A new method for gene discovery in large-scale microarray data

Microarrays are an effective tool for monitoring genome-wide gene expression levels. In current microarray analyses, the majority of genes on arrays are frequently eliminated for further analysis because the changes in their expression levels (ratios) are considered to be not significant. This strategy risks failure to discover whole sets of genes related to a quantitative trait of interest, which is generally controlled by several loci that make various contributions. Here, we describe a high-throughput gene discovery method based on correspondence analysis with a new index for expression ratios [arctan (1/ratio)] and three artificial marker genes. This method allows us to quickly analyze the whole microarray dataset and discover up-/down-regulated genes related to a trait of interest. We employed an example dataset to show the theoretical advantage of this method. We then used the method to identify 88 cancer-related genes from a published microarray data from patients with breast cancer. This method also allows us to predict the phenotype of a given sample from the gene expression profile. This method can be easily performed and the result is also visible in 3D viewing software that we have developed.

[1]  R. Kiyama,et al.  Transcription factor EGR3 is involved in the estrogen-signaling pathway in breast cancer cells. , 2004, Journal of molecular endocrinology.

[2]  Adrian V. Lee,et al.  Structure-function analysis of the estrogen receptor alpha corepressor scaffold attachment factor-B1: identification of a potent transcriptional repression domain. , 2004, The Journal of biological chemistry.

[3]  H. Grüneberg,et al.  Introduction to quantitative genetics , 1960 .

[4]  西里 静彦,et al.  Analysis of categorical data : dual scaling and its applications , 1980 .

[5]  Michael Karin,et al.  NF-kappaB in cancer: from innocent bystander to major culprit. , 2002, Nature reviews. Cancer.

[6]  B. O’Malley,et al.  Reduction of coactivator expression by antisense oligodeoxynucleotides inhibits ERalpha transcriptional activity and MCF-7 proliferation. , 2002, Molecular endocrinology.

[7]  R. Spielman,et al.  Natural variation in human gene expression assessed in lymphoblastoid cells , 2003, Nature Genetics.

[8]  Jerry Li,et al.  Within the fold: assessing differential expression measures and reproducibility in microarray assays , 2002, Genome Biology.

[9]  M. Hirai,et al.  Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Bing Zhang,et al.  GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies , 2004, BMC Bioinformatics.

[11]  W. Schiemann,et al.  The use of cystatin C to inhibit epithelial–mesenchymal transition and morphological transformation stimulated by transforming growth factor-β , 2005, Breast Cancer Research.

[12]  E. Schmidt,et al.  IKKα Provides an Essential Link between RANK Signaling and Cyclin D1 Expression during Mammary Gland Development , 2001, Cell.

[13]  M. Widschwendter,et al.  DNA methylation in serum of breast cancer patients: an independent prognostic marker. , 2003, Cancer research.

[14]  T. Poggio,et al.  Prediction of central nervous system embryonal tumour outcome based on gene expression , 2002, Nature.

[15]  J. Hoheisel,et al.  Correspondence analysis applied to microarray data , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[16]  F. Sigaux,et al.  Transgenic mice for MTCP1 develop T-cell prolymphocytic leukemia. , 1998, Blood.

[17]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[18]  S. Sugano,et al.  Large-scale identification and characterization of human genes that activate NF-kappaB and MAPK signaling pathways. , 2003, Oncogene.

[19]  Honglin Zhou,et al.  Bcl10 activates the NF-kappaB pathway through ubiquitination of NEMO. , 2004, Nature.

[20]  F. Latif,et al.  Role of the Ras-association domain family 1 tumor suppressor gene in human cancers. , 2005, Cancer research.

[21]  G. M. Southward,et al.  Analysis of Categorical Data: Dual Scaling and Its Applications , 1981 .

[22]  Honglin Zhou,et al.  Bcl10 activates the NF-κB pathway through ubiquitination of NEMO , 2004, Nature.

[23]  S. Falkow,et al.  Distinct gene expression profiles characterize the histopathological stages of disease in Helicobacter-induced mucosa-associated lymphoid tissue lymphoma , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[24]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[25]  T. Zhu,et al.  Finding Unexpected Patterns in Microarray Data1 , 2003, Plant Physiology.

