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Journal of Biomedicine and Biotechnology
Volume 2012 (2012), Article ID 797812, 16 pages
Inference of Tumor Phylogenies from Genomic Assays on Heterogeneous Samples
1Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
2Intelligent Oncotherapeutics, Pittsburgh, PA 15243, USA
3Department of Biological Sciences and Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Received 2 November 2011; Accepted 21 February 2012
Academic Editor: Ali Khraibi
Copyright © 2012 Ayshwarya Subramanian et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- C. M. Perou, T. Sørile, M. B. Eisen et al., “Molecular portraits of human breast tumours,” Nature, vol. 406, no. 6797, pp. 747–752, 2000.
- T. R. Golub, D. K. Slonim, P. Tamayo et al., “Molecular classification of cancer: class discovery and class prediction by gene expression monitoring,” Science, vol. 286, no. 5439, pp. 531–527, 1999.
- C. Sotiriou, S. Y. Neo, L. M. McShane et al., “Breast cancer classification and prognosis based on gene expression profiles from a population-based study,” Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 18, pp. 10393–10398, 2003.
- T. Sørlie, C. M. Perou, R. Tibshirani et al., “Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications,” Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 19, pp. 10869–10874, 2001.
- D. T. Ross, U. Scherf, M. B. Eisen et al., “Systematic variation in gene expression patterns in human cancer cell lines,” Nature Genetics, vol. 24, no. 3, pp. 227–235, 2000.
- M. D. Pegram, G. Konecny, and D. J. Slamon, “The molecular and cellular biology of HER2/neu gene amplification/overexpression and the clinical development of herceptin (trastuzumab) therapy for breast cancer,” Cancer Treatment and Research, vol. 103, pp. 57–75, 2000.
- A. Kamb, S. Wee, and C. Lengauer, “Why is cancer drug discovery so difficult?” Nature Reviews Drug Discovery, vol. 6, no. 2, pp. 115–120, 2007.
- I. Bozic, T. Antal, H. Ohtsuki et al., “Accumulation of driver and passenger mutations during tumor progression,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 43, pp. 18545–18550, 2010.
- C. A. Smith, A. A. Pollice, L. P. Gu et al., “Correlations among p53, Her-2/neu, and ras overexpression and aneuploidy by multiparameter flow cytometry in human breast cancer: evidence for a common phenotypic evolutionary pattern in infiltrating ductal carcinomas,” Clinical Cancer Research, vol. 6, no. 1, pp. 112–126, 2000.
- R. Desper, F. Jiang, O. P. Kallioniemi, H. Moch, C. H. Papadimitriou, and A. A. Schäffer, “Inferring tree models for oncogenesis from comparative genome hybridization data,” Journal of Computational Biology, vol. 6, no. 1, pp. 37–51, 1999.
- R. Schwartz and S. E. Shackney, “Applying unmixing to gene expression data for tumor phylogeny inference,” BMC Bioinformatics, vol. 11, article no. 42, 2010.
- G. Pennington, C. A. Smith, S. Shackney, and R. Schwartz, “Reconstructing tumor phylogenies from heterogeneous single-cell data.,” Journal of Bioinformatics and Computational Biology, vol. 3, no. 2, pp. 407–427, 2007.
- G. Pennington, C. A. Smith, S. Shackney, and R. Schwartz, “Expectation-maximization method for reconstructing tumor phylogenies from single-cell data,” in Computational Systems Bioinformatics Conference (CSB '06), pp. 371–380, 2006.
- N. Navin, A. Krasnitz, L. Rodgers et al., “Inferring tumor progression from genomic heterogeneity,” Genome Research, vol. 20, no. 1, pp. 68–80, 2010.
- R. Etzioni, S. Hawley, D. Billheimer, L. D. True, and B. Knudsen, “Analyzing patterns of staining in immunohistochemical studies: application to a study of prostate cancer recurrence,” Cancer Epidemiology Biomarkers and Prevention, vol. 14, no. 5, pp. 1040–1046, 2005.
- N. Beerenwinkel, M. Däumer, T. Sing et al., “Estimating HIV evolutionary pathways and the genetic barrier to drug resistance,” Journal of Infectious Diseases, vol. 191, no. 11, pp. 1953–1960, 2005.
- D. Tolliver, C. Tsourakakis, A. Subramanian, S. Shackney, and R. Schwartz, “Robust unmixing of tumor states in array comparative genomic hybridization data,” Bioinformatics, vol. 26, no. 12, pp. i106–i114, 2010.
