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Computational identification of novel potential genetic pathogenesis and otherwise biomarkers in acute liver allograft rejection.
Zhang, Cheng; Chen, Jun-Ze; Dong, Kun; Jian, Yong-Yuan; Huang, Kai-Yong; Su, Rui-Ling; Tan, Xue-Lin; Yuan, Guan-Dou; Lan, Yu-Yan; He, Song-Qing; Dong, Chun-Qiang.
Affiliation
  • Zhang C; Department of Organ Transplantation, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Chen JZ; Department of Organ Transplantation, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Dong K; Department of Organ Transplantation, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Jian YY; Department of Organ Transplantation, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Huang KY; Department of Organ Transplantation, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Su RL; Department of Organ Transplantation, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Tan XL; Department of Organ Transplantation, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Yuan GD; Department of Hepatobiliary Surgery, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Lan YY; Key Laboratory of Early Prevention and Treatment for Regional High-Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, China.
  • He SQ; Guangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Nanning, Guangxi, China.
  • Dong CQ; Department of Anesthesiology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Heliyon ; 10(15): e33359, 2024 Aug 15.
Article de En | MEDLINE | ID: mdl-39170115
ABSTRACT
Acute cellular rejection (ACR) is a prevalent postoperative complication following liver transplantation (LT), exhibiting an increasing incidence of morbidity and mortality. However, the molecular mechanisms of ACR following LT remain unclear. To explore the genetic pathogenesis and identify biomarkers of ACR following LT, three relevant Gene Expression Omnibus (GEO) datasets consisting of data on ACR or non-ACR patients after LT were comprehensively investigated by computational analysis. A total of 349 upregulated and 260 downregulated differentially expressed genes (DEGs) and eight hub genes (ISG15, HELZ2, HNRNPK, TIAL1, SKIV2L2, PABPC1, SIRT1, and PPARA) were identified. Notably, HNRNPK, TIAL1, and PABPC1 exhibited the highest predictive potential for ACR with AUCs of 0.706, 0.798, and 0.801, respectively. KEGG analysis of hub genes revealed that ACR following LT was predominately associated with ferroptosis, protein processing in the endoplasmic reticulum, complement and coagulation pathways, and RIG-I/NOD/Toll-like receptor signaling pathway. According to the immune cell infiltration analysis, γδT cells, NK cells, Tregs, and M1/M2-like macrophages had the highest levels of infiltration. Compared to SIRT1, ISG15 was positively correlated with γδT cells and M1-like macrophages but negatively correlated with NK cells, CD4+ memory T cells, and Tregs. In conclusion, this study identified eight hub genes and their potential pathways, as well as the immune cells involved in ACR following LT with the greatest levels of infiltration. These findings provide a new direction for future research on the underlying mechanism of ACR following LT.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Heliyon Année: 2024 Type de document: Article Pays d'affiliation: Chine Pays de publication: Royaume-Uni

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Heliyon Année: 2024 Type de document: Article Pays d'affiliation: Chine Pays de publication: Royaume-Uni