Dataset Information

Immune Checkpoints: Novel Therapeutic Targets to Attenuate Sepsis-Induced Immunosuppression.

ABSTRACT: Sepsis is a leading cause of death in intensive care units and survivors develop prolonged immunosuppression and a high incidence of recurrent infections. No definitive therapy exists to treat sepsis and physicians rely on supportive care including antibiotics, intravenous fluids, and vasopressors. With the rising incidence of antibiotic resistant microbes, it is becoming increasingly critical to discover novel therapeutics. Sepsis-induced leukocyte dysfunction and immunosuppression is recognized as an important contributor towards increased morbidity and mortality. Pre-clinical and clinical studies show that specific cell surface inhibitory immune checkpoint receptors and ligands including PD-1, PD-L1, CTLA4, BTLA, TIM3, OX40, and 2B4 play important roles in the pathophysiology of sepsis by mediating a fine balance between host immune competency and immunosuppression. Pre-clinical studies targeting the inhibitory effects of these immune checkpoints have demonstrated reversal of leukocyte dysfunction and improved host resistance of infection. Measurement of immune checkpoint expression on peripheral blood leukocytes may serve as a means of stratifying patients to direct individualized therapy. This review focuses on advances in our understanding of the role of immune checkpoints in the host response to infections, and the potential clinical application of therapeutics targeting the inhibitory immune checkpoint pathways for the management of septic patients.

SUBMITTER: McBride MA

PROVIDER: S-EPMC7886986 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Immune Checkpoints: Novel Therapeutic Targets to Attenuate Sepsis-Induced Immunosuppression.

McBride Margaret A MA Patil Tazeen K TK Bohannon Julia K JK Hernandez Antonio A Sherwood Edward R ER Patil Naeem K NK

Frontiers in immunology 20210203

Sepsis is a leading cause of death in intensive care units and survivors develop prolonged immunosuppression and a high incidence of recurrent infections. No definitive therapy exists to treat sepsis and physicians rely on supportive care including antibiotics, intravenous fluids, and vasopressors. With the rising incidence of antibiotic resistant microbes, it is becoming increasingly critical to discover novel therapeutics. Sepsis-induced leukocyte dysfunction and immunosuppression is recognize ...[more]

PMID: 33613563

Similar Datasets

Project description:BackgroundSepsis is one of the most lethal diseases worldwide. Pyroptosis is a unique form of cell death, and the mechanism of interaction with sepsis is not yet clear. The aim of this study was to uncover pyroptosis genes associated with sepsis and to provide early therapeutic targets for the treatment of sepsis.MethodsBased on the GSE134347 dataset, sepsis-related genes were mined by differential expression analysis and weighted gene coexpression network analysis (WGCNA). Subsequently, the sepsis-related genes were analysed for enrichment, and a protein‒protein interaction (PPI) network was constructed. We performed unsupervised consensus clustering of sepsis patients based on 33 pyroptosis-related genes (PRGs) provided by prior reviews. We finally obtained the PRGs mostly associated with sepsis by machine learning prediction models combined with prior reviews. The GSE32707 dataset served as an external validation dataset to validate the model and PRGs via receiver operating characteristic (ROC) curves. The NetworkAnalyst online tool was utilized to create a ceRNA network of lncRNAs and miRNAs around PRGs mostly associated with sepsis.ResultsA total of 170 genes associated with sepsis and 13 hub genes were acquired by WGCNA and PPI network analysis. The results of the enrichment analysis implied that these genes were mainly involved in the regulation of the inflammatory response and the positive regulation of bacterial and fungal defence responses. The prolactin signalling pathway and IL-17 signalling pathway were the primary enrichment pathways. Thirty-three PRGs can effectively classify septic patients into two subtypes, implying that there is a reciprocal relationship between sepsis and pyroptosis. Eventually, NLRC4 was considered the PRG most strongly associated with sepsis. The validation results of the prediction model and NLRC4 based on ROC curves were 0.74 and 0.67, respectively, both of which showed better predictive values. Meanwhile, the ceRNA network consisting of 6 lncRNAs and 2 miRNAs was constructed around NLRC4.ConclusionNLRC4, as the PRG mostly associated with sepsis, could be considered a potential target for treatment. The 6 lncRNAs and 2 miRNAs centred on NLRC4 could serve as a further research direction to uncover the deeper pathogenesis of sepsis.

Dataset Information

Immune Checkpoints: Novel Therapeutic Targets to Attenuate Sepsis-Induced Immunosuppression.

Publications

Immune Checkpoints: Novel Therapeutic Targets to Attenuate Sepsis-Induced Immunosuppression.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets