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Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation.

Whale AS, Huggett JF, Cowen S, Speirs V, Shaw J, Ellison S, Foy CA, Scott DJ - Nucleic Acids Res. (2012)

Bottom Line: One of the benefits of Digital PCR (dPCR) is the potential for unparalleled precision enabling smaller fold change measurements.An example of an assessment that could benefit from such improved precision is the measurement of tumour-associated copy number variation (CNV) in the cell free DNA (cfDNA) fraction of patient blood plasma.Using an existing model (based on Poisson and binomial distributions) to derive an expression for the variance inherent in dPCR, we produced a power calculation to define the experimental size required to reliably detect a given fold change at a given template concentration.

View Article: PubMed Central - PubMed

Affiliation: LGC Limited, Queens Road, Teddington, Middlesex TW11 0LY, UK.

ABSTRACT
One of the benefits of Digital PCR (dPCR) is the potential for unparalleled precision enabling smaller fold change measurements. An example of an assessment that could benefit from such improved precision is the measurement of tumour-associated copy number variation (CNV) in the cell free DNA (cfDNA) fraction of patient blood plasma. To investigate the potential precision of dPCR and compare it with the established technique of quantitative PCR (qPCR), we used breast cancer cell lines to investigate HER2 gene amplification and modelled a range of different CNVs. We showed that, with equal experimental replication, dPCR could measure a smaller CNV than qPCR. As dPCR precision is directly dependent upon both the number of replicate measurements and the template concentration, we also developed a method to assist the design of dPCR experiments for measuring CNV. Using an existing model (based on Poisson and binomial distributions) to derive an expression for the variance inherent in dPCR, we produced a power calculation to define the experimental size required to reliably detect a given fold change at a given template concentration. This work will facilitate any future translation of dPCR to key diagnostic applications, such as cancer diagnostics and analysis of cfDNA.

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Determination of CNV detection of digital and quantitative real-time PCR. Quantitation of HER2:RNase P ratios using (a) dPCR and (b) qPCR generated from the in vitro gene-amplification model. The x-axis shows the expected HER2:RNase P ratio and the y-axis shows the observed HER2:RNase P ratios with the 95% CI. (a) For dPCR, four panels for each assay were analyzed for ratios > 1.5 (daggered symbol) and eight panels for each assay for ratios <1.5. In all cases, λr was approximately 0.2. The error bars represent the 95% CIs. (b) For qPCR, eight reactions were performed for each assay and all ratios. The error bars represent the 95% CIs calculated from the standard error of the mean and associated T-value with 95% confidence and seven degrees-of-freedom. Key: black triangle: normal female gDNA, black diamond: significantly different from normal female gDNA (P < 0.05), gray diamond: not significantly different from normal female gDNA (P > 0.05). Solid line of linear correlation is shown for those ratios that were significantly different from normal female gDNA. Dashed line is the extrapolation of the linear correlation showing intersection with HER2:RNase P ratio of 1.0. R2 and equations are given for the linear correlation.
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gks203-F2: Determination of CNV detection of digital and quantitative real-time PCR. Quantitation of HER2:RNase P ratios using (a) dPCR and (b) qPCR generated from the in vitro gene-amplification model. The x-axis shows the expected HER2:RNase P ratio and the y-axis shows the observed HER2:RNase P ratios with the 95% CI. (a) For dPCR, four panels for each assay were analyzed for ratios > 1.5 (daggered symbol) and eight panels for each assay for ratios <1.5. In all cases, λr was approximately 0.2. The error bars represent the 95% CIs. (b) For qPCR, eight reactions were performed for each assay and all ratios. The error bars represent the 95% CIs calculated from the standard error of the mean and associated T-value with 95% confidence and seven degrees-of-freedom. Key: black triangle: normal female gDNA, black diamond: significantly different from normal female gDNA (P < 0.05), gray diamond: not significantly different from normal female gDNA (P > 0.05). Solid line of linear correlation is shown for those ratios that were significantly different from normal female gDNA. Dashed line is the extrapolation of the linear correlation showing intersection with HER2:RNase P ratio of 1.0. R2 and equations are given for the linear correlation.

