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Isothermal amplification-mediated lateral flow biosensors for in vitro diagnosis of gastric cancer-related microRNAs

Authors
Seo, S.B.Hwang, J.-S.Kim, E.Kim, K.Roh, S.Lee, G.Lim, J.Kang, B.Jang, S.Son, S.U.Kang, T.Jung, J.Kim, J.-S.Keun-Hur,Han, T.-S.Lim, E.-K.
Issue Date
2022
Publisher
Elsevier B.V.
Keywords
Gastric cancer; In vitro diagnosis; Lateral flow biosensor; microRNAs; Rolling circle amplification
Citation
Talanta, v.246
Indexed
SCIE
SCOPUS
Journal Title
Talanta
Volume
246
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/142090
DOI
10.1016/j.talanta.2022.123502
ISSN
0039-9140
Abstract
MicroRNAs (miRNAs) are important diagnostic and prognostic biomarkers for various tumors. Currently, many diagnostic systems have been developed to detect miRNAs, but simple techniques for detecting miRNAs are still required. Recently, we reported that the expression of miRNA-135b is upregulated in gastric epithelial cells during gastric inflammation and carcinogenesis. Our aim was to develop an in vitro diagnostic platform to analyze the expression of gastric cancer-related biomarkers in the blood. The diagnostic platform comprised an isothermal amplification-based lateral flow biosensor (IA-LFB) that enables easy diagnosis of gastric cancer through visual observation. In this platform, trace amounts of biomarkers are isothermally amplified through rolling circle amplification (RCA), and the amplified product is grafted to the LFB. The performance of the IA-LFB was confirmed using RNAs extracted from in vitro and in vivo models. The platform could detect target miRNAs within 3 h with excellent sensitivity and selectivity. In particular, the IA-LFB could detect the overexpression of gastric cancer-related markers (miRNA-135b and miRNA-21) in RNAs extracted from the blood of patients with various stages (stages 1–4) of gastric cancer compared to that in healthy volunteers. Therefore, IA-LFB is a simple and sensitive in vitro diagnostic system for detecting gastric cancer-related biomarkers and can contribute to the early diagnosis and prognosis monitoring of gastric cancer. Furthermore, this technology can be applied to systems that can detect multiple biomarkers related to various diseases (such as infectious and genetic diseases). © 2022 The Authors
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