Development of a scalable in-vivo drug discovery platform allows for deep interrogation of mechanisms of KRAS.G12C inhibitors.
Skip to main content
eScholarship
Open Access Publications from the University of California

UCSF

UC San Francisco Electronic Theses and Dissertations bannerUCSF

Development of a scalable in-vivo drug discovery platform allows for deep interrogation of mechanisms of KRAS.G12C inhibitors.

Abstract

Drug discovery in small molecule oncology has traditionally been conducted using high-throughput, single-target screening approaches against a panel of arrayed test compounds. Since the inception of small-molecule screening around thirty years ago, the field has primarily progressed by automating this process using robotics or by moving to cell-based reporter assays. However, fundamental limitations exist namely: lack of in-vivo context of biochemical or reporter assays, lack of generalizability of screening discoveries across many different types of genetic backgrounds, and coarse data readouts that prevent simultaneous inference of deep biological interactions and mechanisms of compounds. The work herein describes in detail 1) the challenges and advances made in advancement of novel technologies aimed at addressing these problems as well as 2) the development of the GENEVA method as a method for simultaneously addressing these challenges in a multiplexed assay format scalable for in-vitro, organoid, and in-vivo model system 3) the discoveries enabled by GENEVA within the context of understanding KRAS.G12C inhibitor mechanisms. In addition to a discussion of both methods and discoveries from GENEVA, I will also present a focused chapter on the dissection of RBMS1, an RNA binding protein that we go on to show rewires transcriptome networks to produce a pro-metastatic phenotype. I will describe the identification of this protein as a metastasis-relevant master regulator, the validation of using in-vivo metastasis assays, and the downstream effects of shutting down RBMS1 on both specific transcripts and on gene networks broadly.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View