Summary
Our goal is to identify new molecular targets for drug design and improve understanding of the molecular basis of clinical behavior and therapeutic response of breast cancer (BC). Pure populations of BC cells were procured by laser capture microdissection (LCM) from deidentified tissue specimens. RNA from either LCM-procured cells or whole tissue sections was extracted, purified, and quantified by RT-qPCR using β-actin for relative quantification. RNA was amplified, Cy5-labeled, and hybridized for microarray. Spectrophotometric and BioAnalyzer™ analyses evaluated aRNA yield, purity, and transcript length for gene microarray. Unsupervised and supervised methods selected 7 000 genes with significant variation. Expression profiles of BC cells were dominated by genes associated with estrogen receptor-α (ERα) status; over 3 000 genes were identified as differentially expressed between ERα+ and ERα- BC cells. Other prominent gene expression patterns divided ERα+ BCs into subgroups, which were associated with significantly different clinical outcomes (p < 0.01). While exploiting larger gene sets derived from LCM-cells and reports using whole tissues, a preliminary 14 gene subset was selected by UniGene Cluster analysis. Additionally, ERE-binding proteins (ERE-BP) were detected by EMSA, which were not recognized by ERα antibodies. Kaplan-Meier analysis indicated that patients with ERE-BP positive BCs had lower over-all survival than those with ERE-BP negative cancers. Collectively, these results will establish molecular signatures for assessing clinical features of BC and aid in the selection of molecular targets for drug development.
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References
Wittliff JL, Erlander MG (2002) Laser capture microdissection and its applications in genomics and proteomics. Methods Enzymol 356:12–25.
Wittliff JL, Pasic R, Bland KI (1998) Steroid and Peptide Hormone Receptors: Methods, Quality Control and Clinical Use. In: Bland KI, Copeland III EM, editors. Breast: Comprehensive Management of Benign and Malignant Diseases. Philadelphia, PA: W.B. Saunders, Co., p. 458–498.
Cole KA, Krizman DB, Emmert-Buck MR (1999) The genetics of cancer – a 3D model. Nat Genet 21:38–41.
Bonner RF, Emmert-Buck M, Cole K, et al. (1997) Laser capture microdissection: molecular analysis of tissue. Science 278(5342):1481–1483.
Emmert-Buck MR, Bonner RF, Smith PD, et al. (1996) Laser capture microdissection. Science 274 (5289):998–1001.
Simone NL, Bonner RF, Gillespie JW, et al. (1998) Laser-capture microdissection: opening the microscopic frontier to molecular analysis. Trends Genet 14(7):272–276.
Wittliff JL, Kunitake ST, Chu SS, Travis JC (2000) Applications of laser capture microdissection in genomics and proteomics. J Clin Ligand Assay 23:66–73.
Ma XJ, Wang W, Salunga R, et al. (2003) Gene expression associated with clinical outcome in breast cancer via laser capture microdissection. Breast Cancer Res Treat 82(S15).
Wittliff JL, Ma XJ, Wang W, et al. (2003) Expression of estrogen receptor-associated genes in breast cancer cells procured by laser capture microdissection correlate with clinical outcome. Jensen Symposium, 81.
van’t Veer JL, Dai H, Van de Vijver MJ, et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415(6871):530–536.
Kang Y, Siegel PM, Shu W, et al. (2003) A multigenic program mediating breast cancer metastasis to bone. Cancer Cell 3(6):537–549.
Ma XJ, Salunga R, Tuggle JT, et al. (2003) Gene expression profiles of human breast cancer progression. Proc Natl Acad Sci USA 100(10):5974–5979.
Ramaswamy S, Ross KN, Lander ES, Golub TR (2003) A molecular signature of metastasis in primary solid tumors. Nat Genet 33(1):49–54.
Sorlie T, Tibshirani R, Parker J, et al. Repeated Observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 100:8418–8423.
Sotiriou C, Neo S-Y, McShane LM, et al. (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA 100:10393–10398.
Ma XJ, Wang Z, Ryan PD, et al. (2004) A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 5(6):607–616.
Jansen MPHM, Foekens JA, van Staveren IL, et al. (2005) Molecular classification of tamoxifen-resistant breast carcinomas by gene expression profiling. J Clin Oncol 23:732–740.
Wang Y, Klijn JG, Zhang Y, et al. (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365(9460):671–679.
Graumann K, Wittliff JL, Raffelsberger W, et al. (1996) Structural and functional analysis of N-terminal point mutants of the human estrogen receptor. J Steroid Biochem Mol Biol 57(5–6):293–300.
Wittliff JL, Wenz LL, Dong J, et al. (1990) Expression and characterization of an active human estrogen receptor as a ubiquitin fusion protein from Escherichia coli. J Biol Chem 265(35):22016–22022.
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Wittliff, J.L., Kruer, T.L., Andres, S.A., Smolenkova, I. (2008). Molecular Signatures of Estrogen Receptor-Associated Genes in Breast Cancer Predict Clinical Outcome. In: Li, J.J., Li, S.A., Mohla, S., Rochefort, H., Maudelonde, T. (eds) Hormonal Carcinogenesis V. Advances in Experimental Medicine and Biology, vol 617. Springer, New York, NY. https://doi.org/10.1007/978-0-387-69080-3_33
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DOI: https://doi.org/10.1007/978-0-387-69080-3_33
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