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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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“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]
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
“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
“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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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
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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
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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
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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-citationPrimary, 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
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Mariathasan, S., Turley, S. J., Nickles, D., Castiglioni, A., Yuen, K., Wang, Y., Kadel III, E. E., Koeppen, H., Astarita, J. L., Cubas, R., et al. (2018) · Nature · doi:10.1038/nature25501 · Cited by 5,400
Elements of cancer immunity and the cancer–immune set point
Chen, D. S., & Mellman, I. (2017) · Nature · doi:10.1038/nature21349 · Cited by 5,352
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Sivan, A., Corrales, L., Hubert, N., Williams, J. B., Aquino-Michaels, K., Earley, Z. M., Benyamin, F. W., Man Lei, Y., Jabri, B., Alegre, M.-L., et al. (2015) · Science · doi:10.1126/science.aac4255 · Cited by 3,888
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Chen, B., Khodadoust, M. S., Liu, C. L., Newman, A. M., & Alizadeh, A. A. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7493-1_12 · Cited by 3,929
Molecular and genetic properties of tumors associated with local immune cytolytic activity
Rooney, M. S., Shukla, S. A., Wu, C. J., Getz, G., & Hacohen, N. (2015) · Cell · doi:10.1016/j.cell.2014.12.033 · Cited by 3,825
IFN-γ–related mRNA profile predicts clinical response to PD-1 blockade
Ayers, M., Lunceford, J., Nebozhyn, M., Murphy, E., Loboda, A., Kaufman, D. R., Albright, A., Cheng, J. D., Kang, S. P., Shankaran, V., et al. (2017) · Journal of Clinical Investigation · doi:10.1172/jci91190 · Cited by 3,788
Self-citationGenomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma
Hugo, W., Zaretsky, J. M., Sun, L., Song, C., Moreno, B. H., Hu-Lieskovan, S., Berent-Maoz, B., Pang, J., Chmielowski, B., Cherry, G., et al. (2016) · Cell · doi:10.1016/j.cell.2016.02.065 · Cited by 3,448
Self-citationApproaches to treat immune hot, altered and cold tumours with combination immunotherapies
Galon, J., & Bruni, D. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-018-0007-y · Cited by 3,520
Mutations Associated with Acquired Resistance to PD-1 Blockade in Melanoma
Zaretsky, J. M., Garcia-Diaz, A., Shin, D. S., Escuin-Ordinas, H., Hugo, W., Hu-Lieskovan, S., Torrejon, D. Y., Abril-Rodriguez, G., Sandoval, S., Barthly, L., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1604958 · Cited by 3,237
Self-citationFundamental 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
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Akbani, R., Akdemir, K. C., Aksoy, B. A., Albert, M., Ally, A., Amin, S. B., Arachchi, H., Arora, A., Auman, J. T., Ayala, B., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.044 · Cited by 3,151
The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients
Matson, V., Fessler, J., Bao, R., Chongsuwat, T., Zha, Y., Alegre, M.-L., Luke, J. J., & Gajewski, T. F. (2018) · Science · doi:10.1126/science.aao3290 · Cited by 3,107
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Chen, G., Huang, A. C., Zhang, W., Zhang, G., Wu, M., Xu, W., Yu, Z., Yang, J., Wang, B., Sun, H., et al. (2018) · Nature · doi:10.1038/s41586-018-0392-8 · Cited by 2,813
Nivolumab and ipilimumab versus ipilimumab in untreated melanoma
Postow, M. A., Chesney, J., Pavlick, A. C., Robert, C., Grossmann, K., McDermott, D., Linette, G. P., Meyer, N., Giguere, J. K., Agarwala, S. S., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1414428 · Cited by 2,781
