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The analysis of novel microRNA mimic sequences in cancer cells reveals lack of specificity in stem-loop RT-qPCR-based microRNA detection

Overview of attention for article published in BMC Research Notes, November 2017
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Title
The analysis of novel microRNA mimic sequences in cancer cells reveals lack of specificity in stem-loop RT-qPCR-based microRNA detection
Published in
BMC Research Notes, November 2017
DOI 10.1186/s13104-017-2930-0
Pubmed ID
Authors

Patrick Winata, Marissa Williams, Eileen McGowan, Najah Nassif, Nico van Zandwijk, Glen Reid

Abstract

MicroRNAs are frequently downregulated in cancer, and restoring expression has tumour suppressive activity in tumour cells. Our recent phase I clinical trial investigated microRNA-based therapy in patients with malignant pleural mesothelioma. Treatment with TargomiRs, microRNA mimics with novel sequence packaged in EGFR antibody-targeted bacterial minicells, revealed clear signs of clinical activity. In order to detect delivery of microRNA mimics to tumour cells in future clinical trials, we tested hydrolysis probe-based assays specific for the sequence of the novel mimics in transfected mesothelioma cell lines using RT-qPCR. The custom assays efficiently and specifically amplified the consensus mimics. However, we found that these assays gave a signal when total RNA from untransfected and control mimic-transfected cells were used as templates. Further investigation revealed that the reverse transcription step using stem-loop primers appeared to introduce substantial non-specific amplification with either total RNA or synthetic RNA templates. This suggests that reverse transcription using stem-loop primers suffers from an intrinsic lack of specificity for the detection of highly similar microRNAs in the same family, especially when analysing total RNA. These results suggest that RT-qPCR is unlikely to be an effective means to detect delivery of microRNA mimic-based drugs to tumour cells in patients.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 22%
Student > Bachelor 2 11%
Professor 2 11%
Other 1 6%
Student > Ph. D. Student 1 6%
Other 3 17%
Unknown 5 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 44%
Agricultural and Biological Sciences 3 17%
Medicine and Dentistry 2 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Unknown 4 22%