Accelerated drug-resistant variant discovery with an enhanced, scalable mutagenic base editor platform

Area of Science:

• Genomics
• Molecular Biology
• Cancer Research

Background:

• Personalized cancer therapies rely on tumor genetic profiles but face challenges from acquired drug resistance via mutations.
• Identifying resistance-conferring mutations is often costly, resource-intensive, and time-consuming.

Purpose of the Study:

• To develop and optimize a novel base editing system for efficient, large-scale in situ screening of gene variants that cause drug resistance.
• To identify specific mutations in EGFR and BRAF that confer resistance to EGFR inhibitors.

Main Methods:

• Adaptation and optimization of a conditional activation-induced cytidine deaminase (AID)-dead Cas9 (dCas9) base editing system.
• Utilizing a custom single guide RNA (sgRNA) library for targeted gene variant screening.
• Analysis of identified variants in epidermal growth factor receptor (EGFR) and v-raf murine sarcoma viral oncogene homolog B1 (BRAF) genes.

Main Results:

• The optimized AID-dCas9 system demonstrated greater edit heterogeneity and an expanded editing footprint compared to the standard BE4 base editor.
• Successfully identified individual and compound variants in EGFR and BRAF that confer resistance to EGFR inhibitors.
• Established a scalable platform for discovering drug-modifying variants and understanding protein structure-function relationships.

Conclusions:

• The developed base editing system offers a simple, scalable, and efficient platform for discovering cancer drug resistance mechanisms.
• This approach facilitates the identification of novel therapeutic targets and strategies for overcoming drug resistance in cancer treatment.
• Provides valuable insights into the genetic basis of drug resistance, advancing personalized oncology.