ArticleFrontiers in microbiology2016
Genome-Wide Expression Profiling Reveals S100B as Biomarker for Invasive Aspergillosis.
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.
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Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- HIF‑1 and macrophage activation signalling pathways are potential biomarkers of invasive aspergillosis.Experimental and therapeutic medicine · 2024Article
- Article
- Differential genes expression analysis of invasive aspergillosis: a bioinformatics study based on mRNA/microRNA.Molecular biology research communications · 2020Article
- Advances in Understanding Human Genetic Variations That Influence Innate Immunity to Fungi.Frontiers in cellular and infection microbiology · 2020Review
- Fungal biomarker discovery by integration of classifiers.BMC genomics · 2017Article
- Association of S100B polymorphisms and serum S100B with risk of systemic lupus erythematous in a Chinese population.Genetics and molecular biologyArticle
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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