Mentions: To determine the limit of detection for analysis of CNVs by dPCR, an in vitro gene-amplification model was used, whereby T-47D gDNA was spiked into normal female gDNA to generate a theoretical range of HER2:RNase P ratios between 1.00 and 2.00 at low copy number (2.1 ng/μl) for analysis using dPCR and qPCR (Supplementary Table S2). Using dPCR, a ratio of 1.17 or more was significantly different from the experimentally derived normal female gDNA ratio of 1.03 (P < 0.0003) when eight panels where used (Figure 2a). There was good linear correlation between the expected and the observed ratios when measuring a CNV of ≥1.17 (R2 = 0.9974) and this linear correlation was maintained when the line was extrapolated through the observed ratio for normal female gDNA (Figure 2a; dashed line). Furthermore, the slope and intercept of the linear correlation were measured as 1.05 and 0.05, respectively, demonstrating the accuracy in the measured ratios, and that no bias was introduced. An expected ratio of 1.12 was not significantly different from normal female gDNA when using eight panels (P = 0.67; Figure 2a). In all cases, the RNase P counts observed for each measurement were not significantly different from one another (P ≥ 0.75). Analysing the in vitro gene-amplification model with qPCR demonstrated that ratios of 1.27 or more were significantly different from normal female gDNA (P < 0.0005) and maintained a linear correlation (R2 = ≥0.99; Figure 2b; dashed line). As was observed with the dPCR analysis, the observed ratios were accurate with no introduced bias as shown by the slope (1.01) and intercept (<0.001) of the linear correlation. Ratios of ≤1.22 did not differ significantly from female gDNA (P > 0.05; Figure 2b). As with dPCR, in all cases, the RNase P counts observed for each measurement were not significantly different from one another (P ≥ 0.27). Furthermore, no statistically significant inter-run variability was observed for either the RNase P or the HER2 assays (P ≥ 0.99 and P ≥ 0.15, respectively).Figure 2.


Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation.

Whale AS, Huggett JF, Cowen S, Speirs V, Shaw J, Ellison S, Foy CA, Scott DJ - Nucleic Acids Res. (2012)

