Timothy A. Chan: Overview

We are interested in decoding master regulators of complex phenotypes central to cancer. Cancers share a number of common phenotypes that play critical roles in oncogenesis. We are working to explain the genetic root causes of these ill defined but critically important cancer phenotypes and genetic programs. These qualities include cancer’s response to therapy, epigenomic reprogramming, mitotic instability, and metastasis. Despite the advent of high-throughput technologies that have removed genomic data acquisition bottlenecks, these cancer-associated programs are still poorly understood.

We have successfully identified the genetic drivers of a number of important cancer phenotypes and genetic programs, as shown in the figure below. Several major efforts are currently ongoing in the lab:


  1. Decoding the genomic determinants underlying response to immunotherapies

  2. Deciphering the role of isocitrate dehydrogenase mutations (IDH) as a driver of epigenomic reprogramming in gliomas

  3. Characterizing PARK2 as a guardian of mitotic stability

  4. Investigating the master regulators driving metastasis programs

  5. Characterizing the genetic drivers of STAT3 and Wnt hyperactivation in cancers

We seek to use our findings to open the door to more-effective diagnostics and therapies for cancer patients.

Examples of our contributions are the first demonstration that tumor mutational density drives clinical response to immune checkpoint blockade therapy and a demonstration that the extent of molecular damage in tumor genomes from smoking helps determine whether lung cancer patients derive benefit from anti-PD1 treatment.

Decoding the genetic drivers of critical complex phenotypes driving cancer.

Fig 1. Research Focus: Decoding the genetic drivers of critical complex phenotypes driving cancer. Our laboratory aims to dissect the molecular causes of complex genetic programs and processes central to cancer, examples of which are shown in the left panel. Using high-order multidimensional analysis, we work to identify and characterize the genetic drivers of these phenotypes.