Identification of S1PR3 gene signature involved in survival of sepsis patients

Free Radical-Associated Gene Signature Predicts Survival in Sepsis Patients

Sepsis continues to overwhelm hospital systems with its high mortality rate and prevalence. A strategy to reduce the strain of sepsis on hospital systems is to develop a diagnostic/prognostic measure that identifies patients who are more susceptible to septic death. Current biomarkers fail to achieve this outcome, as they only have moderate diagnostic power and limited prognostic capabilities. Sepsis disrupts a multitude of pathways in many different organ systems, making the identification of a single powerful biomarker difficult to achieve. However, a common feature of many of these perturbed pathways is the increased generation of reactive oxygen species (ROS), which can alter gene expression, changes in which may precede the clinical manifestation of severe sepsis. Therefore, the aim of this study was to evaluate whether ROS-related circulating molecular signature can be used as a tool to predict sepsis survival. Here we created a ROS-related gene signature and used two Gene Expression Omnibus datasets from whole blood samples of septic patients to generate a 37-gene molecular signature that can predict survival of sepsis patients. Our results indicate that peripheral blood gene expression data can be used to predict the survival of sepsis patients by assessing the gene expression pattern of free radical-associated -related genes in patients, warranting further exploration.

Synthesis, radiosynthesis and biochemical evaluation of fluorinated analogues of sphingosine-1-phosphate receptor 3 specific antagonists using PET

Sphingosine-1-phosphate and its receptors (S1PRs) are involved in several diseases such as auto immunity, inflammation and cardiovascular disorders. The S1P analogue fingolimod (Gilenya®) is currently in use for the treatment of relapsing multiple sclerosis. S1PRs are also promising targets for clinical molecular imaging in vivo. The organ distribution of individual S1PRs can be potentially achieved by using S1PR subtype-specific (radiolabeled) chemical probes. Here, we report our efforts on synthesis and in vivo potency determination of new ligands for the S1P receptor 3 (S1P3) based on the S1P3 antagonist TY-52156 and in validation of a potential imaging tracer in vivo using Positron Emission Tomography (PET) after 18F-labelling. A p-fluorophenyl derivative exhibited excellent S1P3 antagonist activity in vitro, good serum stability, and medium lipophilicity. In vivo biodistribution experiments using 18F-PET exhibited significant uptake in the myocardium suggesting potential applications in cardiac imaging.

Sphingosine-1-Phosphate Receptor 3 Induces Endothelial Barrier Loss via ADAM10-Mediated Vascular Endothelial-Cadherin Cleavage

Mechanical ventilation (MV) is a life-supporting strategy employed in the Intensive Care Unit (ICU). However, MV-associated mechanical stress exacerbates existing lung inflammation in ICU patients, resulting in limited improvement in mortality and a condition known as Ventilator-Induced Lung Injury (VILI). Sphingosine-1-phosphate (S1P) is a circulating bioactive lipid that maintains endothelial integrity primarily through S1P receptor 1 (S1PR1). During VILI, mechanical stress upregulates endothelial S1PR3 levels. Unlike S1PR1, S1PR3 mediates endothelial barrier disruption through Rho-dependent pathways. However, the specific impact of elevated S1PR3 on lung endothelial function, apart from Rho activation, remains poorly understood. In this study, we investigated the effects of S1PR3 in endothelial pathobiology during VILI using an S1PR3 overexpression adenovirus. S1PR3 overexpression caused cytoskeleton rearrangement, formation of paracellular gaps, and a modified endothelial response towards S1P. It resulted in a shift from S1PR1-dependent barrier enhancement to S1PR3-dependent barrier disruption. Moreover, S1PR3 overexpression induced an ADAM10-dependent cleavage of Vascular Endothelial (VE)-cadherin, which hindered endothelial barrier recovery. S1PR3-induced cleavage of VE-cadherin was at least partially regulated by S1PR3-mediated NFκB activation. Additionally, we employed an S1PR3 inhibitor TY-52156 in a murine model of VILI. TY-52156 effectively attenuated VILI-induced increases in bronchoalveolar lavage cell counts and protein concentration, suppressed the release of pro-inflammatory cytokines, and inhibited lung inflammation as assessed via a histological evaluation. These findings confirm that mechanical stress associated with VILI increases S1PR3 levels, thereby altering the pulmonary endothelial response towards S1P and impairing barrier recovery. Inhibiting S1PR3 is validated as an effective therapeutic strategy for VILI.

[Knockout of S1PR3 attenuates acute lung injury in mice by inhibiting the MAPK pathway]

OBJECTIVE

To investigate whether knockout of S1PR3 improves lipopolysaccharide (LPS)-induced acute lung injury in mice by inhibiting mitogen activated protein kinases (MAPKs).

