NEW YORK — Researchers have developed sensors to measure base editing efficiency with the goal of enabling the characterization of single-variant nucleotides in cancer-linked genes.
Genomic studies have tied variants in a range of genes to cancer risk, but the effects of some of those variants are not clear. As base editing can introduce SNVs, that approach can be used to determine the functional effects of such changes. However, Weill Cornell Medicine's Lukas Dow noted in an email that it can be difficult to determine which single-guide RNA will be the most efficient for base editing, and that this becomes even harder when dealing with a number of variants or pooled screens.
As he and his colleagues reported in Nature Biotechnology on Monday, they developed sensors to gauge the efficiency of base editing, which they applied to more than 200,000 sgRNA-base editor combinations. Through this, they established a resource for examining cancer-linked SNVs in model systems, which they then used to characterize an unknown mutant TP53 allele that contributes to cancer development and proliferation.
"Our experience over the past five years using base-editing enzymes is that — unlike Cas9-based editing — it is difficult to predict which sgRNAs will work efficiently," Dow wrote in an email. "To determine both on-target efficiency and collateral editing (editing of bases other than the intended target) requires one-by-one sequence validation. For individual targets this is feasible, but for large numbers of variants or pooled screens, it becomes very difficult."
Their modular base-editing sensor includes an sgRNA that is linked to its cognate target site in cis. That way, the sgRNAs drive the editing of the linked sensor target site and editing efficiency can be determined through PCR amplification and sequencing of the sensor cassette. With their tool, the researchers could then home in on the optimal sgRNAs for engineering variants within different combinations of base editors and cell lines.
When they tested their approach in human and mouse cell lines, they found that the base-editor sensor library reported known features of base editors, indicating its reliability.
The researchers also coupled their base-editing sensor libraries with high-throughput screening approaches. That way, they could examine the functional effects of cancer-linked SNVs in parallel. They screened mouse pancreatic cell lines using the mouse base-editor sensor library to find significantly enriched sgRNAs. They found 150 sgRNAs that appeared to promote or inhibit cell line proliferation. They in particular focused on TP53 and noted an enrichment of a number of missense and nonsense mutations, including Trp-R213.
Further analysis showed the alteration leads to editing at an adjacent cytosine, creating a T211I mutation, which the researchers noted has been observed in human cancers. Mice transplanted with these cells developed disease and died, indicating that the variant is a driver mutation in a mouse model of pancreatic cancer.
The findings suggested to the researchers that the approach could be used to characterize cancer-associated SNVs in vivo and help determine their effects.
"The technology is very powerful for understanding how particular cancer-associated mutations might influence the response to cancer therapies," Dow added. "Using either the established pan-cancer sgRNA libraries, or through the development of cancer-specific or gene-specific mutation libraries, understanding the contribution of gene variants to disease progression and therapy response may help guide improved precision medicine-based approaches to patient stratification and cancer treatment."
He and his colleagues also developed a pipeline dubbed annotated mutation-informed nucleotide base-editor sgRNA search, or AMINEsearch, to generate base-editing sensor libraries from genomic data and developed a web application called BE-SCAN, for BE sensor-validated cancer-associated mutations, that other scientists can browse through to select sgRNAs by species, target, and more.