Modular DNA Logic Computing for Multi-Bit Fluorescent Encoding: Precision Subtype Diagnostics in Breast Cancer

Abstract

Breast cancer, the most common cancer worldwide, exhibits high heterogeneity, posing significant challenges for precise diagnosis and subtype classification. Existing diagnostic methods are subjective and variable, reducing accuracy and patient compliance. These issues are particularly critical in recurrent or metastatic tumors, where accurate subtype identification is essential for effective treatment. To identify subtype-specific breast cancer, we developed a modular, multivalent cascaded DNA logic platform through detection of three key miRNAs (miR-21, miR-587, and miR-210) correlated with subtype features. Specifically, a universal biomarker for breast cancer, microRNA-21 promotes DNAzyme cleavage module as the YES logic gate. The logic computation module is composed of basic logic operations, such as AND and OR gates in response to dual targets microRNA-587 and microRNA-210 dysregulated expression correlated with breast cancer subtypes. Fluorescent output module accepts upstream logic outputs to perform strand displacement and entropy driven reactions, generating amplified Cy3 and FAM signals. By encoding fluorescence signals into binary codes, our system translates complex molecular information into unique three-bit binary patterns representing non-tumorigenic, malignant (Luminal/HER2+), and metastatic (triple-negative) breast cells. Validated via intracellular imaging and clinical plasma sample analysis, the platform precisely differentiates breast cancer subtypes using miRNA-specific logic computing. The integration of binary coding and fluorescence amplification establishes a foundation for intelligent diagnostic systems in personalized oncology, providing a new cost-effective and scalable tool for accurate breast cancer subtype identification.

Note:
Funding declaration: This work was supported by the National Natural Science Foundation of China (Nos. 22174137 and 22322410), the Science and Technology Development Plan Project of Jilin Province (Nos. SKL202302030, SKL202402017, JJKH20231296KJ and 20230204113YY), International Partnership Program of the Chinese Academy of Sciences (No. 029GJHZ2023146FN).

Conflict of Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ethical Approval: Approved by the ethical committee of the First Hospital of Jilin University, Changchun, Jilin, China (No. 2018-467).

Keywords: breast cancer, DNA logic gate, fluorescent encoding, clinical samples diagnosis, subtypes discrimination