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Cancer Systems Biology in the Era of Single‐Cell Multi‐Omics
Author(s) -
Cheng Hanjun,
Fan Rong,
Wei Wei
Publication year - 2020
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201900106
Subject(s) - epigenome , biology , transcriptome , epigenetics , carcinogenesis , computational biology , omics , stromal cell , single cell analysis , systems biology , proteome , tumor microenvironment , cell , metastasis , immune system , metabolome , cancer , bioinformatics , cancer research , metabolomics , genetics , dna methylation , gene , gene expression
Tumor tissue is a multifaceted ecosystem in which tumors cells are surrounded and influenced by a myriad of non-cancerous cells including immune, stromal, vascular, and other cell types.[1] Driven by stochastic geneticmutations, epigeneticmodifications, and aberrant gene expression profiles, tumor cells themselves also exhibit extraordinary intratumoral heterogeneity that gives rise to malfunctioning of signaling networks and plays important roles in tumor invasion, proliferation, metastasis, as well as stromal remodeling and immune system suppression.[2,3] This pronounced cell-to-cell variationsmake traditional bulk-level profiling far away from an accurate representation of the tumor ecosystem. In this regard, single-cell multi-omics tools provide a great opportunity for researchers to improve the understanding of molecular roles of tumor heterogeneity, thanks to their high spatiotemporal resolutions down to the level of single cells as well as their analytical capacity at the systems scale.[4-6] To date, a panoply of mono-omics technologies have been developed to effectively profile different molecular layers of single cells including genome, epigenome, transcriptome, proteome, metabolome, and so forth.[7-9] The quantification of these molecular signatures of cellular processes at single-cell resolution enables us to ask questions from perspectives previously unattainable and thereby facilitates our understanding of the cause and consequence of tumor heterogeneity in tumorigenesis, metastasis, and immune response. In addition, building on the development of these mono-omics technologies, tools for simultaneous measurement of multiple omic layers from the same single cells have emerged in recent years through the rational design of bio-recognition interface and the leverage of advanced biotechnologies.[10-13] Single-cell multi-omics tools allow for interrogating the links between different classes of biomolecules to resolve the interplays between distinct molecular landscapes. These integrated measurements not only offer a holistic view of cellular compositions and phenotypic states of a given population, but also enable detailed investigations into the developmental history, interand intracellular signal transduction, as well as the roles of significant subpopulations or rare cell