Rapid detection of cancer DNA in human blood using cysteamine-capped AuNPs and a machine learning-enabled smartphone.
Sireemas KoowattanasuchatSawinee NgernpimaiPiyaporn MatulakulJanpen ThonghluengWitthawat PhanchaiApiwat ChompoosorUthumporn PanitanarakYupaporn WannaThanapong IntharahKanokon ChootawiriyasakulPimjai AnataPrajuab ChaimneeRaynoo ThananChadamas SakonsinsiriTheerapong PuangmaliPublished in: RSC advances (2023)
DNA methylation occurs when a methyl group is added to a cytosine (C) residue's fifth carbon atom, forming 5-methylcytosine (5-mC). Cancer genomes have a distinct methylation landscape (Methylscape), which could be used as a universal cancer biomarker. This study developed a simple, low-cost, and straightforward Methylscape sensing platform using cysteamine-decorated gold nanoparticles (Cyst/AuNPs), in which the sensing principle is based on methylation-dependent DNA solvation. Normal and cancer DNAs have distinct methylation profiles; thus, they can be distinguished by observing the dispersion of Cyst/AuNPs adsorbed on these DNA aggregates in MgCl 2 solution. After optimising the MgCl 2 , Cyst/AuNPs, DNA concentration, and incubation time, the optimised conditions were used for leukemia screening, by comparing the relative absorbance (Δ A 650/525 ). Following the DNA extraction from actual blood samples, this sensor demonstrated effective leukemia screening in 15 minutes with high sensitivity, achieving 95.3% accuracy based on the measurement by an optical spectrophotometer. To further develop for practical realisation, a smartphone assisted by machine learning was used to screen cancer patients, achieving 90.0% accuracy in leukemia screening. This sensing platform can be applied not only for leukemia screening but also for other cancers associated with epigenetic modification.
Keyphrases
- dna methylation
- papillary thyroid
- circulating tumor
- machine learning
- acute myeloid leukemia
- cell free
- gold nanoparticles
- single molecule
- bone marrow
- genome wide
- gene expression
- high throughput
- endothelial cells
- molecular dynamics
- childhood cancer
- big data
- artificial intelligence
- lymph node metastasis
- mass spectrometry
- copy number