Unraveling cell populations in tumors by single-cell mass cytometry

Serena Di Palma; Bernd Bodenmiller

doi:10.1016/j.copbio.2014.07.004

Unraveling cell populations in tumors by single-cell mass cytometry

Serena Di Palma
, Bernd Bodenmiller

extern
Department for Evolutionary Biology and Environmental Studies, University of Zürich, Zürich, Switzerland.

Research output: Contribution to journal › Review article › peer-review

Abstract

The development of new biotechnologies for the analysis of individual cells in heterogeneous populations is an important direction of life science research. This review provides a critical overview of relevant and recent advances in the field of single-cell mass cytometry, focusing on the latest applications in the study of cell heterogeneity. New approaches for multiparameter single-cell imaging, alongside advanced computational tools for deep mining of high-dimensional mass cytometric data, are facilitating the visualization of specific cell types and their interactions in complex cellular assemblies, such as tumors, potentially revealing new insights into cancer biology.

Original language	English
Pages (from-to)	122-9
Number of pages	8
Journal	Current Opinion in Biotechnology
Volume	31
DOIs	https://doi.org/10.1016/j.copbio.2014.07.004
Publication status	Published - Feb 2015

Bibliographical note

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Cell Count
Flow Cytometry/methods
Humans
Neoplasms/pathology
Single-Cell Analysis/methods

Access to Document

10.1016/j.copbio.2014.07.004

Cite this

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title = "Unraveling cell populations in tumors by single-cell mass cytometry",

abstract = "The development of new biotechnologies for the analysis of individual cells in heterogeneous populations is an important direction of life science research. This review provides a critical overview of relevant and recent advances in the field of single-cell mass cytometry, focusing on the latest applications in the study of cell heterogeneity. New approaches for multiparameter single-cell imaging, alongside advanced computational tools for deep mining of high-dimensional mass cytometric data, are facilitating the visualization of specific cell types and their interactions in complex cellular assemblies, such as tumors, potentially revealing new insights into cancer biology. ",

keywords = "Cell Count, Flow Cytometry/methods, Humans, Neoplasms/pathology, Single-Cell Analysis/methods",

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doi = "10.1016/j.copbio.2014.07.004",

language = "English",

volume = "31",

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journal = "Current Opinion in Biotechnology",

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T1 - Unraveling cell populations in tumors by single-cell mass cytometry

AU - Di Palma, Serena

AU - Bodenmiller, Bernd

PY - 2015/2

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N2 - The development of new biotechnologies for the analysis of individual cells in heterogeneous populations is an important direction of life science research. This review provides a critical overview of relevant and recent advances in the field of single-cell mass cytometry, focusing on the latest applications in the study of cell heterogeneity. New approaches for multiparameter single-cell imaging, alongside advanced computational tools for deep mining of high-dimensional mass cytometric data, are facilitating the visualization of specific cell types and their interactions in complex cellular assemblies, such as tumors, potentially revealing new insights into cancer biology.

AB - The development of new biotechnologies for the analysis of individual cells in heterogeneous populations is an important direction of life science research. This review provides a critical overview of relevant and recent advances in the field of single-cell mass cytometry, focusing on the latest applications in the study of cell heterogeneity. New approaches for multiparameter single-cell imaging, alongside advanced computational tools for deep mining of high-dimensional mass cytometric data, are facilitating the visualization of specific cell types and their interactions in complex cellular assemblies, such as tumors, potentially revealing new insights into cancer biology.

KW - Cell Count

KW - Flow Cytometry/methods

KW - Humans

KW - Neoplasms/pathology

KW - Single-Cell Analysis/methods

U2 - 10.1016/j.copbio.2014.07.004

DO - 10.1016/j.copbio.2014.07.004

M3 - Review article

C2 - 25123841

SN - 0958-1669

VL - 31

SP - 122

EP - 129

JO - Current Opinion in Biotechnology

JF - Current Opinion in Biotechnology

ER -

Unraveling cell populations in tumors by single-cell mass cytometry

Abstract

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this