Relational Analysis of CpG Islands Methylation and Gene Expression in Human Lymphomas Using Possibilistic C-Means Clustering and Modified Cluster Fuzzy Density
Authors: 
Ozy Sjahputera, James M. Keller, J. Wade Davis, Kristen H. Taylor, Farahnaz Rahmatpanah, Huidong Shi, Derek T. Anderson, Samuel N. Blisard, Robert H. Luke, Mihail Popescu, Gerald C. Arthur, Charles W. CaldwellAuthors Info & Claims
Pages 176 - 189
Abstract
Heterogeneous genetic and epigenetic alterations are commonly found in human non-Hodgkin's lymphomas (NHL). One such epigenetic alteration is aberrant methylation of gene promoter-related CpG islands, where hypermethylation frequently results in transcriptional inactivation of target genes, while a decrease or loss of promoter methylation (hypomethylation) is frequently associated with transcriptional activation. Discovering genes with these relationships in NHL or other types of cancers could lead to a better understanding of the pathobiology of these diseases. The simultaneous analysis of promoter methylation using Differential Methylation Hybridization (DMH) and its associated gene expression using Expressed CpG Island Sequence Tag (ECIST) microarrays generates a large volume of methylation-expression relational data. To analyze this data, we propose a set of algorithms based on fuzzy sets theory, in particular Possibilistic c-Means (PCM) and cluster fuzzy density. For each gene, these algorithms calculate measures of confidence of various methylation-expression relationships in each NHL subclass. Thus, these tools can be used as a means of high volume data exploration to better guide biological confirmation using independent molecular biology methods.
References
[1]
{1} A. M. Glas, M. J. Kersten, L. J. Delahaye, A. T. Witteveen, R. E. Kibbelaar, A. Velds, L. F. Wessels, P. Joosten, R. M. Kerkhoven, R. Bernards, J. H. van Krieken, P. M. Kluin, L. J. van't Veer, and D. de Jong, "Gene Expression Profiling in Follicular Lymphoma to Assess Clinical Aggressiveness and to Guide the Choice of Treatment," Blood, vol. 105, pp. 301-307, 2005.
[2]
{2} H. Husson, E. G. Carideo, D. Neuberg, J. Schultze, O. Munoz, P. W. Marks, J. W. Donovan, A. C. Chillemi, P. O'Connell, and A. S. Freedman, "Gene Expression Profiling of Follicular Lymphoma and Normal Germinal Center B Cells Using cDNA Arrays," Blood, vol. 99, pp. 282-289, 2002.
[3]
{3} P. Adorjan, J. Distler, E. Lipscher, F. Model, J. Muller, C. Pelet, A. Braun, A. R. Florl, D. Gutig, G. Grabs, A. Howe, M. Kursar, R. Lesche, E. Leu, A. Lewin, A. S. Maier, V. Muller, T. Otto, C. Scholz, W. A. Schulz, H. H. Seifert, I. Schwope, H. Ziebarth, K. Berlin, C. Piepenbrock, and A. Olek, "Tumour Class Prediction and Discovery by Microarray-Based DNA Methylation Analysis," Nucleic Acids Research, vol. 30, p. e21, 2002.
[4]
{4} T. H. Huang, M. R. Perry, and D. E. Laux, "Methylation Profiling of CpG Islands in Human Breast Cancer Cells," Human Molecular Genetics, vol. 8, pp. 459-470, 1999.
[5]
{5} H. Shi, P. S. Yan, C. M. Chen, F. Rahmatpanah, C. Lofton-Day, C. W. Caldwell, and T. H. Huang, "Expressed CpG Island Sequence Tag Microarray for Dual Screening of DNA Hypermethylation and Gene Silencing in Cancer Cells," Cancer Research, vol. 62, no. 11, pp. 3214-3220, June 1,2002.
[6]
{6} L. Zadeh, "Fuzzy Sets," J. Information and Control, vol. 8, pp. 338- 353, 1965.
[7]
{7} R. Krishnapuram and J. M. Keller, "A Possibilistic Approach to Clustering," IEEE Trans. Fuzzy Systems, vol. 1, no. 2, pp. 98-110, 1993.
[8]
{8} R. Krishnapuram and J. M. Keller, "The Possibilistic C-Means Algorithm: Insights and Recommendations," IEEE Trans. Fuzzy Systems, vol. 4, no. 3, pp. 385-393, 1996.
[9]
{9} I. Gath and A. B. Geva, "Unsupervised Optimal Fuzzy Clustering," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, pp. 773-847, 1989.
[10]
{10} Y. Li, H. Nagai, T. Ohno, M. Yuge, S. Hatano, E. Ito, N. Mori, H. Saito, and T. Kinoshita, "Aberrant DNA Methylation of p57(KIP2) Gene in the Promoter Region in Lymphoid Malignancies of B-Cell Phenotype," Blood, vol. 100, pp. 2572-2577, 2002.
