Abstract 6359: MUTE-Seq: An ultrasensitive method for detecting low-frequency mutations in cfDNA with engineered advanced-fidelity FnCas9
Sunghyeok Ye, Jin‐Soo Kim, Ki-Yeon Kim, Yoon‐Ho Won, Taegun Park, Sungjae An, Haerin Jeong, Hee‐Joon Chung, In Seon Lee, Jae Won Rhee, Ri-Ra Kang, C . Yong Kang, Myounghee Kang, Mi Young Kim, Jeong‐An Gim, Yonggoo Kim, Song Cheol Kim, Sung Ho Lee, Junho K. Hur, Junseok W. Hur
Abstract In this study, we present the development of the Mutation tagging by CRISPR-based Ultra-precise Targeted Elimination in Sequencing (MUTE-Seq) method. We engineered a highly precise advanced-fidelity FnCas9 variant, named FnCas9-AF2, to effectively discriminate single-base mismatches at all positions of the single guide RNA (sgRNA) target sequences. FnCas9-AF2 exhibited significantly lower off-target effects compared to existing high-fidelity CRISPR-Cas9 variants. MUTE-Seq leverages FnCas9-AF2 for the enrichment of mutant DNA through the exclusive cleavage of perfectly matched wild-type DNA, allowing for sensitive detection of low-frequency cancer-associated mutant alleles. MUTE-Seq enabled sensitive monitoring of minimal residual disease (MRD) from the bone marrow of patients with Acute Myeloid Leukemia (AML). Furthermore, MUTE-Seq was applied in a multiplexed manner on cell-free DNA (cfDNA) from patients diagnosed with non-small cell lung cancer (NSCLC) and pancreatic cancer. This approach demonstrated a significant improvement in the sensitivity of simultaneous mutant detection and highlighted its clinical utility for early-stage cancer patients with extremely low levels of circulating tumor DNA (ctDNA). We anticipate that the FnCas9-AF2-based MUTE-Seq could offer a valuable clinical tool to facilitate improved molecular diagnosis, prognosis evaluation, and treatment planning for cancers in various stages. Citation Format: Sunghyeok Ye, Jin-Soo Kim, Ki-Yeon Kim, Yoon-Ho Won, Taegun Park, Sungjae An, Haerin Jeong, Hee-Joon Chung, In Seon Lee, Jae Won Rhee, Raehee Kang, Chanyoung Kang, Myoung-Hee Kang, Mi Young Kim, Jeong-An Gim, Yonggoo Kim, Song Cheol Kim, Sungho Lee, Junho K. Hur, Junseok W. Hur. MUTE-Seq: An ultrasensitive method for detecting low-frequency mutations in cfDNA with engineered advanced-fidelity FnCas9 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6359.
https://doi.org/10.1158/1538-7445.am2025-6359
Computational biology
Medicine
Computer science
Biology
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