Integrating isothermal amplification techniques and LNA-based AI-assisted electrochemical bioassay for analysis of KRAS G12V point mutation
Jazyk angličtina Země Nizozemsko Médium print-electronic
Typ dokumentu časopisecké články
PubMed
39961243
DOI
10.1016/j.talanta.2025.127709
PII: S0039-9140(25)00195-X
Knihovny.cz E-zdroje
- Klíčová slova
- DNA point mutation, Electrochemistry, KRAS gene, Locked nucleic acid, Rolling circle amplification,
- MeSH
- biotest * metody MeSH
- bodová mutace * MeSH
- elektrochemické techniky * metody MeSH
- lidé MeSH
- mutační analýza DNA metody MeSH
- nádorové buněčné linie MeSH
- oligonukleotidy * chemie genetika MeSH
- protoonkogenní proteiny p21(ras) * genetika MeSH
- techniky amplifikace nukleových kyselin * metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- KRAS protein, human MeSH Prohlížeč
- locked nucleic acid MeSH Prohlížeč
- oligonukleotidy * MeSH
- protoonkogenní proteiny p21(ras) * MeSH
The KRAS mutation is a crucial biomarker for determining targeted cancer therapies, making its accurate and cost-effective detection vital for precision oncology. However, current methodologies, such as next-generation sequencing (NGS) or PCR-based methods, are often expensive and technically complex, limiting their accessibility. Here, we present a novel bioassay for KRAS G12V mutation analysis that combines rolling circle amplification (RCA) with locked nucleic acid (LNA)-modified magnetic beads, electrochemical detection using carbon electrode chips, and AI-assisted analysis via a logistic regression classifier. Our platform demonstrated exceptional selectivity in distinguishing the KRAS G12V mutation from wild-type (wt) sequences, enabling analysis <1 % of mutated DNA in a wt sample. We validated the bioassay on 7 cancer cell lines and 11 patient-derived samples, achieving results that perfectly correlated with NGS data. This innovative approach simplifies the workflow, reduces costs, and offers high sensitivity and specificity, making it a promising tool for clinical diagnostics and personalized cancer treatment strategies.
Citace poskytuje Crossref.org