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      Transcriptional Landscape of Human Tissue Lymphocytes Unveils Uniqueness of Tumor-Infiltrating T Regulatory Cells

      research-article
      1 , 13 , 1 , 13 , 1 , 13 , 1 , 13 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 2 , 4 , 2 , 4 , 3 , 3 , 4 , 5 , 5 , 6 , 6 , 7 , 7 , 7 , 8 , 8 , 8 , 9 , 1 , 1 , 10 , 1 , 11 , , 1 , 12 , 14 , ∗∗
      Immunity
      Cell Press

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          Summary

          Tumor-infiltrating regulatory T lymphocytes (Treg) can suppress effector T cells specific for tumor antigens. Deeper molecular definitions of tumor-infiltrating-lymphocytes could thus offer therapeutic opportunities. Transcriptomes of T helper 1 (Th1), Th17, and Treg cells infiltrating colorectal or non-small-cell lung cancers were compared to transcriptomes of the same subsets from normal tissues and validated at the single-cell level. We found that tumor-infiltrating Treg cells were highly suppressive, upregulated several immune-checkpoints, and expressed on the cell surfaces specific signature molecules such as interleukin-1 receptor 2 (IL1R2), programmed death (PD)-1 Ligand1, PD-1 Ligand2, and CCR8 chemokine, which were not previously described on Treg cells. Remarkably, high expression in whole-tumor samples of Treg cell signature genes, such as LAYN, MAGEH1, or CCR8, correlated with poor prognosis. Our findings provide insights into the molecular identity and functions of human tumor-infiltrating Treg cells and define potential targets for tumor immunotherapy.

          Highlights

          • Transcriptome analysis performed on tumor-resident CD4 + Th1, Th17, and Treg cells

          • Tumor-infiltrating Treg cells are defined by the expression of signature genes

          • Treg-specific signature genes correlate with patients’ survival in both CRC and NSCLC

          Abstract

          Tumor-infiltrating regulatory T cells can suppress effector T cells specific for tumor antigens. De Simone et al. (2016) demonstrate that tumor-infiltrating Treg cells display specific gene signatures that were also validated at the single-cell level. These data can contribute to dissect the molecular networks underlying the biology of tumor-infiltrating Treg cells. As part of the IHEC consortium, this study integrates genetic, epigenetic, and transcriptomic profiling in three immune cell types from nearly 200 people to characterize the distinct and cooperative contributions of diverse genomic inputs to transcriptional variation. Explore the Cell Press IHEC webportal at www.cell.com/consortium/IHEC.

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          Most cited references23

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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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            Anti-CTLA-4 antibodies of IgG2a isotype enhance antitumor activity through reduction of intratumoral regulatory T cells.

            Antitumor activity of CTLA-4 antibody blockade is thought to be mediated by interfering with the negative regulation of T-effector cell (Teff) function resulting from CTLA-4 engagement by B7-ligands. In addition, a role for CTLA-4 on regulatory T cells (Treg), wherein CTLA-4 loss or inhibition results in reduced Treg function, may also contribute to antitumor responses by anti-CTLA-4 treatment. We have examined the role of the immunoglobulin constant region on the antitumor activity of anti-CTLA-4 to analyze in greater detail the mechanism of action of anti-CTLA-4 antibodies. Anti-CTLA-4 antibody containing the murine immunoglobulin G (IgG)2a constant region exhibits enhanced antitumor activity in subcutaneous established MC38 and CT26 colon adenocarcinoma tumor models compared with anti-CTLA-4 containing the IgG2b constant region. Interestingly, anti-CTLA-4 antibodies containing mouse IgG1 or a mutated mouse IgG1-D265A, which eliminates binding to all Fcγ receptors (FcγR), do not show antitumor activity in these models. Assessment of Teff and Treg populations at the tumor and in the periphery showed that anti-CTLA-4-IgG2a mediated a rapid and dramatic reduction of Tregs at the tumor site, whereas treatment with each of the isotypes expanded Tregs in the periphery. Expansion of CD8(+) Teffs is observed with both the IgG2a and IgG2b anti-CTLA-4 isotypes, resulting in a superior Teff to Treg ratio for the IgG2a isotype. These data suggest that anti-CTLA-4 promotes antitumor activity by a selective reduction of intratumoral Tregs along with concomitant activation of Teffs. ©2013 AACR.
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              Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer.

              Staging inadequately predicts metastatic risk in patients with colon cancer. We used a gene expression profile derived from invasive, murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify patients with colon cancer at risk of recurrence. This phase 1, exploratory biomarker study used 55 patients with colorectal cancer from Vanderbilt Medical Center (VMC) as the training dataset and 177 patients from the Moffitt Cancer Center as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined with comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A metastasis score derived from the biologically based classifier was tested in the Moffitt dataset. A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathologic stages and specifically in stage II and stage III patients. The metastasis score was shown to independently predict risk of cancer recurrence and death in univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk of cancer recurrence (hazard ratio, 4.7; 95% confidence interval, 1.566-14.05). Furthermore, the metastasis score identified patients with stage III disease whose 5-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not increase survival time. A gene expression profile identified from an experimental model of colon cancer metastasis predicted cancer recurrence and death, independently of conventional measures, in patients with colon cancer. Copyright 2010 AGA Institute. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Immunity
                Immunity
                Immunity
                Cell Press
                1074-7613
                1097-4180
                15 November 2016
                15 November 2016
                : 45
                : 5
                : 1135-1147
                Affiliations
                [1 ]Istituto Nazionale Genetica Molecolare INGM ‘Romeo ed Enrica Invernizzi,’ Milan 20122, Italy
                [2 ]Division of Pathology, IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan 20122, Italy
                [3 ]Division of Thoracic Surgery, IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan 20122, Italy
                [4 ]Department of Pathophysiology and Organ Transplantation, Università degli Studi di Milano, Milano 20122, Italy
                [5 ]Department of Pathology, San Gerardo Hospital, Monza 20900, Italy
                [6 ]Department of Surgery, San Gerardo Hospital, Monza 20900, Italy
                [7 ]School of Medicine and Surgery, Milano-Bicocca University, Monza 20900 Italy
                [8 ]UO Chirurgia Epatobiliopancreatica e Digestiva Ospedale San Paolo, Milan 20142, Italy
                [9 ]Department of Health Sciences, Università degli Studi di Milano, Milano 20122, Italy
                [10 ]Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, The Netherlands
                [11 ]Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milano 20122, Italy
                [12 ]Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milano 20129, Italy
                Author notes
                []Corresponding author abrignani@ 123456ingm.org
                [∗∗ ]Corresponding author pagani@ 123456ingm.org
                [13]

                Co-first author

                [14]

                Lead contact

                Article
                S1074-7613(16)30432-0
                10.1016/j.immuni.2016.10.021
                5119953
                27851914
                fc7da3d5-0e82-478f-b2aa-30f5d932c4bd
                © 2016 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 3 March 2016
                : 7 September 2016
                : 4 October 2016
                Categories
                Resource

                Immunology
                Immunology

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