46
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Single-cell profiling of tumor heterogeneity and the microenvironment in advanced non-small cell lung cancer

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Lung cancer is a highly heterogeneous disease. Cancer cells and cells within the tumor microenvironment together determine disease progression, as well as response to or escape from treatment. To map the cell type-specific transcriptome landscape of cancer cells and their tumor microenvironment in advanced non-small cell lung cancer (NSCLC), we analyze 42 tissue biopsy samples from stage III/IV NSCLC patients by single cell RNA sequencing and present the large scale, single cell resolution profiles of advanced NSCLCs. In addition to cell types described in previous single cell studies of early stage lung cancer, we are able to identify rare cell types in tumors such as follicular dendritic cells and T helper 17 cells. Tumors from different patients display large heterogeneity in cellular composition, chromosomal structure, developmental trajectory, intercellular signaling network and phenotype dominance. Our study also reveals a correlation of tumor heterogeneity with tumor associated neutrophils, which might help to shed light on their function in NSCLC.

          Abstract

          Comprehensive profiles of tumour and microenvironment are critical to understand heterogeneity in non-small cell lung cancer (NSCLC). Here, the authors profile 42 late-stage NSCLC patients with single-cell RNA-seq, revealing immune landscapes that are associated with cancer subtype or heterogeneity.

          Related collections

          Most cited references39

          • Record: found
          • Abstract: found
          • Article: not found

          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

            Abstract Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Pembrolizumab plus Chemotherapy in Metastatic Non–Small-Cell Lung Cancer

              First-line therapy for advanced non-small-cell lung cancer (NSCLC) that lacks targetable mutations is platinum-based chemotherapy. Among patients with a tumor proportion score for programmed death ligand 1 (PD-L1) of 50% or greater, pembrolizumab has replaced cytotoxic chemotherapy as the first-line treatment of choice. The addition of pembrolizumab to chemotherapy resulted in significantly higher rates of response and longer progression-free survival than chemotherapy alone in a phase 2 trial.
                Bookmark

                Author and article information

                Contributors
                caicunzhoudr@163.com
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                5 May 2021
                5 May 2021
                2021
                : 12
                : 2540
                Affiliations
                [1 ]GRID grid.24516.34, ISNI 0000000123704535, Department of Medical Oncology, Shanghai Pulmonary Hospital, , Tongji University School of Medicine, ; Shanghai, China
                [2 ]GRID grid.508212.c, Singleron Biotechnologies, ; Nanjing, Jiangsu China
                [3 ]GRID grid.24516.34, ISNI 0000000123704535, Department of Pathology, Shanghai Pulmonary Hospital, , Tongji University School of Medicine, ; Shanghai, China
                [4 ]GRID grid.411097.a, ISNI 0000 0000 8852 305X, Institute of Pathology, , University Hospital of Cologne, ; Cologne, Germany
                [5 ]GRID grid.6190.e, ISNI 0000 0000 8580 3777, Center for Molecular Medicine Cologne, , University of Cologne, ; Cologne, Germany
                Author information
                http://orcid.org/0000-0002-2424-0960
                http://orcid.org/0000-0001-8806-4786
                http://orcid.org/0000-0001-6234-8932
                http://orcid.org/0000-0002-6958-0766
                Article
                22801
                10.1038/s41467-021-22801-0
                8100173
                33953163
                d5d5cd23-1ea9-435b-bdba-04de3b70fc3a
                © The Author(s) 2021

                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 April 2020
                : 24 March 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003399, Science and Technology Commission of Shanghai Municipality (Shanghai Municipal Science and Technology Commission);
                Award ID: 19411950300
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 81871865
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100008750, Shanghai Hospital Development Center (SHDC);
                Award ID: SHDC2020CR4001
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                cancer genomics,cancer microenvironment,non-small-cell lung cancer,tumour heterogeneity

                Comments

                Comment on this article