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The evolving landscape of 'next-generation' immune checkpoint inhibitors: A review

期刊

EUROPEAN JOURNAL OF CANCER
卷 117, 期 -, 页码 14-31

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ejca.2019.04.035

关键词

Next generation; immune-checkpoints; LAG3; TIGIT; TIM3; 4-1BB; IDO1; GITR; Colony stimulating factor-1 (CSF-1) pathway; TLR, RLR and cGAS/STING

类别

资金

  1. European Society of Medical Oncology fellowship program
  2. Fondazione IEO-Centro Cardiologico Monzino Funding fellowship program

向作者/读者索取更多资源

'First-generation' immune checkpoint inhibitors targeting Cytotoxic T-Lymphocyte Antigen 4 (CTLA4) and Programmed death-ligand 1 (PD(L)1) have undoubtedly revolutionised the treatment of multiple cancers in the advanced setting. Targeting signalling pathways other than core inhibitory modules may strongly impact the outcome of the antitumour immune response. Drugs targeting these pathways ('next-generation' immune modulators, NGIMs) constitute a major frontier in translational research and have generated unprecedented scientific and financial investment. Here, we systematically reviewed published literature, abstracts from major cancer conferences and pharma pipelines to identify NGIMs that have reached clinical development. We identified 107 molecules targeting 16 pathways, which we classified into 6 groups according to function (inhibitory vs stimulatory) and cell of predominant expression (lymphoid, non-lymphoid and natural killer). We identified all registered past and ongoing clinical trials (n = 428). We summarise the preclinical rationale for these targets, extracting translationally relevant information, and review published and preliminary clinical results. Some targets like indoleamine-2,3-dioxygenase 1, lymphocyte activation gene-3 and IL15 have experienced exceptional growth of interest, measured in terms of activated studies and expected patient enrolment over time. We conclude that in this vast and rapidly changing drug development landscape, novel trial designs and better biomarker identification are necessary to optimise resource allocation (C) 2019 Elsevier Ltd. All rights reserved.

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