11
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Spatial omics: Navigating to the golden era of cancer research

      review-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

          The idea that tumour microenvironment (TME) is organised in a spatial manner will not surprise many cancer biologists; however, systematically capturing spatial architecture of TME is still not possible until recent decade. The past five years have witnessed a boom in the research of high‐throughput spatial techniques and algorithms to delineate TME at an unprecedented level. Here, we review the technological progress of spatial omics and how advanced computation methods boost multi‐modal spatial data analysis. Then, we discussed the potential clinical translations of spatial omics research in precision oncology, and proposed a transfer of spatial ecological principles to cancer biology in spatial data interpretation. So far, spatial omics is placing us in the golden age of spatial cancer research. Further development and application of spatial omics may lead to a comprehensive decoding of the TME ecosystem and bring the current spatiotemporal molecular medical research into an entirely new paradigm.

          Abstract

          1. Spatial omics is transforming our understanding of the cancer ecosystem at the systemic level.

          2. The integration of spatial omics and single‐cell omics can fundamentally improve our understanding of tumourigenesis and cancer microenvironment.

          3. Generating the spatial atlas of human cancers across multiple omics and timescales will potentially pioneer the revolution of spatiotemporal molecular medicine.

          Related collections

          Most cited references151

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

          Integrating single-cell transcriptomic data across different conditions, technologies, and species

          Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            A Mathematical Theory of Communication

            C. Shannon (1948)
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Microenvironmental regulation of tumor progression and metastasis.

              Cancers develop in complex tissue environments, which they depend on for sustained growth, invasion and metastasis. Unlike tumor cells, stromal cell types within the tumor microenvironment (TME) are genetically stable and thus represent an attractive therapeutic target with reduced risk of resistance and tumor recurrence. However, specifically disrupting the pro-tumorigenic TME is a challenging undertaking, as the TME has diverse capacities to induce both beneficial and adverse consequences for tumorigenesis. Furthermore, many studies have shown that the microenvironment is capable of normalizing tumor cells, suggesting that re-education of stromal cells, rather than targeted ablation per se, may be an effective strategy for treating cancer. Here we discuss the paradoxical roles of the TME during specific stages of cancer progression and metastasis, as well as recent therapeutic attempts to re-educate stromal cells within the TME to have anti-tumorigenic effects.
                Bookmark

                Author and article information

                Contributors
                gaoqiang@fudan.edu.cn
                Journal
                Clin Transl Med
                Clin Transl Med
                10.1002/(ISSN)2001-1326
                CTM2
                Clinical and Translational Medicine
                John Wiley and Sons Inc. (Hoboken )
                2001-1326
                18 January 2022
                January 2022
                : 12
                : 1 ( doiID: 10.1002/ctm2.v12.1 )
                : e696
                Affiliations
                [ 1 ] Center for Tumor Diagnosis & Therapy and Department of Cancer Center Jinshan Hospital and Jinshan Branch of Zhongshan Hospital Zhongshan Hospital Fudan University Shanghai 200540 China
                [ 2 ] Department of Liver Surgery and Transplantation and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education) Liver Cancer Institute Zhongshan Hospital Fudan University Shanghai China
                [ 3 ] Department of Pulmonary and Critical Care Medicine Zhongshan Hospital Institute for Clinical Science Shanghai Institute of Clinical Bioinformatics Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases Jinshan Hospital Centre for Tumor Diagnosis and Therapy Fudan University Shanghai Medical College Shanghai China
                [ 4 ] Key Laboratory of Medical Epigenetics and Metabolism Institutes of Biomedical Sciences, Fudan University Shanghai China
                [ 5 ] State Key Laboratory of Genetic Engineering Fudan University Shanghai China
                Author notes
                [*] [* ] Correspondence

                Qiang Gao, Department of Cancer Center, Center for Tumor Diagnosis & Therapy, Jinshan Hospital and Jinshan Branch of Zhongshan Hospital, Fudan University, Shanghai 200540, China; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China.

                Email: gaoqiang@ 123456fudan.edu.cn

                Author information
                https://orcid.org/0000-0001-9473-546X
                https://orcid.org/0000-0002-8406-7928
                https://orcid.org/0000-0002-6695-9906
                Article
                CTM2696
                10.1002/ctm2.696
                8764875
                35040595
                ccd304b7-6f73-46f6-bb56-0b83bcbc6dd4
                © 2022 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 December 2021
                : 19 July 2021
                : 20 December 2021
                Page count
                Figures: 5, Tables: 1, Pages: 18, Words: 10039
                Funding
                Funded by: Shanghai Municipal Key Clinical Specialty
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 81961128025
                Award ID: 91942313
                Funded by: Program of Shanghai Academic Research Leader , doi 10.13039/501100012247;
                Award ID: 19XD1420700
                Funded by: Sanming Project of Medicine in Shenzhen , doi 10.13039/501100012151;
                Award ID: SZSM202003009
                Categories
                Review
                Reviews
                Custom metadata
                2.0
                January 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.7.0 mode:remove_FC converted:18.01.2022

                Medicine
                cancer ecology,single‐cell rna‐seq,spatial omics,tumour microenvironment
                Medicine
                cancer ecology, single‐cell rna‐seq, spatial omics, tumour microenvironment

                Comments

                Comment on this article