Abstract
Traditional analysis in cancer initiates an empirical screening on bulk tumors based on standard equipment. Nonetheless, the tumors inherently exhibit distinct characteristics, including heterogeneity/plasticity/morphology of cells, cell-matrix or cell-cell interactions, and in-depth mass transport. Such traditional analysis may not acquire the invaluable yield since the critical cells of interest are in the minority as well as their activities could be altered during preparation. In recent years, emerging techniques in single-cell analysis have opened a new avenue targeting precise cancer medicine, including single-cell genome/transcriptome, next-generation sequencing, tumor spheroid formation targeting cancer stem cells, and microfluidic approach for the physical assay of cell size (mass/volume/density), deformability, and electrokinetic properties from single cells. In this chapter, an overall view of current techniques and commercial equipment for single-cell analysis in cancer and their potential translation into clinic will be present.
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References
Ahmmed S, Bithi S, Pore A et al (2018) Multi-sample deformability cytometry of cancer cells. APL Bioeng 2:032002
Amir E-A, Davis K, Tadmor M et al (2013) viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat Biotechnol 31:545–552
Antfolk M, Kim S, Koizumi S et al (2017) Label-free single-cell separation and imaging of cancer cells using an integrated microfluidic system. Sci Rep 7:46507
Bacher R, Kendziorski C (2016) Design and computational analysis of single-cell RNA-sequencing experiments. Genome Biol 17:63
Barer R, Ross K, Tkaczyk S (1953) Refractometry of living cells. Nature 171:720–724
Baslan T, Hicks J (2017) Unravelling biology and shifting paradigms in cancer with single-cell sequencing. Nat Rev Cancer 17:557–569
Bendall S, Simonds E, Qiu P, Amir E-A, Krutzik P, Finck R, Bruggner R, Melamed R, Trejo A, Ornastsky O, Balderas R et al (2011) Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 6:687–696
Borgstrom E, Paterlini M, Mold J et al (2017) Comparison of whole genome amplification techniques for human single cell exome sequencing. PLoS One 12:e0171566
Bryan A, Hecht V, Shen W et al (2014) Measuring single cell mass, volume, and density with dual suspended microchannel resonators. Lab Chip 14:569–576
Chaffer C, Juan BS, Lim E et al (2016) EMT, cell plasticity and metastasis. Cancer Metastasis Rev 35:645–654
Datlinger P, Rendeiro A, Schmidl C et al (2017) Pooled CRISPR screening with single-cell transcriptome readout. Nat Methods 14:297–301
Dean F, Hosono S, Fang L et al (2002) Comprehensive human genome amplification using multiple displacement amplification. PNAS 99:5261–5266
Dou M, Clari G, Tsai C et al (2019) High-throughput single cell proteomics enabled by multiplex isobaric labelling in a Nanodroplet sample preparation platform. Anal Chem. https://doi.org/10.1021/acs.analchem.9b03349
Emmert-Buck MR, Bonner RF, Smith PD et al (1996) Laser capture microdissection. Science 274:998–1001
Filipovic N, Djukic T, Radovic M et al (2014) Electromagnetic field investigation on different cancer cell lines. Cancer Cell Int 14:84
Fröhlich J, König H (2000) New techniques for isolation of single prokaryotic cells. FEMS Microbiol 24:567–572
Gawad C, Koh W, Quake S (2014) Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics. PNAS 111:17947–17952
Gill N, Nyberg K, Lee L et al (2019) A scalable filtration method for high throughput screening based on cell deformability. Lab Chip 19:343–357
Goding JW (1980) Antibody production by hybridomas. J Immunol Methods 185:285–308
Gross A, Schoendube J, Zimmermann S et al (2015) Techniques for single-cell isolation. Int J Mol Sci 16:16897–16919
Grover W, Bryan A, Diez-Silva M et al (2011) Measuring single-cell density. PNAS 108:10992–10996
