Sequencing based quantitative and qualitative analyses of the microRNA transcriptome in hepatitis B related hepatocellular carcinoma.

2007 Fiscal Year Final Research Report Summary

• Project/Area Number: 18390372
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Digestive surgery
• Research Institution: Nippon Medical School
• Principal Investigator: TAJIRI Takashi Nippon Medical School, 大学院・医学研究科, 教授 (20163462)
• Co-Investigator(Kenkyū-buntansha): ARIMA Yasuo 日本医科大学, 医学部, 講師 (30168025) ; YOSHIDA Hiroshi 日本医科大学, 医学部, 准教授 (60246999) ; YOKOMURO Shigeki 日本医科大学, 医学部, 准教授 (30267223) ; MIZUGUCHI Yoshiaki 日本医科大学, 医学部, 特別研究生 (70409217)
• Project Period (FY): 2006 – 2007
• Keywords: Hepatocellular carcinoma / MicroRNA / Hepatitis B virus / Bioinformatics / Sequencing

Research Abstract

MicroRNAs (miRNAs) participate in crucial biological processes, and it is now evident that miRNA alterations are involved in the progression of human cancers. A large number of miRNAs, however, have yet to be discovered, and the precise dynamics of these elements need to be elucidated. Recent studies on miRNA profiling performed with cloning techniques suggest that sequencing methods are superior for the detection of novel miRNAs, modifications, and precise compositions, and that cloning frequencies calculated by clone count analysis are reproducible. Here we focus on sequencing of miRNA to obtain a comprehensive profile and characterization of these transcriptomes as they relate to human liver. The usefulness of sequencing will be shown for the discovery of novel miRNAs and miRNA biomarkers in the patients with hepatitis B associated hepatocellular carcinoma (HCC). We identified reliable reads of more than 314000 miRNAs from HCC and more than 268000 from adjacent normal liver (ANL) for registered human miRNAs. Computational bioinformatics identified more than 250 novel miRNAs. Some novel sequences were derived from the same arm of known precursors, including miR-21, resulting in the identification of three mature sequences. Moreover, the sequence survey revealed various modifications of mature miRNAs. Expression profiling using clone count analysis was used to identify miRNAs including miR-21, miR-122, miR-122*, that are expressed aberrantly in cancer. In this regard, miR-21 appears to be a predictive biomarker for HCC. We believe that sequencing will accelerate the discovery of novel miRNAs and miRNA biomarkers involved in human liver cancer.