METHODS

Male C57BL/6J and S1PR3 knockout (S1PR3^-/-) mice were both randomized into two groups (n=8) for intratracheal instillation of normal saline or LPS to induce acute lung injury. The expressions of S1PR3, IL-1β and IL-18 in the lung tissues were detected using RT-qPCR, lung tissue injury was observed with HE staining, and cell apoptosis was detected using flow cytometry. Western blotting was performed to detect the expression levels of caspase-1, GSDMD, p-JNK, p-ERK and p-p38 proteins. In the cell experiment, type II alveolar epithelial cells (MLE-12 cells) were treated with PBS, LPS, CYM5541 (a S1PR3 agonist), or CYM5541 + LPS, and the cell apoptosis and expression levels of MAPK signal pathway molecules were detected.

RESULTS

The expression of S1PR3 was up-regulated and serum IL-1β and IL-18 levels were elevated significantly in the nontransgenic mice with acute lung injury (P < 0.001). By comparison, the elevation of IL-1β and IL-18 levels was obviously reduced in S1PR3 knockout mice with acute lung injury, which also showed significant improvement of pulmonary hemorrhage, inflammation and exudation, lowered wet-to-dry ratio of the lungs, and decreased cell apoptosis and expressions of cleaved caspase-1 and GSDMD (P < 0.05). In MLE-12 cells, treatment with the S1PR3 agonist significantly increased the expression of pyroptosis-associated proteins (P < 0.05). S1PR3 knockout strongly inhibited the activation of MAPKs family (JNK and ERK p38; P < 0.05), but their expressions were significantly increased following treatment with the S1PR3 agonist (P < 0.05).

CONCLUSION

Inhibition of S1PR3 can improve LPSinduced acute lung injury in mice by inhibiting the activation of MAPK signaling.

Development and validation of novel inflammatory response-related gene signature for sepsis prognosis

Due to the low specificity and sensitivity of biomarkers in sepsis diagnostics, the prognosis of sepsis patient outcomes still relies on the assessment of clinical symptoms. Inflammatory response is crucial to sepsis onset and progression; however, the significance of inflammatory response-related genes (IRRGs) in sepsis prognosis is uncertain. This study developed an IRRG-based signature for sepsis prognosis and immunological function. The Gene Expression Omnibus (GEO) database was retrieved for two sepsis microarray datasets, GSE64457 and GSE69528, followed by gene set enrichment analysis (GSEA) comparing sepsis and healthy samples. A predictive signature for IRRGs was created using least absolute shrinkage and selection operator (LASSO). To confirm the efficacy and reliability of the new prognostic signature, Cox regression, Kaplan-Meier (K-M) survival, and receiver operating characteristic (ROC) curve analyses were performed. Subsequently, we employed the GSE95233 dataset to independently validate the prognostic signature. A single-sample GSEA (ssGSEA) was conducted to quantify the immune cell enrichment score and immune-related pathway activity. We found that more gene sets were enriched in the inflammatory response in sepsis patient samples than in healthy patient samples, as determined by GSEA. The signature of nine IRRGs permitted the patients to be classified into two risk categories. Patients in the low-risk group showed significantly better 28-d survival than those in the high-risk group. ROC curve analysis corroborated the predictive capacity of the signature, with the area under the curve (AUC) for 28-d survival reaching 0.866. Meanwhile, the ssGSEA showed that the two risk groups had different immune states. The validation set and external dataset showed that the signature was clinically predictive. In conclusion, a signature consisting of nine IRRGs can be utilized to predict prognosis and influence the immunological status of sepsis patients. Thus, intervention based on these IRRGs may become a therapeutic option in the future.

SOX18-associated gene signature predicts sepsis outcome

OBJECTIVES

Sepsis is a critical medical condition associated with an high mortality. Currently, there are no reliable diagnostic or prognostic biomarkers to evaluate sepsis outcomes. SRY (sex-determining region on the Y chromosome)-box transcription factor 18 (SOX18) is an endothelial barrier protective protein, and a decreased level of SOX18 expression is involved in disruption of human endothelial cell barrier integrity. Over-expression of SOX18 attenuates the bacterial lipopolysaccharide (LPS)-mediated disruption of the vascular barrier and is associated with favorable prognosis. The utility of SOX18-related genes as biomarkers in sepsis is uncertain.

METHODS

Transcriptomic analysis was used to profile the PBMC samples of patients with sepsis across two Gene Expression Omnibus (GEO) datasets with survival data. An 84-gene signature was derived from discovery datasets that correlated with SOX18 gene expression and sepsis survival.

RESULTS

Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed Th1 and Th2 cell differentiation, Cytokine-cytokine receptor interaction, and T cell receptor signaling pathways as the most significantly enriched KEGG pathways among 84 genes. A severity score based on the gene expression of 84 genes was allocated to each patient. A notable increase was detected in sepsis patients compared to healthy controls in both discovery and validation cohorts. SOX18-associated gene signature discriminated severe cases from mild cases and performed significantly better than both random 84-gene sets from whole genomes or sepsis survival-related genes. Furthermore, we obtained an 18-gene signature from screening these 84 genes in a LASSO model, which performed better in both discovery and validation cohorts.

CONCLUSIONS

Data support SOX18-associated gene signatures as a prognostic biomarker for sepsis.