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Home All issues Volume 35 / No 12 (Décembre 2019) Med Sci (Paris), 35 12 (2019) 957-965 References
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Issue
Med Sci (Paris)
Volume 35, Number 12, Décembre 2019
Anticorps monoclonaux en thérapeutique
Page(s) 957 - 965
Section La révolution des anticorps modulateurs de la réponse immunitaire en oncologie
DOI https://doi.org/10.1051/medsci/2019192
Published online 06 January 2020
  1. Brunet JF, Denizot F, Luciani MF, et al. A new member of the immunoglobulin superfamily-CTLA-4. Nature 1987 ; 328: 267–270. [Google Scholar]
  2. Ishida Y, Agata Y, Shibahara K, Honjo T. Induced expression of PD-1, a novel member of the immunoglobulin gene superfamily, upon programmed cell death. EMBO J 1992 ; 11: 3887–3895. [CrossRef] [PubMed] [Google Scholar]
  3. Leung HT, Bradshaw J, Cleaveland JS, Linsley PS. Cytotoxic T lymphocyte-associated molecule-4, a high-avidity receptor for CD80 and CD86, contains an intracellular localization motif in its cytoplasmic tail. J Biol Chem 1995 ; 270: 25107–25114. [CrossRef] [PubMed] [Google Scholar]
  4. Valk E, Leung R, Kang H, et al. T cell receptor-interacting molecule acts as a chaperone to modulate surface expression of the CTLA-4 coreceptor. Immunity 2006 ; 25: 807–821. [CrossRef] [PubMed] [Google Scholar]
  5. Read S, Greenwald R, Izcue A, et al. Blockade of CTLA-4 on CD4+CD25+ regulatory T cells abrogates their function in vivo. J Immunol 2006 ; 177: 4376–4383. [CrossRef] [PubMed] [Google Scholar]
  6. Wing K, Onishi Y, Prieto-Martin P, et al. CTLA-4 control over Foxp3+ regulatory T cell function. Science 2008 ; 322: 271–275. [Google Scholar]
  7. Ren J, Han L, Tang J, et al. Foxp1 is critical for the maintenance of regulatory T-cell homeostasis and suppressive function. PLoS Biol 2019 ; 17: e3000270. [PubMed] [Google Scholar]
  8. Hui E, Cheung J, Zhu J, et al. T cell costimulatory receptor CD28 is a primary target for PD-1-mediated inhibition. Science 2017 ; 355: 1428–1433. [Google Scholar]
  9. Ahn E, Araki K, Hashimoto M, et al. Role of PD-1 during effector CD8 T cell differentiation. Proc Natl Acad Sci U S A 2018 ; 115: 4749–4754. [CrossRef] [PubMed] [Google Scholar]
  10. Kamphorst AO, Wieland A, Nasti T, et al. Rescue of exhausted CD8 T cells by PD-1-targeted therapies is CD28-dependent. Science 2017 ; 355: 1423–1427. [Google Scholar]
  11. Haile ST, Dalal SP, Clements V, et al. Soluble CD80 restores T cell activation and overcomes tumor cell programmed death ligand 1-mediated immune suppression. J Immunol 2013 ; 191: 2829–2836. [CrossRef] [PubMed] [Google Scholar]
  12. Chihara N, Madi A, Kondo T, et al. Induction and transcriptional regulation of the co-inhibitory gene module in T cells. Nature 2018 ; 558: 454–459. [Google Scholar]
  13. Franchini DM, Lanvin O, Tosolini M, et al. Microtubule-driven stress granule dynamics regulate inhibitory immune checkpoint expression in T cells. Cell Rep 2019 ; 26: 94–107 e7. [Google Scholar]
  14. Gong B, Kiyotani K, Sakata S, et al. Secreted PD-L1 variants mediate resistance to PD-L1 blockade therapy in non-small cell lung cancer. J Exp Med 2019 ; 216: 982–1000. [CrossRef] [PubMed] [Google Scholar]
  15. Blank CU, Haanen JB, Ribas A, Schumacher TN. Cancer immunology. The cancer immunogram. Science 2016 ; 352: 658–660. [Google Scholar]
  16. Garon EB, Rizvi NA, Hui R, et al. Keynote-001 investigators. Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med 2015 ; 372: 2018–2028. [Google Scholar]
  17. Nishino M, Ramaiya NH, Hatabu H, Hodi FS. Monitoring immune-checkpoint blockade: response evaluation and biomarker development. Nat Rev Clin Oncol 2017 ; 14: 655–668. [Google Scholar]
  18. Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer 2012 ; 12: 252–264. [Google Scholar]
  19. Larkin J, Chiarion-Sileni V, Gonzalez R, et al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med 2015 ; 373: 23–34. [Google Scholar]
