Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets

Andersen, Claus Lindbjerg; Jensen, Jens Ledet; Ørntoft, Torben Falck

doi:10.1158/0008-5472.can-04-0496

Cited by 7,127Molecular Biology Techniques and ApplicationsGene expression and cancer classificationRNA Research and Splicing

Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets

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Andersen, Claus Lindbjerg, Jensen, Jens Ledet, Ørntoft, Torben Falck·2004·Cancer Research

DOI 10.1158/0008-5472.can-04-0496

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Abstract

Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single constitutively expressed control gene. However, in recent years, it has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions, implying that the expression stability of the intended control gene has to be verified before each experiment. We outline a novel, innovative, and robust strategy to identify stably expressed genes among a set of candidate normalization genes. The strategy is rooted in a mathematical model of gene expression that enables estimation not only of the overall variation of the candidate normalization genes but also of the variation between sample subgroups of the sample set. Notably, the strategy provides a direct measure for the estimated expression variation, enabling the user to evaluate the systematic error introduced when using the gene. In a side-by-side comparison with a previously published strategy, our model-based approach performed in a more robust manner and showed less sensitivity toward coregulation of the candidate normalization genes. We used the model-based strategy to identify genes suited to normalize quantitative RT-PCR data from colon cancer and bladder cancer. These genes are UBC, GAPD, and TPT1 for the colon and HSPCB, TEGT, and ATP5B…

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The geometric mean of RPL13A, RPL4 and GAPDH was used as reference genes, following GeNorm and Normfinder algorithm.
“The geometric mean of RPL13A, RPL4 and GAPDH was taken as reference genes, following GeNorm and Normfinder algorithm [18, 19].”
From Identification of a novel gene signature predicting response to first-line chemotherapy in BRCA wild-type high-grade serous ovarian cancer patients (2022) · cites this paper as [19]
miR-1246 and miR-374b-5p were empirically selected as the two endogenous reference genes based on the NormFinder algorithm.
“The two endogenous references, miR-1246 and miR-374b-5p, were empirically selected based on the NormFinder algorithm (Fig. 2).”
From Intra- and Inter-individual Variability of microRNA Levels in Human Cerebrospinal Fluid: Critical Implications for Biomarker Discovery (2017) · cites this paper as [31]

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“Based on the rankings by the three software tools, BestKeeper, geNorm and NormFinder, only one of the candidate reference genes, pak2b, showed consistent stability, i.e. always ranked among top two most stable reference genes (Table 2).”
Method

Authors: Andersen, C. L., Jensen, J. L., & Ørntoft, T. F.
Affiliations: Aarhus University Hospital (DK)
Aarhus University (DK)
1Molecular Diagnostic Laboratory, Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus N, Denmark, and
ORCID: Andersen, Claus Lindbjerg
Jensen, Jens Ledet
Venue: Cancer Research
Publisher: American Association for Cancer Research (AACR)
Published: 2004-08-01
Volume: 64
Issue: 15
Pages: 5245-5250
ISSN: 0008-5472 (ISSN-L)
1538-7445
DOI: 10.1158/0008-5472.can-04-0496
OpenAlex: W2105423509
Cited by: 7,127
References: 2
Citations by year: 2026: 210 · 2025: 325 · 2024: 390 · 2023: 390 · 2022: 477 · 2021: 524 · 2020: 533 · 2019: 522 · 2018: 522 · 2017: 525 · 2016: 500 · 2015: 452 · 2014: 427 · 2013: 339 · 2012: 290
FWCI: 8.70
Type: journal article
Language: en
Open access: green
cancerres.aacrjournals.org
Locations: Cancer Research (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords: normalization, quantitative real-time RT-PCR, gene expression stability, bladder cancer, colon cancer, glyceraldehyde-3-phosphate dehydrogenase, UBC, TPT1, ATP5B
MeSH terms: Tumor Protein, Translationally-Controlled 1, Urinary Bladder, Urinary Bladder Neoplasms, Colon, Colonic Neoplasms, Gene Expression Regulation, Humans, Models, Theoretical, Neoplasm Proteins, Reference Standards, RNA, Messenger, Sensitivity and Specificity, Biomarkers, Tumor, Reproducibility of Results, Reverse Transcriptase Polymerase Chain Reaction, Gene Expression Profiling

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Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets

Abstract

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