Pengyuan Liu - Personal Profile
1992 - 1996 - B.S., Zhejiang University, Hangzhou, China
1996 - 2002 - Ph.D., Zhejiang University, Hangzhou, China
2002 - 2004 - Postdoctoral Fellow, Creighton University, Omaha, NE
2004 - 2006 - Postdoctoral Associate, Washington University, St Louis, MO
2007 - 2010 - Research Assistant Professor, Washington University, St Louis, MO
2010 - 2016 - Associate Professor, Medical College of Wisconsin, Milwaukee, WI
2016 - Present – Adjunct Associate Professor, Medical College of Wisconsin, Milwaukee, WI
2016 -Present - Professor, Institute of Translational Medicine, Zhejiang University
The research interests of Dr. Pengyuan Liu lie in the area of bioinformatics and cancer genomics. He aims to develop statistical and computational methods for discovery by using the biomedical Big Data.
1. Bioinformatics tools for mutation discovery in cancer genome sequencing studies
Most of cancers arise as a result of changes that have occurred in the DNA sequence of cancer cells. Next-generation sequencing (NGS) technology has revolutionized cancer genomics research by providing an unbiased and comprehensive method of detecting somatic cancer genome alterations. However, major challenges exist that are unique to cancer sequencing data. These challenges include dealing with unknown levels of tumor heterogeneity and the complexity of somatic mutations within the tumor tissues. To address these challenges, we aim to develop a powerful statistical and bioinformatics framework for inference of somatic mutation patterns, estimation of tumor purity, determination of subclones, and recalibration of sequence errors in cancer genome sequencing studies.
2. Role of lncRNA in lung carcinogenesis and progression.
Long non-coding RNAs (lncRNA) are non-protein coding transcripts longer than 200 nucleotides. LncRNAs play an important role in the regulation of gene transcription. Recent recognition that long ncRNAs function in various aspects of cell biology has focused increasing attention on their potential to contribute towards disease aetiology. However, little is known about the role of lincRNA in lung carcinogenesis and progression. We have conducted a comprehensive analysis of lincRNA transcriptomes in lung cancer using RNA-Seq. Over 10,000 lincRNA were identified in lung tumor tissues. Several questions need to be addressed: (1) Which lincRNAs are dysregulated in lung tumors? (2) Are these dysregulated lincRNAs associated with the clinical outcome of lung cancer patients? (3) What are their functional role in lung tumorigenesis and progression?
3. Identification and validation of tRFs in TCGA pan-cancer dataset
Until recently, transfer RNAs (tRNAs) were thought to function in protein translation only. However, recent findings demonstrate that both pre- and mature tRNAs can undergo endonucleolytic cleavage (with yet unknown mechanisms) originating different types of small non-coding RNAs, known as tRNA-derived RNA fragments (tRFs). tRFs are a novel class of small non-coding RNAs and are abundant in many organisms, yet their role in cancer remains largely unexplored. Generally, at least five types of tRFs have been defined based on their cleavage sites in tRNAs: 5ʹ-and 3ʹ-halves (>30 nt), 5ʹ- and 3ʹ-tRFs (15-30 nt), and 3ʹU-tRFs (also named as tsRNAs). However, identification of tRFs from small RNA sequencing data presents two main challenges: 1) lack of evidence-based tRFs annotation, and 2) multiple potential mapping loci in the human genome for most of tRFs. Standard analysis procedures for miRNAs are unable to effectively mine these fragments. In this project, we will develop a computational workflow for de novo tRFs mining from TCGA pan-cancer dataset. Additionally, we will further perform functional assays to validate the role of several driver tRFs in cancer development and progression.
Next-generation sequencing, high performance computation, statistics, computer programming, tumor tissue bank, sequencing library construction, cell assays, mouse models.