Wei Li, PhD
Genome Engineering and Data Science Approaches for Cancer Drug Discovery
Summary
CRISPR/Cas9 is an evolutionary tool that allows the manipulation of human DNA. One exciting application of CRISPR/Cas9 is CRISPR screening that quickly identifies interesting genes from tens of thousands of candidates. Unfortunately, data generated from CRISPR screening is inherently biased towards different factors (e.g., copy number variation, different cell conditions, etc.). Furthermore, people still don’t know how to inform precision medicine from CRISPR screening. This research project seeks to facilitate an understanding of cancer essential genes and a search of drug targets, by developing computational frameworks for CRISPR/ Cas9 screening. The project builds algorithms to correct biases that are widely present in current CRISPR screening data, process combinatorial screening data that directly knocks out two genes, and use genomics profiles to predict cancer essential genes and “synthetic lethal” genes (genes whose knockout kills cancer cells but keeps normal cells intact). This project will provide necessary tools for scientists around the world to better analyze and interpret CRISPR screening results, and to identify and predict synthetic lethal targets to accelerate the search of potential drug targets. Furthermore, novel cancer driver genes and synthetic lethal targets will be identified, leading to novel therapeutic targets in cancer.
I am extremely honored to receive the PhRMA Foundation Research Starter Grant in Informatics. It was critical for me to start my informatics laboratory as an assistant professor. Furthermore, it has enabled me to explore the opportunity to use data intensive approaches to understand the Achilles heel of cancer cells and to inform novel drug targets.
