Base and Prime Editing Scan EGFR Variants for Drug Response
Key Insights
Researchers used base editing to scan EGFR (search) mutations, identifying variants that impact cell viability and drug resistance in lung cancer.
The study identified known and novel EGFR (search)-activating mutations, expanding the number of likely pathogenic variants in tyrosine kinase and extracellular domains.
Prime editing was leveraged to introduce a broader spectrum of clinically relevant mutations, uncovering additional pathogenic EGFR (search) variants.
Researchers have developed a high-throughput screening approach using base and prime editing to scan genetic variants in the epidermal growth factor receptor (EGFR (search)) gene. This method identifies mutations that impact cell viability, drug sensitivity, and resistance to tyrosine kinase inhibitors (TKIs) in lung cancer. The study, published in Nature Biotechnology, provides a comprehensive analysis of EGFR variants and their functional consequences, offering insights into personalized cancer therapy.
Base Editing Identifies EGFR Mutations
The team utilized base editing to introduce a spectrum of mutations in EGFR (search), a gene frequently mutated in non-small cell lung cancer (search) (NSCLC (search)). By applying cytidine and adenine base editors (CBEs and ABEs) in a massively parallel manner, they interrogated the effects of various EGFR mutations on cell growth and survival. The screens identified both loss-of-function (LOF) and oncogenic mutations, providing a detailed map of EGFR variant effects.
In MCF10A cells, an epithelial cell line, the researchers introduced EGFR (search) mutations and assessed their impact on cell viability in the presence or absence of epidermal growth factor (EGF). The base editing screens identified several EGFR-activating mutations, particularly in the tyrosine kinase domain, which is crucial for EGFR autophosphorylation. Some of these mutations, such as Thr790Met and Pro596Ser, are known pathogenic variants, while others were previously observed in tumor samples but not classified as pathogenic.
Drug-Resistant Variant Discovery
The study expanded the screening approach to evaluate the sensitivity of EGFR (search) variants to clinically approved TKIs, gefitinib and osimertinib. By treating cells with these drugs after base editing, the researchers identified variants that confer resistance to either first-generation (gefitinib) or third-generation (osimertinib) TKIs. For example, the Thr790Met variant, known to confer resistance to gefitinib, was strongly enriched under gefitinib treatment but not under osimertinib treatment.
Further analysis revealed that many drug-resistant mutations are located in the ATP-binding pocket of the tyrosine kinase domain, which is the binding site for both drugs. The study also identified previously unknown resistant mutations affecting Val726, Met766, and Thr854, all in direct contact with the receptor-bound molecule. These findings suggest that mutations impacting these residues can directly affect the binding affinity of gefitinib and osimertinib.
Prime Editing for Patient-Derived Variants
To explore a broader range of clinically relevant mutations, the researchers leveraged prime editing, which can introduce all possible base substitutions, as well as short insertions and deletions. They designed a prime editing guide RNA (pegRNA) library targeting EGFR (search) variants listed in the ClinVar and COSMIC databases. This approach allowed them to introduce patient-derived mutations and assess their impact on EGFR activation.
The prime editing screen revealed several pathogenic mutations, including those affecting the Ala289 and Thr263 residues in the extracellular domain. These mutations are frequently found in glioblastoma (search) but not in epithelial cell-derived breast cancers. The screen also identified exon 20 insertions affecting the αC-β4 loop of the tyrosine kinase domain, a category of oncogenic mutations associated with resistance to TKIs.
Implications for Personalized Therapy
The study demonstrates the power of base and prime editing to comprehensively scan genetic variants and identify those that drive cancer progression and drug resistance. By identifying both known and novel EGFR (search) mutations, this approach can help guide therapeutic decisions and personalize cancer therapy. The researchers also found variants that increase drug sensitivity, which may help prioritize drugs for patients with specific EGFR variants.
"These results provide new insights into EGFR (search) variant-dependent drug sensitivities, which may help guide therapeutic decisions in the future for clinicians faced with EGFR variants for which clinical data are currently absent," the authors noted.
The study highlights the importance of evaluating drug resistance variants in relevant genomic contexts, including pre-existing EGFR (search) mutations, and confirms the relevance of sequencing the target site to validate base editor screen hits.