Literature DB >> 24671264

High-dimensional single-cell cancer biology.

Jonathan M Irish1, Deon B Doxie.   

Abstract

Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.

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Mesh:

Year:  2014        PMID: 24671264      PMCID: PMC4216808          DOI: 10.1007/82_2014_367

Source DB:  PubMed          Journal:  Curr Top Microbiol Immunol        ISSN: 0070-217X            Impact factor:   4.291


  78 in total

1.  High-content single-cell drug screening with phosphospecific flow cytometry.

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Journal:  Nat Chem Biol       Date:  2007-12-23       Impact factor: 15.040

2.  Histone H3 phosphorylation and expression of cyclins A and B1 measured in individual cells during their progression through G2 and mitosis.

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Journal:  Cytometry       Date:  1998-06-01

3.  Prevalence of antigen receptor variants in human T cell lines and tumors.

Authors:  H T Maecker; R Levy
Journal:  J Immunol       Date:  1989-02-15       Impact factor: 5.422

Review 4.  New insights into pre-BCR and BCR signalling with relevance to B cell malignancies.

Authors:  Robert C Rickert
Journal:  Nat Rev Immunol       Date:  2013-08       Impact factor: 53.106

5.  Homeostatic chemokines drive migration of malignant B cells in patients with non-Hodgkin lymphomas.

Authors:  Livio Trentin; Anna Cabrelle; Monica Facco; Davide Carollo; Marta Miorin; Alicia Tosoni; Paola Pizzo; Gianni Binotto; Linda Nicolardi; Renato Zambello; Fausto Adami; Carlo Agostini; Gianpietro Semenzato
Journal:  Blood       Date:  2004-03-04       Impact factor: 22.113

6.  Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue.

Authors:  Michael J Gerdes; Christopher J Sevinsky; Anup Sood; Sudeshna Adak; Musodiq O Bello; Alexander Bordwell; Ali Can; Alex Corwin; Sean Dinn; Robert J Filkins; Denise Hollman; Vidya Kamath; Sireesha Kaanumalle; Kevin Kenny; Melinda Larsen; Michael Lazare; Qing Li; Christina Lowes; Colin C McCulloch; Elizabeth McDonough; Michael C Montalto; Zhengyu Pang; Jens Rittscher; Alberto Santamaria-Pang; Brion D Sarachan; Maximilian L Seel; Antti Seppo; Kashan Shaikh; Yunxia Sui; Jingyu Zhang; Fiona Ginty
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-01       Impact factor: 11.205

7.  Histo-cytometry: a method for highly multiplex quantitative tissue imaging analysis applied to dendritic cell subset microanatomy in lymph nodes.

Authors:  Michael Y Gerner; Wolfgang Kastenmuller; Ina Ifrim; Juraj Kabat; Ronald N Germain
Journal:  Immunity       Date:  2012-08-02       Impact factor: 31.745

8.  Quantitative analysis of p53-targeted gene expression and visualization of p53 transcriptional activity following intratumoral administration of adenoviral p53 in vivo.

Authors:  Shoichiro Ohtani; Shunsuke Kagawa; Yasuhisa Tango; Tatsuo Umeoka; Naoyuki Tokunaga; Yousuke Tsunemitsu; Jack A Roth; Yoichi Taya; Noriaki Tanaka; Toshiyoshi Fujiwara
Journal:  Mol Cancer Ther       Date:  2004-01       Impact factor: 6.261

9.  Targeting BTK with ibrutinib in relapsed or refractory mantle-cell lymphoma.

Authors:  Michael L Wang; Simon Rule; Peter Martin; Andre Goy; Rebecca Auer; Brad S Kahl; Wojciech Jurczak; Ranjana H Advani; Jorge E Romaguera; Michael E Williams; Jacqueline C Barrientos; Ewa Chmielowska; John Radford; Stephan Stilgenbauer; Martin Dreyling; Wieslaw Wiktor Jedrzejczak; Peter Johnson; Stephen E Spurgeon; Lei Li; Liang Zhang; Kate Newberry; Zhishuo Ou; Nancy Cheng; Bingliang Fang; Jesse McGreivy; Fong Clow; Joseph J Buggy; Betty Y Chang; Darrin M Beaupre; Lori A Kunkel; Kristie A Blum
Journal:  N Engl J Med       Date:  2013-06-19       Impact factor: 91.245

