Self-Assembled DNA Machine and Selective Complexation Recognition Enable Rapid Homogeneous Portable Quantification of Lung Cancer CTCs.
Yue WangCongcong ShenChengyong WuZixuan ZhanRunlian QuYi XiePiaopiao ChenPublished in: Research (Washington, D.C.) (2024)
In this study, we systematically investigated the interactions between Cu 2+ and various biomolecules, including double-stranded DNA, Y-shaped DNA nanospheres, the double strand of the hybridization chain reaction (HCR), the network structure of cross-linked HCR (cHCR), and small molecules (PPi and His), using Cu 2+ as an illustrative example. Our research demonstrated that the coordination between Cu 2+ and these biomolecules not only is suitable for modulating luminescent material signals through complexation reactions with Cu 2+ but also enhances signal intensities in materials based on chemical reactions by increasing spatial site resistance and local concentration. Building upon these findings, we harnessed the potential for signal amplification in self-assembled DNA nanospheres and the selective complexation modulation of calcein in conjunction with the aptamer targeting mucin 1 as a recognition probe. We applied this approach to the analysis of circulating tumor cells, with the lung cancer cell line A549 serving as a representative model. Our assay, utilizing both a fluorometer and a handheld detector, achieved impressive detection limits of ag/ml and single-cell levels for mucin 1 and A549 cells, and this approach was successfully validated using 46 clinical samples, yielding 100% specificity and 86.5% sensitivity. Consequently, our strategy has paved the way for more portable and precise disease diagnosis.
Keyphrases
- circulating tumor
- circulating tumor cells
- nucleic acid
- single molecule
- cell free
- single cell
- quantum dots
- metal organic framework
- label free
- induced apoptosis
- aqueous solution
- high throughput
- loop mediated isothermal amplification
- computed tomography
- gold nanoparticles
- signaling pathway
- binding protein
- atomic force microscopy
- magnetic resonance imaging
- cell cycle arrest
- risk assessment
- machine learning
- small molecule
- cell death
- cell proliferation
- drug delivery
- real time pcr
- highly efficient