Rapid detection of cancer DNA in human blood using cysteamine-capped AuNPs and a machine learning-enabled smartphone
dc.contributor.author | Koowattanasuchat S. | |
dc.contributor.author | Ngernpimai S. | |
dc.contributor.author | Matulakul P. | |
dc.contributor.author | Thonghlueng J. | |
dc.contributor.author | Phanchai W. | |
dc.contributor.author | Chompoosor A. | |
dc.contributor.author | Panitanarak U. | |
dc.contributor.author | Wanna Y. | |
dc.contributor.author | Intharah T. | |
dc.contributor.author | Chootawiriyasakul K. | |
dc.contributor.author | Anata P. | |
dc.contributor.author | Chaimnee P. | |
dc.contributor.author | Thanan R. | |
dc.contributor.author | Sakonsinsiri C. | |
dc.contributor.author | Puangmali T. | |
dc.contributor.other | Mahidol University | |
dc.date.accessioned | 2023-05-19T07:37:19Z | |
dc.date.available | 2023-05-19T07:37:19Z | |
dc.date.issued | 2023-01-05 | |
dc.description.abstract | 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 MgCl2 solution. After optimising the MgCl2, Cyst/AuNPs, DNA concentration, and incubation time, the optimised conditions were used for leukemia screening, by comparing the relative absorbance (ΔA650/525). 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. | |
dc.identifier.citation | RSC Advances Vol.13 No.2 (2023) , 1301-1311 | |
dc.identifier.doi | 10.1039/d2ra05725e | |
dc.identifier.eissn | 20462069 | |
dc.identifier.scopus | 2-s2.0-85146095288 | |
dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/20.500.14594/81721 | |
dc.rights.holder | SCOPUS | |
dc.subject | Chemical Engineering | |
dc.title | Rapid detection of cancer DNA in human blood using cysteamine-capped AuNPs and a machine learning-enabled smartphone | |
dc.type | Article | |
mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85146095288&origin=inward | |
oaire.citation.endPage | 1311 | |
oaire.citation.issue | 2 | |
oaire.citation.startPage | 1301 | |
oaire.citation.title | RSC Advances | |
oaire.citation.volume | 13 | |
oairecerif.author.affiliation | Faculty of Medicine, Khon Kaen University | |
oairecerif.author.affiliation | Ramkhamhaeng University | |
oairecerif.author.affiliation | Khon Kaen University | |
oairecerif.author.affiliation | Mahidol University |