June 27, 2019
Date/Time:
Thursday, June 27, 2019
4:00 PM – 5:00 PM EDT
The Path to Personalized Medicine in Lymphoma
Personalized medicine – identifying the best treatment for the individual patient – is not new, but its role in lymphoma treatment is rapidly increasing.The aim of personalized medicine is to optimize outcomes by tailoring therapy to the individual patient’s tumour biology and clinical information. Better knowledge of a cancer’s molecular biology and a greater ability to measure biologic characteristics helps point to the use of a specific, or targeted drug. In lymphoma, many treatment options available, and knowing more about the different subtypes enables the most effective treatments to be selected for each patient.
Speaker:
Dr. Rob Laister, PhD
Scientific Associate
Princess Margaret Cancer Centre
Toronto, Ontario
Dr. Laister completed his doctoral training at the University of Toronto in the department of Medical Biophysics where he studied protein NMR spectroscopy and the DNA damage response in the laboratory of Dr. Cheryl Arrowsmith. As a post-doctoral fellow, Dr. Laister trained with Dr. Mark Minden where he worked on tumour cell metabolism and drug discovery in acute myeloid leukemia. He was also a member of Dr. Frank Sicheri’s laboratory at the Samuel Lunenfeld Research Institute studying the structural biology of protein kinase complexes. Dr. Laister currently leads a research group at the Princess Margaret Cancer Centre that focuses on pre-clinical drug development for hematological malignancies. Two major themes to the group’s current work include understanding how blood cancers adapt to conditions of nutrient stress and determining how metabolites communicate signals between the cellular components of the tumour microenvironment. Dr. Laister’s group also collaborates with the lymphoma program at the Princess Margaret Cancer Centre and the CCTG Hematology group to develop and implement clinical trial companion studies aimed at identifying and characterizing the function of proteomic and metabolic markers correlated with clinical outcomes.
