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Pharmacogenomic discovery of genetically targeted cancer therapies optimized against clinical outcomes
Peter Truesdell1,2, Jessica Chang1, Doris Coto Villa1
1Leapfrog Bio, San Mateo, USA.
Abstract:
Despite the clinical success of dozens of genetically targeted cancer therapies, the vast majority of patients with tumors caused by loss-of-function (LoF) mutations do not have access to these treatments. This is primarily due to the challenge of developing a drug that treats a disease caused by the absence of a protein target. The success of PARP inhibitors has solidified synthetic lethality (SL) as a means to overcome this obstacle. Recent mapping of SL networks using pooled CRISPR-Cas9 screens is a promising approach for expanding this concept to treating cancers driven by additional LoF drivers. In practice, however, translating signals from cell lines, where these screens are typically conducted, to patient outcomes remains a challenge. We developed a pharmacogenomic (PGx) approach called "Clinically Optimized Driver Associated-PGx" (CODA-PGX) that accurately predicts genetically targeted therapies with clinical-stage efficacy in specific LoF driver contexts. Using approved targeted therapies and cancer drugs with available real-world evidence and molecular data from hundreds of patients, we discovered and optimized the key screening principles predictive of efficacy and overall patient survival. In addition to establishing basic technical conventions, such as drug concentration and screening kinetics, we found that replicating the driver perturbation in the right context, as well as selecting patients where those drivers are genuine founder mutations, were key to accurate translation. We used CODA-PGX to screen a diverse collection of clinical stage drugs and report dozens of novel LoF genetically targeted opportunities; many validated in xenografts and by real-world evidence. Notable examples include treating STAG2-mutant tumors with Carboplatin, SMARCB1-mutant tumors with Oxaliplatin, and TP53BP1-mutant tumors with Etoposide or Bleomycin.
Insights
Developing new cancer therapies for loss-of-function mutations is challenging. Our CODA-PGX approach accurately predicts effective genetically targeted therapies for patients with specific cancer drivers, improving treatment outcomes.
Area of Science:
- Oncology
- Genomics
- Pharmacogenomics
Background:
- Most cancer patients lack targeted therapies for loss-of-function (LoF) mutations due to challenges in targeting absent proteins.
- Synthetic lethality (SL) offers a strategy to overcome this, with CRISPR-Cas9 screens mapping SL networks for LoF drivers.
- Translating cell line screening data to patient outcomes remains a significant hurdle.
Purpose of the Study:
- To develop a pharmacogenomic (PGx) approach, CODA-PGX, for predicting the efficacy of genetically targeted therapies in specific LoF driver contexts.
- To identify key principles for accurately translating preclinical screening data to clinical patient outcomes.
- To discover novel LoF genetically targeted therapy opportunities.
Main Methods:
- Developed the CODA-PGX (Clinically Optimized Driver Associated-PGx) pharmacogenomic approach.
- Utilized real-world evidence and molecular data from hundreds of patients with approved targeted therapies.
- Optimized screening principles including drug concentration, kinetics, driver perturbation context, and founder mutation identification.
Main Results:
- CODA-PGX accurately predicts clinical-stage efficacy for genetically targeted therapies in LoF driver contexts.
- Identified critical factors for successful translation, including replicating driver perturbation and selecting patients with founder mutations.
- Discovered and validated dozens of novel LoF genetically targeted therapy opportunities, including STAG2-mutant tumors with Carboplatin, SMARCB1-mutant tumors with Oxaliplatin, and TP53BP1-mutant tumors with Etoposide or Bleomycin.
Conclusions:
- CODA-PGX provides a robust framework for identifying effective genetically targeted cancer therapies for LoF mutations.
- The study highlights the importance of context and patient selection for successful translation of preclinical findings.
- Numerous new therapeutic strategies for specific LoF-driven cancers have been identified and validated.
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