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      Tissues and Tumor Microenvironment (TME) in 3D: Models to Shed Light on Immunosuppression in Cancer

      review-article
      1 , * , 2 , 3 , *
      Cells
      MDPI
      organoid, immunosuppression, tumor microenvironment, MDSC, humanized mouse models

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          Abstract

          Immunosuppression in cancer has emerged as a major hurdle to immunotherapy efforts. Immunosuppression can arise from oncogene-induced signaling within the tumor as well as from tumor-associated immune cells. Understanding various mechanisms by which the tumor can undermine and evade therapy is critical in improving current cancer immunotherapies. While mouse models have allowed for the characterization of key immune cell types and their role in tumor development, extrapolating these mechanisms to patients has been challenging. There is need for better models to unravel the effects of genetic alterations inherent in tumor cells and immune cells isolated from tumors on tumor growth and to investigate the feasibility of immunotherapy. Three-dimensional (3D) organoid model systems have developed rapidly over the past few years and allow for incorporation of components of the tumor microenvironment such as immune cells and the stroma. This bears great promise for derivation of patient-specific models in a dish for understanding and determining the impact on personalized immunotherapy. In this review, we will highlight the significance of current experimental models employed in the study of tumor immunosuppression and evaluate current tumor organoid-immune cell co-culture systems and their potential impact in shedding light on cancer immunosuppression.

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          Most cited references150

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          The blockade of immune checkpoints in cancer immunotherapy.

          Among the most promising approaches to activating therapeutic antitumour immunity is the blockade of immune checkpoints. Immune checkpoints refer to a plethora of inhibitory pathways hardwired into the immune system that are crucial for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses in peripheral tissues in order to minimize collateral tissue damage. It is now clear that tumours co-opt certain immune-checkpoint pathways as a major mechanism of immune resistance, particularly against T cells that are specific for tumour antigens. Because many of the immune checkpoints are initiated by ligand-receptor interactions, they can be readily blocked by antibodies or modulated by recombinant forms of ligands or receptors. Cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) antibodies were the first of this class of immunotherapeutics to achieve US Food and Drug Administration (FDA) approval. Preliminary clinical findings with blockers of additional immune-checkpoint proteins, such as programmed cell death protein 1 (PD1), indicate broad and diverse opportunities to enhance antitumour immunity with the potential to produce durable clinical responses.
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            Cancer immunotherapy using checkpoint blockade

            The release of negative regulators of immune activation (immune checkpoints) that limit antitumor responses has resulted in unprecedented rates of long-lasting tumor responses in patients with a variety of cancers. This can be achieved by antibodies blocking the cytotoxic T lymphocyte antigen-4 (CTLA-4) or the programmed death-1 (PD-1) pathway, either alone or in combination. The main premise for inducing an immune response is the pre-existence of antitumor T cells that were limited by specific immune checkpoints. Most patients who have tumor responses maintain long lasting disease control, yet one third of patients relapse. Mechanisms of acquired resistance are currently poorly understood, but evidence points to alterations that converge on the antigen presentation and interferon gamma signaling pathways. New generation combinatorial therapies may overcome resistance mechanisms to immune checkpoint therapy.
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              Understanding the tumor immune microenvironment (TIME) for effective therapy

              The clinical successes in immunotherapy have been both astounding and at the same time unsatisfactory. Countless patients with varied tumor types have seen pronounced clinical response with immunotherapeutic intervention; however, many more patients have experienced minimal or no clinical benefit when provided the same treatment. As technology has advanced, so has the understanding of the complexity and diversity of the immune context of the tumor microenvironment and its influence on response to therapy. It has been possible to identify different subclasses of immune environment that have an influence on tumor initiation and response and therapy; by parsing the unique classes and subclasses of tumor immune microenvironment (TIME) that exist within a patient’s tumor, the ability to predict and guide immunotherapeutic responsiveness will improve, and new therapeutic targets will be revealed.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Cells
                Cells
                cells
                Cells
                MDPI
                2073-4409
                07 April 2021
                April 2021
                : 10
                : 4
                : 831
                Affiliations
                [1 ]p53Lab, Agency for Science, Technology and Research (A*STAR), 8A Biomedical Grove, Neuros/Immunos, #06-04/05, Singapore 138648, Singapore
                [2 ]Laboratory for Translational and Molecular Imaging (LTMI), Cancer and Stem Cell Biology Programme, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore
                [3 ]Cancer Immunotherapy Imaging “CITI” Programme, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore
                Author notes
                Author information
                https://orcid.org/0000-0002-0094-4285
                Article
                cells-10-00831
                10.3390/cells10040831
                8067689
                33917037
                a59c9bf8-559e-425b-aaa5-a848b716e0a5
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 03 February 2021
                : 02 April 2021
                Categories
                Review

                organoid,immunosuppression,tumor microenvironment,mdsc,humanized mouse models

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