Determination of CNV detection of digital and quantitative real-time PCR. Quantitation of HER2:RNase P ratios using (a) dPCR and (b) qPCR generated from the in vitro gene-amplification model. The x-axis shows the expected HER2:RNase P ratio and the y-axis shows the observed HER2:RNase P ratios with the 95% CI. (a) For dPCR, four panels for each assay were analyzed for ratios > 1.5 (daggered symbol) and eight panels for each assay for ratios <1.5. In all cases, λr was approximately 0.2. The error bars represent the 95% CIs. (b) For qPCR, eight reactions were performed for each assay and all ratios. The error bars represent the 95% CIs calculated from the standard error of the mean and associated T-value with 95% confidence and seven degrees-of-freedom. Key: black triangle: normal female gDNA, black diamond: significantly different from normal female gDNA (P < 0.05), gray diamond: not significantly different from normal female gDNA (P > 0.05). Solid line of linear correlation is shown for those ratios that were significantly different from normal female gDNA. Dashed line is the extrapolation of the linear correlation showing intersection with HER2:RNase P ratio of 1.0. R2 and equations are given for the linear correlation.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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gks203-F2: Determination of CNV detection of digital and quantitative real-time PCR. Quantitation of HER2:RNase P ratios using (a) dPCR and (b) qPCR generated from the in vitro gene-amplification model. The x-axis shows the expected HER2:RNase P ratio and the y-axis shows the observed HER2:RNase P ratios with the 95% CI. (a) For dPCR, four panels for each assay were analyzed for ratios > 1.5 (daggered symbol) and eight panels for each assay for ratios <1.5. In all cases, λr was approximately 0.2. The error bars represent the 95% CIs. (b) For qPCR, eight reactions were performed for each assay and all ratios. The error bars represent the 95% CIs calculated from the standard error of the mean and associated T-value with 95% confidence and seven degrees-of-freedom. Key: black triangle: normal female gDNA, black diamond: significantly different from normal female gDNA (P < 0.05), gray diamond: not significantly different from normal female gDNA (P > 0.05). Solid line of linear correlation is shown for those ratios that were significantly different from normal female gDNA. Dashed line is the extrapolation of the linear correlation showing intersection with HER2:RNase P ratio of 1.0. R2 and equations are given for the linear correlation.
Mentions: To determine the limit of detection for analysis of CNVs by dPCR, an in vitro gene-amplification model was used, whereby T-47D gDNA was spiked into normal female gDNA to generate a theoretical range of HER2:RNase P ratios between 1.00 and 2.00 at low copy number (2.1 ng/μl) for analysis using dPCR and qPCR (Supplementary Table S2). Using dPCR, a ratio of 1.17 or more was significantly different from the experimentally derived normal female gDNA ratio of 1.03 (P < 0.0003) when eight panels where used (Figure 2a). There was good linear correlation between the expected and the observed ratios when measuring a CNV of ≥1.17 (R2 = 0.9974) and this linear correlation was maintained when the line was extrapolated through the observed ratio for normal female gDNA (Figure 2a; dashed line). Furthermore, the slope and intercept of the linear correlation were measured as 1.05 and 0.05, respectively, demonstrating the accuracy in the measured ratios, and that no bias was introduced. An expected ratio of 1.12 was not significantly different from normal female gDNA when using eight panels (P = 0.67; Figure 2a). In all cases, the RNase P counts observed for each measurement were not significantly different from one another (P ≥ 0.75). Analysing the in vitro gene-amplification model with qPCR demonstrated that ratios of 1.27 or more were significantly different from normal female gDNA (P < 0.0005) and maintained a linear correlation (R2 = ≥0.99; Figure 2b; dashed line). As was observed with the dPCR analysis, the observed ratios were accurate with no introduced bias as shown by the slope (1.01) and intercept (<0.001) of the linear correlation. Ratios of ≤1.22 did not differ significantly from female gDNA (P > 0.05; Figure 2b). As with dPCR, in all cases, the RNase P counts observed for each measurement were not significantly different from one another (P ≥ 0.27). Furthermore, no statistically significant inter-run variability was observed for either the RNase P or the HER2 assays (P ≥ 0.99 and P ≥ 0.15, respectively).Figure 2.

Bottom Line: One of the benefits of Digital PCR (dPCR) is the potential for unparalleled precision enabling smaller fold change measurements.An example of an assessment that could benefit from such improved precision is the measurement of tumour-associated copy number variation (CNV) in the cell free DNA (cfDNA) fraction of patient blood plasma.Using an existing model (based on Poisson and binomial distributions) to derive an expression for the variance inherent in dPCR, we produced a power calculation to define the experimental size required to reliably detect a given fold change at a given template concentration.

View Article: PubMed Central - PubMed

Affiliation: LGC Limited, Queens Road, Teddington, Middlesex TW11 0LY, UK.

ABSTRACT
One of the benefits of Digital PCR (dPCR) is the potential for unparalleled precision enabling smaller fold change measurements. An example of an assessment that could benefit from such improved precision is the measurement of tumour-associated copy number variation (CNV) in the cell free DNA (cfDNA) fraction of patient blood plasma. To investigate the potential precision of dPCR and compare it with the established technique of quantitative PCR (qPCR), we used breast cancer cell lines to investigate HER2 gene amplification and modelled a range of different CNVs. We showed that, with equal experimental replication, dPCR could measure a smaller CNV than qPCR. As dPCR precision is directly dependent upon both the number of replicate measurements and the template concentration, we also developed a method to assist the design of dPCR experiments for measuring CNV. Using an existing model (based on Poisson and binomial distributions) to derive an expression for the variance inherent in dPCR, we produced a power calculation to define the experimental size required to reliably detect a given fold change at a given template concentration. This work will facilitate any future translation of dPCR to key diagnostic applications, such as cancer diagnostics and analysis of cfDNA.

Show MeSH
Related in: MedlinePlus