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A comparison between quantitative PCR and droplet digital PCR technologies for circulating microRNA quantification in human lung cancer

Overview of attention for article published in BMC Biotechnology, August 2016
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Title
A comparison between quantitative PCR and droplet digital PCR technologies for circulating microRNA quantification in human lung cancer
Published in
BMC Biotechnology, August 2016
DOI 10.1186/s12896-016-0292-7
Pubmed ID
Authors

Paola Campomenosi, Elisabetta Gini, Douglas M. Noonan, Albino Poli, Paola D’Antona, Nicola Rotolo, Lorenzo Dominioni, Andrea Imperatori

Abstract

Selected microRNAs (miRNAs) that are abnormally expressed in the serum of patients with lung cancer have recently been proposed as biomarkers of this disease. The measurement of circulating miRNAs, however, requires a highly reliable quantification method. Quantitative real-time PCR (qPCR) is the most commonly used method, but it lacks reliable endogenous reference miRNAs for normalization of results in biofluids. When used in absolute quantification, it must rely on the use of external calibrators. Droplet digital PCR (ddPCR) is a recently introduced technology that overcomes the normalization issue and may facilitate miRNA measurement. Here we compared the performance of absolute qPCR and ddPCR techniques for quantifying selected miRNAs in the serum. In the first experiment, three miRNAs, proposed in the literature as lung cancer biomarkers (miR-21, miR-126 and let-7a), were analyzed in a set of 15 human serum samples. Four independent qPCR and four independent ddPCR amplifications were done on the same samples and used to estimate the precision and correlation of miRNA measurements obtained with the two techniques. The precision of the two methods was evaluated by calculating the Coefficient of Variation (CV) of the four independent measurements obtained with each technique. The CV was similar or smaller in ddPCR than in qPCR for all miRNAs tested, and was significantly smaller for let-7a (p = 0.028). Linear regression analysis of the miRNA values obtained with qPCR and ddPCR showed strong correlation (p < 0.001). To validate the correlation obtained with the two techniques in the first experiment, in a second experiment the same miRNAs were measured in a larger cohort (70 human serum samples) by both qPCR and ddPCR. The correlation of miRNA analyses with the two methods was significant for all three miRNAs. Moreover, in our experiments the ddPCR technique had higher throughput than qPCR, at a similar cost-per-sample. Analyses of serum miRNAs performed with qPCR and ddPCR were largely concordant. Both qPCR and ddPCR can reliably be used to quantify circulating miRNAs, however, ddPCR revealed similar or greater precision and higher throughput of analysis.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Austria 1 <1%
Unknown 172 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 18%
Student > Ph. D. Student 27 16%
Student > Bachelor 22 13%
Student > Master 17 10%
Other 13 7%
Other 24 14%
Unknown 39 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 50 29%
Agricultural and Biological Sciences 27 16%
Medicine and Dentistry 13 7%
Engineering 6 3%
Neuroscience 4 2%
Other 26 15%
Unknown 48 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 June 2017.
All research outputs
#15,381,416
of 22,883,326 outputs
Outputs from BMC Biotechnology
#668
of 935 outputs
Outputs of similar age
#218,834
of 343,111 outputs
Outputs of similar age from BMC Biotechnology
#6
of 12 outputs
Altmetric has tracked 22,883,326 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 935 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 343,111 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.