Guo G, Luc S, Marco E et al (2013) Mapping cellular hierarchy by single-cell analysis of the cell surface repertoire. Cell Stem Cell 13:492–505
Hang C, Chen H, Yen M et al (2011) Gene expression of human lung Cancer cell line CL1–5 in response to a direct current electric field. PLoS One 6:e25928
Hierahn T, Wadsworth MH, Hughes T et al (2017) Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput. Nat Methods 14:395–398
Hirsch J, Gallian E (1968) Methods for the determination of adipose cell size in man and animals. J Lipid Res 9:110–119
Hong Y, Fang F, Zhang Q (2016) Circulating tumor cell clusters: what we know and what we expect. Int J Oncol 49:2206–2216
Hou H, Chang H, Cheng J (2015) Electrotaxis studies of lung cancer cells using a multichannel dual-electric-field microfluidic chip. J Vis Exp 106:53340
Jaitin D, Kenigsberg E, Keren-Shaul H et al (2014) Massively parallel single cell RNA-Seq for marker-free decomposition of tissues into cell types. Science 343:776–779
Justus C, Leffler N, Ruiz-Echevarria M et al (2014) In vitro cell migration and invasion assays. J Vis Exp 88:51046
Khamenehfar A, Li P (2016) Microfluidic devices for circulating tumor cells isolation and subsequent analysis. Curr Pharm Biotechnol 17:810–821
Kimmerling R, Prakadan S, Gupta A et al (2018) Linking single-cell measurements of mass, growth rate, and gene expression. Genome Biol 19:207
Kramer N, Walzl A, Unger C et al (2013) In vitro cell migration and invasion assays. Mutat Res 752:10–24
Kuo C, Chiang C, Chang C et al (2014) Modeling of cancer metastasis and drug resistance via biomimetic nano-cilia and microfluidics. Biomaterials 35:1562–1571
Kuo C, Wang J, Lin Y et al (2017a) Three-dimensional spheroid culture targeting versatile tissue bioassays using a PDMS-based hanging drop array. Sci Rep 7:4363
Kuo C, Wang J, Wo A et al (2017b) ParaStamp and its applications to cell patterning, drug synergy screening, and rewritable devices for droplet storage. Adv Biosyst 1:1700048
Kuo C, Lu S, Chen W et al (2018) Facilitating tumor spheroid-based bioassays and in vitro blood vessel modeling via bioinspired selfformation microstructure devices. Lab Chip 18:2453–2465
Kuo C, Wang J, Lu S et al (2019) A nanodroplet cell processing platform facilitating drug synergy evaluations for anti-cancer treatments. Sci Rep 9:10120
Kyrochristos I, Roukos D (2019) Comprehensive intra-individual genomic and transcriptional heterogeneity: evidence-based colorectal cancer precision medicine. Cancer Treat Rev 80:101894
Landwehr G, Kristof A, Rahman S et al (2018) Biophysical analysis of fluid shear stress induced cellular deformation in a microfluidic device. Biomicrofluidics 12:054109
Lee J, Mhawech-Fauceglia P, Lee N et al (2013) A three-dimensional microenvironment alters protein expression and chemosensitivity of epithelial ovarian cancer cells in vitro. Lab Investig 93:528–542
Li L, Lu M, Fan Y et al (2019a) High-throughput and ultra-sensitive single-cell profiling of multiple microRNAs and identification of human cancer. Chem Commun (Camb) 55:10404–10407
Li R, Jia F, Zhang W et al (2019b) Device for whole genome sequencing single circulating tumor cells from whole blood. Lab Chip. https://doi.org/10.1039/c9lc00473d
Liu D, Paczkowski P, Mackay S et al (2020) Single-cell multiplexed proteomics on the IsoLight resolves cellular functional heterogeneity to reveal clinical responses of cancer patients to immunotherapies. Methods Mol Biol 2055:413–431
Ma W, Hsiung L, Wang C et al (2015) A novel 96well-formatted micro-gap plate enabling drug response profiling on primary tumour samples. Sci Rep 5:9656
Mani S, Guo W, Liao M et al (2008) The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell 133:704–715
Milardi D, Grande G, Vincerzoni F et al (2019) Proteomics for the identification of biomarkers in testicular cancer-review. Front Endocrinol (Lausanne) 10:462
