Abstract
BACKGROUND: Liver ischemia-reperfusion is one of the common complications after liver surgery. Uncontrolled liver ischemia-reperfusion will lead to many serious consequences such as surgical failure. It is an urgent clinical problem to search for diagnostic markers and explore its potential pathogenesis. METHODS: In this study, we focus on 1411 candidate RNA binding protein. Through several GEO (Gene Expression Omnibus) online datasets, we construct a diagnostic model and perform interactive validation. We evaluate the efficacy of the prognostic model. Using bioinformatics methods, we predicted the relevant signaling pathways of liver ischemia-reperfusion and key genes. We also evaluated the association of RNA binding protein with immune cell infiltration. Single cell sequencing datasets were used to explore the expression profiles of key genes at the single cell level. Machine learning algorithm is used to predict key gene RNA binding domains. RESULTS: ROC (Receiver Operating Characteristic) and DCA (Decision Curve Analysis) curves showed that the above diagnostic model had good and stable diagnostic efficacy and clinical practicability. We identified three key genes (BTG2, CCNL1 and DNAJB1) in liver ischemia-reperfusion. DNAJB1, BTG2 and CCNL1 are mainly expressed in immune cells such as macrophages and T cells, and are closely related to inflammatory pathways such as TNF-α, highlighting their importance in hepatic ischemia reperfusion. We identified RNA-binding domains of the above three genes. We found that the expression of DNAJB1, CCNL1 and BTG2 in the ischemia-reperfusion group were significantly higher than those in the sham operation group. CONCLUSION: Our study revealed the importance of the candidate RNA binding protein in liver ischemia reperfusion injury and provided new insights into the therapeutic of hepatic ischemia-reperfusion injury.