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SIDRA

GXB

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Description

Identification of biomarkers of response to IFNg during endotoxin tolerance: application to septic shock - GSE46914

Purpose

The rapid development in septic patients of features of marked immunosuppression associated with increased risk of nosocomial infections and mortality represents the rational for the initiation of immune targeted treatments in sepsis. However, as there is no clinical sign of immune dysfunctions, the current challenge is to develop biomarkers that will help clinicians identify the patients that would benefit from immunotherapy and monitor its efficacy. Using an in vitro model of endotoxin tolerance (ET), a pivotal feature of sepsis-induced immunosuppression in monocytes, we identified using gene expression profiling by microarray a panel of transcripts associated with the development of ET which expression was restored after immunostimulation with interferon-gamma (IFN-?). These results were confirmed by qRT-PCR. Importantly, this short-list of markers was further evaluated in patients. Of these transcripts, six (TNFAIP6, FCN1, CXCL10, GBP1, CXCL5 and PID1) were differentially expressed in septic shock patients’ blood compared to healthy blood upon ex vivo LPS stimulation and were restored by IFN-?. In this study, by combining a microarray approach in an in vitro model and a validation in clinical samples, we identified a panel of six transcripts that could be used for the identification of septic patients eligible for IFNg therapy. The potential value of these markers should now be evaluated in a larger cohort of patients. Upon favorable results, they could serve as stratification tools prior to immunostimulatory treatment and to monitor drug efficacy.

Experimental Design

PBMCs from 6 healthy donor were left unstimulated (medium) or with 1 shot of LPS (LPS unprimed), 2 shots of LPS (LPS primed) or 2 shots of LPS and Interferon gamma (LPS primed + IFNg).

Experimental Variables

Lipopolysaccharide exposure (2021 ICD-10-CM code* = Not Applicable)

Methods

Expression data were generated using the Robust Multi-array Average (RMA) method implemented in the Affymetrix package of the Bioconductor microarray analysis environment (http://www.bioconductor.org).

Additional Information

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE46914

Platform Affymetrix HG-U133_Plus_2
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