October 14 @ 4:00 – 5:00 pm
Speaker: Di Wu, PhD
Presented from UNC-CH
Broadcast Link: Seminar
A major challenge in human genetics is to devise a systematic strategy to integrate disease datasets with diverse genomic biological and drug datasets in order to provide insight into disease mechanism and guide drug discovery. To achieve this, Dr. Wu will discuss two areas of her research.
First, Dr. Wu will demonstrate how to identify the “cells of origin” for breast cancer sub-types using mammary gland cell sub-population data and publicly available data. This helps find potential drug targets. A variety of statistical methods are developed and used, including defining gene signature scores for each sample and some novel gene set testing methods. Gene set tests are valuable for increasing statistical power, rotation gene set test, ROAST, overcomes the limitation of sample size and inter-gene correlation. ROMER and CAMERA gene set tests test different statistical hypotheses.
Dr. Wu will then discuss another major work: to integrate Genome-wide association study (GWAS) risk SNPs with public drug databases to repurpose drugs for complex traits, e.g., cancer and autoimmune diseases. Although a large amount of identified risk variants may well capture the characteristics of the diseases, there is still a bottleneck of developing new therapeutics. Drug repurposing is to assess whether the available drugs of certain diseases can be re-used for the treatment of other diseases. It is cost effective and has fewer safety issues. Two main goals are achieved in Dr. Wu’s study; the genetics based drug repurposing pipeline and evaluation of how much genetics “guides” drug discovery/repurposing. How to infer the drug sensitivity across lung cancer subtypes may also be mentioned.
Dr. Wu is a biostatistician working in the bioinformatics field. She completed her PhD in statistical bioinformatics at the Walter and Eliza Hall Institute (WEHI) of Medical Research, University of Melbourne, Australia. She completed a postdoc at Harvard University, jointly in the statistics department and the medical school. In the past, Dr. Wu worked primarily on statistical methods to analyze genomic data and data integration of genomic data and drug database, applied in cancer research and autoimmune disease research for precision medicine and drug repurposing. Dr. Wu joined UNC-Chapel Hill a few months ago and is developing a data integration strategy with Electronic Medical Records (EMR) for drug repurposing. She is also working on omics data integration (microbiome, metabolomics and DNA/RNA levels) in oral biology.