Next-Generation Sequencing (NGS) provides a revolutionary platform in identifying tumorigenic events, whereas data analysis remains as a challenge. We focus on the development and application of NGS programs that accurately detect genomic alterations for cancer research and clinical application.
Our main approach is to perform intergrative analyses of large-scale, multi-dimentional data to unveal the molecular mechanism of disease initiation, progression and prognosis. Most commonly by using Whole Genome Sequencing (WGS) or Whole Exome Sequencing (WES), we are capable of performing genome wide detection of somatic acquired mutations, and inherited germline variants. Further analyses of recurring mutations will help reveal commonly shared mutations in the same cohort. Transcriptome sequencing (RNASeq) will provide additional insights that helps reveal the mechanism of tumorigenesis.
To understand the process of tumor progression, we will study clonal evolution by comparing multiple tumors from the same patient at multiple time points, and/or look into the heterogeneity inside the same tumor. The dynamic pattern will help identify commonly shared key mutations for tumor maintainance and De Novo mutations that are responsible for relapse.
A key application will be personalized medicine. Compared with traditional methods, NGS-based clinical sequencing provides a much more robust and cost-effective method to exam the entire mutation landscape in the tumor. Accurate characterization of individual tumor profile helps the decision making process, not only in finding more effective treatment, but also help avoid unnecessary risk to the patient.
Education and Training:
PhD - University at Buffalo, the State University of New York, Buffalo, NY
2012-2013 - St. Jude Children's Research Hospital, Bioinformatics Scientist
2010-2012 - St. Jude Children's Research Hospital, Postdoctoral follow, Bioinformatics & Pathology