[11]
{11} E. E. Cameron, S. B. Baylin, and J. G. Herman, "p15(INK4B) CpG Island Methylation in Primary Acute Leukemia Is Heterogeneous and Suggests Density as a Critical Factor for Transcriptional Silencing," Blood, vol. 94, pp. 2445-2451, 1999.
[12]
{12} R. A. Katzenellenbogen, S. B. Baylin, and J. G. Herman, "Hypermethylation of the DAP-Kinase CpG Island Is a Common Alteration in B-Cell Malignancies," Blood, vol. 93, pp. 4347-4353, 1999.
[13]
{13} G. Egger, G. Liang, A. Aparicio, and P. A. Jones, "Epigenetics in Human Disease and Prospects for Epigenetic Therapy," Nature, vol. 429, pp. 457-463, 2004.
[14]
{14} J. F. Costello, M. C. Fruhwald, D. J. Smiraglia, L. J. Rush, G. P. Robertson, X. Gao, F. A. Wright, J. D. Feramisco, P. Peltomaki, J. C. Lang, D. E. Schuller, L. Yu, C. D. Bloomfield, M. A. Caligiuri, A. Yates, R. Nishikawa, H. H. Su, N. J. Petrelli, X. Zhang, M. S. O'Dorisio, W. A. Held, W. K. Cavenee, and C. Plass, "Aberrant CpG-Island Methylation Has Non-Random and Tumour-Type-Specific Patterns," Nature Genetics, vol. 24, pp. 132-138, 2000.
[15]
{15} T. Nagasawa, Q. Zhang, P. N. Raghunath, H. Y. Wong, M. El-Salem, A. Szallasi, M. Marzec, P. Gimotty, A. H. Rook, E. C. Vonderheid, N. Odum, and M. A. Wasik, "Multi-Gene Epigenetic Silencing of Tumor Suppressor Genes in T-Cell Lymphoma Cells; Delayed Expression of the p16 Protein upon Reversal of the Silencing," Leukemia Research, vol. 30, no. 3, pp. 303-312, Mar. 2006.
[16]
{16} F. Rahmatpanah, S. J. Carstens, J. Guo, O. Sjahputera, K. H. Taylor, D. J. Duff, H. Shi, J. W. Davis, S. I. Hooshmand, R. Chitma-Matsiga, and C. W. Caldwell, "Differential DNA Methylation Patterns of Small B-Cell Lymphoma Subclasses with Different Clinical Behavior," Leukemia, 2006.
[17]
{17} H. Shi, J. Guo, D. J. Duff, F. Rahmatpanah, R. Chitma-Matsiga, M. Al-Kuhlani, K. H. Taylor, O. Sjahputera, M. Andreski, J. E. Wooldridge, and C. W. Caldwell, "Discovery of Novel Epigenetic Markers in Non-Hodgkin's Lymphoma," Carcinogenesis, 2006.
[18]
{18} K. H. Taylor, K. E. Pena-Hernandez, J. W. Davis, G. C. Arthur, D. Duff, H. Shi, F. Rahmatpanah, O. Sjahputera, and C. W. Caldwell, "Large-Scale CpG Methylation Analysis Identifies Novel Candidate Genes and Reveals Methylation Hot Spots in Acure Lymphoblastic Leukemia," Cancer Research, to appear, 2007.
[19]
{19} J. G. Herman, J. R. Graff, S. Myohanen, B. D. Nelkin, and S. B. Baylin, "Methylation-Specific PCR: A Novel PCR Assay for Methylation Status of CpG Islands," Proc. Nat'l Academy of Sciences USA, vol. 93, pp. 9821-9826, 1996.
[20]
{20} Z. Xiong and P. W. Laird, "COBRA: A Sensitive and Quantitative DNA Methylation Assay," Nucleic Acids Research, vol. 25, no. 12, pp. 2532-2534, 1997.
[21]
{21} P. S. Yan, C. M. Chen, H. Shi, F. Rahmatpanah, S. H. Wei, C. W. Caldwell, and T. H. Huang, "Dissecting Complex Epigenetic Alterations in Breast Cancer Using CpG Island Microarrays," Cancer Research, vol. 61, pp. 8375-8380, 2001.
[22]
{22} Y. H. Yang, S. Dudoit, P. Luu, D. M. Lin, V. Peng, J. Ngai, and T. P. Speed, "Normalization for cDNA Microarray Data: A Robust Composite Method for Addressing Single and Multiple Slide Systematic Variation," Nucleic Acid Research, vol. 30, no. 4, p. e15, 2002.
