Two IBBME students named 2017 Jennifer Dorrington Graduate Research Award recipients

IBBME doctoral students Yonatan Lipsitz and Stanley Wai-Kwong Ng are two recipients of this year’s Jennifer Dorrington Graduate Research Award. Issued by the University of Toronto’s Donnelly Centre for Cellular & Biomolecular Research, the award recognizes research excellence conducted by master’s or PhD students in the Faculty of Medicine within the Donnelly Centre.

Lipsitz and Ng are among a total of three recipients awarded this year. The Donnelly Centre houses 35 faculty members and more than 500 research staff and students.

Lipsitz, a member of Professor Peter Zandstra‘s Laboratory for Stem Cell Bioengineering, came to biomedical research after graduating in chemical engineering from McGill University. He was interested in applying his chemical processing knowledge to some of the key challenges in regenerative medicine—production of large quantities of human cells for future cell therapies.

“Peter’s lab applies core chemical engineering to biological systems using cutting-edge technologies to overcome the challenges of the scale-up process. For example, we are engineering pluripotent stem cells to boost their ability to expand in manufacturing systems,” said Lipsitz.

For Lipsitz, who joined the Zandstra lab five years ago, the timing could not have been better. The last few years have seen a push in Canada and Toronto towards translation of stem cell science into therapies, in which Zandstra plays a key role as co-founder of the Centre for Commercialization of Regenerative Medicine and executive director of U of T’s Medicine by Design initiative.

“I am very excited about seeing these therapies curing patients,” said Lipsitz who is eyeing a career in the biotech sector after completing his PhD. “I want to be part of making cell therapies accessible to patients.”

Lipsitz is already becoming involved in the regenerative medicine community in Toronto. Last month, he and a team of U of T scientists and entrepreneurs identified key bottlenecks in stem cell commercialization and presented their findings to a panel of industry experts.

Ng is another member of Professor Zandstra’s lab. His background in machine learning equipped him with the know-how for detecting subtle patterns in big data. This allowed him to effectively apply a statistical learning algorithm to derive a formula and develop an assay that can rapidly—within 24 to 48 hours—predict clinical outcome in patients with acute myeloid leukemia (AML).

Based on gene expression profiling of rare leukaemia stem cells (LSC) in patient blood or bone marrow, the test, known as the LSC17 score, estimates precision prognosis, including overall survival, time to relapse, and how likely the patient is to respond to drugs. Because AML is an aggressive blood cancer that progresses quickly, patients usually start chemotherapy soon after diagnosis, while typically waiting several weeks before tests results come back to reveal patient risk and help doctors decide on the best course of further treatment.

Ng’s work, which was done in close collaboration with Drs. John Dick, Jean Wang and Mark Minden at the Princess Margaret (PM) Cancer Centre, could vastly cut the time it takes to accurately rank patients according to their risk, and choose the right treatment, early in the disease. It also netted the team a high-profile research paper in Nature, with Ng as the lead author.

“It’s an honour to receive this award. I read that Dr. Dorrington died of cancer, so this award is very meaningful to me as my primary motivation for contributing to cancer research is to directly impact and improve patient survival,” said Ng, who joined Professor Zandstra’s group after graduating from McMaster University four years ago.

The Jennifer Dorrington Graduate Research Award was established by the Dorrington family in 2006 as a tribute to Dr. Jennifer Dorrington who was a professor in the Banting and Best Department of Medical Research. Dorrington’s pioneering research greatly advanced our understanding of reproductive biology and ovarian cancer.