Dataset Information

LPS-stimulated endothelial cells using SILAC

ABSTRACT: Severe sepsis and septic shock, which occur with high incidence and are prevalent in the emergency department setting, are among the most common causes of death in hospitalized patients worldwide, and there has been a continuous increase in the incidence of sepsis of approximately 5–10% per year. Endothelial cells constitute an important metabolic organ in the physiological homeostasis of blood vessels and play a pivotal role in orchestrating the inflammatory response triggered by sepsis or endotoxemia. The secretome is defined as the subset of the proteome that contains all the proteins actively exported by a cell following a particular event.

INSTRUMENT(S): LTQ FT

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Sangkyu Lee

PROVIDER: MSV000081707 | MassIVE | Fri Nov 10 12:18:00 GMT 2017

SECONDARY ACCESSION(S): PXD002220

REPOSITORIES: MassIVE

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Publications

In-depth proteomics approach of secretome to identify novel biomarker for sepsis in LPS-stimulated endothelial cells.

Kwon Oh Kwang OK Lee Wonhwa W Kim Sun Ju SJ Lee You-Mie YM Lee Ju Yeon JY Kim Jin Young JY Bae Jong-Sup JS Lee Sangkyu S

Electrophoresis 20150913 23

Sepsis and septic shock, which are conditions triggered by infection, occur with high incidence in emergency departments and are among the most common causes of death in hospitalized patients worldwide. Therefore, the identification of sepsis biomarkers for the rapid diagnosis is a major goal for researchers in the field of critical care. Endothelial cells play a pivotal role in orchestrating the inflammatory response triggered by sepsis. In this study, we used proteomics to investigate the secr ...[more]

PMID: 26257168

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Project description:Goal of the experiment: To identify correlated genes, pathways and groups of patients with systemic inflammatory response syndrome and septic shock that is indicative of biologically important processes active in these patients. Background: We measured gene expression levels and profiles of children with systemic inflammatory response syndrome (SIRS) and septic shock as a means for discovering patient sub-groups and gene signatures that are active in disease-affected individuals and potentially in patients with poor outcomes. Methods: Microarray and bioinformatics analyses of 123 microarray chips representing whole blood derived RNA from controls, children with SIRS, and children with septic shock. Results: A discovery-based filtering approach was undertaken to identify genes whose expression levels were altered in patients with SIRS or septic shock. Clustering of these genes identified 3 Major and several minor sub-groups of patients with SIRS or septic shock. The three groups differed with respect to incidence of septic shock and trended toward differences in mortality. Statistical analyses demonstrated that 6,435 gene probes were differentially regulated between the three patient sub-groups (false discovery rate < 0.001%). Of these gene probes, 623 gene probes within 7 major gene ontologies accounted for the majority of group differentiation. Network analyses of these 623 gene probes demonstrated 5 major gene networks that were differentially expressed between the 3 groups. Statistical comparison of septic shock survivors and non-survivors identified one major gene network that was under expressed in a high fraction of the non-survivors and identified potential biomarkers for poor outcome. Conclusions: This is the first genome-level demonstration of pediatric patient sub-groups with SIRS and septic shock. The sub-groups differ clinically and differentially express 5 major gene networks. We have identified gene signatures and potential biomarkers associated with poor outcome in children with septic shock. These data represent a major advancement in our genome-level understanding of pediatric SIRS and septic shock. Experiment Overall Design: Children < 10 years of age admitted to the pediatric intensive care unit and meeting the criteria for either SIRS or septic shock were eligible for the study. SIRS and septic shock were defined based on pediatric-specific criteria. We did not use separate categories of "sepsis" or "severe sepsis". Patients meeting criteria for "sepsis" or "severe sepsis" were placed in the categories of SIRS and septic shock, respectively, for study purposes. Control patients were recruited from the outpatient or inpatient departments of the participating institutions using the following exclusion criteria: a recent febrile illness (within 2 weeks), recent use of anti-inflammatory medications (within 2 weeks), or any history of chronic or acute disease associated with inflammation. Experiment Overall Design: After obtaining informed consent, blood samples were obtained on Day 1 of the study, and when possible on Day 3 of the study. Blood samples were divided for RNA extraction and isolation of serum. Severity of illness was calculated based on the PRISM III score. Organ failure was defined based on pediatric-specific criteria. Annotated clinical and laboratory data were collected daily while in the intensive care unit. Study patients were placed in the study categories of SIRS or Septic Shock on Day 1 of the study. On Day 3 of the study, patients were classified as SIRS, Septic Shock, or SIRS resolved (no longer meeting criteria for SIRS). All study patients were followed for 28 days to determine mortality or survival. Clinical, laboratory, and biological data were entered and stored using a web-based data base developed locally.

Dataset Information

LPS-stimulated endothelial cells using SILAC

Publications

In-depth proteomics approach of secretome to identify novel biomarker for sepsis in LPS-stimulated endothelial cells.

Similar Datasets

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