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

被引:359
作者
Whale, Alexandra S. [1 ]
Huggett, Jim F. [1 ]
Cowen, Simon [1 ]
Speirs, Valerie [2 ]
Shaw, Jacqui [3 ]
Ellison, Stephen [1 ]
Foy, Carole A. [1 ]
Scott, Daniel J. [1 ]
机构
[1] LGC Ltd, Teddington TW11 0LY, Middx, England
[2] Univ Leeds, St Jamess Univ Hosp, Leeds Inst Mol Med, Leeds LS9 7TF, W Yorkshire, England
[3] Univ Leicester, Leicester Royal Infirm, Leicester LE2 7LX, Leics, England
关键词
POLYMERASE-CHAIN-REACTION; HUMAN-BREAST-CANCER; IN-SITU HYBRIDIZATION; REAL-TIME PCR; CELL-FREE DNA; GENE AMPLIFICATION; HUMAN-DISEASE; HUMAN HEALTH; QUANTIFICATION; PLASMA;
D O I
10.1093/nar/gks203
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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 tumourassociated 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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页数:9
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