Aberrant expression of microRNAs (miRNAs), short non-coding RNA molecules regulating gene expression, is often found in tumor cells, making the miRNAs suitable candidates as cancer biomarkers. Electrochemistry is an interesting alternative to current standard methods of miRNA detection by offering cheaper instrumentation and faster assays times. In this paper, we labeled miRNA in a quick, simple, two-step procedure with electroactive complex of osmium(VI) and 2,2'-bipyridine, Os(VI)bipy, which specifically binds to the ribose at the 3'-end of the miRNA, and hybridized such labeled miRNA with biotinylated capture probe attached to the streptavidin magnetic beads. Labeled miRNA was then detected at hanging mercury drop electrode at femtomole level due to an electrocatalytic nature of the peak from the Os(VI)bipy label. We obtained good selectivity of the assay using elevated hybridization temperatures for better discrimination of perfect duplex from single and double mismatches. After optimization of the protocol, we demonstrated feasibility of our assay by detecting target miRNA in real total RNA samples isolated from human cancer cells.
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http://dx.doi.org/10.1016/j.aca.2014.01.023 | DOI Listing |
Biosensors (Basel)
January 2025
School of Chemistry and Chemical Engineering, Linyi University, Linyi 276005, China.
MicroRNA122 (miR-122) is a microRNA that is highly expressed in hepatocytes and has been identified as a prospective therapeutic target and biomarker for liver injury. An expanding body of research has demonstrated that miR-122 is a critical regulator in both the initiation and progression of a wide range of liver diseases. Traditional methods for detecting miR-122 mainly include Northern blotting and qRT-PCR, but they are technically complex and cumbersome, requiring expensive instruments and high technical requirements.
View Article and Find Full Text PDFComput Biol Chem
January 2025
Department of Computer Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon, 22212, Republic of Korea. Electronic address:
Cancer metastasis is the dissemination of tumor cells from the primary tumor site to other parts of the body via the lymph system or bloodstream. Metastasis is the leading cause of cancer associated death. Despite the significant advances in cancer research and treatment over the past decades, metastasis is not fully understood and difficult to predict in advance.
View Article and Find Full Text PDFClin Cancer Res
January 2025
City Of Hope National Medical Center, Monrovia, CA, United States.
PURPOSE EXONERATE (EXOsome and cell-free micro-RNAs of anti-EGFR ResistAnce) was an open-label, biomarker interventional study designed to develop, test, and validate a liquid biopsy predictive of progression-free survival (PFS), overall survival (OS), and objective response rate (ORR) for first-line EGFR inhibitors in metastatic colorectal cancer (mCRC). PATIENTS AND METHODS Patients with newly diagnosed RAS-WT, chemotherapy-naïve mCRC, both right- and left-sided, were enrolled in 2-nationwide trials to receive cetuximab or panitumumab along with chemotherapy. The primary endpoint was 12-month PFS, which was hierarchically tested in left- and right-sided mCRC to predict PFS, OS, and ORR.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Research and Development, Ichimaru Pharcos Co. Ltd., Motosu, Gifu, Japan.
Hyaluronic acid (HA) is an important component of the skin's extracellular matrix, and its degradation leads to wrinkles. Hyaluronan-binding protein involved in hyaluronan depolymerization (HYBID) is the main factor responsible for HA degradation in dermis. This study aimed to identify natural plant materials that can effectively suppress HYBID expression and protect HA from degradation.
View Article and Find Full Text PDFBMC Genom Data
January 2025
Department of Management Information Systems, National Chung Hsing University, Taichung, 402, Taiwan.
Background: miRNAs (microRNAs) are endogenous RNAs with lengths of 18 to 24 nucleotides and play critical roles in gene regulation and disease progression. Although traditional wet-lab experiments provide direct evidence for miRNA-disease associations, they are often time-consuming and complicated to analyze by current bioinformatics tools. In recent years, machine learning (ML) and deep learning (DL) techniques are powerful tools to analyze large-scale biological data.
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