Unraveling the Complexity of the Cancer Microenvironment With Multidimensional Genomic and Cytometric Technologies

Review (2020)
Authors

Natasja L. de Vries (Leiden University Medical Center)

A.M.E.T.A. Mahfouz (TU Delft - Pattern Recognition and Bioinformatics, Leiden University Medical Center)

Frits Koning (Leiden University Medical Center)

Noel F. C. C. de Miranda (Leiden University Medical Center)

Research Group
Pattern Recognition and Bioinformatics
Copyright
© 2020 Natasja L. de Vries, A.M.E.T.A. Mahfouz, Frits Koning, Noel F.C.C. de Miranda
To reference this document use:
https://doi.org/10.3389/fonc.2020.01254
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Natasja L. de Vries, A.M.E.T.A. Mahfouz, Frits Koning, Noel F.C.C. de Miranda
Research Group
Pattern Recognition and Bioinformatics
Volume number
10
Pages (from-to)
1-15
DOI:
https://doi.org/10.3389/fonc.2020.01254
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Abstract

Cancers are characterized by extensive heterogeneity that occurs intratumorally, between lesions, and across patients. To study cancer as a complex biological system, multidimensional analyses of the tumor microenvironment are paramount. Single-cell technologies such as flow cytometry, mass cytometry, or single-cell RNA-sequencing have revolutionized our ability to characterize individual cells in great detail and, with that, shed light on the complexity of cancer microenvironments. However, a key limitation of these single-cell technologies is the lack of information on spatial context and multicellular interactions. Investigating spatial contexts of cells requires the incorporation of tissue-based techniques such as multiparameter immunofluorescence, imaging mass cytometry, or in situ detection of transcripts. In this Review, we describe the rise of multidimensional single-cell technologies and provide an overview of their strengths and weaknesses. In addition, we discuss the integration of transcriptomic, genomic, epigenomic, proteomic, and spatially-resolved data in the context of human cancers. Lastly, we will deliberate on how the integration of multi-omics data will help to shed light on the complex role of cell types present within the human tumor microenvironment, and how such system-wide approaches may pave the way toward more effective therapies for the treatment of cancer.