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BioTechniques
Article . 2005 . Peer-reviewed
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BioTechniques
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BioTechniques
Article . 2005
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BioTechniques
Article . 2005
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Housekeeping Genes in Cancer: Normalization of Array Data

Authors: Anis H. Khimani; Abner M. Mhashilkar; Alvydas Mikulskis; Michael O'Malley; Jennifer Liao; Eva E. Golenko; Pat Mayer; +3 Authors

Housekeeping Genes in Cancer: Normalization of Array Data

Abstract

Biological maintenance of cells under variable conditions should affect gene expression of only certain genes while leaving the rest unchanged. The latter, termed "housekeeping genes," by definition must reflect no change in their expression levels during cell development, treatment, or disease state anomalies. However, deviations from this rule have been observed. Using DNA microarray technology, we report here variations in expression levels of certain housekeeping genes in prostate cancer and a colorectal cancer gene therapy model system. To highlight, differential expression was observed for ribosomal protein genes in the prostate cancer cells and beta-actin in treated colorectal cells. High-throughput differential gene expression analysis via microarray technology and quantitative PCR has become a common platform for classifying variations in similar types of cancers, response to chemotherapy, identifying disease markers, etc. Therefore, normalization of the system based on housekeeping genes, such as those reported here in cancer, must be approached with caution.

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Keywords

Male, QH301-705.5, Gene Expression Profiling, Prostatic Neoplasms, Reproducibility of Results, Sensitivity and Specificity, Neoplasm Proteins, Jurkat Cells, Cell Line, Tumor, Calibration, Biomarkers, Tumor, Humans, Biology (General), Colorectal Neoplasms, Algorithms, Oligonucleotide Array Sequence Analysis

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    52
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Top 10%
Top 10%
Top 10%
gold