Advertisement
Trends in Cancer
This journal offers authors two options (open access or subscription) to publish research

Multicellular modules as clinical diagnostic and therapeutic targets

  • Marc-A. Baertsch
    Affiliations
    Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA

    Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA

    Department of Hematology, Oncology and Rheumatology, Heidelberg University Hospital, 69121 Heidelberg, Germany
    Search for articles by this author
  • Garry P. Nolan
    Correspondence
    Correspondence:
    Affiliations
    Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA

    Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA
    Search for articles by this author
  • John W. Hickey
    Correspondence
    Correspondence:
    Affiliations
    Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA

    Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA
    Search for articles by this author
Published:December 03, 2021DOI:https://doi.org/10.1016/j.trecan.2021.11.004

      Highlights

      • Multiplex tissue imaging enables in situ detection of more than 50 proteins or 1000 RNAs in the same tissue section with single cell resolution.
      • Analyses of spatially resolved cellular phenotypes, interactions, and neighborhoods have revealed mechanistic insights into physiological and pathological processes.
      • Multicellular, spatially informed signatures can serve as disease biomarkers and provide new targets for therapeutic development.
      The complex determinants of health and disease can be determined when approached as a system of interactions of biological agents at different scales. Similar to the physicochemical properties that govern nucleic acids and proteins, there should be a finite set of rules that dictate the behavior of cells to form tissues. Thus, the occurrence of disease can be seen as flaws in processes that are governed by rules pertaining to multicellular structures. Multiplexed imaging is a technology that connects information that bridges multiple biological scales (i.e., molecules, cells, and tissues) and enables elucidation of rules associated with the formation of multicellular structures. Uncovering important multicellular structures associated with disease will propel a wave of development of new categories of diagnostics and therapeutics.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access

      Read-It-Now

      Purchase access to all full-text HTML articles for 6 or 36 hr at a low cost. Click here to explore this opportunity.

      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Trends in Cancer
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Tan W.C.C.
        • et al.
        Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy.
        Cancer Commun. 2020; 40: 135-153
        • Rozenblatt-Rosen O.
        • et al.
        The Human Tumor Atlas Network: charting tumor transitions across space and time at single-cell resolution.
        Cell. 2020; 181: 236-249
        • HuBMAP Consortium
        The human body at cellular resolution: the NIH Human Biomolecular Atlas Program.
        Nature. 2019; 574: 187-192
        • Regev A.
        • et al.
        The human cell atlas.
        eLife. 2017; 6e27041
        • Keren L.
        • et al.
        A structured tumor-immune microenvironment in triple negative breast cancer revealed by multiplexed ion beam imaging.
        Cell. 2018; 174: 1373-1387
        • Schürch C.M.
        • et al.
        Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front.
        Cell. 2020; 182: 1341-1359
        • Berry S.
        • et al.
        Analysis of multispectral imaging with the AstroPath platform informs efficacy of PD-1 blockade.
        Science (80- ). 2021; 372eaba2609
        • Phillips D.
        • et al.
        Immune cell topography predicts response to PD-1 blockade in cutaneous T cell lymphoma.
        Nature. 2021; (Published online November 18, 2021)
        • Patwa A.
        • et al.
        Multiplexed imaging analysis of the tumor-immune microenvironment reveals predictors of outcome in triple-negative breast cancer.
        Commun. Biol. 2021; 4: 852
        • Rovira-Clave X.
        • et al.
        Spatial epitope barcoding reveals subclonal tumor patch behaviors.
        SSRN Electron. J. 2021; (Published online June 17, 2021)
        • Lin J.-R.
        • et al.
        Multiplexed 3D atlas of state transitions and immune interactions in colorectal cancer.
        bioRxiv. 2021; (Published online April 2, 2021)
        • Rovira-Clavé X.
        • et al.
        Subcellular localization of biomolecules and drug distribution by high-definition ion beam imaging.
        Nat. Commun. 2021; 12: 4628
        • Goltsev Y.
        • et al.
        Deep profiling of mouse splenic architecture with CODEX multiplexed imaging.
        Cell. 2018; 174: 968-981
        • Hartmann F.J.
        • et al.
        Single-cell metabolic profiling of human cytotoxic T cells.
        Nat. Biotechnol. 2021; 39: 186-197
        • Jiang S.
        • et al.
        Virus-dependent immune conditioning of tissue microenvironments.
        bioRxiv. 2021; (Published online May 25, 2021)
        • McCaffrey E.F.
        • et al.
        Multiplexed imaging of human tuberculosis granulomas uncovers immunoregulatory features conserved across tissue and blood.
        bioRxiv. 2020; (Published online June 9, 2020)
        • Bruni D.
        • et al.
        The immune contexture and Immunoscore in cancer prognosis and therapeutic efficacy.
        Nat. Rev. Cancer. 2020; 20: 662-680
        • Lu S.
        • et al.
        Comparison of biomarker modalities for predicting response to PD-1/PD-L1 checkpoint blockade.
        JAMA Oncol. 2019; 5: 1195
        • Bhate S.S.
        • et al.
        Tissue schematics map the specialization of immune tissue motifs and their appropriation by tumors.
        Cell Syst. 2021; (Published online October 14, 2021)
        • Egen J.G.
        • et al.
        Human anti-tumor immunity: insights from immunotherapy clinical trials.
        Immunity. 2020; 52: 36-54
        • Hickey J.W.
        • et al.
        Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging.
        Nat. Methods. 2021; (Published online November 22, 2021. https://doi.org/10.1038/s41592-021-01316-y)
        • Black S.
        • et al.
        CODEX multiplexed tissue imaging with DNA-conjugated antibodies.
        Nat. Protoc. 2021; 16: 3802-3835
        • Taube J.M.
        • et al.
        The Society for Immunotherapy of Cancer statement on best practices for multiplex immunohistochemistry (IHC) and immunofluorescence (IF) staining and validation.
        J. Immunother. Cancer. 2020; 8e000155
        • Liu Y.
        • et al.
        High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue.
        Cell. 2020; 183: 1665-1681
        • Govek K.W.
        • et al.
        Single-cell transcriptomic analysis of mIHC images via antigen mapping.
        Sci. Adv. 2021; 7eabc5464
        • Greenwald N.F.
        • et al.
        Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning.
        Nat. Biotechnol. 2021; (Published online November 18, 2021)
        • Ghahremani P.
        • et al.
        DeepLIIF: Deep Learning-Inferred Multiplex ImmunoFluorescence for IHC image quantification.
        bioRxiv. 2021; (Published online July 27, 2021)
        • Zhang B.
        • et al.
        Advances in organ-on-a-chip engineering.
        Nat. Rev. Mater. 2018; 3: 257-278
        • Gaharwar A.K.
        • et al.
        Engineered biomaterials for in situ tissue regeneration.
        Nat. Rev. Mater. 2020; 5: 686-705
        • Kim J.
        • et al.
        Human organoids: model systems for human biology and medicine.
        Nat. Rev. Mol. Cell Biol. 2020; 21: 571-584
        • Skalnik C.J.
        • et al.
        Whole-colony modeling of Escherichia coli.
        bioRxiv. 2021; (Published online April 27, 2021)