Expression and Clinical Significance of Decoy Receptor 3 in Acute-on-Chronic Liver Failure

Research Progress of DcR3 in the Diagnosis and Treatment of Sepsis

Decoy receptor 3 (DcR3), a soluble glycosylated protein in the tumor necrosis factor receptor superfamily, plays a role in tumor and inflammatory diseases. Sepsis is a life-threatening organ dysfunction caused by the dysregulation of the response to infection. Currently, no specific drug that can alleviate or even cure sepsis in a comprehensive and multi-level manner has been found. DcR3 is closely related to sepsis and considerably upregulated in the serum of those patients, and its upregulation is positively correlated with the severity of sepsis and can be a potential biomarker for diagnosis. DcR3 alone or in combination with other markers has shown promising results in the early diagnosis of sepsis. Furthermore, DcR3 is a multipotent immunomodulator that can bind FasL, LIGHT, and TL1A through decoy action, and block downstream apoptosis and inflammatory signaling. It also regulates T-cell and macrophage differentiation and modulates immune status through non-decoy action; therefore, DcR3 could be a potential drug for the treatment of sepsis. The application of DcR3 in the treatment of a mouse model of sepsis also achieved good efficacy. Here, we introduce and discuss the progress in, and suggest novel ideas for, research regarding DcR3 in the diagnosis and treatment of sepsis.

Identification of a costimulatory molecule-based signature for predicting prognosis risk and immunotherapy response in patients with lung adenocarcinoma

Background

Costimulatory molecules play significant roles in mounting anti-tumor immune responses, and antibodies targeting these molecules are recognized as promising adjunctive cancer immunotherapies. Here, we aim to conduct a first full-scale exploration of costimulatory molecules from the B7-CD28 and TNF families in patients with lung adenocarcinoma (LUAD) and generated a costimulatory molecule-based signature (CMS) to predict survival and response to immunotherapy.

Methods

We enrolled 1549 LUAD cases across 10 different cohorts and included 502 samples from TCGA for discovery. The validation set included 970 cases from eight different Gene Expression Omnibus (GEO) datasets and 77 frozen tumor tissues with qPCR data. The underlying mechanisms and predictive immunotherapy capabilities of the CMS were also explored.

Results

A five gene-based CMS (CD40LG, TNFRSF6B, TNFSF13, TNFRSF13C, and TNFRSF19) was initially constructed using the bioinformatics method from TCGA that classifies cases as high- vs. low-risk groups per OS. Multivariable Cox regression analysis confirmed that the CMS was an independent prognostic factor. As expected, CMS exhibited prognostic significance in the stratified cohorts and different validation cohorts. Additionally, the prognostic meta-analysis revealed that CMS was superior to the previous signature. Samples in high- and low-risk groups exhibited significantly different tumor-infiltrating leukocytes and inflammatory activities. Importantly, we found that the CMS scores were closely related to multiple immunotherapy biomarkers.

Conclusion

We conducted the first and most comprehensive costimulatory molecule landscape analysis of patients with LUAD and built a clinically feasible CMS for prognosis and immunotherapy response prediction, which will be helpful for further optimize immunotherapies for cancer.