- R. Ehrlich and W. Full, “Sorting out geology—unmixing mixtures,” in Use and Abuse of Statistical Methods in the Earth Sciences, pp. 33–46, Oxford University Press, 1987.
- D. D. Lee and H. S. Seung, “Learning the parts of objects by non-negative matrix factorization,” Nature, vol. 401, no. 6755, pp. 788–791, 1999.
- A. W. F. Edwards and C. L. L. Sforza, “The reconstruction of evolution,” Heredity, vol. 18, 1963.
- D. L. Swofford, PAUP*. Phylogenetic Analysis Using Parsimony (*and other methods), Version 4. Sinauer Associates, Sunderland, Mass, USA, 2003.
- J. Ellson, E. Gansner, L. Koutsofios, S. North, and G. Woodhull, “Graphviz— open source graph drawing tools,” in Graph Drawing, P. Mutzel, M. Jünger, and S. Leipert, Eds., vol. 2265 of Lecture Notes in Computer Science, pp. 594–597, Springer, Berlin, Germany, 2002.
- W. James Kent, C. W. Sugnet, T. S. Furey et al., “The human genome browser at UCSC,” Genome Research, vol. 12, no. 6, pp. 996–1006, 2002.
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University (Baltimore, MD) and National Center for Biotechnology Information, National Library of Medicine (Bethesda, MD). Online Mendelian Inheritance in Man, OMIM (tm), 2010, http://www.ncbi.nlm.nih.gov/omim/.
- J. R. Pollack, T. Sørlie, C. M. Perou et al., “Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors,” Proceedings of the National Academy of Sciences of the United States of America, vol. 99, no. 20, pp. 12963–12968, 2002.
- C. D. Bajdik, B. Kuo, S. Rusaw, S. Jones, and A. Brooks-Wilson, “CGMIM: automated text-mining of Online Mendelian Inheritance in Man (OMIM) to identify genetically-associated cancers and candidate genes,” BMC Bioinformatics, vol. 6, article no. 78, 2005.
- N. Navin, J. Kendall, J. Troge et al., “Tumour evolution inferred by single-cell sequencing,” Nature, vol. 472, no. 7341, pp. 90–95, 2011.
- J. S. Ross and J. A. Fletcher, “The HER-2/neu oncogene in breast cancer: prognostic factor, predictive factor, and target for therapy,” Stem Cells, vol. 16, no. 6, pp. 413–428, 1998.
- S. Saito, K. Morita, and T. Hirano, “High frequency of common DNA copy number abnormalities detected by bacterial artificial chromosome array comparative genomic hybridization in 24 breast cancer cell lines,” Human Cell, vol. 22, no. 1, pp. 1–10, 2009.
- I. Bièche and R. Lidereau, “Genome-based and transcriptome-based molecular classification of breast cancer,” Current Opinion in Oncology, vol. 23, no. 1, pp. 93–99, 2011.
- K. Mu, L. Li, Q. Yang et al., “Detection of CHK1 and CCND1 gene copy number changes in breast cancer with dual-colour fluorescence in-situ hybridization,” Histopathology, vol. 58, no. 4, pp. 601–607, 2011.
- B. M. Zaharieva, R. Simon, P. A. Diener et al., “High-throughput tissue microarray analysis of 11qI3 gene amplification (CCND1, FGF3, FGF4, EMS1) in urinary bladder cancer,” Journal of Pathology, vol. 201, no. 4, pp. 603–608, 2003.
- E. Schuuring, E. Verhoeven, W. J. Mooi, and R. J. A. M. Michalides, “Identification and cloning of two overexpressed genes, U21B31/PRAD1 and EMS1, within the amplified chromosome 11q13 region in human carcinomas,” Oncogene, vol. 7, no. 2, pp. 355–361, 1992.
- S. M. Aukema, R. Siebert, E. Schuuring et al., “Double-hit B-cell lymphomas,” Blood, vol. 117, no. 8, pp. 2319–2331, 2011.
- H. R. Park, S. K. Min, H. D. Cho, D. H. Kim, H. S. Shin, and Y. E. Park, “Expression of Osteoprotegerin and RANK Ligand in Breast Cancer Bone Metastasis,” Journal of Korean Medical Science, vol. 18, no. 4, pp. 541–546, 2003.
- D. H. Jones, T. Nakashima, O. H. Sanchez et al., “Regulation of cancer cell migration and bone metastasis by RANKL,” Nature, vol. 440, no. 7084, pp. 692–696, 2006.
