Evidence map›Paper›PMID 36526955›Full record

ArticleBMC bioinformatics2022

AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database.

Benedek Bozoky, Laszlo Szekely, Ingemar Ernberg, Andrii Savchenko

Abstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 citing papers in PubMed.

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  6. Bioinformatics screened of biomarkers for the prognosis of hepatocellular carcinoma.Cancer biomarkers : section A of Disease markers · 2025
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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

4 authors.

Benedek BozokyDepartment of Microbiology, Tumor and Cell Biology (MTC), Biomedicum C8, Solnavägen 9, 171 65, Solna, Sweden. benedek.bozoky@ki.se.ORCID http://orcid.org/0000-0003-3388-7210
Laszlo SzekelyDepartment of Laboratory Medicine, Karolinska Institutet, Alfred Nobels Allé 8, 171 77, Huddinge, Sweden.
Ingemar ErnbergDepartment of Microbiology, Tumor and Cell Biology (MTC), Biomedicum C8, Solnavägen 9, 171 65, Solna, Sweden.
Andrii SavchenkoDepartment of Microbiology, Tumor and Cell Biology (MTC), Biomedicum C8, Solnavägen 9, 171 65, Solna, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe human protein atlas (HPA) is an online database containing large sets of protein expression data in normal and cancerous tissues in image form from immunohistochemically (IHC) stained tissue microarrays. In these, the tissue architecture is preserved and thus provides information on the spatial distribution and localization of protein expression at the cellular and extracellular levels. The database is freely available online through the HPA website but currently without support for large-scale screening and analysis of the images in the database. Features like spatial information are typically lacking in gene expression datasets from homogenized tissues or single-cell analysis. To enable high throughput analysis of the HPA database, we developed the AtlasGrabber software. It is available freely under an open-source license. Based on a predefined gene list, the software fetches the images from the database and displays them for the user. Several filters for specific antibodies or images enable the user to customize her/his image analysis. Up to four images can be displayed simultaneously, which allows for the comparison of protein expression between different tissues and between normal and cancerous tissues. An additional feature is the XML parser that allows the extraction of a list of available antibodies, images, and genes for specific tissues or cancer types from the HPA's database file.

resultsCompared to existing software designed for a similar purpose, ours provide more functionality and is easier to use. To demonstrate the software's usability, we identified six new markers of basal cells of the prostate. A comparison to prostate cancer showed that five of them are absent in prostate cancer.

conclusionsThe HPA is a uniquely valuable database. By facilitating its usefulness with the AtlasGrabber, we enable researchers to exploit its full capacity. The loss of basal cell markers is diagnostic for prostate cancer and can help refine the histopathological diagnosis of prostate cancer. As proof of concept, with the AtlasGrabber we identified five new potential biomarkers specific for prostate basal cells which are lost in prostate cancer and thus can be used for prostate cancer diagnostics.

Indexed as

Prostatic NeoplasmsSoftwareDatabases, ProteinHumansImmunohistochemistryMaleProteomicsAtlasGrabberBasal cellsBiomarkersHuman protein atlasImmunohistochemistryProstate cancerProtein expressionTissue microarray

Identifiers

PMID36526955
PMCPMC9758778

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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.