Abstract
Although techniques such as RT-PCR and in situ hybridization (ISH) can give information about gene expression, they are limited in scope as typically one gene product is evaluated with each assay. The advent of transcriptional profiling using DNA microarray has revolutionized the field of molecular medicine as measurement of thousands of genes simultaneously in a given sample provide a vast amount of data for new disease classifications and biomarker discoveries. DNA microarray-based gene expression profiling relies on nucleic acid polymers, immobilized on a solid surface, which act as probes for complementary gene sequences.1 Microarrays typically contain several thousand single-stranded DNA sequences, which are “arrayed” at specific locations on a synthetic “chip” through covalent linkage. These DNA fragments provide a matrix of probes for fluorescently labeled complementary RNA (cRNA) derived from the sample of interest. The expression of each gene in the sample is quantified by the intensity of fluorescence emitted from a specific location on the array matrix which is proportional to the amount of that gene product (Figure 10.1).2
Reprinted from Sauter G, Simon R. Predictive molecular pathology. N Engl J Med 2002;347:1995–1996. (Copyright 2002 Massachusetts Medical Society)
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References
Southern E, Mir K, Shchepinov M. Molecular interactions on microarrays. Nat Genet 1999;21:5–9.
Sauter G, Simon R. Predictive molecular pathology. N Engl J Med 2002;347:1995–1996.
Ramaswamy S, Golub TR. DNA microarrays in clinical oncology. J Clin Oncol 2002;20:1932–1941.
Cheung VG, Morley M, Aguilar F, et al. Making and reading microarrays. Nat Genet 1999;21:15–19.
Lockhart DJ, Dong H, Byrne MC, et al. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol 1996;14:1675–1680.
Goldsmith ZG, Dhanasekaran N. The microrevolution: applications and impacts of microarray technology on molecular biology and medicine (review). Int J Mol Med 2004; 13:483-495.
Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 2001;98:10869–10874.
van’t Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415: 530–536.
Wang Y, Klijn JG, Zhang Y, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 2005;365:671–679.
Rouzier R, Rajan R, Wagner P, et al. Microtubule-associated protein tau: a marker of paclitaxel sensitivity in breast cancer. Proc Natl Acad Sci USA 2005;102:8315–8320.
Chang JC, Wooten EC, Tsimelzon A, et al. Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet 2003;362:362–369.
Battifora H. The multitumor (sausage) tissue block: novel method for immunohistochemical antibody testing. Lab Invest 1986;55: 244–248.
Kononen J, Bubendorf L, Kallioniemi A, et al. Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med 1998;4:844–847.
DiVito KA, Charette LA, Rimm DL, et al. Long-term preservation of antigenicity on tissue microarrays. Lab Invest 2004;84:1071–1078.
Camp RL, Charette LA, Rimm DL. Validation of tissue microarray technology in breast carcinoma. Lab Invest 2000;80:1943–1949.
Torhorst J, Bucher C, Kononen J, et al. Tissue microarrays for rapid linking of molecular changes to clinical endpoints. Am J Pathol 2001; 159:2249–2256.
Garcia JF, Camacho FI, Morente M, et al. Hodgkin and ReedSternberg cells harbor alterations in the major tumor suppressor pathways and cell-cycle checkpoints: analyses using tissue microarrays. Blood 2003;101:681–689.
Maitra A, Adsay NV, Argani P, et al. Multicomponent analysis of the pancreatic adenocarcinoma progression model using a pancreatic intraepithelial neoplasia tissue microarray. Mod Pathol 2003; 16: 902–912.
Engellau J, Akerman M, Anderson H, et al. Tissue microarray technique in soft tissue sarcoma: immunohistochemical Ki-67 expression in malignant fibrous histiocytoma. Appl Immunohistochem Mol Morphol 2001;9:358–363.
Wang S, Saboorian MH, Frenkel EP, et al. Assessment of HER-2/ neu status in breast cancer. Automated Cellular Imaging System (ACIS)-assisted quantitation of immunohistochemical assay achieves high accuracy in comparison with fluorescence in situ hybridization assay as the standard. Am J Clin Pathol 2001;116:495–503.
Sauter G, Simon R, Hillan K. Tissue microarrays in drug discovery. Nat Rev Drug Discov 2003;2:962–972.
Camp RL, Chung GG, Rimm DL. Automated subcellular localization and quantification of protein expression in tissue microarrays. Nat Med 2002;8:1323–1327.
Camp RL, Dolled-Filhart M, King BL, et al. Quantitative analysis of breast cancer tissue microarrays shows that both high and normal levels of HER2 expression are associated with poor outcome. Cancer Res 2003;63:1445–1448.
Psyrri A, Yu Z, Weinberger PM, et al. Quantitative determination of nuclear and cytoplasmic epidermal growth factor receptor expression in oropharyngeal squamous cell cancer by using automated quantitative analysis. Clin Cancer Res 2005;11:5856–5862.
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Abu-Khalaf, M.M., Harris, L.N., Chung, G.G. (2007). DNA and Tissue Microarrays. In: Patel, H.R.H., Arya, M., Shergill, I.S. (eds) Basic Science Techniques in Clinical Practice. Springer, London. https://doi.org/10.1007/978-1-84628-740-4_10
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