Deciphering the Functional Role of PPP2R1A Mutations in Cancer

University Of Michigan At Ann Arbor, Ann Arbor MI

Investigators

Abstract

Project Summary The adoption of next-generation sequencing (NGS) for patient tumor samples has transformed the approach to cancer treatment by clinicians and researchers in the past five years. Most mutations identified through sequencing in cancer are genes mutated across a wide range of cancers or in a specific cancer type. One gene mutated primarily in high grade gynecological malignancies is PPP2R1A, which encodes the alpha isoform of the A subunit (A⍺) of Protein Phosphatase 2A (PP2A), an established tumor suppressor. PP2A is a family of Serine/Threonine phosphatases composed of a C (Catalytic) subunit, which binds an A (Scaffolding) subunit allowing for one of 20 distinct B (Regulatory) subunits to bind. Depending on the B subunit bound, there can be over 60 different PP2A heterotrimeric holoenzymes active in the cell at any time. PP2A inactivation occurs through nongenetic and genetic mechanisms in human cancer. In cancer, the most mutated subunit of PP2A is A⍺. Interestingly, missense mutations in this subunit are highly enriched in select tumor types, specifically high- grade endometrial cancers. Hotspot mutations in this subunit are enriched in two domains, known as HEAT 5 and HEAT 7. These mutations bias heterotrimer formation by attenuating tumor suppressive PP2A B subunit binding, resulting in tumorigenesis. Our group identified a series of small molecule PP2A Molecular Glues (PMGs) that restore tumor suppressive B subunit binding to mutant A scaffolds and drive significant tumor growth inhibition and regressions in vivo. However, many cancer-associated mutations lie outside these hotspot regions. While hotspot mutations represent approximately 30% of identified mutations in A⍺, 70% of all the identified mutations remain uncharacterized. There are multiple ways to evaluate gene/protein function using cell-based assays. One such approach is Deep Mutational Scanning (DMS), which simultaneously assesses the impact of multiple gene variants. Therefore, I hypothesize there are uncharacterized mutations that 1) drive tumorigenesis and 2) will impact response to drugs targeting PP2A (PMGs). Based on this hypothesis and our preliminary data, I propose to use DMS to characterize the function of all possible A⍺ mutations and combine DMS with targeted based approaches to determine the effects of A⍺ mutations on therapeutic response to PMGs. Experiments in Aim 1 will profile a functional assessment of every possible missense variant of A⍺ to determine their pathogenicity. Aim 2 will use our generated HEAT 5/7 libraries as well as the top 10 recurrent A mutations under the selective pressure of PMG treatment to determine which mutations will be responsive or resistant. This is important information for the lead PMG in this series as it is planned to undergo clinical trials in 2025. Combined, this data will provide a comprehensive understanding of the mutational landscape regulating PP2A function and activity as well as serve as a resource for many researchers in and outside our field (Aim 1), while providing critical inclusion and exclusion criteria in the design of the first clinical trials for the lead PMG (Aim 2).