[26]  C. Sherr.  Cancer Cell Cycles , 1996, Science.

[27]  P. Brown,et al.  Gene expression patterns in human embryonic stem cells and human pluripotent germ cell tumors , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[28]  C. Perou,et al.  A custom microarray platform for analysis of microRNA gene expression , 2004, Nature Methods.

[29]  J. Russo,et al.  Activation of NF-kappaB/Rel occurs early during neoplastic transformation of mammary cells. , 2000, Carcinogenesis.

[30]  Carlos S. Moreno,et al.  MTA3, a Mi-2/NuRD Complex Subunit, Regulates an Invasive Growth Pathway in Breast Cancer , 2003, Cell.

[31]  Nan Li,et al.  Cyclin L2, a Novel RNA Polymerase II-associated Cyclin, Is Involved in Pre-mRNA Splicing and Induces Apoptosis of Human Hepatocellular Carcinoma Cells* , 2004, Journal of Biological Chemistry.

[32]  Michael Karin,et al.  NF-κB in cancer: from innocent bystander to major culprit , 2002, Nature Reviews Cancer.

[33]  Lucila Ohno-Machado,et al.  Analysis of matched mRNA measurements from two different microarray technologies , 2002, Bioinform..

[34]  Yudong D. He,et al.  Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer , 2001, Nature Biotechnology.

[35]  P. Duncombe,et al.  Multivariate Descriptive Statistical Analysis: Correspondence Analysis and Related Techniques for Large Matrices , 1985 .

[36]  M. Greenacre.  Correspondence analysis in practice , 1993 .

[37]  F. Sigaux,et al.  MTCP-1: a novel gene on the human chromosome Xq28 translocated to the T cell receptor alpha/delta locus in mature T cell proliferations. , 1993, Oncogene.

[38]  H. Nakano,et al.  Multiple Pathways of TWEAK-Induced Cell Death1 , 2002, The Journal of Immunology.

[39]  B. Zhang,et al.  Molecular cloning of a novel human gene encoding histone acetyltransferase-like protein involved in transcriptional activation of hTERT. , 2003, Biochemical and biophysical research communications.

[40]  Matthew A. Zapala,et al.  Elevated gene expression levels distinguish human from non-human primate brains , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Silvio Bicciato,et al.  Prediction of in vivo synergistic activity of antiangiogenic compounds by gene expression profiling. , 2002, Cancer research.

[42]  D. Louis,et al.  A transcript map of the chromosome 19q-arm glioma tumor suppressor region. , 2000, Genomics.

[43]  Barrett C. Foat,et al.  Identification of genes expressed in C. elegans touch receptor neurons , 2002, Nature.

[44]  D. Landsittel,et al.  Expression of myopodin induces suppression of tumor growth and metastasis. , 2003, The American journal of pathology.

[45]  Y. Nomura,et al.  Activation signal of nuclear factor-kappa B in response to endoplasmic reticulum stress is transduced via IRE1 and tumor necrosis factor receptor-associated factor 2. , 2003, Biological & pharmaceutical bulletin.

[46]  H Kishino,et al.  Correspondence analysis of genes and tissue types and finding genetic links from microarray data. , 2000, Genome informatics. Workshop on Genome Informatics.

[47]  Partha S. Vasisht.  Computational Analysis of Microarray Data , 2003 .

[48]  Janet Rossant,et al.  Gene expression profiling of embryo-derived stem cells reveals candidate genes associated with pluripotency and lineage specificity. , 2002, Genome research.

[49]  Ash A. Alizadeh,et al.  Individuality and variation in gene expression patterns in human blood , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[50]  C. Schmitt.  Senescence, apoptosis and therapy — cutting the lifelines of cancer , 2003, Nature Reviews Cancer.

[51]  J. Juang,et al.  Involvement of Cdk5/p25 in Digoxin-triggered Prostate Cancer Cell Apoptosis* , 2004, Journal of Biological Chemistry.

[52]  T. Okamoto,et al.  RNA helicase A interacts with nuclear factor kappaB p65 and functions as a transcriptional coactivator. , 2004, European journal of biochemistry.

[53]  E. Schmidt,et al.  IKKalpha provides an essential link between RANK signaling and cyclin D1 expression during mammary gland development. , 2001, Cell.