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Li, B., Severson, E. A., Pignon, J., Zhao, H., Li, T., Novak, J. S. S., Jiang, P., Shen, H., Aster, J. C., Rodig, S. J., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1028-7 · Cited by 2,432
Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy
Cristescu, R., Mogg, R., Ayers, M., Albright, A., Murphy, E., Yearley, J., Sher, X., Liu, X. Q., Lu, H., Nebozhyn, M., et al. (2018) · Science · doi:10.1126/science.aar3593 · Cited by 2,301
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Hegde, P. S., & Chen, D. S. (2020) · Immunity · doi:10.1016/j.immuni.2019.12.011 · Cited by 2,238
Zou, W., Wolchok, J. D., & Chen, L. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aad7118 · Cited by 2,400
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Buchbinder, E. I., & Desai, A. (2016) · American Journal of Clinical Oncology · doi:10.1097/coc.0000000000000239 · Cited by 2,360
“Other markers of response to anti-PD-1 or PD-L1 therapy have also been explored and include features associated with PD-L1-mediated suppression of preexisting immunity.(48,76) As with CTLA-4, mutational burden and higher neoantigen burden have recently been shown to be associated with efficacy in patients with NSCLC t…”
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Johnson, D. B., Balko, J. M., Compton, M. L., Chalkias, S., Gorham, J., Xu, Y., Hicks, M., Puzanov, I., Alexander, M. R., Bloomer, T. L., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1609214 · Cited by 2,308
Bagchi, S., Yuan, R., & Engleman, E. G. (2021) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-042020-042741 · Cited by 2,189
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Garcia-Diaz, A., Shin, D. S., Moreno, B. H., Saco, J., Escuin-Ordinas, H., Rodriguez, G. A., Zaretsky, J. M., Sun, L., Hugo, W., Wang, X., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.04.031 · Cited by 1,942
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Siddiqui, I., Schaeuble, K., Chennupati, V., Fuertes Marraco, S. A., Calderon-Copete, S., Pais Ferreira, D., Carmona, S. J., Scarpellino, L., Gfeller, D., Pradervand, S., et al. (2019) · Immunity · doi:10.1016/j.immuni.2018.12.021 · Cited by 1,679
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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
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Huang, A. C., Postow, M. A., Orlowski, R. J., Mick, R., Bengsch, B., Manne, S., Xu, W., Harmon, S., Giles, J. R., Wenz, B., et al. (2017) · Nature · doi:10.1038/nature22079 · Cited by 1,664
Alsaab, H. O., Sau, S., Alzhrani, R. M., Tatiparti, K., Bhise, K., Kashaw, S. K., & Iyer, A. K. (2017) · Frontiers in Pharmacology · doi:10.3389/fphar.2017.00561 · Cited by 1,750
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Bruni, D., Angell, H. K., & Galon, J. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-0285-7 · Cited by 1,586
STK11/LKB1 Mutations and PD-1 Inhibitor Resistance in KRAS -Mutant Lung Adenocarcinoma
Skoulidis, F., Goldberg, M. E., Greenawalt, D. M., Hellmann, M. D., Awad, M. M., Gainor, J. F., Schrock, A. B., Hartmaier, R. J., Trabucco, S. E., Gay, L., et al. (2018) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-0099 · Cited by 1,641
“Months KL KP K-only 54(0) 56(0) 64(0) 11(2) 26(3) 29(0) 5(3) 14(6) 20(3) 4(3) 9(10) 9(8) 2(4) 5(14) 3(13) 2(4) 1(15) 2(14) 1(4) 0(15) 2(14) 1(4) 0(15) 1(14) 0(4) 0(15) 0(15)”
CD8+ cytotoxic T lymphocytes in cancer immunotherapy: A review
Farhood, B., Najafi, M., & Mortezaee, K. (2018) · Journal of Cellular Physiology · doi:10.1002/jcp.27782 · Cited by 1,701
Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing
Guo, X., Zhang, Y., Zheng, L., Zheng, C., Song, J., Zhang, Q., Kang, B., Liu, Z., Jin, L., Xing, R., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0045-3 · Cited by 1,651
Predictive biomarkers for checkpoint inhibitor-based immunotherapy
Gibney, G. T., Weiner, L. M., & Atkins, M. B. (2016) · The Lancet Oncology · doi:10.1016/s1470-2045(16)30406-5 · Cited by 1,635
