Department of Biochemistry
Functional Genomics to Guide Cancer Therapy
McIntyre Medical Sciences Building
3655 promenade Sir-William-Osler
Office: Room 800C; Lab: 800
Montreal, Quebec H3G 1Y6
Tel: 514-398-4447; Lab: 514-398-5446
Email: sidong [dot] huang [at] mcgill [dot] ca
2003 – PhD, University of California, San Francisco
Our laboratory uses functional genomic tools to study cancer-relevant pathways and to guide targeted cancer therapy. We aim to identify novel genes and networks that modulate response to cancer drugs, and to uncover genetic dependencies between the major signaling pathways in cancer that can be exploited therapeutically.
Mechanisms of drug resistance to targeted cancer therapeutics
Cancer therapy is often hampered by the rapid emergence of drug resistance. This is not only true for the conventional chemotherapies, but also for the new generation of drugs targeting those components that are mutated or deregulated in tumor cells. Understanding molecular mechanisms of drug resistance will enable the rational development of treatment strategies to overcome such challenge.
Using functional genomic tools such as high-throughput RNA interference (RNAi) loss-of-function genetic screens, we aim to uncover novel genes and networks that modulate response to targeted cancer therapeutics. Complementary genetic and biochemical approaches are used to investigate the mechanism of action and to provide treatment strategies to overcome resistance. Whenever possible, the expressions of these candidate biomarkers are examined in tumour samples of cancer patients to correlate with clinical response to the cancer drugs.
We have used this powerful approach to identify novel components of signalling pathways and mechanisms of drug resistance in preclinical models of cancer. For example, we recently uncovered MED12, a component of the transcriptional MEDIATOR complex that is mutated in cancers, as a major determinant of response to both chemotherapies and targeted agents in multiple cancers. Loss of MED12 strongly activates TGFβR signalling which in turn is responsible for drug resistance. A gene signature induced by MED12 loss is highly predictive for chemotherapy response in colon cancer patients and is associated with resistance to EGFR inhibitors in lung cancer patients. Inhibition of TGFβ signaling restores drug responsiveness in MED12-deficient cells, suggesting a strategy to treat these drug-resistant tumours. We will continue studying the resistance mechanisms to targeted cancer therapeutics in multiple cancer types.
Functional genetic screens as a tool to map genetic dependencies of cancer-relevant pathways and to identify effective drug combinations
Genotype-based therapy in which the signaling pathways that are activated by oncogenic mutations are targeted by highly selective inhibitors holds great promise for the treatment of cancer. However, presence of an oncogenic driver mutation does not always confer sensitivity to the drug that inhibits that driver, indicating that genotyping alone is not sufficient to match all patients to effective treatments.
For example, the clinical responses to the highly selective small molecule inhibitor PLX4032 (vemurafenib) of the BRAFV600E oncoprotein differ widely, ranging from some 80% in melanoma to only 5% in BRAF mutant colorectal cancer. Through an unbiased RNAi screen, we have recently uncovered that unresponsiveness of colorectal cancer to BRAFV600E inhibition is through feedback activation of EGFR, and blockade of EGFR therefore shows strong synergy with BRAFV600E inhibition. Hence, functional genetic screens provide a powerful tool to map feedback interactions between signaling pathways in cancer and to guide the selection of combination treatments.
To identify the effective drug combinations, we use druggable gene-family shRNA libraries (e.g. Kinome and Phosphatome) to identify the second target whose inhibition is synthetic lethal with a primary targeted agent in cell lines that match to resistant tumour subtypes of interests. RNAi and drugs targeting the same candidates are used in combination with the primary agent to validate the synergy. Our studies will deliver novel insights into the genetic dependencies of cancer-relevant pathways and provide new treatment strategies to overcome drug resistance, resulting in clinical benefit for cancer patients.