10.  Critical assessment of automated flow cytometry data analysis techniques.

Authors:  Nima Aghaeepour; Greg Finak; Holger Hoos; Tim R Mosmann; Ryan Brinkman; Raphael Gottardo; Richard H Scheuermann
Journal:  Nat Methods       Date:  2013-02-10       Impact factor: 28.547

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  26 in total

Review 1.  The role of automated cytometry in the new era of cancer immunotherapy.

Authors:  Marco Danova; Martina Torchio; Giuditta Comolli; Andrea Sbrana; Andrea Antonuzzo; Giuliano Mazzini
Journal:  Mol Clin Oncol       Date:  2018-08-20

2.  Methods for discovery and characterization of cell subsets in high dimensional mass cytometry data.

Authors:  Kirsten E Diggins; P Brent Ferrell; Jonathan M Irish
Journal:  Methods       Date:  2015-05-13       Impact factor: 3.608

3.  Microfluidic flow cytometry: The role of microfabrication methodologies, performance and functional specification.

Authors:  Anil B Shrirao; Zachary Fritz; Eric M Novik; Gabriel M Yarmush; Rene S Schloss; Jeffrey D Zahn; Martin L Yarmush
Journal:  Technology (Singap World Sci)       Date:  2018-03-16

4.  Preparing Viable Single Cells from Human Tissue and Tumors for Cytomic Analysis.

Authors:  Nalin Leelatian; Deon B Doxie; Allison R Greenplate; Justine Sinnaeve; Rebecca A Ihrie; Jonathan M Irish
Journal:  Curr Protoc Mol Biol       Date:  2017-04-03

Review 5.  Systems immune monitoring in cancer therapy.

Authors:  Allison R Greenplate; Douglas B Johnson; P Brent Ferrell; Jonathan M Irish
Journal:  Eur J Cancer       Date:  2016-05-04       Impact factor: 9.162

6.  Training Novices in Generation and Analysis of High-Dimensional Human Cell Phospho-Flow Cytometry Data.

Authors:  Caroline E Roe; Madeline J Hayes; Sierra M Barone; Jonathan M Irish
Journal:  Curr Protoc Cytom       Date:  2020-03

7.  CyTOF supports efficient detection of immune cell subsets from small samples.

Authors:  Yi Yao; Rebecca Liu; Min Sun Shin; Mark Trentalange; Heather Allore; Ala Nassar; Insoo Kang; Jordan S Pober; Ruth R Montgomery
Journal:  J Immunol Methods       Date:  2014-11-04       Impact factor: 2.303

8.  Single cell analysis of human tissues and solid tumors with mass cytometry.

Authors:  Nalin Leelatian; Deon B Doxie; Allison R Greenplate; Bret C Mobley; Jonathan M Lehman; Justine Sinnaeve; Rondi M Kauffmann; Jay A Werkhaven; Akshitkumar M Mistry; Kyle D Weaver; Reid C Thompson; Pierre P Massion; Mary A Hooks; Mark C Kelley; Lola B Chambless; Rebecca A Ihrie; Jonathan M Irish
Journal:  Cytometry B Clin Cytom       Date:  2016-10-04       Impact factor: 3.058

Review 9.  Beyond the message: advantages of snapshot proteomics with single-cell mass cytometry in solid tumors.

Authors:  Akshitkumar M Mistry; Allison R Greenplate; Rebecca A Ihrie; Jonathan M Irish
Journal:  FEBS J       Date:  2019-01-07       Impact factor: 5.542

10.  Multiparameter analysis of stimulated human peripheral blood mononuclear cells: A comparison of mass and fluorescence cytometry.

Authors:  Katherine J Nicholas; Allison R Greenplate; David K Flaherty; Brittany K Matlock; Juan San Juan; Rita M Smith; Jonathan M Irish; Spyros A Kalams
Journal:  Cytometry A       Date:  2015-11-24       Impact factor: 4.355

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