HepatomiR® – MicroRNA Biomarkers of Liver Function: from Discovery to Implementation as a Diagnostic Test to Support Management of Liver Cancer Patients

HepatomiR® – MicroRNA Biomarkers of Liver Function: from Discovery to Implementation as a Diagnostic Test to Support Management of Liver Cancer Patients

Abstract
Background: MicroRNAs (miRNAs) are considered biomarker candidates since their detection in liquid biopsies. However, few circulating miRNAs have been successfully validated and implemented in diagnostic routines. Common technical challenges on the path to validation of miRNA biomarkers are pre-analytical variability, analytical bias, and bridging from discovery assays to targeted assay formats.
However, the tissue-specificity of miRNAs is a strength that can be exploited for application as a minimal-invasive biomarker of chronic or acute organ disease. In this context, the liver is a promising organ for miRNA-based diagnostics. Liver cancer is associated with high mortality. Surgical removal of liver tumors (hepatectomy) improves patient outcomes such as overall survival (OS) but is associated with an increased risk of post-hepatectomy liver failure (PHLF). There is an urgent need for a preoperative test to predict the risk of PHLF, specifically as current markers are expensive, time-consuming, and invasive.
Method: We followed a systematic approach to discover, validate, and implement a miRNA biomarker to predict PHLF (hepatomiR®). First, we assessed the impact of sample collection protocols on miRNA detection and selected platelet-poor citrate/CTAD plasma as the best matrix. Next, we applied an optimized small RNA-sequencing assay (miND®) to 48 plasma samples to select the lead miRNA biomarker candidates, miR-122, miR-151a, and miR-192. We re-analyzed the samples by RT-qPCR to complete assay bridging and developed an algorithm that converts miRNA raw data into an actionable Probability-Score (“P-score”). After analytical validation, the test was applied to 86 patients with end-stage liver disease and the preoperative plasma of 333 patients undergoing hepatic resection. Statistics were based on non-parametric tests, receiver operating characteristics (ROC) analysis, Cox regression, and log-rank tests.
Results: P-score showed moderate correlations with liver function tests (GOT: r=0.528, GPT r=0.388, p<0.001). However, P-score showed a high predictive potential for PHLF with an area under the curve (AUC) of 0.774, which was superior to indocyanine green clearance (ICG) testing (PDR: AUC=0.569, R15: AUC=0.618), Limax (AUC=0.564), and HVPG (AUC=0.664). P-score was significantly associated with OS upon Cox-regression (hazard ratio [HR]=4.34, 95% confidence interval [CI]: 1.90-9.98, p=0.001), which remained significant in a multivariable model adjusting for age, sex, tumor entity, and extent of resection. We observed a net benefit in cost-effectiveness after the introduction of the P-score as a standard of risk assessment prior to hepatic resection. Conclusion: The data was used to prepare the technical documentation for the authorization of hepatomiR® as a CE-IVD test in Europe. The test can become vital for the personalized treatment of patients subjected to hepatic resection and to reduce PHLF and postoperative mortality in this cohort.