About the Lab
The research of our laboratory lies in the interface between novel single cell technologies and quantitative biology. We pursue the development of new quantitative and high-throughput methods for characterizing genomic, epigenetic and transcriptional variations at single cell resolution. We focus on the tumorigenesis of pancreatic cancer.
With the rapid development of next-generation sequencing technology, high-throughput sequencing has become a powerful tool for biological research. In our lab, we are interested in examining the genome at single cell resolution, in contrast to the genome averaged from an ensemble of cells. As the demonstration of the principle, we are able to detect the genomic variations between individual cancer cells. We are interested in detecting early events that drive tumorigenesis as well as the early stage of tumor heterogeneity that will influence later tumor development. The lab will focus on pancreatic cancer in particular.
In addition to the genome at single cell resolution, we are also interested in developing novel methods for single cell transcriptional and epigenetic profiling. The goal is to capture the development in action, particularly adult stem cell differentiation. Much finer temporal and spatial resolution will allow us to unveil the early signature transcriptome and epigenome changes, which are often buried among downstream responses by late stage and ensemble profiling. The modeling of complex cellular decision-making processes at multiple layers of pathways and regulatory networks will also be pursued in the lab with the enriched heterogeneous and dynamic information extracted from single cells.
Tumorigenesis involves with dedifferentiation/transdifferentiation, which allows the cancer initiating cell to gain more plasticity and proliferation by hijacking existing developmental or tissue self-renewal mechanisms, and mutations, which are the essential evolution force. The stochasticity caused by the instability of dedifferentiation/transdifferentiation and random mutations can lead to the heterogeneity among cells even at early stage of tumorigenesis. The onset as well as the potential enormous complexity of heterogeneity demands single cell analysis to detect the genomic changes and dissect the functional variances among the tumor initiating cells.
We actively pursue clinical applications of single cell techniques, including prenatal genetic testing as well as early cancer diagnosis.