Summary
Perturbations in genes play a key role in the pathogenesis of cancer. Microarray-based technology is an ideal way in which to study the effects and interactions of multiple genes in cancer. There are many technologic challenges in running a microarray study, including annotation of genes likely to be involved, designing the appropriate experiment, and ensuring adequate quality assurance steps are implemented. Once data are normalized, they need to be analyzed; and for this, there are numerous software packages and approaches.
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Abbreviations
- GO:
-
gene ontology
- RT-PCR:
-
reverse transcriptase PCR
References
Balmain, A. (2001) Cancer genetics: from boveri and mendel to microarrays. Nat. Rev. Cancer 1, 77ā82.
Watson, J. D., and Crick, F. H. (1953) Genetical implications of the structure of deoxyribonucleic acid. Nature 171, 964ā967.
Stehelin, D., Varmus, H. E., Bishop, J. M., and Vogt, P. K. (1976) DNA related to the transforming gene(s) of avian sarcoma viruses is present in normal avian DNA. Nature 260, 170ā173.
Friend, S. H., Bernards, R., Rogelj, S., Weinberg, R. A., Rapaport, J. M., Albert, D. M., et al. (1986) A human DNA segment with properties of the gene that predisposes to retinoblastoma and osteosarcoma. Nature 323, 643ā646.
Hanahan, D., and Weinberg, R. A. (2000) The Hallmarks of Cancer. Cell 100, 57ā70.
Nowell, P. C. (2002). Tumor progression: a brief historical perspective. Semin. Cancer Biol. 12, 261ā266.
Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., et al. (2001) Initial sequencing and analysis of the human genome. Nature 409, 860ā921.
International Human Genome Sequencing Consortium. (2004) Human genome sequencing, C. Finishing the euchromatic sequence of the human genome. Nature 431, 931ā945.
Pennisi, E. (2003) Bioinformatics: gene counters struggle to get the right answer. Science 301, 1040ā1041.
Stein, L. D. (2003) Integrating biological databases. Nat. Rev. Genet. 4, 337ā345.
Strausberg, R. L., Simpson, A. J. G., and Wooster, R. (2003) Sequence-based cancer genomics: progress, lessons and opportunities. Nat. Rev. Genet. 4, 409ā418.
Schena, M., Shalon, D., Davis, R. W., and Brown, P. O. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467ā470.
Fodor, S. P., Read, J. L., Pirrung, M. C., Stryer, L., Lu, A. T., and Solas, D. (1991) Light-directed, spatially addressable parallel chemical synthesis. Science 251, 767ā773.
Fodor, S. P., Rava, R. P., Huang, X. C., Pease, A. C., Holmes, C. P., and Adams, C. L. (1993) Multiplexed biochemical assays with biological chips. Nature 364, 555ā556.
Ludwig, J. A., and Weinstein, J. N. (2005) Biomarkers in cancer staging, prognosis and treatment selection. Nat. Rev. Cancer 5, 845ā856.
Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., et al. (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531ā537.
Alizadeh, A. A. (2000) Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503ā511.
Ramaswamy, S., Ross, K., Lander, E., and Golub, T. (2003) A molecular signature of metastasis in primary solid tumors. Nat. Genet. 33, 49ā54.
Rhodes, D. R., and Chinnaiyan, A. M. (2005) Integrative analysis of the cancer transcriptome. Nat. Genet. 37(Suppl), S31āS37.
Pittman, J., Huang, E., Dressman, H., Horng, C. F., Cheng, S. H., Tsou, M. H., et al. (2004). Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes. Proc. Natl. Acad. Sci. U S A 101, 8431ā8436.
Paik, S., Shak, S., Tang, G., Kim, C., Baker, J., Cronin, M., et al. (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N. Engl. J. Med. 351, 2817ā2826.
Segal, E., Friedman, N., Kaminski, N., Regev, A., and Koller, D. (2005) From signatures to models: understanding cancer using microarrays. Nat. Genet. 37(Suppl), S38āS45.
Glinsky, G. V., Berezovska, O., and Glinskii, A. B. (2005) Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple types of cancer. J. Clin. Invest. 115, 1503ā1521.
Dhanasekaran, S. M., Barrette, T. R., Ghosh, D., Shah, R., Varambally, S., Kurachi, K., et al. (2001) Delineation of prognostic biomarkers in prostate cancer. Nature 412, 822ā826.
Lapointe, J., Li, C., Higgins, J. P., van de Rijn, M., Bair, E., Montgomery, K., et al. (2004) Gene expression profiling identifies clinically relevant subtypes of prostate cancer. Proc. Natl. Acad. Sci. U S A 101, 811ā816.
Schaner, M. E., Ross, D. T., Ciaravino, G., Sorlie, T., Troyanskaya, O., Diehn, M., et al. (2003) Gene expression patterns in ovarian carcinomas. Mol. Biol. Cell 14, 4376ā4386.
