DATE: April 20th, 2017
TIME: 10:00AM SGT, 11:00AM KST, 12:00PM AEST, 2:00PM NZST

With increasing breadth and depth of genomics studies across a range of cancers, it is now apparent that there exists significant inter and intra tumoural heterogeneity, with complex genotypes comprising of multiple co-existing genetic and epigenetic alterations. Current efforts at genomic characterization of individual cancers however, has several limitations: A significant proportion of patients invariably develop resistance to current targeted therapies, for which the mechanisms are not fully unraveled, and there remain a paucity of treatment options. More than 1 genomic alteration may co-exist, and the effect of co-mutations can be unpredictable from a target modulation perspective.

In this project, we plan to propagate patient derived cell lines in order to allow functional studies that may expand therapeutic opportunities beyond genomic-based markers. Functional studies comprise both chemical and genetic tools that perturb the signaling networks in the primary cell cultures, in order to unravel complex signaling networks that interact through crosstalk and feedback loops, which modify therapeutic vulnerability. Such screens can therefore provide insights into mediators of resistance and sensitivities, yielding predictive biomarkers as well as novel drug combinations to circumvent drug resistance.

Two crucial components include an efficient scalable system to explore therapeutic combinations and the development of representative preclinical models: Patient-derived cells in 3D culture models reflect an integration of genetic, epigenetic, and environmental influences, and may closely mimic the chemotherapeutic (or pathway specific inhibitor)-response of the actual tumor in patients. Thus we aim to exploit the relevance and scalability of patient-derived cell lines to perform HTS/HCS based screens.

Learning Objectives:

• Cancer heterogeneity and resistance 
• Power of High content screening in disease biology 
• 3D cell culture models and importance