A possible role of microRNAs as predictive markers for the recurrence of hepatocellular carcinoma after liver transplantation

• DOI: 10.1111/tri.12733
• Publication Date: 2015-12-23T15:04:38Z
• Authors: Juliane Liese; Jan Peveling-Oberhag; Claudia Doering; Andreas A. Schnit...; Eva Herrmann; Stephan Zangos; Martin L. Hansmann; Christian Moench; Martin W. Welker; Stefan Zeuzem; Wolf O. Bechstein; Frank Ulrich
• Keywords: Adult; Male; Carcinoma, Hepatocellular; Liver Neoplasms; Middle Aged; Liver Transplantation; 3. Good health; MicroRNAs; 03 medical and health sciences; Postoperative Complications; 0302 clinical medicine; Humans; Female; Neoplasm Recurrence, Local; Biomarkers; Aged; Oligonucleotide Array Sequence Analysis; Retrospective Studies

With favourable 5-year survival rates up to 75%, liver transplantation (LT) is the treatment of choice for hepatocellular carcinoma (HCC). Nonetheless, tumour recurrence after LT remains a challenge. The aim of this retrospective study was to develop a predictive score for tumour recurrence after LT by combining clinical parameters with HCC biomarkers (microRNA). A microRNA (miRNA) microarray analysis was used to compare miRNA expression patterns in tissue samples of 40 patients with and without HCC recurrence after LT. In a screening cohort (n = 18), the miRNA analysis identified significant differences in the expression of 13 miRNAs in patients with tumour recurrence. Using the most significant miRNAs in this screening cohort, we could develop a predictive score, which combined the expression levels of miR-214, miR-3187 and the Milan criteria, and we could define low- and high-risk groups for tumour recurrence and death. The above score was evaluated in a second and independent cohort (n = 22). In contrast to the Milan criteria alone, this score was significantly associated with tumour recurrence. Our analysis indicated that the use of a specific miRNA expression pattern in combination with a limited tumour burden as defined by the Milan criteria may lead to a more accurate prediction of tumour recurrence.