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Polymerase-based DNA reactions for molecularly computing cancerous diagnostic valences of multiple miRNAs

文献类型： 外文期刊

作者： Yan, Yumin 1 ; Zhao, Hongyang 2 ; Xing, Lijie 3 ; Ouyang, Ye 2 ; Zhang, Linghao 2 ; Yang, Jiayu 2 ; Qiu, Jing 1 ; Qian, Yongzhong 1 ; Ma, Liang 4 ; Weng, Rui 1 ; Su, Xin 2 ;

作者机构： 1.Chinese Acad Agr Sci, Minist Agr & Rural Affairs, Inst Qual Stand & Testing Technol Agroprod, Key Lab Agrofood Safety & Qual, Beijing 100081, Peoples R China

2.Beijing Univ Chem Technol, Coll Life Sci & Technol, Beijing Adv Innovat Ctr Soft Matter Sci & Engn, Beijing Key Lab Bioproc,State Key Lab Organ Inorga, Beijing 100029, Peoples R China

3.Xinjiang Acad Agr & Reclamat Sci, Anal & Testing Ctr, Shihezi 832000, Peoples R China

4.China Japan Friendship Hosp, Clin Lab, Beijing 100029, Peoples R China

5.Chinese Acad Agr Sci, Natl Nanfan Res Inst, Sanya 572024, Peoples R China

关键词： DNA computing; miRNA; Machine learning; NSCLC diagnostics

期刊名称：JOURNAL OF NANOBIOTECHNOLOGY （ 影响因子：12.6； 五年影响因子：12.3 ）

ISSN：

年卷期： 2025 年 23 卷 1 期

页码：

收录情况： SCI

摘要： Conventional miRNA-based diagnostic methods often treat all biomarkers equally, overlooking the fact that each miRNA contributes differently to disease classification. This differential diagnostic importance is captured by the concept of Cancerous Diagnostic Valence (CDV)-a metric that quantifies both the direction (oncogenic or protective) and magnitude of each miRNA's association with cancer. Here, we introduce a polymerase-based DNA molecular computing system that directly encodes and integrates CDVs to perform weighted molecular classification of non-small cell lung cancer (NSCLC). By coupling DNA polymerase-mediated strand extension and displacement (PB-DSD and cascade PB-DSD), the system translates miRNA inputs into proportional molecular signals spanning a wide CDV range (1-25), with minimal probe complexity. Seven NSCLC-related miRNAs with machine learning-derived CDVs were used to construct a diagnostic classifier, achieving 95% accuracy in tissue and 90% in plasma samples. Compared to conventional toehold strand displacement systems, this approach offers broader scalability, lower background interference, and more accurate diagnostic logic. Furthermore, we demonstrate its utility for therapeutic monitoring by tracking drug-induced shifts in CDV-weighted miRNA profiles in tumor-bearing mice treated with allicin and curcumin. This work establishes a molecularly programmable and biologically informed diagnostic platform that advances the precision and interpretability of miRNA-based cancer diagnostics.

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