Modeling qRT-PCR dynamics with application to cancer biomarker quantification

Statistical Methods in Medical Research
Inna ChervonevaScott A Waldman

Abstract

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is widely used for molecular diagnostics and evaluating prognosis in cancer. The utility of mRNA expression biomarkers relies heavily on the accuracy and precision of quantification, which is still challenging for low abundance transcripts. The critical step for quantification is accurate estimation of efficiency needed for computing a relative qRT-PCR expression. We propose a new approach to estimating qRT-PCR efficiency based on modeling dynamics of polymerase chain reaction amplification. In contrast, only models for fluorescence intensity as a function of polymerase chain reaction cycle have been used so far for quantification. The dynamics of qRT-PCR efficiency is modeled using an ordinary differential equation model, and the fitted ordinary differential equation model is used to obtain effective polymerase chain reaction efficiency estimates needed for efficiency-adjusted quantification. The proposed new qRT-PCR efficiency estimates were used to quantify GUCY2C (Guanylate Cyclase 2C) mRNA expression in the blood of colorectal cancer patients. Time to recurrence and GUCY2C expression ratios were analyzed in a joint model for survival and longitudinal ou...Continue Reading

References

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Apr 6, 2005·Journal of Theoretical Biology·Holger DetteNikolay Strigul
Oct 31, 2007·Statistics in Medicine·Inna ChervonevaTerry Hyslop
May 1, 2008·BMC Bioinformatics·Andrej-Nikolai SpiessChristian Ritz
Feb 20, 2009·JAMA : the Journal of the American Medical Association·Scott A WaldmanDavid S Weinberg
May 18, 2010·BMC Bioinformatics·Inna ChervonevaTerry Hyslop

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Methods Mentioned

BETA
PCR

Software Mentioned

R
R package
R package qpcR
R package ‘ fda ’
qpcR

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