Evidence map›Paper›PMID 38803925›Full record

ArticleHeliyon2024

Development of a high dimensional imaging mass cytometry panel to investigate spatial organization of tissue microenvironment in formalin-fixed archival clinical tissues.

Stian Tornaas, Dimitrios Kleftogiannis, Siren Fromreide, Hilde Ytre-Hauge Smeland, Hans Jørgen Aarstad, Olav Karsten Vintermyr, Lars Andreas Akslen, Daniela Elena Costea, Harsh Nitin Dongre

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
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

9 authors.

Stian TornaasCenter for Cancer Biomarkers (CCBIO) and Department of Clinical Medicine, University of Bergen, Norway.
Dimitrios KleftogiannisCenter for Cancer Biomarkers (CCBIO) and Department of Clinical Medicine, University of Bergen, Norway.
Siren FromreideCenter for Cancer Biomarkers (CCBIO) and Department of Clinical Medicine, University of Bergen, Norway.
Hilde Ytre-Hauge SmelandCenter for Cancer Biomarkers (CCBIO) and Department of Clinical Medicine, University of Bergen, Norway.
Hans Jørgen AarstadDepartment for Ear-Nose-and-Throat, Head and Neck Clinic, Haukeland University Hospital, Bergen, Norway.
Olav Karsten VintermyrDepartment of Pathology, Haukeland University Hospital, Bergen, Norway.
Lars Andreas AkslenCenter for Cancer Biomarkers (CCBIO) and Department of Clinical Medicine, University of Bergen, Norway.
Daniela Elena CosteaCenter for Cancer Biomarkers (CCBIO) and Department of Clinical Medicine, University of Bergen, Norway.
Harsh Nitin DongreCenter for Cancer Biomarkers (CCBIO) and Department of Clinical Medicine, University of Bergen, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To decipher the interactions between various components of the tumor microenvironment (TME) and tumor cells in a preserved spatial context, a multiparametric approach is essential. In this pursuit, imaging mass cytometry (IMC) emerges as a valuable tool, capable of concurrently analyzing up to 40 parameters at subcellular resolution. In this study, a set of antibodies was selected to spatially resolve multiple cell types and TME elements, including a comprehensive panel targeted at dissecting the heterogeneity of cancer-associated fibroblasts (CAF), a pivotal TME component. This antibody panel was standardized and optimized using formalin-fixed paraffin-embedded tissue (FFPE) samples from different organs/lesions known to express the markers of interest. The final composition of the antibody panel was determined based on the performance of conjugated antibodies in both immunohistochemistry (IHC) and IMC. Tissue images were segmented employing the Steinbock framework. Unsupervised clustering of single-cell data was carried out using a bioinformatics pipeline developed in R program. This paper provides a detailed description of the staining procedure and analysis workflow. Subsequently, the panel underwent validation on clinical FFPE samples from head and neck squamous cell carcinoma (HNSCC). The panel and bioinformatics pipeline established here proved to be robust in characterizing different TME components of HNSCC while maintaining a high degree of spatial detail. The platform we describe shows promise for understanding the clinical implications of TMA heterogeneity in large patient cohorts with FFPE tissues available in diagnostic biobanks worldwide.

Indexed as

BioinformaticsCancer associated fibroblastsImaging mass cytometryImmunohistochemistrySingle-cell dataTumor microenvironment

Identifiers

PMID38803925
PMCPMC11128903

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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.