Gastric cancer remains a disease of high mortality worldwide due to its poor prognosis. Previous studies have shown that microRNAs (miRNAs) are effective biomarkers for early diagnosis of gastric cancer. To realize sensitive detection of related miRNAs for improved early diagnosis, classification, and survival prognosis of gastric cancer, herein we developed a framework nucleic acid (FNA)-mediated microarray for quantitative analysis of multiple miRNAs. By rationally designing FNA with different sizes, we systematically modulated the surface density and lateral interactions of DNA probes, which provides an effective means for programmable tailoring of the hybridization efficiency and kinetics of the biosensing interface. We found that the hybridization efficiency was increased along with the size of the FNA and was optimum for FNA-17. In combination with the hybridization chain reaction amplification strategy, this established FNA microarray can serve as an ultrasensitive and selective analytical platform for simultaneous multiplexed detection of miRNA (e.g., FNA-miR-652, FNA-miR-627, and FNA-miR-629) biomarkers in gastric cancer.
Keyphrases
- nucleic acid
- fine needle aspiration
- long non coding rna
- poor prognosis
- cell proliferation
- sensitive detection
- ultrasound guided
- label free
- loop mediated isothermal amplification
- long noncoding rna
- machine learning
- quantum dots
- type diabetes
- gold nanoparticles
- cardiovascular events
- single molecule
- high throughput
- risk factors
- small molecule
- photodynamic therapy
- single cell
- circulating tumor cells
- aqueous solution