Framework nucleic acid-based linear amplification platform for sensitive detection of bladder cancer-related miRNAs

doi:10.3969/j.issn.1674-8115.2025.03.001

Abstract

Abstract:

Objective ·To construct a framework nucleic acid-based linear amplification platform for the sensitive and quantitative detection of bladder cancer-related microRNAs (miRNAs), facilitating early screening and accurate diagnosis of bladder cancer. Methods ·This study combined a plasma fluorescence-enhanced chip with high-performance tetrahedral framework nucleic acid (tFNA) probes, targeting miRNAs as biomarkers, to construct a framework nucleic acid-based linear signal amplification platform for precise and high-throughput quantitative analysis of multiple targets. First, atomic force microscope (AFM) was used to verify the efficient synthesis of tFNA. The signal linear amplification capability of the reporter unit was verified by polyacrylamide gel electrophoresis (PAGE) and total internal reflection fluorescent microscope (TIRFM). The performance of the sensing interface substrates was compared, and the golden island chip with signal amplification was selected. The specificity of the detection system was verified by an interface specificity experiment. Five bladder cancer-related miRNAs were selected to construct standard curves for quantitative detection. Results ·The efficient synthesis of tetrahedral monomer and dimer structures was verified by AFM. PAGE and TIRFM characterization verified the linear amplification of fluorescence signals from 1 to 6 valence fluorescence reporter units. In order to achieve further signal amplification, the plasma island chip and the traditional glass chip were compared. The results showed that the gold island chip exhibited a plasmonic effect, which significantly enhanced the near-infrared (NIR) fluorescence, with a signal amplification of up to 13.6 times compared to the glass chip. The specificity verification experiment showed that the signal-to-noise ratio of the system ranged from 7 to 10, demonstrating high specificity. Based on the high specificity of the system, along with the good interface regulation ability and linear amplification of the framework nucleic acid-based interface, dual-color parallel detection of the targets was finally realized. The working range was 100 fmol/L‒10 nmol/L (R²≥0.991), and the detection limit was as low as 100 fmol/L. Conclusion ·The establishment of this platform opens new avenues for highly sensitive quantitative analysis of biomarkers. Furthermore, the developed framework nucleic acid-based detection platform holds great potential for clinical diagnosis and prognosis of bladder cancer and other major diseases. Through early detection and precise subtype diagnosis, doctors can formulate more personalized treatment plans for patients, improving treatment efficacy and reducing unnecessary treatment plans and associated side effects. Therefore, this liquid biopsy technology not only provides new possibilities for early screening of bladder cancer but also serves as reference for research and clinical applications in other types of cancer.

Key words: bladder cancer, framework nucleic acid, biosensing, fluorescence chip

CLC Number:

O652.7

MAO Chenzhou, ZHANG Ruiyun, CHEN Haige, YIN Fangfei, ZUO Xiaolei. Framework nucleic acid-based linear amplification platform for sensitive detection of bladder cancer-related miRNAs[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2025, 45(3): 253-260.

Figures/Tables 6

TrendMD

References 34

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DNA	Sequence (5′→3′)
A37-1	CCCTGTACTGGCTAGGAATTCACGTTTTAATCTGGGCTTTGGGTTAAGAAACTCCCCG
A37-2	CGCTGGAGGCGCATCACCGTTTGCGTATGTGTTCTGTGCGGCCTGCCGTCCCGTGTGGG
B37-1	CGGTGATGCGCCTCCAGCGCGGGGAGTTTCTTAACCCTTTCCGACTTACAAGAGCCGG
B37-2	GCGAGACTCAGGTGGTGCCTTTGGCATTCGACCAGGAGATATCGCGTTCAGCTATGCCC
C37-1	CCCATGAGAATAATACCGCCGATTTACGTCAGTCCGGTTTCCCACACGGGACGGCAGGC
C37-2	CGCACAGAACACATACGCTTTGGGCATAGCTGAACGCGATATCTCCTGGTCGAATGCC
D37-1	GCCCAGATTAAAACGTGAATTCCTAGCCAGTACAGGGTTTCCGGACTGACGTAAATCGG
D37-2	CGGTATTATTCTCATGGGTTTGGCACCACCTGAGTCTCGCCCGGCTCTTGTAAGTCGG

DNA	Sequence (5′→3′)
A37-1	CCCTGTACTGGCTAGGAATTCACGTTTTAATCTGGGCTTTGGGTTAAGAAACTCCCCG
A37-2	CGCTGGAGGCGCATCACCGTTTGCGTATGTGTTCTGTGCGGCCTGCCGTCCCGTGTGGG
B37-1	CGGTGATGCGCCTCCAGCGCGGGGAGTTTCTTAACCCTTTCCGACTTACAAGAGCCGG
B37-2	GCGAGACTCAGGTGGTGCCTTTGGCATTCGACCAGGAGATATCGCGTTCAGCTATGCCC
C37-1	CCCATGAGAATAATACCGCCGATTTACGTCAGTCCGGTTTCCCACACGGGACGGCAGGC
C37-2	CGCACAGAACACATACGCTTTGGGCATAGCTGAACGCGATATCTCCTGGTCGAATGCC
D37-1	GCCCAGATTAAAACGTGAATTCCTAGCCAGTACAGGGTTTCCGGACTGACGTAAATCGG
D37-2	CGGTATTATTCTCATGGGTTTGGCACCACCTGAGTCTCGCCCGGCTCTTGTAAGTCGG

miRNA	Sequence (5′→3′)
miRNA-10a-5p	UACCCUGUAGAUCCGAAUUUGUG
miRNA-182-5p	UUUGGCAAUGGUAGAACUCACACU
miRNA-1-3p	UGGAAUGUAAAGAAGUAUGUAU
miRNA-30a-5p	UGUAAACAUCCUCGACUGGAAG
miRNA-100-5p	AACCCGUAGAUCCGAACUUGUG

miRNA	Sequence (5′→3′)
miRNA-10a-5p	UACCCUGUAGAUCCGAAUUUGUG
miRNA-182-5p	UUUGGCAAUGGUAGAACUCACACU
miRNA-1-3p	UGGAAUGUAAAGAAGUAUGUAU
miRNA-30a-5p	UGUAAACAUCCUCGACUGGAAG
miRNA-100-5p	AACCCGUAGAUCCGAACUUGUG

DNA	Sequence (5′→3′)
Signal-10a-Cy5	Cy5-CACAAATTCGGATCTACTAA
Signal-182-Cy5	Cy5-AGTGTGAGTTCTACCATTGA
Signal-1-Cy5	Cy5-ATACATACTTCTTTACATGA
Signal-30a-Cy5	Cy5-CTTCCAGTCGAGGATGTTGA
Signal-100-Cy5	Cy5-CACAAGTTCGGATCTACTGA