Analysis of Immune and Prognostic-Related lncRNA PRKCQ-AS1 for Predicting Prognosis and Regulating Effect in Sepsis - Ding X; Liang W; Xia H; Liu Y; Liu S; Xia X; Zhu X; Pei Y; Zhang D (Dove Medical Press, 2024)
Xian Ding,1,* Wenqi Liang,2,* Hongjuan Xia,1,* Yuee Liu,2 Shuxiong Liu,1 Xinyu Xia,1 Xiaoli Zhu,1 Yongyan Pei,3 Dewen Zhang4 1Department of Emergency, Third Affiliated Hospital of Naval Medical University, Shanghai, People's Republic of China; 2Department of Emergency, Shanghai Changhai Hospital, Naval Medical University, Shanghai, People's Republic of China; 3School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Zhongshan, People's Republic of China; 4Longhua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China*These authors contributed equally to this workCorrespondence: Yongyan Pei, School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, No. 9-13, Zhongshan Campus, No. 13, Changmingshui Avenue, Wuguishan, Zhongshan City, Guangdong Province, People's Republic of China, Email peiyongyan@gdpu.edu.cn Dewen Zhang, Longhua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New Area, Shanghai, People's Republic of China, Email zhangdewen120@hotmail.comBackground: Sepsis was a high mortality and great harm systemic inflammatory response syndrome caused by infection. lncRNAs were potential prognostic marker and therapeutic target. Therefore, we expect to screen and analyze lncRNAs with potential prognostic markers in sepsis.Methods: Transcriptome sequencing and limma was used to screen dysregulated RNAs. Key RNAs were screened by correlation analysis, lncRNA-mRNA co-expression and weighted gene co-expression network analysis. Immune infiltration, gene set enrichment analysis and gene set variation analysis were used to analyze the immune correlation. Kaplan-Meier curve, receiver operator characteristic curve, Cox regression analysis and nomogram were used to analyze the correlation between key RNAs and prognosis. Sepsis model was established by lipopolysaccharide-induced HUVECs injury, and then cell viability and migration ability were detected by cell counting kit-8 and wound healing assay. The levels of apoptosis-related proteins and inflammatory cytokines were detected by RT-qPCR and Western blot. Reactive Oxygen Species and superoxide dismutase were detected by commercial kit.Results: Fourteen key differentially expressed lncRNAs and 663 key differentially expressed genes were obtained. And these lncRNAs were closely related to immune cells, especially T cell activation, immune response and inflammation. Subsequently, Subsequently, lncRNA PRKCQ-AS1 was identified as the regulator for further investigation in sepsis. RT-qPCR results showed that PRKCQ-AS1 expression was up-regulated in clinical samples and sepsis model cells, which was an independent prognostic factor in sepsis patients. Immune correlation analysis showed that PRKCQ-AS1 was involved in the immune response and inflammatory process of sepsis. Cell function tests confirmed that PRKCQ-AS1 could inhibit sepsis model cells viability and promote cell apoptosis, inflammatory damage and oxidative stress.Conclusion: We constructed immune-related lncRNA-mRNA regulatory networks in the progression of sepsis and confirmed that PRKCQ-AS1 is an important prognostic factor affecting the progression of sepsis and is involved in immune response.Keywords: sepsis, immune-related lncRNA, lncRNA-mRNA, PRKCQ-AS1, prognosis and progress