Evidence map›Paper›PMID 25170899›Full record

ArticlePloS one2014

Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

Craig A Gedye, Ali Hussain, Joshua Paterson, Alannah Smrke, Harleen Saini, Danylo Sirskyj, Keira Pereira, Nazleen Lobo, Jocelyn Stewart, Christopher Go and 17 more

Erratum issuedOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 88 citations in OpenAlex.

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  10. Revisiting the Experimental Methods for Human Skin T-Cell Analysis.JID innovations : skin science from molecules to population health · 2022
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4 · The record

Corrections and comments

  • Erratum issued
    Meyer, Mona [added]
5 · Who and what money

Authors and funding

27 authors at 4 institutions in 1 country.

Craig A GedyePrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Ali HussainDept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Joshua PatersonPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Alannah SmrkePrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Harleen SainiPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Danylo SirskyjPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Keira PereiraDept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Nazleen LoboDept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Jocelyn StewartDept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Christopher GoPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Jenny HoPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Mauricio MedranoDept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Elzbieta HyattHospital for Sick Children Research Institute, Toronto, ON, Canada.
Julie YuanHospital for Sick Children Research Institute, Toronto, ON, Canada.
Stevan LauriaultHospital for Sick Children Research Institute, Toronto, ON, Canada.
Mona Meyer
Maria KondratyevPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Twan van den BeuckenPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Michael JewettPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Peter DirksHospital for Sick Children Research Institute, Toronto, ON, Canada.
Cynthia J GuidosHospital for Sick Children Research Institute, Toronto, ON, Canada.
Jayne DanskaHospital for Sick Children Research Institute, Toronto, ON, Canada.
Jean WangPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Bradly WoutersPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Dept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Benjamin NeelPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Dept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Robert RottapelPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Laurie E AillesPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Dept. of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Princess Margaret Cancer Centre · CAUniversity Health Network · CAHospital for Sick Children · CAUniversity of Toronto · CA

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.

Indexed as

Antigens, SurfaceBiomarkersCell Line, TumorCells, CulturedCluster AnalysisFlow CytometryHumansJurkat CellsMCF-7 CellsMicroscopy, FluorescenceProteomeProteomicsReproducibility of ResultsAntigens, SurfaceBiomarkersProteome

Identifiers

PMID25170899
PMCPMC4149490
OpenAlexW2106496177

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.