  20. Ansell SM, Lesokhin AM, Borrello I, et al. PD-1 blockade with nivolumab in relapsed or refractory Hodgkin’s lymphoma. N Engl J Med 2015 ; 372: 311–319. [Google Scholar]
  21. Bensch F, van der Veen EL, Lub-de Hooge MN, et al. 89Zr-atezolizumab imaging as a non-invasive approach to assess clinical response to PD-L1 blockade in cancer. Nat Med 2018 ; 24: 1852–1858. [CrossRef] [PubMed] [Google Scholar]
  22. Tumeh PC, Harview CL, Yearley JH, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 2014 ; 515: 568–571. [Google Scholar]
  23. Hu-Lieskovan S, Lisberg A, Zaretsky JM, et al. Tumor characteristics associated with benefit from pembrolizumab in advanced non-small cell lung cancer. Clin Cancer Res 2019 May 21. pii: clincanres.4275.2018. [Google Scholar]
  24. Ott PA, Bang YJ, Piha-Paul SA, et al. T-cell-inflamed gene-expression profile, programmed death ligand 1 expression, and tumor mutational burden predict efficacy in patients treated with pembrolizumab across 20 cancers: keynote-028. J Clin Oncol 2019 ; 37: 318–327. [CrossRef] [PubMed] [Google Scholar]
  25. Havel JJ, Chowell D, Chan TA. The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy. Nat Rev Cancer 2019 ; 19: 133–150. [Google Scholar]
  26. McGranahan N, Furness AJ, Rosenthal R, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 2016 ; 351: 1463–1469. [Google Scholar]
  27. Hellmann MD, Ciuleanu TE, Pluzanski A, et al. Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden. N Engl J Med 2018 ; 378: 2093–2104. [Google Scholar]
  28. Yarchoan M, Hopkins A, Jaffee EM. Tumor mutational burden and response rate to PD-1 inhibition. N Engl J Med 2017 ; 377: 2500–2501. [Google Scholar]
  29. Prasad V, Kaestner V, Mailankody S. Cancer drugs approved based on biomarkers and not tumor type-FDA approval of pembrolizumab for mismatch repair-deficient solid cancers. JAMA Oncol 2018 ; 4: 157–158. [CrossRef] [PubMed] [Google Scholar]
  30. Spranger S, Gajewski TF. Impact of oncogenic pathways on evasion of antitumour immune responses. Nat Rev Cancer 2018 ; 18: 139–147. [Google Scholar]
  31. Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. Science. 2018 ; 359: 1350–1355. [Google Scholar]
  32. Ménétrier-Caux C, Ray-Coquard I, Blay JY, Caux C. Lymphopenia in cancer patients and its effects on response to immunotherapy: an opportunity for combination with cytokines?. J Immunother Cancer 2019 ; 7: 85. [Google Scholar]
  33. Yi M, Jiao D, Xu H, et al. Biomarkers for predicting efficacy of PD-1/PD-L1 inhibitors. Mol Cancer 2018 ; 17: 129. [CrossRef] [PubMed] [Google Scholar]
  34. Costantini A, Julie C, Dumenil C, et al. Predictive role of plasmatic biomarkers in advanced non-small cell lung cancer treated by nivolumab. Oncoimmunology 2018 ; 7: e1452581. [CrossRef] [PubMed] [Google Scholar]
  35. Chen G, Huang AC, Zhang W, et al. Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response. Nature 2018 ; 560: 382–386. [Google Scholar]
  36. Morello S, Capone M, Sorrentino C, et al. Soluble CD73 as biomarker in patients with metastatic melanoma patients treated with nivolumab. J Transl Med 2017 ; 15: 244. [CrossRef] [PubMed] [Google Scholar]
  37. Huang AC, Postow MA, Orlowski RJ, et al. T-cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature 2017 ; 545: 60–65. [Google Scholar]
  38. Shukla SA, Bachireddy P, Schilling B, et al. Cancer-germline antigen expression discriminates clinical outcome to CTLA-4 blockade. Cell 2018 ; 173: 624–33 e8. [Google Scholar]
  39. Spranger S, Gajewski TF. Impact of oncogenic pathways on evasion of antitumour immune responses. Nat Rev Cancer 2018 ; 18: 139–147. [Google Scholar]
  40. Ribas A, Dummer R, Puzanov I, et al. Oncolytic virotherapy promotes intratumoral T cell infiltration and improves anti-PD-1 immunotherapy. Cell 2017 ; 170: 1109–19.e10. [CrossRef] [PubMed] [Google Scholar]

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