Moldavan A (1934) Photo-electric technique for the counting of microscopial cells. Science 80:188–189
Nagrath S, Sequist L, Maheswaran S et al (2007) Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature 450:1235–1239
Picelli S (2017) Single-cell RNA-sequencing: the future of genome biology is now. RNA Biol 14:637–660
Punjiya M, Nejad H, Mathews J et al (2019) A flow through device for simultaneous dielectrophoretic cell trapping and AC electroporation. Sci Rep 9:11988
Rantalainen M (2018) Application of single-cell sequencing in human cancer. Brief Funct Genomics 17:273–282
Riethdorf S, Fritsche H, Muller V et al (2007) Detection of circulating tumor cells in peripheral blood of patients with metastatic breast cancer: a validation study of the cell search system. Clin Cancer Res 13:920–928
Saadatpour A, Lai S, Guo G et al (2015) Single-cell analysis in cancer genomics. Trends Genet 31:576–586
Stegle O, Teichmann S, Marioni J (2015) Computational and analytical challenges in single-cell transcriptomics. Nat Rev Genet 16:133–145
Stoechius M, Hafemeister C, Stephenson W et al (2017) Simultaneous epitope and transcriptome measurement in single cells. Nat Methods 14:865–868
Stubbington M, Rozenblatt-Rosen O, Regev A et al (2017) Single-cell transcriptomics to explore the immune system in health and disease. Science 358:58–63
Telenius H, Carter N, Bebb C et al (1992) Degenerate oligonucleotide-primed PCR: general amplification of target DNA by a single degenerate primer. Genomics 13:718–725
Tung Y, Hsiao A, Allen S et al (2011) High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array. Analyst 136:473–478
Tzur A, Moore J, Jorgensen P et al (2011) Optimizing optical flow cytometry for cell volume-based sorting and analysis. PLoS One 6:e16053
Vitak S, Torkenczy K, Rosenkrantz J et al (2017) Sequencing thousands of single-cell genomes with combinatorial indexing. Nat Methods 14:302–308
Wills QF, Mead AJ (2015) Application of single-cell genomics in cancer: promise and challenges. Hum Mol Genet 24:R74–R84
Wu P, Aroush D, Asnacios A et al (2018) A comparison of methods to assess cell mechanical properties. Nat Methods 15:491–498
Yin Y, Jiang Y, Lam K et al (2019) High-throughput single-cell sequencing with linear amplification. Mol Cell S1097-2765(19):30618–30615
Yoon C, Till J, Cho S et al (2019) KRAS activation in gastric adenocarcinoma stimulates epithelial-to-mesenchymal transition to cancer stem-like cells and promotes metastasis. Mol Cancer Res 17:1945–1957
Yu M, Bardia A, Aceto N et al (2014) Ex vivo culture of circulating breast tumor cells for individualized testing of drug susceptibility. Science 345:216–220
Zhang K, Gao M, Chong Z et al (2016) Single-cell isolation by a modular single-cell pipette for RNA-sequencing. Lab Chip 16:4742–4748
Zhou W, Ji Z, Fang W et al (2019) Global prediction of chromatin accessibility using small-cell-number and single-cell RNA-seq. Nucleic Acids Res 47(19):e121
Zhu Y, Piehowski P, Zhao R et al (2018) Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells. Nat Commun 9:882
Zhu L, Pan R, Zhou D et al (2019) BCL11A enhances stemness and promotes progression by activating Wnt/β-catenin signaling in breast cancer. Cancer Manag Res 11:2997–3007
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Financial support from the Ministry of Science and Technology (MOST), Taiwan, under the grant 107-2622-8-002-018 is gratefully acknowledged.
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Kuo, CT., Lee, H. (2020). Analytical Technology for Single-Cancer-Cell Analysis. In: Santra, T., Tseng, FG. (eds) Handbook of Single Cell Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-10-4857-9_33-1
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DOI: https://doi.org/10.1007/978-981-10-4857-9_33-1
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