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Hepatology. 2019 Feb 19. doi: 10.1002/hep.30572. [Epub ahead of print]

Predicting Postoperative Liver Dysfunction Based on Blood-Derived MicroRNA Signatures.

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Department of Surgery, Medical University of Vienna, General Hospital, Vienna, Austria.
Division of Bioinformatics, Biocenter, Medical University of Innsbruck, Innsbruck, Austria.
TAmiRNA GmbH, Vienna, Austria.
Department of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.
Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
Department of Surgery I, Rudolfstiftung Hospital, Vienna, Austria.


There is an urgent need for an easily assessable preoperative test to predict postoperative liver function recovery and thereby determine the optimal time point of liver resection, specifically as current markers are often expensive, time consuming, and invasive. Emerging evidence suggests that microRNA (miRNA) signatures represent potent diagnostic, prognostic, and treatment-response biomarkers for several diseases. Using next-generation sequencing as an unbiased systematic approach, 554 miRNAs were detected in preoperative plasma of 21 patients suffering from postoperative liver dysfunction (LD) after liver resection and 27 matched controls. Subsequently, we identified a miRNA signature-consisting of miRNAs 151a-5p, 192-5p, and 122-5p-that highly correlated with patients developing postoperative LD after liver resection. The predictive potential for postoperative LD was subsequently confirmed using real-time PCR in an independent validation cohort of 98 patients. Ultimately, a regression model of the two miRNA ratios 151a-5p to 192-5p and 122-5p to 151a-5p was found to reliably predict postoperative LD, severe morbidity, prolonged intensive care unit and hospital stays, and even mortality before an operation with a remarkable accuracy, thereby outperforming established markers of postoperative LD. Ultimately, we documented that miRNA ratios closely followed liver function recovery after partial hepatectomy. Conclusion: Our data demonstrate the clinical utility of an miRNA-based biomarker to support the selection of patients undergoing partial hepatectomy. The dynamical changes during liver function recovery indicate a possible role in individualized patient treatment. Thereby, our data might help to tailor surgical strategies to the specific risk profile of patients.


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