A transcriptome-based risk model in sepsis enables prognostic prediction and drug repositioning

Autor: Qiuyue Long, Hongli Ye, Shixu Song, Jiwei Li, Jing Wu, Jingsong Mao, Ran Li, Ke Li, Zhancheng Gao, Yali Zheng
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: iScience, Vol 27, Iss 12, Pp 111277- (2024)
Druh dokumentu: article
ISSN: 2589-0042
DOI: 10.1016/j.isci.2024.111277
Popis: Summary: Septic management presented a tremendous challenge due to heterogeneous host responses. We aimed to develop a risk model for early septic stratification based on transcriptomic signature. Here, we combined genes OLAH, LY96, HPGD, and ABLIM1 into a prognostic risk score model, which demonstrated exceptional performance in septic diagnosis (AUC = 0.99–1.00) and prognosis (AUC = 0.61–0.70), outperforming that of Mars and SRS endotypes. Also, the model unveiled immunosuppressive status in high-risk patients and a poor response to hydrocortisone in low-risk individuals. Single-cell transcriptome analysis further elucidated expression patterns and effects of the four genes across immune cell types, illustrating integrated host responses reflected by this model. Upon distinct transcriptional profiles of risk subgroups, we identified fenretinide and meloxicam as therapeutic agents, which significantly improved survival in septic mice models. Our study introduced a risk model that optimized risk stratification and drug repurposing of sepsis, thereby offering a comprehensive management approach.
Databáze: Directory of Open Access Journals