A research group at the Medical University of Vienna has shown that a particular microRNA signature has the potential to serve as a rapid and reliable predictor of postoperative liver failure, which is the most serious complication that can occur following liver resection to remove liver tumors.1

There is an urgent need for an easily accessible preoperative test to predict postoperative liver function recovery—and thereby determine the optimal timing for liver resection—particularly since the currently available methods for performing preoperative risk stratification are costly, time-consuming, and invasive.

Patrick Starlinger, MD, PhD.

Patrick Starlinger, MD, PhD, Medical University of Vienna.

For several years, a group of Vienna researchers led by Patrick Starlinger, MD, PhD, an associate professor of surgery, and Alice Assinger, PhD, an associate professor in the center for physiology and pharmacology, have been focusing on the prediction of postoperative liver dysfunction and clinical outcomes that can be expected following liver resection. MicroRNA signatures represent a new approach in this research and are already known as potent diagnostic, prognostic, and treatment response biomarkers for many different diseases.

The researchers have identified particular microRNA signatures as biomarkers for liver failure. Using next-generation sequencing, 554 miRNAs were detected in preoperative plasma of 21 patients suffering from postoperative liver dysfunction following liver resection and 27 matched controls.

Subsequently, the researchers also identified a miRNA signature consisting of miRNAs 151a-5p, 192-5p, and 122-5p, which strongly correlated with patients developing postoperative liver dysfunction following liver resection. The predictive potential for postoperative liver dysfunction was subsequently confirmed in an independent validation cohort of 98 patients. The two miRNA ratios 151a-5p:192-5p and 122-5p:151a-5p were found to reliably predict postoperative liver dysfunction, severe morbidity, prolonged intensive care unit and hospital stay, and even mortality, prior to surgery.

“We were able to achieve a remarkable degree of accuracy, thereby outperforming established markers,” explains Starlinger. “This will help us in terms of individualized patient care and to tailor surgical strategies to the specific risk profile of the patient.”

For further information, visit Medical University of Vienna.

Reference

  1. Starlinger P, Hackl H, Pereyra D, et al. Predicting postoperative liver dysfunction based on blood-derived microRNA signatures. Hepatology. Epub ahead of print, February 19, 2019; doi: 10.1002/hep.30572.