Koyama, S., Akbay, E. A., Li, Y. Y., Herter-Sprie, G. S., Buczkowski, K. A., Richards, W. G., Gandhi, L., Redig, A. J., Rodig, S. J., Asahina, H., et al. (2016) · Nature Communications · doi:10.1038/ncomms10501 · Cited by 1,580
Saxena, M., van der Burg, S. H., Melief, C. J. M., & Bhardwaj, N. (2021) · Nature reviews. Cancer · doi:10.1038/s41568-021-00346-0 · Cited by 1,581
CD4+ T cell help in cancer immunology and immunotherapy
Borst, J., Ahrends, T., Bąbała, N., Melief, C. J. M., & Kastenmüller, W. (2018) · Nature Reviews Immunology · doi:10.1038/s41577-018-0044-0 · Cited by 1,585
Ribas, A., Puzanov, I. J., Dummer, R., Schadendorf, D., Hamid, O., Robert, C., Hodi, F. S., Schachter, J., Pavlick, A. C., Lewis, K. D., et al. (2015) · The Lancet Oncology · doi:10.1016/s1470-2045(15)00083-2 · Cited by 1,590
Self-citationOncolytic virotherapy promotes intratumoral T cell infiltration and improves anti-PD-1 immunotherapy
Ribas, A., Dummer, R., Puzanov, I., VanderWalde, A., Andtbacka, R. H. I., Michielin, O., Olszanski, A. J., Malvehy, J., Cebon, J., Fernandez, E., et al. (2017) · Cell · doi:10.1016/j.cell.2017.08.027 · Cited by 1,520
Self-citationTumour-intrinsic resistance to immune checkpoint blockade
Kalbasi, A. K., & Ribas, A. (2019) · Nature reviews. Immunology · doi:10.1038/s41577-019-0218-4 · Cited by 1,525
Self-citationSchadendorf, D., van Akkooi, A. C. J., Berking, C., Griewank, K., Gutzmer, R., Hauschild, A., Stang, A., Roesch, A., & Ugurel, S. (2018) · The Lancet · doi:10.1016/s0140-6736(18)31559-9 · Cited by 1,557
Macrophages and Therapeutic Resistance in Cancer
Ruffell, B., & Coussens, L. M. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.02.015 · Cited by 1,474
Spranger, S., Dai, D., Horton, B., & Gajewski, T. F. (2017) · Cancer Cell · doi:10.1016/j.ccell.2017.04.003 · Cited by 1,441
CD8+ T cell states in human cancer: insights from single-cell analysis
van der Leun, A. M., Thommen, D. S., & Schumacher, T. N. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-019-0235-4 · Cited by 1,487
Chalabi, M., Fanchi, L. F., Dijkstra, K. K., Van den Berg, J. G., Aalbers, A. G., Sikorska, K., Lopez-Yurda, M., Grootscholten, C., Beets, G. L., Snaebjornsson, P., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0805-8 · Cited by 1,417
Classifying Cancers Based on T-cell Infiltration and PD-L1
Teng, M. W. L., Ngiow, S. F., Ribas, A., & Smyth, M. J. (2015) · Cancer Research · doi:10.1158/0008-5472.can-15-0255 · Cited by 1,436
Self-citationRizvi, N. A., Mazières, J., Planchard, D., Stinchcombe, T. E., Dy, G. K., Antonia, S. J., Horn, L., Lena, H., Minenza, E., Mennecier, B., et al. (2015) · The Lancet Oncology · doi:10.1016/s1470-2045(15)70054-9 · Cited by 1,415
Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations
Seidel, J. A., Otsuka, A., & Kabashima, K. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00086 · Cited by 1,360
A review of cancer immunotherapy toxicity
Kennedy, L. B., & Salama, A. K. S. (2020) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21596 · Cited by 1,396
Rizvi, H., Sanchez-Vega, F., La, K., Chatila, W., Jonsson, P., Halpenny, D., Plodkowski, A., Long, N., Sauter, J. L., Rekhtman, N., et al. (2018) · Journal of Clinical Oncology · doi:10.1200/jco.2017.75.3384 · Cited by 1,367
Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution
McGranahan, N., Rosenthal, R., Hiley, C. T., Rowan, A. J., Watkins, T. B. K., Wilson, G. A., Birkbak, N. J., Veeriah, S., Van Loo, P., Herrero, J., et al. (2017) · Cell · doi:10.1016/j.cell.2017.10.001 · Cited by 1,298
Davoli, T., Uno, H., Wooten, E. C., & Elledge, S. J. (2017) · Science · doi:10.1126/science.aaf8399 · Cited by 1,347
Molecular and Biochemical Aspects of the PD-1 Checkpoint Pathway
Boussiotis, V. A. (2016) · New England Journal of Medicine · doi:10.1056/nejmra1514296 · Cited by 1,372
Primary Resistance to PD-1 Blockade Mediated by JAK1/2 Mutations
Shin, D. S., Zaretsky, J. M., Escuin-Ordinas, H., Garcia-Diaz, A., Hu-Lieskovan, S., Kalbasi, A., Grasso, C. S., Hugo, W., Sandoval, S., Torrejon, D. Y., et al. (2017) · Cancer Discovery · doi:10.1158/2159-8290.cd-16-1223 · Cited by 1,337
