Reference miRNAs for colorectal cancer: analysis and verification of current data.
Elisa DaneseA M MinicozziM BenatiE PaviatiG Lima-OliveiraM GusellaF PasiniGian Luca SalvagnoM MontagnanaGian Luca SalvagnoPublished in: Scientific reports (2017)
MicroRNAs (miRNAs) hold great promise in cancer research. The use of appropriate reference miRNAs for normalization of qPCR data is crucial for accurate expression analysis. We present here analysis and verification of current data, proposing a workflow strategy for identification of reference miRNAs in colorectal cancer (CRC). We performed a systematic review of studies aimed to identify stable reference miRNAs in CRC through high-throughput screening. Among the candidate miRNAs selected from the literature we excluded those predicted to target oncogenes or tumor suppressor gene. We then assessed the expression levels of the remaining candidates in exosomes, plasma and tissue samples from CRC patients and healthy controls. The expression stability was evaluated by box-plot, ∆Cq analysis, NormFinder and BestKeeper statistical algorithms. The effects of normalisers on the relative quantification of the oncogenic miR-1290 was also assessed. Our results consistently showed that different combinations of miR-520d, miR-1228 and miR-345 provided the most stably expressed reference miRNAs in the three biological matrices. We identified suitable reference miRNAs for future miRNA expression studies in exosomes plasma and tissues CRC samples. We also provided a novel conceptual framework that overcome the need of performing ex novo identification of suitable reference genes in single experimental systems.
Keyphrases
- long non coding rna
- poor prognosis
- cell proliferation
- long noncoding rna
- electronic health record
- mesenchymal stem cells
- stem cells
- machine learning
- transcription factor
- ejection fraction
- end stage renal disease
- binding protein
- genome wide
- systematic review
- genome wide identification
- gene expression
- prognostic factors
- deep learning
- dna methylation
- mass spectrometry
- bioinformatics analysis
- current status
- patient reported outcomes