作者: Prasong Khaenam , Darawan Rinchai , Matthew C Altman , Laurent Chiche , Surachat Buddhisa
关键词: Gene expression profiling 、 Transcriptome 、 Immune system 、 Bioinformatics 、 Biology 、 Immune dysregulation 、 Peripheral blood mononuclear cell 、 Reporter gene 、 Proteome 、 Sepsis
摘要: Background: There are diverse molecules present in blood plasma that regulate immune functions and also a potential source of disease biomarkers therapeutic targets. Genome-wide profiling has become powerful method for assessing responses on systems scale, but technologies can measure the proteome still face considerable challenges. An alternative approach to direct assessment is transcriptome reporter cells exposed vitro plasma. In this report we describe such “transcriptomic assay” assess from patients with sepsis, which common severe systemic infectious process physicians lack efficient diagnostic or prognostic markers. Methods: Plasma samples collected culture-confirmed bacterial sepsis uninfected healthy controls were used stimulate three separate cell types – neutrophils, peripheral mononuclear cells, monocyte-derived dendritic cells. Whole genome microarrays generated stimulated transcriptional responses. Unsupervised analysis enriched functional networks evaluated each type. Principal component analyses variability A random K-nearest neighbor feature selection algorithm was identify markers predictive severity, then validated an independent data set. Results: Neutrophils demonstrated most distinct response septic 709 genes showing altered expression profiles, many involved established immunologic pathways. The amplitude neutrophil transcriptomic shown be correlated severity two sets comprised 64 total patients. subset 30 transcripts selected using one set have high degree accuracy (82-90%) predicting outcomes other This included several previously pathogenesis as well novel genes. Conclusions: These results demonstrate both suitability clinical relevance assay studying plasma, case distinctive signature found could potentially help predict guide treatment. Our findings shed new light mechanisms dysregulation sepsis.