Evidence map›Paper›PMID 27047454›Full record

ArticleFrontiers in microbiology2016

Genome-Wide Expression Profiling Reveals S100B as Biomarker for Invasive Aspergillosis.

Andreas Dix, Kristin Czakai, Jan Springer, Mirjam Fliesser, Michael Bonin, Reinhard Guthke, Anna L Schmitt, Hermann Einsele, Jörg Linde, Jürgen Löffler

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Andreas DixSystems Biology / Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology Hans-Knöll-Institute Jena, Germany.
Kristin CzakaiUniversity Hospital Würzburg, Medical Hospital II Würzburg, Germany.
Jan SpringerUniversity Hospital Würzburg, Medical Hospital II Würzburg, Germany.
Mirjam FliesserUniversity Hospital Würzburg, Medical Hospital II Würzburg, Germany.
Michael BoninIMGM Laboratories Martinsried, Germany (Formerly Department of Medical Genetics and Applied Genomics, University Hospital Tübingen, Tübingen, Germany).
Reinhard GuthkeSystems Biology / Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology Hans-Knöll-Institute Jena, Germany.
Anna L SchmittUniversity Hospital Würzburg, Medical Hospital II Würzburg, Germany.
Hermann EinseleUniversity Hospital Würzburg, Medical Hospital II Würzburg, Germany.
Jörg LindeSystems Biology / Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology Hans-Knöll-Institute Jena, Germany.
Jürgen LöfflerUniversity Hospital Würzburg, Medical Hospital II Würzburg, Germany.
Universitätsklinikum Würzburg · DELeibniz-Institut für Naturstoff-Forschung und Infektionsbiologie e. V. - Hans-Knöll-Institut (HKI) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasive aspergillosis (IA) is a devastating opportunistic infection and its treatment constitutes a considerable burden for the health care system. Immunocompromised patients are at an increased risk for IA, which is mainly caused by the species Aspergillus fumigatus. An early and reliable diagnosis is required to initiate the appropriate antifungal therapy. However, diagnostic sensitivity and accuracy still needs to be improved, which can be achieved at least partly by the definition of new biomarkers. Besides the direct detection of the pathogen by the current diagnostic methods, the analysis of the host response is a promising strategy toward this aim. Following this approach, we sought to identify new biomarkers for IA. For this purpose, we analyzed gene expression profiles of hematological patients and compared profiles of patients suffering from IA with non-IA patients. Based on microarray data, we applied a comprehensive feature selection using a random forest classifier. We identified the transcript coding for the S100 calcium-binding protein B (S100B) as a potential new biomarker for the diagnosis of IA. Considering the expression of this gene, we were able to classify samples from patients with IA with 82.3% sensitivity and 74.6% specificity. Moreover, we validated the expression of S100B in a real-time reverse transcription polymerase chain reaction (RT-PCR) assay and we also found a down-regulation of S100B in A. fumigatus stimulated DCs. An influence on the IL1B and CXCL1 downstream levels was demonstrated by this S100B knockdown. In conclusion, this study covers an effective feature selection revealing a key regulator of the human immune response during IA. S100B may represent an additional diagnostic marker that in combination with the established techniques may improve the accuracy of IA diagnosis.

Indexed as

allogeneic stem cell transplantationfungal infectiongene expression datahuman biomarkerinvasive aspergillosis

Identifiers

PMID27047454
PMCPMC4800190
OpenAlexW2319717746

What OpenQuestion holds

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Registered trials

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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.