Display options
Cite
Dix A, Czakai K, Springer J, et al. Genome-Wide Expression Profiling Reveals S100B as Biomarker for Invasive Aspergillosis. Front Microbiol. 2016;7:320doi: 10.3389/fmicb.2016.00320.
Dix, A., Czakai, K., Springer, J., Fliesser, M., Bonin, M., Guthke, R., Schmitt, A. L., Einsele, H., Linde, J., & Löffler, J. (2016). Genome-Wide Expression Profiling Reveals S100B as Biomarker for Invasive Aspergillosis. Frontiers in microbiology, 7320. https://doi.org/10.3389/fmicb.2016.00320
Dix, Andreas, et al. "Genome-Wide Expression Profiling Reveals S100B as Biomarker for Invasive Aspergillosis." Frontiers in microbiology vol. 7 (2016): 320. doi: https://doi.org/10.3389/fmicb.2016.00320
Dix A, Czakai K, Springer J, Fliesser M, Bonin M, Guthke R, Schmitt AL, Einsele H, Linde J, Löffler J. Genome-Wide Expression Profiling Reveals S100B as Biomarker for Invasive Aspergillosis. Front Microbiol. 2016 Mar 21;7:320. doi: 10.3389/fmicb.2016.00320. eCollection 2016. PMID: 27047454; PMCID: PMC4800190.
Copy Download .nbib Format: NLM
Share it on

Front Microbiol. 2016 Mar 21;7:320. doi: 10.3389/fmicb.2016.00320. eCollection 2016.

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

Frontiers in microbiology

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

Affiliations

  1. Systems Biology / Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology Hans-Knöll-Institute Jena, Germany.
  2. University Hospital Würzburg, Medical Hospital II Würzburg, Germany.
  3. IMGM Laboratories Martinsried, Germany (Formerly Department of Medical Genetics and Applied Genomics, University Hospital Tübingen, Tübingen, Germany).

PMID: 27047454 PMCID: PMC4800190 DOI: 10.3389/fmicb.2016.00320

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.

Keywords: allogeneic stem cell transplantation; fungal infection; gene expression data; human biomarker; invasive aspergillosis

References

  1. J Infect Dis. 2008 Mar 15;197(6):924-31 - PubMed
  2. Clin Infect Dis. 2008 Jun 15;46(12):1813-21 - PubMed
  3. Am J Med Genet B Neuropsychiatr Genet. 2010 Jan 5;153B(1):291-7 - PubMed
  4. Annu Rev Immunol. 2012;30:115-48 - PubMed
  5. Infect Immun. 2006 Sep;74(9):5075-84 - PubMed
  6. Pediatr Res. 2015 Nov;78(5):547-53 - PubMed
  7. Bioinformatics. 2007 Oct 1;23(19):2507-17 - PubMed
  8. Infect Immun. 1997 Feb;65(2):564-70 - PubMed
  9. BMC Bioinformatics. 2009 Feb 03;10:48 - PubMed
  10. J Immunol. 2000 Jul 1;165(1):381-8 - PubMed
  11. PLoS Pathog. 2011 Mar;7(3):e1001315 - PubMed
  12. Sci Transl Med. 2010 Mar 3;2(21):21ra17 - PubMed
  13. Bioinformatics. 2004 Feb 12;20(3):307-15 - PubMed
  14. Clin Chem. 2000 May;46(5):631-5 - PubMed
  15. Nucleic Acids Res. 2001 May 1;29(9):e45 - PubMed
  16. Int J Environ Res Public Health. 2015 Oct 28;12(11):13730-8 - PubMed
  17. Clin Infect Dis. 2010 Feb 1;50(3):405-15 - PubMed
  18. Front Microbiol. 2015 Mar 11;6:171 - PubMed
  19. Clin Infect Dis. 1998 Apr;26(4):781-803; quiz 804-5 - PubMed
  20. PLoS One. 2011;6(8):e24290 - PubMed
  21. Nucleic Acids Res. 2002 Jan 1;30(1):207-10 - PubMed
  22. Clin Infect Dis. 2008 Dec 15;47(12):1507-12 - PubMed
  23. Glia. 2001 Feb;33(2):131-42 - PubMed
  24. J Mol Med (Berl). 2007 Jun;85(6):613-21 - PubMed
  25. Trends Microbiol. 2010 May;18(5):195-204 - PubMed
  26. PLoS One. 2011;6(11):e27962 - PubMed
  27. Methods Mol Biol. 2015;1218:301-19 - PubMed
  28. Oncol Rep. 2012 Sep;28(3):1036-42 - PubMed
  29. J Neurochem. 2005 Feb;92(3):546-53 - PubMed
  30. Nat Genet. 2000 May;25(1):25-9 - PubMed
  31. Proc Natl Acad Sci U S A. 2002 May 14;99(10):6562-6 - PubMed
  32. Nucleic Acids Res. 2009 Apr;37(6):e45 - PubMed
  33. Biostatistics. 2003 Apr;4(2):249-64 - PubMed

Publication Types