4.7 Article

An Interfacial Affinity Interaction-Based Method for Detecting HOTAIR lncRNA in Cancer Plasma Samples

期刊

BIOSENSORS-BASEL
卷 12, 期 5, 页码 -

出版社

MDPI
DOI: 10.3390/bios12050287

关键词

HOTAIR lncRNA; interfacial biosensing; affinity interaction; RNA biosensor; electrochemical detection; ovarian cancer

资金

  1. NHMRC MRFF Grant [APP1199984]
  2. Australian Research Council via Linkage Projects [LP200100016, LP200200758]
  3. Australian Research Council [LP200100016, LP200200758] Funding Source: Australian Research Council

向作者/读者索取更多资源

In this study, we developed a novel and rapid method to detect HOTAIR sequences. The method showed high specificity and sensitivity in clinical samples, making it a potential tool for ovarian cancer diagnosis.
Long non-coding RNA Homeobox transcript antisense intergenic RNA (HOTAIR) is recognized as a participant in different processes of normal cell development. Aberrant overexpression of HOTAIR contributes to the initiation, growth, and invasiveness of ovarian cancer. Using the affinity interaction of target HOTAIR lncRNA sequences towards a screen-printed gold electrode (SPE-Au), herein we report on a novel, rapid and simple method to detect HOTAIR sequences. HOTAIR lncRNA sequences were first extracted from ovarian cancer cell lines and patient plasma samples and were magnetically captured and purified by complimentary capture probe-functionalized magnetic beads. Isolated target HOTAIR lncRNAs were directly adsorbed onto unmodified screen-printed gold electrodes (SPE-Au) for direct quantification with [Fe(CN)(6)](3-/4-) redox couple. Our assay achieved a linear dynamic range of 100 nM and 1 pM for detecting pre-clinical model HOTAIR lncRNA samples (%RSD <= 5%, for n = 3) and was highly specific, showing clear distinction between HOTAIR lncRNA targets and non-specific miR-891 and miR-486 (100 nM) (%RSD <= 5%, for n = 3). The method was tested using ovarian cancer-specific cell lines (SKOV3 and OVCAR3) and mesothelial cell line (MeT-5A)-derived lncRNAs. The analytical performance of our method was validated using RT-qPCR. Finally, the method was tested using clinical samples from ovarian cancer patients and the resulting electrochemical responses show a clear distinction between the ovarian carcinoma and benign samples.

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