Abstract
Human cancers are diverse in their pathology and responsiveness to clinical treatment. This diversity is at least in part due to variations in cellular gene expression programs. Although the analyis of proteins - the key players in cells and potential drug targets - is advancing rapidly, there are situations in which the analysis of RNA rather than proteins can provide valuable information for the diagnosis of cancer. These situations include absense of an antibody for the protein of interest, expression of functionally defective proteins, expressed small nucleotide polymorphisms (SNPs), analysis of alternatively or abnormally spliced molecules, and functional analysis of splice site mutations. In this chapter we will focus on the analysis of RNA from clinical samples and will summarize how gene expression studies on the RNA level using a variety of new tools can be useful for discovering new classes of tumors, for predicting clinical outcome or therapy response, and for designing novel personalized clinical interventions that can not be achieved with histology alone.
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References
Lodish et al. Molecular Cell Biology, 4th Edition, Freeman and Company New York 2000
Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, Powell JI, Yang L, Marti GE, Moore T, Hudson J Jr, Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Staudt LM, et al.: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000 Feb 3;403(6769):503–11
Scherf U, Ross DT, Waltham M, Smith LH, Lee JK, Tanabe L, Kohn KW, Reinhold WC, Myers TG, Andrews DT, Scudiero DA, Eisen MB, Sausville EA, Pommier Y, Botstein D, Brown PO, Weinstein JN. A gene expression database for the molecular pharmacology of cancer. Nat Genet. 2000 Mar;24(3):236–44
Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Eystein Lonning P, BorresenDale AL. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001 Sep 11;98(19):10869–74
van ‘t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, Schreiber GJ, Kerkhoven RM, Roberts C, Linsley PS, Bernards R, Friend SH. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002 Jan 31;415(6871):530–6.
Sidransky D. Nucleic acid-based methods for the detection of cancer. Science. 1997 Nov 7;278(5340):1054–9.
Best CJ, Emmert-Buck MR. Molecular profiling of tissue samples using laser capture microdissection. Expert Rev Mol Diagn. 2001 May;1(1):53–60
Schutze K, Posl H, Lahr G. Laser micromanipulation systems as universal tools in cellular and molecular biology and in medicine. Cell Mol Biol (Noisy-le-grand). 1998 Jul;44(5):735–46
Specht K, Richter T, Muller U, Walch A, Werner M, Höfler H: Quantitative Gene Expression Analysis in Microdissected Archival Formalin-Fixed and Paraffin-Embedded Tumor Tissue. Am. J. Pathol. (2001) 158 (2): 419–429
Rosivatz E, Becker I, Specht K, Fricke E, Luber B, Busch R, Hofler H, Becker KF. Differential Expression of the Epithelial-Mesenchymal Transition Regulators Snail, SIP1, and Twist in Gastric Cancer. Am J Pathol. 2002 Nov;161(5):1881–91.
Vecsey-Semjen B, Becker KF, Sinski A, Blennow E, Vietor I, Zatloukal K, Beug H, Wagner E, Huber LA. Novel colon cancer cell lines leading to better understanding of the diversity of respective primary cancers. Oncogene. 2002 Jul 11;21(30):4646–62
Nakagawa H, Yan H, Lockman J, Hampel H, Kinzler KW, Vogelstein B, De La Chapelle A. Allele separation facilitates interpretation of potential splicing alterations and genomic rearrangements. Cancer Res. 2002 Aug 15;62(16):4579–82
Becker KF, Atkinson MJ, Reich U, Becker I, Nekarda H, Siewert JR, Hofler H. E-cadherin gene mutations provide clues to diffuse type gastric carcinomas. Cancer Res. 1994 Jul 15;54(14):3845–52
Becker KF, Reich U, Schott C, Becker I, Berx G, van Roy F, Hofler H. Identification of eleven novel tumor-associated E-cadherin mutations. Mutations in brief no. 215. Online. Hum Mutat. 1999;13(2):171
Becker KF, Krenuner E, Eulitz M, Schulz S, Mages J, Handschuh G, Wheelock MJ, Cleton-Jansen AM, Hofler H, Becker I. Functional allelic loss detected at the protein level in archival human tumours using allele-specific E-cadherin monoclonal antibodies. J Pathol. 2002 Aug;197(5):567–74
Schuhmacher C, Becker KF, Reich U, Schenk U, Mueller J, Siewert JR, Hofler H. Rapid detection of mutated E-cadherin in peritoneal lavage specimens from patients with diffuse-type gastric carcinoma. Diagn Mol Pathol. 1999 Jun;8(2):66–70.
Yan H, Dobbie Z, Gruber SB, Markowitz S, Romans K, Giardiello FM, Kinzler KW, Vogelstein B. Small changes in expression affect predisposition to tumorigenesis. Nat Genet. 2002 Jan;30(1):25–6
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Höfler, H., Specht, K., Becker, KF. (2003). Molecular Analysis of Gene Expression in Tumor Pathology. In: Llombart-Bosch, A., Felipo, V. (eds) New Trends in Cancer for the 21st Century. Advances in Experimental Medicine and Biology, vol 532. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0081-0_3
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DOI: https://doi.org/10.1007/978-1-4615-0081-0_3
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