1. Reverse transcription-quantitative polymerase chain reaction: description of a RIN-based algorithm for accurate data normalization
- Author
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Marc Ychou, Florence Boissière-Michot, Evelyne Lopez-Crapez, Frédéric Bibeau, Dominic Cellier, Alexandre Ho-Pun-Cheung, Eric Assenat, Caroline Bascoul-Mollevi, Merck Santé - Lyon, Merck & Co. Inc, Département d'oncologie Médicale, CRLCC Val d'Aurelle - Paul Lamarque, Institut de recherche en cancérologie de Montpellier (IRCM - U896 Inserm - UM1), CRLCC Val d'Aurelle - Paul Lamarque-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Montpellier 1 (UM1), Laboratoire d'anatomo-pathologie, Université Montpellier 1 (UM1)-CRLCC Val d'Aurelle - Paul Lamarque-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), and Le Ster, Yves
- Subjects
[SDV.BIO]Life Sciences [q-bio]/Biotechnology ,Biopsy ,RNA Stability ,Statistics as Topic ,MESH: Biopsy ,0302 clinical medicine ,MESH: Reverse Transcriptase Polymerase Chain Reaction ,Gene expression ,[INFO.INFO-BT]Computer Science [cs]/Biotechnology ,0303 health sciences ,lcsh:Cytology ,Reverse Transcriptase Polymerase Chain Reaction ,Methodology Article ,MESH: RNA Stability ,MESH: Gene Expression Regulation ,3. Good health ,MESH: Reproducibility of Results ,Real-time polymerase chain reaction ,030220 oncology & carcinogenesis ,Colonic Neoplasms ,[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Algorithm ,Algorithms ,Normalization (statistics) ,MESH: Cell Line, Tumor ,lcsh:QH426-470 ,MESH: HCT116 Cells ,Breast Neoplasms ,MESH: Algorithms ,Biology ,Database normalization ,03 medical and health sciences ,Cell Line, Tumor ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Humans ,lcsh:QH573-671 ,Molecular Biology ,MESH: Statistics as Topic ,030304 developmental biology ,MESH: Colonic Neoplasms ,Messenger RNA ,MESH: Humans ,Rectal Neoplasms ,Reproducibility of Results ,MESH: Rectal Neoplasms ,RNA ,HCT116 Cells ,Reverse transcriptase ,[SDV.BIO] Life Sciences [q-bio]/Biotechnology ,lcsh:Genetics ,[INFO.INFO-BT] Computer Science [cs]/Biotechnology ,Gene Expression Regulation ,MESH: Breast Neoplasms - Abstract
Background Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the gold standard technique for mRNA quantification, but appropriate normalization is required to obtain reliable data. Normalization to accurately quantitated RNA has been proposed as the most reliable method for in vivo biopsies. However, this approach does not correct differences in RNA integrity. Results In this study, we evaluated the effect of RNA degradation on the quantification of the relative expression of nine genes (18S, ACTB, ATUB, B2M, GAPDH, HPRT, POLR2L, PSMB6 and RPLP0) that cover a wide expression spectrum. Our results show that RNA degradation could introduce up to 100% error in gene expression measurements when RT-qPCR data were normalized to total RNA. To achieve greater resolution of small differences in transcript levels in degraded samples, we improved this normalization method by developing a corrective algorithm that compensates for the loss of RNA integrity. This approach allowed us to achieve higher accuracy, since the average error for quantitative measurements was reduced to 8%. Finally, we applied our normalization strategy to the quantification of EGFR, HER2 and HER3 in 104 rectal cancer biopsies. Taken together, our data show that normalization of gene expression measurements by taking into account also RNA degradation allows much more reliable sample comparison. Conclusion We developed a new normalization method of RT-qPCR data that compensates for loss of RNA integrity and therefore allows accurate gene expression quantification in human biopsies.
- Published
- 2009
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