Evidence map›Paper›PMID 31113192›Full record

ArticleEuropean journal of histochemistry : EJH2019

A method for semi-automated image analysis of HLA class I tumour epithelium expression in rectal cancer.

Daniëlle Krijgsman, Ronald L P Van Vlierberghe, Vaios Evangelou, Alexander L Vahrmeijer, Cornelis J H Van de Velde, Cornelis F M Sier, Peter J K Kuppen

Open access · goldAbstract read
In one paragraph

Article in European journal of histochemistry : EJH, 2019. 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
0.3field-weighted citation impact, top 44% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
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  4. AI in Medical Imaging Informatics: Current Challenges and Future Directions.IEEE journal of biomedical and health informatics · 2020
    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

7 authors at 1 institution in 1 country.

Daniëlle KrijgsmanDepartment of Surgery, Leiden University Medical Centre, Leiden. d.krijgsman@lumc.nl.
Ronald L P Van Vlierberghe
Vaios Evangelou
Alexander L Vahrmeijer
Cornelis J H Van de Velde
Cornelis F M Sier
Peter J K Kuppen
Leiden University Medical Center · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomarkers may hold the key towards development and improvement of personalized cancer treatment. For instance, tumour expression of immune system-related proteins may reveal the tumour immune status and, accordingly, determine choice for type of immunotherapy. Therefore, objective evaluation of tumour biomarker expression is needed but often challenging. For instance, human leukocyte antigen (HLA) class I tumour epithelium expression is cumbersome to quantify by eye due to its presence on both tumour epithelial cells and tumour stromal cells, as well as tumour-infiltrating immune cells. In this study, we solved this problem by setting up an immunohistochemical (IHC) double staining using a tissue microarray (TMA) of rectal tumours wherein HLA class I expression was coloured with a blue chromogen, whereas non-epithelial tissue was visualized with a brown chromogen. We subsequently developed a semi-automated image analysis method that identified tumour epithelium as well as the percentage of HLA class I-positive tumour epithelium. Using this technique, we compared HCA2/HC10 and EMR8-5 antibodies for the assessment of HLA class I tumour expression and concluded that EMR8-5 is the superior antibody for this purpose. This IHC double staining can in principle be used for scoring of any biomarker expressed by tumour epithelium.

Indexed as

AnimalsAntibodies, Monoclonal, Murine-DerivedBiomarkers, TumorEpitheliumHistocompatibility Antigens Class IHumansImmunohistochemistryMiceRabbitsRectal NeoplasmsTissue Array AnalysisAntibodies, Monoclonal, Murine-DerivedBiomarkers, TumorHistocompatibility Antigens Class I

Identifiers

PMID31113192
PMCPMC6536912
OpenAlexW2946252818

What OpenQuestion holds

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LicenceCC BY-NC
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.