Publication:
Serum antibody signature directed against Candida albicans Hsp90 and enolase detects invasive candidiasis in Non-neutropenic patients

Loading...
Thumbnail Image
Full text at PDC
Publication Date
2014
Advisors (or tutors)
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
ACS
Citations
Google Scholar
Research Projects
Organizational Units
Journal Issue
Abstract
Invasive candidiasis (IC) adds significantly to the morbidity and mortality of non-neutropenic patients if not diagnosed and treated early. To uncover serologic biomarkers that alone or in combination could reliably detect IC in this population, IgG antibody-reactivity profiles to the Candida albicans intracellular proteome were examined by serological proteome analysis (SERPA) and data mining procedures in a training set of 24 non-neutropenic patients. Despite the high interindividual molecular heterogeneity, unsupervised clustering analyses revealed that serum 22-IgG antibody-reactivity patterns differentiated IC from non-IC patients. Univariate analyses further highlighted that 15 out of the 22 SERPA-identified IgG antibodies could be useful candidate IC biomarkers. The diagnostic performance of one of these candidates (anti-Hsp90 IgG antibodies) was validated using an ELISA prototype in a test set of 59 non-neutropenic patients. We then formulated an IC discriminator based on the combined immunoproteomic fingerprints of this and another SERPA-detected and previously validated IC biomarker (anti-Eno1 IgG antibodies) in the training set. Its consistency was substantiated using their ELISA prototypes in the test set. Receiver-operating-characteristic curve analyses showed that this two-biomarker signature accurately identified IC in non-neutropenic patients and provided better IC diagnostic accuracy than the individual biomarkers alone. We conclude that this serum IgG antibody signature directed against C. albicans Hsp90 and Eno1, if confirmed prospectively, may be useful for IC diagnosis in non-neutropenic patients.
Description
Keywords
Citation
Collections