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      Immune checkpoint inhibitors: recent progress and potential biomarkers

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          Abstract

          Cancer growth and progression are associated with immune suppression. Cancer cells have the ability to activate different immune checkpoint pathways that harbor immunosuppressive functions. Monoclonal antibodies that target immune checkpoints provided an immense breakthrough in cancer therapeutics. Among the immune checkpoint inhibitors, PD-1/PD-L1 and CTLA-4 inhibitors showed promising therapeutic outcomes, and some have been approved for certain cancer treatments, while others are under clinical trials. Recent reports have shown that patients with various malignancies benefit from immune checkpoint inhibitor treatment. However, mainstream initiation of immune checkpoint therapy to treat cancers is obstructed by the low response rate and immune-related adverse events in some cancer patients. This has given rise to the need for developing sets of biomarkers that predict the response to immune checkpoint blockade and immune-related adverse events. In this review, we discuss different predictive biomarkers for anti-PD-1/PD-L1 and anti-CTLA-4 inhibitors, including immune cells, PD-L1 overexpression, neoantigens, and genetic and epigenetic signatures. Potential approaches for further developing highly reliable predictive biomarkers should facilitate patient selection for and decision-making related to immune checkpoint inhibitor-based therapies.

          Cancer immunotherapy: Markers of success

          Biomarkers that predict a patient’s response to cancer immunotherapy are being developed, and may allow individual tailoring of therapies. Cancer cells can suppress the immune system by activating immune checkpoints, signals that stop the immune system from attacking the host. Immunotherapy, a recently developed treatment, inactivates immune checkpoints, restoring the patient’s immune response against the tumor. Although promising, immunotherapy has a low response rate, and sometimes triggers severe auto-immune reactions. Eyad Elkord at Qatar Biomedical Research Institute in Qatar and coworkers have reviewed biomarkers that could be used to predict individual effects of immunotherapy, identifying nonresponders and preventing adverse immune reactions. They discuss markers based on factors such as immune response level and individual tumor genetics, among others. With further research and testing, these biomarkers could improve the efficacy of this promising new cancer therapy.

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          Most cited references39

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          Effector memory T cells, early metastasis, and survival in colorectal cancer.

          The role of tumor-infiltrating immune cells in the early metastatic invasion of colorectal cancer is unknown. We studied pathological signs of early metastatic invasion (venous emboli and lymphatic and perineural invasion) in 959 specimens of resected colorectal cancer. The local immune response within the tumor was studied by flow cytometry (39 tumors), low-density-array real-time polymerase-chain-reaction assay (75 tumors), and tissue microarrays (415 tumors). Univariate analysis showed significant differences in disease-free and overall survival according to the presence or absence of histologic signs of early metastatic invasion (P<0.001). Multivariate Cox analysis showed that an early conventional pathological tumor-node-metastasis stage (P<0.001) and the absence of early metastatic invasion (P=0.04) were independently associated with increased survival. As compared with tumors with signs of early metastatic invasion, tumors without such signs had increased infiltrates of immune cells and increased levels of messenger RNA (mRNA) for products of type 1 helper effector T cells (CD8, T-BET [T-box transcription factor 21], interferon regulatory factor 1, interferon-gamma, granulysin, and granzyme B) but not increased levels of inflammatory mediators or immunosuppressive molecules. The two types of tumors had significant differences in the levels of expression of 65 combinations of T-cell markers, and hierarchical clustering showed that markers of T-cell migration, activation, and differentiation were increased in tumors without signs of early metastatic invasion. The latter type of tumors also had increased numbers of CD8+ T cells, ranging from early memory (CD45RO+CCR7-CD28+CD27+) to effector memory (CD45RO+CCR7-CD28-CD27-) T cells. The presence of high levels of infiltrating memory CD45RO+ cells, evaluated immunohistochemically, correlated with the absence of signs of early metastatic invasion, a less advanced pathological stage, and increased survival. Signs of an immune response within colorectal cancers are associated with the absence of pathological evidence of early metastatic invasion and with prolonged survival. Copyright 2005 Massachusetts Medical Society.
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            Mechanisms of resistance to immune checkpoint inhibitors

            Immune checkpoint inhibitors (ICI) targeting CTLA-4 and the PD-1/PD-L1 axis have shown unprecedented clinical activity in several types of cancer and are rapidly transforming the practice of medical oncology. Whereas cytotoxic chemotherapy and small molecule inhibitors (‘targeted therapies’) largely act on cancer cells directly, immune checkpoint inhibitors reinvigorate anti-tumour immune responses by disrupting co-inhibitory T-cell signalling. While resistance routinely develops in patients treated with conventional cancer therapies and targeted therapies, durable responses suggestive of long-lasting immunologic memory are commonly seen in large subsets of patients treated with ICI. However, initial response appears to be a binary event, with most non-responders to single-agent ICI therapy progressing at a rate consistent with the natural history of disease. In addition, late relapses are now emerging with longer follow-up of clinical trial populations, suggesting the emergence of acquired resistance. As robust biomarkers to predict clinical response and/or resistance remain elusive, the mechanisms underlying innate (primary) and acquired (secondary) resistance are largely inferred from pre-clinical studies and correlative clinical data. Improved understanding of molecular and immunologic mechanisms of ICI response (and resistance) may not only identify novel predictive and/or prognostic biomarkers, but also ultimately guide optimal combination/sequencing of ICI therapy in the clinic. Here we review the emerging clinical and pre-clinical data identifying novel mechanisms of innate and acquired resistance to immune checkpoint inhibition.
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              High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy

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                Author and article information

                Contributors
                +974 4454 2367 , eelkord@hbku.edu.qa , eyad.elkord@manchester.ac.uk
                Journal
                Exp Mol Med
                Exp. Mol. Med
                Experimental & Molecular Medicine
                Nature Publishing Group UK (London )
                1226-3613
                2092-6413
                13 December 2018
                13 December 2018
                December 2018
                : 50
                : 12
                : 165
                Affiliations
                [1 ]ISNI 0000 0001 0516 2170, GRID grid.418818.c, Cancer Research Center, Qatar Biomedical Research Institute, College of Science and Engineering, , Hamad Bin Khalifa University, Qatar Foundation, ; Doha, Qatar
                [2 ]ISNI 0000000121662407, GRID grid.5379.8, Institute of Cancer Sciences, University of Manchester, ; Manchester, UK
                Author information
                http://orcid.org/0000-0002-3868-0318
                Article
                191
                10.1038/s12276-018-0191-1
                6292890
                30546008
                8bd3ede8-80a0-4d3c-bfdc-3575b7193d72
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 June 2018
                : 22 August 2018
                : 19 September 2018
                Funding
                Funded by: FundRef https://doi.org/10.13039/100007458, Qatar Foundation (Qatar Foundation for Education, Science and Community Development);
                Award ID: VR04
                Award Recipient :
                Categories
                Review Article
                Custom metadata
                © The Author(s) 2018

                Molecular medicine
                Molecular medicine

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