OCT 10, 2018 1:30 PM PDT

Discovery of Biomarkers Predictive of Anticancer Drug Response in Preclinical Settings

Speaker
  • Assistant Professor, Princess Margaret Cancer Center, University of Toronto
    Biography
      Benjamin Haibe-Kains is a Scientist at the Princess Margaret Cancer Centre (PM), University Health Network, and Assistant Professor in the Medical Biophysics and Computer Science departments of the University of Toronto. Dr. Haibe-Kains earned his PhD in Bioinformatics at the Université Libre de Bruxelles (Belgium), for which he was awarded a Solvay Award (Belgium). Supported by a Fulbright Award, Dr. Haibe-Kains did his postdoctoral fellowship at the Dana-farber Cancer Institute and Harvard School of Public Health (USA). Dr. Haibe-Kains started his own laboratory at the Institut de Recherches Cliniques de Montréal (Canada) and moved to PM in November 2013. Dr. Haibe-Kains' research focuses on the integration of high-throughput data from various sources to simultaneously analyze multiple facets of carcinogenesis. Dr. Haibe-Kains and his team are analyzing high-throughput (pharmaco)genomic datasets to develop new prognostic and predictive models and to discover new therapeutic regimens in order to significantly improve disease management. Dr. Haibe-Kains' main scientific contributions include several prognostic gene signatures in breast cancer, subtype classification models for ovarian and breast cancers, as well as genomic predictors of drug response in cancer cell lines.

    Abstract

    One of the main challenges in precision medicine consists of developing predictors of drug response to select the most beneficial therapy for each individual patient. In this context, preclinical models are crucial to study the association between molecular features of tumor cells and response to chemical perturbations. However, only few predictors have been successfully translated to clinical settings. Such a low success rate is due not only to the complexity of the mechanisms underlying anticancer drug response, but also to the lack of robustness of the predictors developed in preclinical settings. To address this issue we developed PharmacoGx, a computational platform enabling meta-analysis of large-scale drug screenings of in vitro and in vivo model systems, and PharmacoDB (pharmacodb.pmgenomics.ca), a web-application enabling quick access to a large compendium of pharmacogenomics datasets. In this presentation I will show how we used our new platforms to (i) identify pathways whose genomic and transcriptomic patterns are preserved between model systems and patient tumors, and (ii) develop univariate and multivariate predictors of drug response that can be validated in clinical trial data. 

    Learning Objectives: 

    1. Learn about the potential and limitations of biomarker discovery using preclinical pharmacogenomic data
    2. Learn about the computational tools available for biomarker discovery in preclinical settings


    Show Resources
    You May Also Like
    JAN 23, 2020 9:00 AM PST
    C.E. CREDITS
    JAN 23, 2020 9:00 AM PST
    DATE: January 23, 2020 TIME: 9:00am PST, 12:00pm EST...
    APR 07, 2020 8:00 AM PDT
    C.E. CREDITS
    APR 07, 2020 8:00 AM PDT
    DATE: April 7, 2020 TIME: 8:00am PT, 11:00am ET This webinar sets out to establish why quality control is key to robust, reliable, reproducible science. We will look at best practice criteri...
    FEB 26, 2020 9:00 AM PST
    C.E. CREDITS
    FEB 26, 2020 9:00 AM PST
    DATE: February 26, 2020 TIME: 9:00am PST 3D cell culture and analysis and the study of organoids and spheroids are becoming more prevalent as a research method in publications as traditional...
    MAY 08, 2020 10:00 AM PDT
    C.E. CREDITS
    MAY 08, 2020 10:00 AM PDT
    DATE: May 8, 2020 TIME: 10:00am PT, 11:00am MT, 1:00pm ET The application of next generation sequencing to interrogate immune repertoires and methods in which these highly complex dataset...
    MAR 03, 2020 9:00 AM JST
    C.E. CREDITS
    MAR 03, 2020 9:00 AM JST
    DATE: March 3, 2020 TIME: 9:00am JST A major limitation in the ex vivo expansion of harvested human hematopoietic stem-progenitor cells (HSPCs) is the rapid differentiation of HSPCs at the e...
    FEB 25, 2020 9:00 AM PST
    C.E. CREDITS
    FEB 25, 2020 9:00 AM PST
    Learn about how to generate a small scale CAR-T workflow using ThermoFisher products See detailed characterization tools that can be utilized and applied in a CAR-T workflow...
    Loading Comments...
    Show Resources
    Attendees
    • See more