Literature DB >> 30549207

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

Akshitkumar M Mistry1,2,3, Allison R Greenplate3,4, Rebecca A Ihrie1,2,3, Jonathan M Irish2,3,4.   

Abstract

Single-cell technologies that can quantify features of individual cells within a tumor are critical for treatment strategies aiming to target cancer cells while sparing or activating beneficial cells. Given that key players in protein networks are often the primary targets of precision oncology strategies, it is imperative to transcend the nucleic acid message and read cellular actions in human solid tumors. Here, we review the advantages of multiplex, single-cell mass cytometry in tissue and solid tumor investigations. Mass cytometry can quantitatively probe nearly any cellular feature or target. In discussing the ability of mass cytometry to reveal and characterize a broad spectrum of cell types, identify rare cells, and study functional behavior through protein signaling networks in millions of individual cells from a tumor, this review surveys publications of scientific advances in solid tumor biology made with the aid of mass cytometry. Advances discussed include functional identification of rare tumor and tumor-infiltrating immune cells and dissection of cellular mechanisms of immunotherapy in solid tumors and the periphery. The review concludes by highlighting ways to incorporate single-cell mass cytometry in solid tumor precision oncology efforts and rapidly developing cytometry techniques for quantifying cell location and sequenced nucleic acids.
© 2018 Federation of European Biochemical Societies.

Entities:  

Keywords:  immune cell; immunotherapy; mass cytometry; proteomics; signaling; single cell

Year:  2019        PMID: 30549207      PMCID: PMC6478512          DOI: 10.1111/febs.14730

Source DB:  PubMed          Journal:  FEBS J        ISSN: 1742-464X            Impact factor:   5.542


  155 in total

1.  Amine reactive dyes: an effective tool to discriminate live and dead cells in polychromatic flow cytometry.

Authors:  Stephen P Perfetto; Pratip K Chattopadhyay; Laurie Lamoreaux; Richard Nguyen; David Ambrozak; Richard A Koup; Mario Roederer
Journal:  J Immunol Methods       Date:  2006-05-19       Impact factor: 2.303

2.  A perivascular niche for brain tumor stem cells.

Authors:  Christopher Calabrese; Helen Poppleton; Mehmet Kocak; Twala L Hogg; Christine Fuller; Blair Hamner; Eun Young Oh; M Waleed Gaber; David Finklestein; Meredith Allen; Adrian Frank; Ildar T Bayazitov; Stanislav S Zakharenko; Amar Gajjar; Andrew Davidoff; Richard J Gilbertson
Journal:  Cancer Cell       Date:  2007-01       Impact factor: 31.743

3.  Study of cell antigens and intracellular DNA by identification of element-containing labels and metallointercalators using inductively coupled plasma mass spectrometry.

Authors:  O I Ornatsky; X Lou; M Nitz; S Schäfer; W S Sheldrick; V I Baranov; D R Bandura; S D Tanner
Journal:  Anal Chem       Date:  2008-03-05       Impact factor: 6.986

4.  Chromatin flow cytometry identifies changes in epigenetic cell states.

Authors:  Nadine Obier; Albrecht M Müller
Journal:  Cells Tissues Organs       Date:  2009-09-18       Impact factor: 2.481

5.  Flow cytometry detection of caspase 3 activation in preapoptotic leukemic cells.

Authors:  F Belloc; M A Belaud-Rotureau; V Lavignolle; E Bascans; E Braz-Pereira; F Durrieu; F Lacombe
Journal:  Cytometry       Date:  2000-06-01

6.  Role of glutathione depletion and reactive oxygen species generation in apoptotic signaling in a human B lymphoma cell line.

Authors:  J S Armstrong; K K Steinauer; B Hornung; J M Irish; P Lecane; G W Birrell; D M Peehl; S J Knox
Journal:  Cell Death Differ       Date:  2002-03       Impact factor: 15.828

7.  Single cell profiling of potentiated phospho-protein networks in cancer cells.

Authors:  Jonathan M Irish; Randi Hovland; Peter O Krutzik; Omar D Perez; Øystein Bruserud; Bjørn T Gjertsen; Garry P Nolan
Journal:  Cell       Date:  2004-07-23       Impact factor: 41.582

Review 8.  Mapping normal and cancer cell signalling networks: towards single-cell proteomics.

