited by 2,135
Robert, C., Ribas, A., Wolchok, J. D., Hodi, F. S., Hamid, O., Kefford, R., Weber, J. S., Joshua, A. M., Hwu, W.-J., Gangadhar, T. C., et al. (2014) · The Lancet · doi:10.1016/s0140-6736(14)60958-2 · Cited by 1,774
Self-citationSpranger, S., Spaapen, R. M., Zha, Y., Williams, J., Meng, Y., Ha, T. T., & Gajewski, T. F. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3006504 · Cited by 1,677
Loss of tumor suppressor PTEN function increases B7-H1 expression and immunoresistance in glioma
Parsa, A. T., Waldron, J. S., Panner, A., Crane, C. A., Parney, I. F., Barry, J. J., Cachola, K. E., Murray, J. C., Tihan, T., Jensen, M. C., et al. (2006) · Nature Medicine · doi:10.1038/nm1517 · Cited by 1,341
Comprehensive assessment of T-cell receptor β-chain diversity in αβ T cells
Robins, H. S., Campregher, P. V., Srivastava, S. K., Wacher, A., Turtle, C. J., Kahsai, O., Riddell, S. R., Warren, E. H., & Carlson, C. S. (2009) · Blood · doi:10.1182/blood-2009-04-217604 · Cited by 1,122
Self-citationDuraiswamy, J., Kaluza, K. M., Freeman, G. J., & Coukos, G. (2013) · Cancer Research · doi:10.1158/0008-5472.can-12-4100 · Cited by 750
Using synthetic templates to design an unbiased multiplex PCR assay
Carlson, C. S., Emerson, R., Sherwood, A., Desmarais, C., Chung, M., Parsons, J. M., Steen, M. S., LaMadrid-Herrmannfeldt, M., Williamson, D. W., Livingston, R. J., et al. (2013) · Nature Communications · doi:10.1038/ncomms3680 · Cited by 568
Self-citationEffects of MAPK and PI3K Pathways on PD-L1 Expression in Melanoma
Atefi, M. S., Avramis, E. V., Lassen, A., Wong, D. J. L., Robert, L., Foulad, D. S., Cerniglia, M., Titz, B., Chodon, T., Graeber, T. G., et al. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-2797 · Cited by 344
Self-citationImmune Cell–Poor Melanomas Benefit from PD-1 Blockade after Targeted Type I IFN Activation
Bald, T., Landsberg, J., Lopez-Ramos, D., Renn, M., Glodde, N., Jansen, P., Gaffal, E., Steitz, J., Tolba, R. H., Kalinke, U., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0458 · Cited by 261
Ribas, A., Hodi, F. S., Kefford, R. F., Hamid, O., DAUD, A. I., Wolchok, J. D., Hwu, W., Gangadhar, T. C., Patnaik, A., Joshua, A. M., et al. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2014.32.18_suppl.lba9000 · Cited by 147
Self-citationDuraiswamy, J., Freeman, G. J., & Coukos, G. (2014) · Cancer Research · doi:10.1158/0008-5472.can-13-2752 · Cited by 53
Vanpouille‐Box, C., Diamond, J. M., Zavadil, J., Babb, J. S., Schaue, D., Barcellos‐Hoff, M. H., McBride, W. H., Formenti, S. C., & Demaria, S. (2014) · Cancer Research · doi:10.1158/1538-7445.am2014-633 · Cited by 17
Cited by
Sorted by citations
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802
Cancer immunotherapy using checkpoint blockade
Ribas, A., & Wolchok, J. D. (2018) · Science · doi:10.1126/science.aar4060 · Cited by 6,791
Self-citationMismatch repair deficiency predicts response of solid tumors to PD-1 blockade
Le, D. T., Durham, J. N., Smith, K. N., Wang, H., Bartlett, B. R., Aulakh, L. K., Lu, S., Kemberling, H., Wilt, C., Luber, B. S., et al. (2017) · Science · doi:10.1126/science.aan6733 · Cited by 6,645
Pembrolizumab for the Treatment of Non–Small-Cell Lung Cancer
Garon, E. B., Rizvi, N. A., Hui, R., Leighl, N., Balmanoukian, A. S., Eder, J. P., Patnaik, A., Aggarwal, C., Gubens, M., Horn, L., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1501824 · Cited by 6,198
Pembrolizumab versus Ipilimumab in Advanced Melanoma
Robert, C., Schachter, J., Long, G. V., Arance, A., Grob, J. J., Mortier, L., Daud, A., Carlino, M. S., McNeil, C., Lotem, M., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1503093 · Cited by 5,887
Self-citation
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review