Evidence map›Paper›PMID 33670410›Full record

ArticleCancers2021

Phenotypic Characterization by Mass Cytometry of the Microenvironment in Ovarian Cancer and Impact of Tumor Dissociation Methods.

Shamundeeswari Anandan, Liv Cecilie V Thomsen, Stein-Erik Gullaksen, Tamim Abdelaal, Katrin Kleinmanns, Jørn Skavland, Geir Bredholt, Bjørn Tore Gjertsen, Emmet McCormack, Line Bjørge

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. CyTOFFrontiers in immunology · 2022
    Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Shamundeeswari AnandanCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.
Liv Cecilie V ThomsenCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.
Stein-Erik GullaksenCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.ORCID 0000-0002-8512-9297
Tamim AbdelaalDelft Bioinformatics Lab, Delft University of Technology, 2600 AA Delft, The Netherlands.
Katrin KleinmannsCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.ORCID 0000-0003-1402-8568
Jørn SkavlandCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.
Geir BredholtCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.
Bjørn Tore GjertsenCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.ORCID 0000-0001-9358-9704
Emmet McCormackCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.
Line BjørgeCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.ORCID 0000-0002-0240-2770
University of Bergen · NOHaukeland University Hospital · NODelft University of Technology · NL

Funding

Helse Bergen 911809, 911852,912171, 240222Helse Vest Regionalt Helseføretak HV1269Horizon 2020 Framework Programme 675743Kreftforeningen 182735Norwegian Research Council 223250, 262652
6 · The paper itself

Abstract

Improved molecular dissection of the tumor microenvironment (TME) holds promise for treating high-grade serous ovarian cancer (HGSOC), a gynecological malignancy with high mortality. Reliable disease-related biomarkers are scarce, but single-cell mapping of the TME could identify patient-specific prognostic differences. To avoid technical variation effects, however, tissue dissociation effects on single cells must be considered. We present a novel Cytometry by Time-of-Flight antibody panel for single-cell suspensions to identify individual TME profiles of HGSOC patients and evaluate the effects of dissociation methods on results. The panel was developed utilizing cell lines, healthy donor blood, and stem cells and was applied to HGSOC tissues dissociated by six methods. Data were analyzed using Cytobank and X-shift and illustrated by t-distributed stochastic neighbor embedding plots, heatmaps, and stacked bar and error plots. The panel distinguishes the main cellular subsets and subpopulations, enabling characterization of individual TME profiles. The dissociation method affected some immune (

Indexed as

cell expression profilecharacterizationCytometry by Time-of-Flight (CyTOF)high-grade serous ovarian cancer (HGSOC)single-cell mass cytometrytumor dissociationtumor microenvironment (TME)

Identifiers

PMID33670410
PMCPMC7918057
OpenAlexW3126635506

What OpenQuestion holds

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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.