DISCERN: Dual-Aptamer-Initiated Sensing Circuit <i>via</i> Engineered Nanozyme for Leukemia Stem Cells Phenotyping
Leukemia stem cell (LSC) phenotyping offers significant potential to enhance minimal residual disease (MRD) monitoring in acute myeloid leukemia (AML), improving therapeutic evaluation and relapse prediction. However, current approaches lack the sufficient sensitivity and specificity to reliably detect rare chemotherapy-resistant LSCs (crLSCs) or identify stem-like phenotypic states, limiting clinical translation. Here, we develop DISCERN (Dual-Aptamer-Initiated Sensing Circuit <i>via</i> Engineered Nanozyme), a colorimetric platform for ultrasensitive LSC phenotyping. DISCERN employs a dual-aptamer system targeting colocalized surface markers (CD33 and CD123) for high-specificity recognition. Its exceptional sensitivity (limit of detection <10 cells/mL) is achieved by a localized catalytic cascade: target-binding initiates on-site rolling circle amplification (RCA), which in turn templates the assembly of PCN-222(Fe) nanozymes that generate amplified colorimetric signals. We demonstrate that DISCERN can track phenotypic plasticity in leukemia cells and identify stem-like subsets in leukemia xenograft models. This cost-effective and robust platform provides a promising tool for AML risk stratification, relapse prediction, and precision therapy.
Authors
- Yunlong Xiao (ORCID: https://orcid.org/0000-0003-0770-1240)
- Suzhen Zhai
- C Zhang
- Bin Zhang (ORCID: https://orcid.org/0000-0003-4703-7524)
- Lu Liu (ORCID: https://orcid.org/0000-0002-6960-5054)
- Hai Shi (ORCID: https://orcid.org/0000-0001-6849-0710)
- Renwu Mu
- Xiaoyan Yang
- Ying Shen
Institutions
- Nanjing University of Chinese Medicine (CN)
- Guiyang Medical University (CN)
- Affiliated Hospital of Guizhou Medical University (CN)
Publication Details
- Journal
- ACS Sensors
- Published
- 2026-02-05
- DOI
- https://doi.org/10.1021/acssensors.5c03906
- Primary Topic
- Advanced Nanomaterials in Catalysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00