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      Collagen promotes anti-PD-1/PD-L1 resistance in cancer through LAIR1-dependent CD8 + T cell exhaustion

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          Abstract

          Tumor extracellular matrix has been associated with drug resistance and immune suppression. Here, proteomic and RNA profiling reveal increased collagen levels in lung tumors resistant to PD-1/PD-L1 blockade. Additionally, elevated collagen correlates with decreased total CD8 + T cells and increased exhausted CD8 + T cell subpopulations in murine and human lung tumors. Collagen-induced T cell exhaustion occurs through the receptor LAIR1, which is upregulated following CD18 interaction with collagen, and induces T cell exhaustion through SHP-1. Reduction in tumor collagen deposition through LOXL2 suppression increases T cell infiltration, diminishes exhausted T cells, and abrogates resistance to anti-PD-L1. Abrogating LAIR1 immunosuppression through LAIR2 overexpression or SHP-1 inhibition sensitizes resistant lung tumors to anti-PD-1. Clinically, increased collagen, LAIR1, and TIM-3 expression in melanoma patients treated with PD-1 blockade predict poorer survival and response. Our study identifies collagen and LAIR1 as potential markers for immunotherapy resistance and validates multiple promising therapeutic combinations.

          Abstract

          Tumor extracellular matrix has been associated with cancer progression, therapy resistance and immune suppression. Here, the authors show that collagen generates resistance to PD-1/PD-L1 immunotherapy by upregulating LAIR1 expression and downstream signaling, leading to increased CD8+ T cell exhaustion.

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          Most cited references39

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          Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.

          Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies. Copyright © 2014 Elsevier Inc. All rights reserved.
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            TGF-β-associated extracellular matrix genes link cancer-associated fibroblasts to immune evasion and immunotherapy failure

            The extracellular matrix (ECM) is a key determinant of cancer progression and prognosis. Here we report findings from one of the largest pan-cancer analyses of ECM gene dysregulation in cancer. We define a distinct set of ECM genes upregulated in cancer (C-ECM) and linked to worse prognosis. We found that the C-ECM transcriptional programme dysregulation is correlated with the activation of TGF-β signalling in cancer-associated fibroblasts and is linked to immunosuppression in otherwise immunologically active tumours. Cancers that activate this programme carry distinct genomic profiles, such as BRAF, SMAD4 and TP53 mutations and MYC amplification. Finally, we show that this signature is a predictor of the failure of PD-1 blockade and outperforms previously-proposed biomarkers. Thus, our findings identify a distinct transcriptional pattern of ECM genes in operation across cancers that may be potentially targeted, pending preclinical validation, using TGF-β blockade to enhance responses to immune-checkpoint blockade.
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              A pan-cancer proteomic perspective on The Cancer Genome Atlas

              Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumors. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyze 3,467 patient samples from 11 TCGA “Pan-Cancer” diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data is integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumor lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumor lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome.
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                Author and article information

                Contributors
                dlgibbon@mdanderson.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                9 September 2020
                9 September 2020
                2020
                : 11
                : 4520
                Affiliations
                [1 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Thoracic/Head and Neck Medical Oncology, , The University of Texas MD Anderson Cancer Center, ; Houston, TX 77030 USA
                [2 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Bioinformatics and Computational Biology, , The University of Texas MD Anderson Cancer Center, ; Houston, TX 77030 USA
                [3 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Department of Medicine, , UCSF Cardiovascular Research Institute, ; San Francisco, CA USA
                [4 ]GRID grid.10698.36, ISNI 0000000122483208, Oral and Craniofacial Health Sciences, , University of North Carolina at Chapel Hill, ; Chapel Hill, NC USA
                [5 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Translational Molecular Pathology, , The University of Texas MD Anderson Cancer Center, ; Houston, TX 77030 USA
                [6 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Molecular and Cellular Oncology, , The University of Texas MD Anderson Cancer Center, ; Houston, TX 77030 USA
                Author information
                http://orcid.org/0000-0001-6995-4492
                http://orcid.org/0000-0002-5398-0802
                http://orcid.org/0000-0002-0780-2677
                http://orcid.org/0000-0002-5280-5527
                http://orcid.org/0000-0003-2105-5556
                http://orcid.org/0000-0002-1253-630X
                http://orcid.org/0000-0001-9068-1636
                Article
                18298
                10.1038/s41467-020-18298-8
                7481212
                31911652
                39e6e43c-7cba-4c70-a30d-fbace77f30eb
                © The Author(s) 2020

                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
                : 31 July 2019
                : 12 August 2020
                Funding
                Funded by: CPRIT RP150405, NIH R37 CA214609, CPRIT-MIRA RP160652, UT Lung Cancer SPORE NCI P50 CA070907, CCSG CA016672
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                cancer microenvironment,cancer immunotherapy,lung cancer,tumour immunology
                Uncategorized
                cancer microenvironment, cancer immunotherapy, lung cancer, tumour immunology

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