Authors:  Jonathan M Irish; Nikesh Kotecha; Garry P Nolan
Journal:  Nat Rev Cancer       Date:  2006-02       Impact factor: 60.716

9.  Analysis of cell cycle by flow cytometry.

Authors:  Piotr Pozarowski; Zbigniew Darzynkiewicz
Journal:  Methods Mol Biol       Date:  2004

10.  A targetable fluorescent probe for imaging hydrogen peroxide in the mitochondria of living cells.

Authors:  Bryan C Dickinson; Christopher J Chang
Journal:  J Am Chem Soc       Date:  2008-07-08       Impact factor: 15.419

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  11 in total

1.  Mass cytometry defines distinct immune profile in germinal center B-cell lymphomas.

Authors:  Mikael Roussel; Faustine Lhomme; Caroline E Roe; Todd Bartkowiak; Pauline Gravelle; Camille Laurent; Thierry Fest; Jonathan M Irish
Journal:  Cancer Immunol Immunother       Date:  2020-01-09       Impact factor: 6.968

2.  Mass Cytometry for the Characterization of Individual Cell Types in Ovarian Solid Tumors.

Authors:  Veronica D Gonzalez; Ying-Wen Huang; Wendy J Fantl
Journal:  Methods Mol Biol       Date:  2022

Review 3.  Single cell metabolism: current and future trends.

Authors:  Ahmed Ali; Shawn Davidson; Ernest Fraenkel; Ian Gilmore; Thomas Hankemeier; Jennifer A Kirwan; Andrew N Lane; Ingela Lanekoff; Mioara Larion; Laura-Isobel McCall; Michael Murphy; Jonathan V Sweedler; Caigang Zhu
Journal:  Metabolomics       Date:  2022-10-01       Impact factor: 4.747

Review 4.  Cancer systems immunology.

Authors:  Nathan E Reticker-Flynn; Edgar G Engleman
Journal:  Elife       Date:  2020-07-13       Impact factor: 8.140

5.  Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells.

Authors:  Nalin Leelatian; Justine Sinnaeve; Akshitkumar M Mistry; Sierra M Barone; Asa A Brockman; Kirsten E Diggins; Allison R Greenplate; Kyle D Weaver; Reid C Thompson; Lola B Chambless; Bret C Mobley; Rebecca A Ihrie; Jonathan M Irish
Journal:  Elife       Date:  2020-06-23       Impact factor: 8.140

6.  Analysis of the Single-Cell Heterogeneity of Adenocarcinoma Cell Lines and the Investigation of Intratumor Heterogeneity Reveals the Expression of Transmembrane Protein 45A (TMEM45A) in Lung Adenocarcinoma Cancer Patients.

Authors:  Patrícia Neuperger; József Á Balog; László Tiszlavicz; József Furák; Nikolett Gémes; Edit Kotogány; Klára Szalontai; László G Puskás; Gábor J Szebeni
Journal:  Cancers (Basel)       Date:  2021-12-29       Impact factor: 6.639

Review 7.  Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective.

Authors:  Teresa W-M Fan; Richard M Higashi; Yelena Chernayavskaya; Andrew N Lane
Journal:  Metabolites       Date:  2020-06-15

Review 8.  The Evolution of Single-Cell Analysis and Utility in Drug Development.

Authors:  Shibani Mitra-Kaushik; Anita Mehta-Damani; Jennifer J Stewart; Cherie Green; Virginia Litwin; Christèle Gonneau
Journal:  AAPS J       Date:  2021-08-13       Impact factor: 4.009

Review 9.  Cancer: a mirrored room between tumor bulk and tumor microenvironment.

Authors:  Pablo Hernández-Camarero; Elena López-Ruiz; Juan Antonio Marchal; Macarena Perán
Journal:  J Exp Clin Cancer Res       Date:  2021-06-28

10.  Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.

Authors:  Sierra M Barone; Alberta Ga Paul; Lyndsey M Muehling; Joanne A Lannigan; William W Kwok; Ronald B Turner; Judith A Woodfolk; Jonathan M Irish
Journal:  Elife       Date:  2021-08-05       Impact factor: 8.713

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