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Aberrant microRNA expression is associated with tumor progression in various organs. Detecting microRNAs as clinical cancer biomarkers can facilitate early cancer diagnosis and monitoring. However, the rapid and accurate quantification of microRNAs from biological samples remains a significant challenge. Here we developed a one-pot isothermal assay utilizing a molecular circuit with CRISPR/Cas13a (CRISPR-circuit) to rapidly convert, amplify and report different microRNAs within 15 min at the attomolar (aM) level. Then the full process was performed on an active centrifugal microfluidic chip and its corresponding portable equipment for parallel detection of multiple microRNAs, including miR-21, miR-141, miR-196a, and miR-1246. We also demonstrated its application for identifying cell lines and clinical samples of cancer patients with varying microRNA levels, which showed a strong correlation with the RT-qPCR. The assay can be easily adapted for the detection of any microRNA by simply modifying the converter primer, thereby holding significant potential for accurate disease detection and clinical diagnosis.
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http://dx.doi.org/10.1016/j.bios.2025.117212 | DOI Listing |
Cell Death Dis
September 2025
Department of Endocrinology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510080, China.
In recent years, there has been a rapid increase in the incidence of thyroid carcinoma (TC). Our study focuses on the regulatory effect of circular RNAs on metabolism of TC, aiming to provide new insights into the mechanisms of progression and a potential therapeutic target for TC. In this study, we identified high expression levels of circPSD3 in TC tissues through RNA sequencing.
View Article and Find Full Text PDFInt Immunopharmacol
September 2025
Department of Animal Science, College of Agricultural, Yanbian University, Yanji 133002, China; Jilin Provincial Key Laboratory of Transgenic Animal and Embryo Engineering, Yanbian University, Yanji 133002, China. Electronic address:
Objective: Long-term administration of dexamethasone (DEX) to treat severe inflammation or autoimmune disorders often result in skeletal muscle atrophy and functional decline. Exosomes facilitate intercellular communication by transferring bioactive molecules, reflecting the characteristics of their tissue of origin. Myostatin-knockout (MSTN) mice exhibit muscle hypertrophy, and their muscle-derived exosomes (KO-EXOs) retain this phenotype.
View Article and Find Full Text PDFJMIR Res Protoc
September 2025
Department of Medical Oncology, Early Phase Unit, Georges-François Leclerc Centre, Dijon, France.
Background: Sarcomas are rare cancer with a heterogeneous group of tumors. They affect both genders across all age groups and present significant heterogeneity, with more than 70 histological subtypes. Despite tailored treatments, the high metastatic potential of sarcomas remains a major factor in poor patient survival, as metastasis is often the leading cause of death.
View Article and Find Full Text PDFPlant J
September 2025
College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China.
Genome imbalance, resulting from varying the dosage of individual chromosomes (aneuploidy), has a more detrimental effect than changes in complete sets of chromosomes (haploidy/polyploidy). This imbalance is likely due to disruptions in stoichiometry and interactions among macromolecular assemblies. Previous research has shown that aneuploidy causes global modulation of protein-coding genes (PCGs), microRNAs, and transposable elements (TEs), affecting both the varied chromosome (cis-located) and unvaried genome regions (trans-located) across various taxa.
View Article and Find Full Text PDFPLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
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