Comprehensive characterization of costimulatory molecule gene for diagnosis, prognosis and recognition of immune microenvironment features in sepsis

Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.

Bibliographische Detailangaben
Veröffentlicht in:Clinical immunology (Orlando, Fla.). - 1999. - 245(2022) vom: 10. Dez., Seite 109179
1. Verfasser: Chen, Zhen (VerfasserIn)
Weitere Verfasser: Dong, Xinhuai, Liu, Genglong, Ou, Yangpeng, Lu, Chuangang, Yang, Ben, Zhu, Xuelian, Zuo, Liuer
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2022
Zugriff auf das übergeordnete Werk:Clinical immunology (Orlando, Fla.)
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Costimulatory molecule Immune microenvironment Machine learning approach Model Multi-transcriptome sepsis CD40 Antigens CD28 Antigens mehr... TNFSF4 protein, human OX40 Ligand
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245 1 0 |a Comprehensive characterization of costimulatory molecule gene for diagnosis, prognosis and recognition of immune microenvironment features in sepsis 
264 1 |c 2022 
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500 |a Date Completed 25.11.2022 
500 |a Date Revised 26.12.2022 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved. 
520 |a The present study, which involved 10 GEO datasets and 3 ArrayExpress datasets, comprehensively characterized the potential effects of CMGs in sepsis. Based on machine learning algorithms (Lasso, SVM and ANN), the CMG classifier was constructed by integrating 6 hub CMGs (CD28, CD40, LTB, TMIGD2, TNFRSF13C and TNFSF4). The CMG classifier exhibit excellent diagnostic values across multiple datasets and time points, and was able to distinguish sepsis from other critical diseases. The CMG classifier performed better in predicting mortality than other clinical characteristics or endotypes. More importantly, from clinical specimens, the CMG classifier showed more superior diagnostic values than PCT and CRP. Alternatively, the CMG classifier/hub CMGs is significantly correlated with immune cells infiltration (B cells, T cells, Tregs, and MDSC), pivotal immune and molecular pathways (inflammation-promoting, complement and coagulation cascades), and several cytokines. Collectively, CMG classifier was a robust tool for diagnosis, prognosis and recognition of immune microenvironment features in sepsis 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Costimulatory molecule 
650 4 |a Immune microenvironment 
650 4 |a Machine learning approach 
650 4 |a Model 
650 4 |a Multi-transcriptome 
650 4 |a sepsis 
650 7 |a CD40 Antigens  |2 NLM 
650 7 |a CD28 Antigens  |2 NLM 
650 7 |a TNFSF4 protein, human  |2 NLM 
650 7 |a OX40 Ligand  |2 NLM 
700 1 |a Dong, Xinhuai  |e verfasserin  |4 aut 
700 1 |a Liu, Genglong  |e verfasserin  |4 aut 
700 1 |a Ou, Yangpeng  |e verfasserin  |4 aut 
700 1 |a Lu, Chuangang  |e verfasserin  |4 aut 
700 1 |a Yang, Ben  |e verfasserin  |4 aut 
700 1 |a Zhu, Xuelian  |e verfasserin  |4 aut 
700 1 |a Zuo, Liuer  |e verfasserin  |4 aut 
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856 4 0 |u http://dx.doi.org/10.1016/j.clim.2022.109179  |3 Volltext 
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