Vasselli, J. R., Shih, J. H., Iyengar, S. R., Maranchie, J., Riss, J., Worrell, R., et al. (2003) Predicting survival in patients with metastatic kidney cancer by gene-expression profiling in the primary tumor. Proc. Natl. Acad. Sci. U S A 100, 6958ā6963.
Sorlie, T., Perou, C., Brown, P., Botstein, D., and Borresen-Dale, A. (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl Acad. Sci. U S A 98, 10869ā10874.
Sotiriou, C. (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc. Natl. Acad. Sci. U S A 100, 10393ā10398.
Garber, M. E. (2001) Diversity of gene expression in adenocarcinoma of the lung. Proc. Natl Acad. Sci. U S A 98, 13784ā13789.
Jones, M. H., Virtanen, C., Honjoh, D., Miyoshi, T., Satoh, Y., Okumura, S., et al. (2004) Two prognostically significant subtypes of high-grade lung neuroendocrine tumours independent of small-cell and large-cell neuroendocrine carcinomas identified by gene expression profiles. Lancet 363, 775ā781.
West, R. B., and van de Rijn, M. (2006) The role of microarray technologies in the study of soft tissue tumours. Histopathology 48, 22ā31.
Tinker, A. V., Boussioutas, A., and Bowtell, D. D. L. (2006) The challenges of gene expression microarrays for the study of human cancer. Cancer Cell 9, 333ā339.
Wadlow, R., and Ramaswamy, S. (2005) DNA microarrays in clinical cancer research. Curr. Mol. Med. 5, 111ā120.
The Tumor Analysis Best Practices Working Group. (2004) Expression profilingāBest practices for data generation and interpretation in clinical trials. Nat. Rev. Genet. 5, 229ā237.
Dai, M., Wang, P., Boyd, A. D., Kostov, G., Athey, B., Jones, E. G., et al. (2005) Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Nucleic Acids Res. 33, e175.
Diehn, M., Sherlock, G., Binkley, G., Jin, H., Matese, J. C., Hernandez-Boussard, T., et al. (2003) Source: a unified genomic resource of functional annotations, ontologies, and gene expression data. Nucleic Acids Res. 31, 219ā223.
Kent, W. J. (2002) BLATāThe BLAST-like alignment tool. Genome Res. 12, 656ā664.
Smit, A., Hubley, R., and Green, P. (1996ā2004) RepeatMasker Open 3.0. http://www.repeatmasker.org/.
Bairoch, A., Apweiler, R., Wu, C. H., Barker, W. C., Boeckmann, B., Ferro, S., et al. (2005) The Universal Protein Resource (UniProt). Nucleic Acids Res. 33, D154āD159.
Pruitt, K. D., Katz, K. S., Sicotte, H., and Maglott, D. R. (2000) Introducing RefSeq and LocusLink: curated human genome resources at the NCBI. Trends Genet. 16, 44ā47.
Wheeler, D. L., Barrett, T., Benson, D. A., Bryant, S. H., Canese, K., Chetvernin, V., et al. (2006) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 34, D173āD180.
Murray, C. G., Larsson, T. P., Hill, T., Bjorklind, R., Fredriksson, R., and Schioth, H. B. (2005) Evaluation of EST-data using the genome assembly. Biochem. Biophys. Res. Commun. 331, 1566ā1576.
Maglott, D., Ostell, J., Pruitt, K. D., and Tatusova, T. (2005) Entrez Gene: gene-centered information at NCBI. Nucleic Acids Res. 33, D54āD58.
Hamosh, A., Scott, A. F., Amberger, J. S., Bocchini, C. A., and McKusick, V. A. (2005) Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 33, D514āD517.
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., et al. (2000) Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25ā29.
Bammler, T., Beyer, R. P., Bhattacharya, S., Boorman, G. A., Boyles, A., Bradford, B. U., et al. (2005) Standardizing global gene expression analysis between laboratories and across platforms. Nat. Methods 2, 351ā356.
Larkin, J. E., Frank, B. C., Gavras, H., Sultana, R., and Quackenbush, J. (2005) Independence and reproducibility across microarray platforms. Nat. Methods 2, 337ā344.
Irizarry, R. A., Warren, D., Spencer, F., Kim, I. F., Biswal, S., Frank, B. C., et al. (2005) Multiple-laboratory comparison of microarray platforms. Nat. Methods 2, 345ā350.
Simon, R. M., and Dobbin, K. (2003) Experimental design of DNA microarray experiments. Biotechniques Suppl, 16ā21.
Kerr, M. K., and Churchill, G. A. (2001) Experimental design for gene expression microarrays. Biostatistics 2, 183ā201.
Dobbin, K., Shih, J. H., and Simon, R. (2003) Questions and answers on design of dual-label microarrays for identifying differentially expressed genes J. Natl. Cancer Inst. 95, 1362ā1369.
Cox, W. G., and Singer, V. L. (2004) Fluorescent DNA hybridization probe preparation using amine modification and reactive dye coupling. Biotechniques 36, 114ā122.
Virtanen, C., Ishikawa, Y., Honjoh, D., Kimura, M., Shimane, M., Miyoshi, T., et al. (2002) Integrated classification of lung tumors and cell lines by expression profiling. Proc. Natl. Acad. Sci. U S A 99, 12357ā12362.
