Abstract
Ovarian cancer is a gynecological cancer characterized by a high mortality rate and tumor heterogeneity. Its early detection and primary prophylaxis are difficult to perform. Detecting biomarkers for ovarian cancer plays a pivotal role in therapy effectiveness and affects patients’ survival. This study demonstrates the detection of microRNAs (miRNAs), which were reported to be associated with ovarian cancer tumorigenesis, with a nanowire biosensor based on silicon-on-insulator structures (SOI-NW biosensor). The advantages of the method proposed for miRNA detection using the SOI-NW biosensor are as follows: (1) no need for additional labeling or amplification reaction during sample preparation, and (2) real-time detection of target biomolecules. The detecting component of the biosensor is a chip with an array of 3 µm wide, 10 µm long silicon nanowires on its surface. The SOI-NW chip was fabricated using the “top-down” method, which is compatible with large-scale CMOS technology. Oligonucleotide probes (oDNA probes) carrying sequences complementary to the target miRNAs were covalently immobilized on the nanowire surface to ensure high-sensitivity biospecific sensing of the target biomolecules. The study involved two experimental series. Detection of model DNA oligonucleotides being synthetic analogs of the target miRNAs was carried out to assess the method’s sensitivity. The lowest concentration of the target oligonucleotides detectable in buffer solution was 1.1 × 10−16 M. In the second experimental series, detection of miRNAs (miRNA-21, miRNA-141, and miRNA-200a) isolated from blood plasma samples collected from patients having a verified diagnosis of ovarian cancer was performed. The results of our present study represent a step towards the development of novel highly sensitive diagnostic systems for the early revelation of ovarian cancer in women.
Funder
Ministry of Science and Higher Education of the Russian Federation
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering
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