- A. M. Sieuwerts, M. P. Look, M. E. Meijer-Van Gelder et al., “Which cyclin E prevails as prognostic marker for breast cancer? Results from a retrospective study involving 635 lymph node-negative breast cancer patients,” Clinical Cancer Research, vol. 12, no. 11, pp. 3319–3328, 2006.
- C. Sotiriou, M. Paesmans, A. Harris, et al., “Cyclin E1 (CCNE1) and E2 (CCNE2) as prognostic and predictive markers for endocrine therapy (ET) in early breast cancer,” Journal of Clinical Oncology, vol. 22, no. 14S, 2004.
- R. Agarwal, A. M. Gonzalez-Angulo, S. Myhre et al., “Integrative analysis of cyclin protein levels identifies cyclin B1 as a classifier and predictor of outcomes in breast cancer,” Clinical Cancer Research, vol. 15, no. 11, pp. 3654–3662, 2009.
- C. B. Moelans, R. A. De Weger, H. N. Monsuur, R. Vijzelaar, and P. J. Van Diest, “Molecular profiling of invasive breast cancer by multiplex ligation-dependent probe amplification-based copy number analysis of tumor suppressor and oncogenes,” Modern Pathology, vol. 23, no. 7, pp. 1029–1039, 2010.
- K. T. Hwang, W. Han, J. Cho et al., “Genomic copy number alterations as predictive markers of systemic recurrence in breast cancer,” International Journal of Cancer, vol. 123, no. 8, pp. 1807–1815, 2008.
- R. Nahta, D. Yu, M. C. Hung, G. N. Hortobagyi, and F. J. Esteva, “Mechanisms of disease: Understanding resistance to HER2-targeted therapy in human breast cancer,” Nature Clinical Practice Oncology, vol. 3, no. 5, pp. 269–280, 2006.
- F. Toledo and G. M. Wahl, “MDM2 and MDM4: p53 regulators as targets in anticancer therapy,” International Journal of Biochemistry and Cell Biology, vol. 39, no. 7-8, pp. 1476–1482, 2007.
- P. van der Lelij, K. H. Chrzanowska, B. C. Godthelp et al., “Warsaw breakage syndrome, a cohesinopathy associated with mutations in the XPD helicase family member DDX11/ChlR1,” American Journal of Human Genetics, vol. 86, no. 2, pp. 262–266, 2010.
- R. Venkatachalam, E. T. P. Verwiel, E. J. Kamping et al., “Identification of candidate predisposing copy number variants in familial and early-onset colorectal cancer patients,” International Journal of Cancer, vol. 129, no. 7, pp. 1635–1642, 2011.
- C. Walowsky, D. J. Fitzhugh, I. B. Castaño, J. Y. Ju, N. A. Levin, and M. F. Christman, “The topoisomerase-related function gene TRF4 affects cellular sensitivity to the antitumor agent camptothecin,” Journal of Biological Chemistry, vol. 274, no. 11, pp. 7302–7308, 1999.
- A. M. Brown, “Wnt signaling in breast cancer: have we come full circle?” Breast Cancer Research, vol. 3, no. 6, pp. 351–355, 2001.
- F. Forozan, E. H. Mahlamäki, O. Monni et al., “Comparative genomic hybridization analysis of 38 breast cancer cell lines: a basis for interpreting complementary DNA microarray data,” Cancer Research, vol. 60, no. 16, pp. 4519–4525, 2000.
- L. E. Janocko, K. A. Brown, C. A. Smith et al., “Distinctive patterns of Her-2/Neu, c-myc, and cyclin D1 gene amplification by fluorescence in situ hybridization in primary human breast cancers,” Communications in Clinical Cytometry, vol. 46, no. 3, pp. 136–149, 2001.
- K. Al-Kuraya, P. Schraml, J. Torhorst et al., “Prognostic relevance of gene amplifications and coamplifications in breast cancer,” Cancer Research, vol. 64, no. 23, pp. 8534–8540, 2004.
- E. A. Mittendorf, Y. Liu, S. L. Tucker et al., “A novel interaction between HER2/neu and cyclin e in breast cancer,” Oncogene, vol. 29, no. 27, pp. 3896–3907, 2010.
- M. Scaltriti, P. J. Eichhorn, J. Cortés et al., “Cyclin E amplification/overexpression is a mechanism of trastuzumab resistance in HER2+ breast cancer patients,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 9, pp. 3761–3766, 2011.
- D. Wangsa, K. Heselmeyer-Haddad, P. Ried et al., “Fluorescence in situ hybridization markers for prediction of cervical lymph node metastases,” American Journal of Pathology, vol. 175, no. 6, pp. 2637–2645, 2009.