AI Article Synopsis

  • MicroRNAs (miRNAs) play a key role in regulating gene expression and are being investigated as potential biomarkers for ovarian cancer, but variability in research protocols complicates their validation.
  • RNA was extracted from various tissue samples and plasma of ovarian cancer patients using different commercial kits, assessing the yield, purity, and stability of the RNA through several algorithms.
  • The study proposes guidelines for RNA isolation and data normalization for miRNA profiling and suggests using quality control panels to enhance accuracy and consistency in research outcomes.

Article Abstract

Background/aim: MicroRNAs (miRNAs) are small noncoding RNAs involved in gene expression regulation and have been investigated as potential biomarkers for various diseases, including ovarian cancer (OC). However, lack of standardized protocols regarding e.g., RNA isolation, cDNA synthesis, spike-in controls for experimental steps, and data normalization, impacts cross validation of results across research groups and hinders implementation of miRNAs as clinical biomarkers.

Materials And Methods: RNA was isolated from matching fresh-frozen tissue (FF), formalin-fixed paraffin embedded (FFPE) tissue, and plasma samples from twenty women diagnosed with OC using three commercial kits: miRNeasy Tissue/Cells, miRNeasy FFPE, and miRNeasy Serum/Plasma (Qiagen, Copenhagen, Denmark). RNA isolation, cDNA synthesis, and PCR performance were tested using miRCURY LNA miRNA Quality Control PCR (QC) Panels (Qiagen). Finally, miRNA stability was assessed using five algorithms: BestKeeper, Normfinder, GeNorm, comparative delta-Ct and comprehensive ranking provided by a web-based RefFinder tool.

Results: RNA from FF, FFPE and plasma was extracted using commercially available kits and the differences in yield and purity were examined. We developed a simple method for identifying and potentially excluding samples based on their crossing point values from RT-qPCR data, which could improve existing manufacture guidelines. Moreover, we discussed how assessment of miRNA stability differs between algorithms, possibly leading to inconsistent results.

Conclusion: We present guidelines for RNA isolation, cDNA synthesis, and data normalization for successful miRNA expression profiling using RT-qPCR in corresponding biological OC specimens. We recommend QC panels in combination with spike-in controls and interplate controls to monitor process efficiencies.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301446PMC
http://dx.doi.org/10.21873/invivo.12869DOI Listing

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