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.
Highlights
Reviewed by: Itai Yanai, New York University, United States Christina Stuelten, National Cancer Institute (NCI), United States
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
Summary
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. Single-cell DNA-sequencing has myriad applications in cancer research including examining intratumoral heterogeneity [26,27,28], investigating clonal evolution during tumorigenic processes [25, 29,30,31,32], tracing metastatic dissemination [33], genomic profiling of circulating tumor cells [34,35,36], measuring mutation rates [37], and gain insight into resistance to therapy [38].
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