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      Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma

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          Abstract

          Advanced metastatic cancer poses utmost clinical challenges and may present molecular and cellular features distinct from an early-stage cancer. Herein, we present single-cell transcriptome profiling of metastatic lung adenocarcinoma, the most prevalent histological lung cancer type diagnosed at stage IV in over 40% of all cases. From 208,506 cells populating the normal tissues or early to metastatic stage cancer in 44 patients, we identify a cancer cell subtype deviating from the normal differentiation trajectory and dominating the metastatic stage. In all stages, the stromal and immune cell dynamics reveal ontological and functional changes that create a pro-tumoral and immunosuppressive microenvironment. Normal resident myeloid cell populations are gradually replaced with monocyte-derived macrophages and dendritic cells, along with T-cell exhaustion. This extensive single-cell analysis enhances our understanding of molecular and cellular dynamics in metastatic lung cancer and reveals potential diagnostic and therapeutic targets in cancer-microenvironment interactions.

          Abstract

          Understanding the mechanisms that lead to lung adenocarcinoma metastasis is important for identifying new therapeutics. Here, the authors document the changes in the transcriptome of human lung adenocarcinoma using single-cell sequencing and link cancer cell signatures to immune cell dynamics.

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          Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage

          Tissue fibrosis is a major cause of mortality that results from the deposition of matrix proteins by an activated mesenchyme. Macrophages accumulate in fibrosis, but the role of specific subgroups in supporting fibrogenesis has not been investigated in vivo. Here we used single-cell RNA sequencing (scRNA-seq) to characterize the heterogeneity of macrophages in bleomycin-induced lung fibrosis in mice. A novel computational framework for the annotation of scRNA-seq by reference to bulk transcriptomes (SingleR) enabled the subclustering of macrophages and revealed a disease-associated subgroup with a transitional gene expression profile intermediate between monocyte-derived and alveolar macrophages. These CX3CR1+SiglecF+ transitional macrophages localized to the fibrotic niche and had a profibrotic effect in vivo. Human orthologues of genes expressed by the transitional macrophages were upregulated in samples from patients with idiopathic pulmonary fibrosis. Thus, we have identified a pathological subgroup of transitional macrophages that are required for the fibrotic response to injury.
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            Microglia and macrophages in brain homeostasis and disease

            Microglia and non-parenchymal macrophages in the brain are mononuclear phagocytes that are increasingly recognized to be essential players in the development, homeostasis and diseases of the central nervous system. With the availability of new genetic, molecular and pharmacological tools, considerable advances have been made towards our understanding of the embryonic origins, developmental programmes and functions of these cells. These exciting discoveries, some of which are still controversial, also raise many new questions, which makes brain macrophage biology a fast-growing field at the intersection of neuroscience and immunology. Here, we review the current knowledge of how and where brain macrophages are generated, with a focus on parenchymal microglia. We also discuss their normal functions during development and homeostasis, the disturbance of which may lead to various neurodegenerative and neuropsychiatric diseases.
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              Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses

              To guide the design of immunotherapy strategies for patients with early stage lung tumors, we developed a multiscale immune profiling strategy to map the immune landscape of early lung adenocarcinoma lesions to search for tumor-driven immune changes. Utilizing a barcoding method that allows a simultaneous single cell analysis of the tumor, non-involved lung and blood cells together with multiplex tissue imaging to assess spatial cell distribution, we provide a detailed immune cell atlas of early lung tumors. We show that stage I lung adenocarcinoma lesions already harbor significantly altered T cell and NK cell compartments. Moreover, we identified changes in tumor infiltrating myeloid cell (TIM) subsets that likely compromise anti-tumor T cell immunity. Paired single cell analyses thus offer valuable knowledge of tumor-driven immune changes, providing a powerful tool for the rational design of immune therapies. Comparing single tumor cells with adjacent normal tissue and blood from patients with lung adenocarcinoma charts early changes in tumor immunity and provides insights to guide immunotherapy design.
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                Author and article information

                Contributors
                silk.ahn@samsung.com
                haeocklee@catholic.ac.kr
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                8 May 2020
                8 May 2020
                2020
                : 11
                : 2285
                Affiliations
                [1 ]ISNI 0000 0001 0640 5613, GRID grid.414964.a, Samsung Genome Institute, , Samsung Medical Center, ; Seoul, 06351 Korea
                [2 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Department of Molecular Cell Biology, , Sungkyunkwan University School of Medicine, ; Suwon, 16419 Korea
                [3 ]ISNI 0000 0004 0470 4224, GRID grid.411947.e, Department of Biomedicine and Health Sciences, Graduate School, , The Catholic University of Korea, ; Seoul, 06591 Korea
                [4 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; Seoul, 06351 Korea
                [5 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; 06351 Seoul, Korea
                [6 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences &Technology, , Sungkyunkwan University, ; Seoul, 06355 Korea
                [7 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Department of Neurosurgery, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; Seoul, 06351 Korea
                [8 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Department of Pathology, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; Seoul, 06351 Korea
                [9 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Samsung Biomedical Research Institute, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; Seoul, 06351 Korea
                [10 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Laboratory of Cancer Genomics and Molecular Pathology, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; Seoul, 06351 Korea
                [11 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Department of Pathology and Translational Genomics, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; Seoul, 06351 Korea
                [12 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Division of Haematology-Oncology, Department of Medicine, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; Seoul, 06351 Korea
                Author information
                http://orcid.org/0000-0003-3202-750X
                http://orcid.org/0000-0002-1642-8111
                http://orcid.org/0000-0001-6683-433X
                http://orcid.org/0000-0002-8081-4121
                http://orcid.org/0000-0002-3626-9576
                http://orcid.org/0000-0003-4234-0380
                http://orcid.org/0000-0002-5740-9654
                http://orcid.org/0000-0001-5123-0322
                Article
                16164
                10.1038/s41467-020-16164-1
                7210975
                32385277
                3732531e-52c1-4ef2-8da3-376487b82129
                © 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
                : 22 September 2019
                : 17 April 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003725, National Research Foundation of Korea (NRF);
                Award ID: NRF-2017M3C9A6044636
                Award ID: NFR-2017M3C9A6044633
                Award Recipient :
                Categories
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                Custom metadata
                © The Author(s) 2020

                Uncategorized
                cancer microenvironment,non-small-cell lung cancer,tumour heterogeneity,data mining

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