Research
Technology Development
Transformative discoveries often require technologies that surpass current limitations. Our lab is dedicated to developing and applying innovative methods to dissect the complexity of cancer biology. We have a track record of developing new methods to explore biology at unprecedented resolution. We developed the highly-sensitive STAR ChIP-seq method, which requires as few as ~200 cells, to profile the epigenetic landscape in mouse embryos. We also devised a multimodal assay that simultaneously measures chromatin marks and cell surface proteins within individual cells. Cell identity is represented not only by the transcriptome but also by the epigenome, proteome and beyond. To fully capture all existing cell states in cancer, including transitional states, we continue to invent methods that capture multiple layers of information from each cell, enabling us to detect critical cell states that were previously "invisible."
Cancer Plasticity
Cancer is characterized by remarkable cellular plasticity, which enables cancer cells to reprogram and adapt to new environments, making tumors more aggressive and harder to eradicate. Using our single-cell multiomic toolkit, we aim to capture the dynamic continuum of cellular states and map how cancer cells switch from one state to another. For example, we might look at how a tumor cell could gain stem-like traits or activate a previously silent program under stress. We are particularly interested in the epigenetic mechanisms driving these shifts. By unraveling how cancer plasticity works, we aim to identify key points where medical intervention can be most effective.
Interpatient Variability in Cancer Treatment
A long-standing question in cancer therapy is why patients respond so differently to the same treatment. Our lab is excited to explore whether epigenetics ¡ª the dynamic regulatory layer controlling gene expression beyond the genetic code ¡ª could be the missing piece of this puzzle. Epigenetic mechanisms not only dictate a cell¡¯s current behavior but also influence how it may respond to future stimuli. By pairing baseline epigenetic states with drug treatment responses, our lab seeks to determine whether inherent epigenomic differences could explain the interpatient variability observed in cancer treatment. We aim to pinpoint epigenetic signatures that can predict drug sensitivity.