Self-citationHiam-Galvez, K. J., Allen, B. M., & Spitzer, M. H. (2021) · Nature Reviews Cancer · doi:10.1038/s41568-021-00347-z · Cited by 1,400
Thommen, D. S., & Schumacher, T. N. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.03.012 · Cited by 1,351
Combination cancer immunotherapy and new immunomodulatory targets
Mahoney, K. M., Rennert, P. D., & Freeman, G. J. (2015) · Nature Reviews Drug Discovery · doi:10.1038/nrd4591 · Cited by 1,294
Genomic spectra of biliary tract cancer
Nakamura, H. K., Arai, Y., Totoki, Y., Shirota, T., Elzawahry, A., Kato, M., Hama, N., Hosoda, F., Urushidate, T., Ohashi, S., et al. (2015) · Nature Genetics · doi:10.1038/ng.3375 · Cited by 1,306
PD-1 Blockade with pembrolizumab in advanced Merkel-cell carcinoma
Nghiem, P. T., Bhatia, S., Lipson, E. J., Kudchadkar, R. R., Miller, N. J., Annamalai, L., Berry, S., Chartash, E. K., Daud, A., Fling, S. P., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1603702 · Cited by 1,258
Self-citationTargeted agents and immunotherapies: optimizing outcomes in melanoma
Luke, J. J., Flaherty, K. T., Ribas, A., & Long, G. V. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.43 · Cited by 1,269
Self-citationGainor, J. F., Shaw, A. T., Sequist, L. V. D., Fu, X., Azzoli, C. G., Piotrowska, Z., Huynh, T. G., Zhao, L., Fulton, L. E., Schultz, K. R., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-3101 · Cited by 1,268
Hargadon, K. M., Johnson, C. E., & Williams, C. J. (2018) · International Immunopharmacology · doi:10.1016/j.intimp.2018.06.001 · Cited by 1,211
Mutant MHC class II epitopes drive therapeutic immune responses to cancer
Kreiter, S., Vormehr, M., van de Roemer, N., Diken, M., Löwer, M., Diekmann, J., Boegel, S., Schrörs, B., Vascotto, F., Castle, J. C., et al. (2015) · Nature · doi:10.1038/nature14426 · Cited by 1,243
Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade
Benci, J. L., Xu, B., Qiu, Y., Wu, T. J., Dada, H., Twyman-Saint Victor, C., Cucolo, L., Lee, D. S. M., Pauken, K. E., Huang, A. C., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.022 · Cited by 1,216
Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy
Chowell, D., Morris, L. G. T., Grigg, C. M., Weber, J. K., Samstein, R. M., Makarov, V., Kuo, F., Kendall, S. M., Requena, D., Riaz, N., et al. (2018) · Science · doi:10.1126/science.aao4572 · Cited by 1,142
Salmon, H., Idoyaga, J., Rahman, A. H., Leboeuf, M., Remark, R., Jordan, S., Casanova-Acebes, M., Khudoynazarova, M. N., Agudo, J., Tung, N., et al. (2016) · Immunity · doi:10.1016/j.immuni.2016.03.012 · Cited by 1,222
Epigenetic silencing of TH1-type chemokines shapes tumour immunity and immunotherapy
Peng, D., Kryczek, I., Nagarsheth, N., Zhao, L., Wei, S., Wang, W., Sun, Y., Zhao, E., Vatan, L., Szeliga, W., et al. (2015) · Nature · doi:10.1038/nature15520 · Cited by 1,201
Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer
Initiative, A. P. C. G., Balachandran, V. P., Łuksza, M., Zhao, J. N., Makarov, V., Moral, J. A., Remark, R., Herbst, B., Askan, G., Bhanot, U., et al. (2017) · Nature · doi:10.1038/nature24462 · Cited by 1,191
Overcoming T cell exhaustion in infection and cancer
Pauken, K. E., & Wherry, E. J. (2015) · Trends in Immunology · doi:10.1016/j.it.2015.02.008 · Cited by 1,220
Melief, C. J. M., van Hall, T., Arens, R., OSSENDORP, F. A., & van der Burg, S. H. (2015) · Journal of Clinical Investigation · doi:10.1172/jci80009 · Cited by 1,192
Keren, L., Bosse, M., Marquez, D., Angoshtari, R., Jain, S., Varma, S., Yang, S.-R., Kurian, A., Van Valen, D., West, R., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.039 · Cited by 1,183
Tertiary lymphoid structures in cancer
Schumacher, T. N., & Thommen, D. S. (2022) · Science · doi:10.1126/science.abf9419 · Cited by 1,170
“A first, relatively straightforward refinement is the subdivision of T cells based on their location at the tumor border or in the tumor parenchyma (9).”
Background
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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