Mukherjee, S., Tamayo, P., Rogers, S., Rifkin, R., Engle, A., Campbell, C., et al. (2003) Estimating dataset size requirements for classifying DNA microarray data. J. Comput. Biol. 10, 119ā142.
Tibshirani, R. (2006). A simple method for assessing sample sizes in microarray experiments. BMC Bioinformatics 7, 106.
Tsai, C.-A., Wang, S.-J., Chen, D.-T., and Chen, J. J. (2005) Sample size for gene expression microarray experiments. Bioinformatics 21, 1502ā1508.
Gentleman, R., Carey, V., Bates, D., Bolstad, B., Dettling, M., Dudoit, S., et al. (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80.
Quackenbush, J. (2002) Microarray data normalization and transformation. Nat. Genet. 32(Suppl), 496ā501.
Smyth, G. K., Yang, Y. H., and Speed, T. (2003) Statistical issues in cDNA microarray data analysis. Methods Mol. Biol. 224, 111ā136.
Weiner, A. M. (2002) SINEs and LINEs: the art of biting the hand that feeds you. Curr. Opin. Cell Biol. 14, 343ā350.
DeRisi, J., Penland, L., Brown, P. O., Bittner, M. L., Meltzer, P. S., Ray, M., et al. (1996) Use of a cDNA microarray to analyse gene expression patterns in human cancer. Nat. Genet. 14, 457ā460.
Yang, I., Chen, E., Hasseman, J., Liang, W., Frank, B., Wang, S., et al. (2002) Within the fold: assessing differential expression measures and reproducibility in microarray assays. Genome Biol. 3, R0062.
Eisen, M. B., Spellman, P. T., Brown, P. O., and Botstein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. U S A 95, 14863ā14868.
Yeung, K. Y., Haynor, D. R., and Ruzzo, W. L. (2001) Validating clustering for gene expression data. Bioinformatics 17, 309ā318.
Raychaudhuri, S., Stuart, J. M., and Altman, R. B. (2000) Principal components analysis to summarize microarray experiments: application to sporulation time series. Pac. Symp. Biocomput. 455ā466.
Cui, X., and Churchill, G. (2003) Statistical tests for differential expression in cDNA microarray experiments. Genome Biol. 4, 210.
Benjamini, Y., and Hochberg, Y. (1995) Controlling the false discover rate: a practical and powerful approach to multiple testing. J. Royal Stats. Soc. 57, 289ā300.
Tusher, V. G., Tibshirani, R., and Chu, G. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. U S A 98, 5116ā5121.
Hastie, T., Tibshirani, R., Eisen, M., Alizadeh, A., Levy, R., Staudt, L., et al. (2000) āGene shavingā as a method for identifying distinct sets of genes with similar expression patterns. Genome Biol. 1, R0003.
Rajeevan, M. S., Vernon, S. D., Taysavang, N., and Unger, E. R. (2001) Validation of Array-based gene expression profiles by real-time (Kinetic) RT-PCR. J. Mol. Diagn. 3, 26ā31.
Beissbarth, T., and Speed, T. P. (2004) GOstat: find statistically overrepresented gene ontologies within a group of genes. Bioinformatics 20, 1464ā1465.
Zhong, S., Tian, L., Li, C., Storch, K. F., and Wong, W. H. (2004) Comparative analysis of gene sets in the gene ontology space under the multiple hypothesis testing framework. Proc. IEEE. Comput. Syst. Bioinform Conf. 425ā435.
Bussey, K. J., Chin, K., Lababidi, S., Reimers, M., Reinhold, W. C., Kuo, W. L., et al. (2006) Integrating data on DNA copy number with gene expression levels and drug sensitivities in the NCI-60 cell line panel. Mol. Cancer Ther. 5, 853ā867.
Mootha, V. K., Lepage, P., Miller, K., Bunkenborg, J., Reich, M., Hjerrild, M., et al. (2003) From the cover: identification of a gene causing human cytochrome c oxidase deficiency by integrative genomics. Proc. Natl. Acad. Sci. U S A 100, 605ā610.
Segal, E., Wang, H., and Koller, D. (2003) Discovering molecular pathways from protein interaction and gene expression data. Bioinformatics 19, i264āi272.
van Noort, V., Snel, B., and Huynen, M. A. (2003) Predicting gene function by conserved co-expression. Trends Genet. 19, 238ā242.
Semon, M., and Duret, L. (2006) Evolutionary origin and maintenance of coexpressed gene clusters in mammals. Mol. Biol. Evol. 23, 1715ā1723.
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Virtanen, C., Woodgett, J. (2008). Clinical Uses of Microarrays in Cancer Research. In: Trent, R.J. (eds) Clinical Bioinformatics. Methods in Molecular Medicineā¢, vol 141. Humana Press. https://doi.org/10.1007/978-1-60327-148-6_6
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DOI: https://doi.org/10.1007/978-1-60327-148-6_6
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