Myeloid-Derived Suppressor-like Cells as a Prognostic Marker in Critically Ill Patients: Insights from Experimental Endotoxemia and Intensive Care Patients.
Irene T SchrijverJacobus HerderscheeCharlotte ThéroudeAntonios KritikosGuus LeijteDidier Le RoyMaëlick BrochutJean-Daniel ChicheMatthieu PerreauGiuseppe PantaleoBenoit GueryMatthijs KoxPeter PickkersThierry CalandraThierry RogerPublished in: Cells (2024)
Patients admitted to the intensive care unit (ICU) often experience endotoxemia, nosocomial infections and sepsis. Polymorphonuclear and monocytic myeloid-derived suppressor cells (PMN-MDSCs and M-MDSCs) can have an important impact on the development of infectious diseases, but little is known about their potential predictive value in critically ill patients. Here, we used unsupervised flow cytometry analyses to quantify MDSC-like cells in healthy subjects challenged with endotoxin and in critically ill patients admitted to intensive care units and at risk of developing infections. Cells phenotypically similar to PMN-MDSCs and M-MDSCs increased after endotoxin challenge. Similar cells were elevated in patients at ICU admission and normalized at ICU discharge. A subpopulation of M-MDSC-like cells expressing intermediate levels of CD15 (CD15 int M-MDSCs) was associated with overall mortality ( p = 0.02). Interestingly, the high abundance of PMN-MDSCs and CD15 int M-MDSCs was a good predictor of mortality ( p = 0.0046 and 0.014), with area under the ROC curve for mortality of 0.70 (95% CI = 0.4-1.0) and 0.86 (0.62-1.0), respectively. Overall, our observations support the idea that MDSCs represent biomarkers for sepsis and that flow cytometry monitoring of MDSCs may be used to risk-stratify ICU patients for targeted therapy.
Keyphrases
- intensive care unit
- flow cytometry
- induced apoptosis
- end stage renal disease
- cell cycle arrest
- mechanical ventilation
- chronic kidney disease
- ejection fraction
- newly diagnosed
- prognostic factors
- infectious diseases
- peritoneal dialysis
- risk factors
- acute kidney injury
- emergency department
- cardiovascular disease
- machine learning
- oxidative stress
- type diabetes
- endoplasmic reticulum stress
- escherichia coli
- inflammatory response
- lps induced
- patient reported outcomes
- cell death
- microbial community
- klebsiella pneumoniae
- coronary artery disease
- pseudomonas aeruginosa
- drug resistant
- wastewater treatment
- pi k akt