Hydrogel-Based Microdroplet Ensembles Encapsulating Multiplexed EXPAR Assays for Trichromic Digital Profiling of MicroRNAs and in-Depth Classification of Primary Urethral Cancers
The primary challenge in microarray-based biological analysis lies in achieving the sensitive and specific detection of single-molecule targets while ensuring high reproducibility. A user-friendly digital imaging platform has been developed for the encoded trichromic profiling of circulating microRNAs (miRNAs). This platform replaces the traditional exponential polymerase amplification reaction (EXPAR) conducted on the microliter scale with a system that confines the amplification process within thousands of femtoliter-sized microdroplet reactors, cross-linked from tetra-armed poly(ethylene glycol) acrylate (Tetra-PEGA) and poly(ethylene glycol) dithiol (HS-PEG-SH), thus offering significant advantages, including minimal sample input, enhanced reactivity, and simplified analytical procedures. The quantitative analysis relies on digital counting of fluorescently positive microdroplets, each containing an individual miRNA sequence. This approach significantly reduces nonspecific amplification and improves sensitivity by over 2 orders of magnitude. The system has shown great potential in differentiating between subtypes of primary urethral carcinoma, suggesting its practical application in routine cancer diagnostics through simple urinalysis.
Authors
- Chanyu Yao
- Xiaohui Lü (ORCID: https://orcid.org/0000-0002-3628-7221)
- Xiaofeng Chen (ORCID: https://orcid.org/0000-0003-0261-3807)
- Zheng Li (ORCID: https://orcid.org/0000-0001-9066-5791)
- Qiang Wang (ORCID: https://orcid.org/0000-0002-1715-8758)
Institutions
- Shenzhen University (CN)
- Hainan University (CN)
- Shenzhen Second People's Hospital (CN)
Publication Details
- Journal
- Nano Letters
- Published
- 2024-11-25
- DOI
- https://doi.org/10.1021/acs.nanolett.4c04898
- Citations
- 5
- Primary Topic
- Bladder and Urothelial Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.86
Funders
- National Natural Science Foundation of China
- Shenzhen University
- Natural Science Foundation of Guangdong Province for Distinguished Young Scholars