[23]
{23} R. M. Simon, E. L. Korn, L. M. McShane, M. D. Radmacher, G. W. Wright, and Y. Zhao, Design and Analysis of DNA Microarray Investigations. Springer-Verlag, 2004.
[24]
{24} E. Eisenberg and E. Y. Levanon, "Human Housekeeping Genes Are Compact," Trends in Genetics, vol. 19, no. 7, pp. 362-365, July 2003.
[25]
{25} W. S. Cleveland, "Robust Locally-Weighted Regression and Smoothing Scatterplots," J. Am. Statistical Assoc., vol. 74, pp. 829- 836, 1979.
[26]
{26} W. S. Cleveland, S. J. Devlin, and E. Grosse, "Regression by Local Fitting," J. Econometrics, vol. 37, pp. 87-114, 1988.
[27]
{27} W. S. Cleveland and E. Grosse, "Computational Methods for Local Regression," Statistics and Computing, vol. 1, pp. 47-62, 1991.
[28]
{28} Matlab Bioinformatics Toolbox Version 2.2, The MathWorks Inc., http://www.mathworks.com/products/bioinfo/index.html?fp, 2007.
[29]
{29} Matlab Fuzzy Logic Toolbox Ver. 2.2.2, The MathWorks Inc., http://www.mathworks.com/products/fuzzylogic/?BB=1, 2007.
[30]
{30} H. Frigui and R. Krishnapuram, "A Robust Competitive Clustering Algorithm with Applications in Computer Vision," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 5, 1999.
[31]
{31} M. H. Asyali and M. Alci, "Reliability Analysis of Microarray Data Using Fuzzy C-Means and Normal Mixture Modeling Based Classification Methods," Bioinformatics, vol. 21, no. 5, pp. 644-649, Mar. 2005.
[32]
{32} J. Wang, T. H. Bo, I. Jonassen, O. Myklebost, and E. Hovig, "Tumor Classification and Marker Gene Prediction by Feature Selection and Fuzzy C-Means Clustering Using Microarray Data," BMC Bioinformatics, vol. 4, p. 60, Dec. 2003.
[33]
{33} J. C. Bezdek, "Cluster Validity with Fuzzy Sets," J. Cybernetics, vol. 3, no. 3, pp. 58-72, 1974.
[34]
{34} J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, 1981.
[35]
{35} R. P. Leng, Y. Lin, W. Ma, H. Wu, B. Lemmers, S. Chung, J. M. Parant, G. L. R. Hakem, and S. Benchimol, "Pirh2, a p53-Induced Ubiquitin-Protein Ligase, Promotes p53 Degradation," Cell, vol. 112, no. 6, pp. 779-791, Mar. 2003.
[36]
{36} W. Duan, L. Gao, L. J. Druhan, W. G. Zhu, C. Morrison, G. A. Otterson, and M. A. Villalona-Calero, "Expression of Pirh2, a Newly Identified Ubiquitin Protein Ligase, in Lung Cancer," J. Nat'l Cancer Inst., vol. 96, no. 22, pp. 1718-1721, Nov. 2004.
[37]
{37} H. Santos-Rosa and C. Caldas, "Chromatin Modifier Enzymes, the Histone Code and Cancer," European J. Cancer, vol. 41, no. 16, pp. 2381-2402, Nov. 2005.
[38]
{38} J. P. Himanen, M. J. Chumley, M. Lackmann, C. Li, W. A. Barton, P. D. Jeffrey, C. Vearing, D. Geleick, D. A. Feldheim, A. W. Boyd, M. Henkemeyer, and D. B. Nikolov, "Repelling Class Discrimination: Ephrin-A5 Binds to and Activates EphB2 Receptor Signaling," Nature Neuroscience, vol. 7, pp. 501-509, 2004.
[39]
{39} P. Huusko, D. Ponciano-Jackson, M. Wolf, J. A. Kiefer, D. O. Azorsa, S. Tuzmen, D. Weaver, C. Robbins, T. Moses, M. Allinen, S. Hautaniemi, Y. Chen, A. Elkahloun, M. Basik, G. S. Bova, L. Bubendorf, A. Lugli, G. Sauter, J. Schleutker, H. Ozcelik, S. Elowe, T. Pawson, J. M. Trent, J. D. Carpten, O. P. Kallioniemi, and S. Mousses, "Nonsense-Mediated Decay Microarray Analysis Identifies Mutations of EPHB2 in Human Prostate Cancer," Nature Genetics, vol. 36, pp. 979-983, 2004.
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- Relational Analysis of CpG Islands Methylation and Gene Expression in Human Lymphomas Using Possibilistic C-Means Clustering and Modified Cluster Fuzzy Density
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Published: 01 April 2007
Published in TCBB Volume 4, Issue 2
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