The University of Texas MD Anderson Cancer Center
Department of Bioinformatics and Computational Biology
The finding in genome-wide association studies that most disease-associated loci are non-coding suggests that the non-coding human genome may contribute significantly to the etiology of complex diseases. Cumulatively, ~70% of the human genome is transcribed; whereas less than 2% of the genome encodes protein. The human genome encodes over 10,000 long (>200 base pairs) non-coding RNAs (lncRNAs) that have little protein-coding capacity. Growing evidence suggests that lncRNAs may mediate oncogenic or tumor suppressing effects and show promise as a new class of cancer therapeutic targets. In addition, studies have shown that lncRNAs may serve as cancer diagnostic or prognostic biomarkers that are independent of protein-coding genes. While a handful of lncRNAs have been discovered as potential therapeutic targets or biomarkers in cancer, little is known about the function of most lncRNAs and their potential utility as therapeutic targets in cancer treatments or as biomarkers in cancer diagnosis and prognosis. To address these challenges, my lab utilizes integrative computational and multi-omic (genomic, epigenomic, transcriptomic, and proteomic) approaches, to decipher the mechanism of RNA-mediated pathogenesis in cancer with a focus on the RNA-based gene regulation in both tumor (e.g. cancer stem cells) and immune cells (e.g. T cells). On the translational research side, my group aims at identifying RNAs that may serve as predictive biomarkers for both targeted- and immuno-therapy and developing RNA-based targeted- and immuno-therapy for treating difficult-to-treat cancer types such as glioblastoma multiform (GBM), non-small cell lung cancer (NSCLC) and triple negative breast cancer (TNBC).
Education & Training
PhD, The University of North Carolina at Chapel Hill, 2007