Key genes for modulating information flow play a temporal role as breast tumor coexpression networks are dynamically rewired by letrozole

BMC Medical Genomics

Volumn 6, Issue SUPPL2, 2013, Pages

  Penrod, Nadia M ^a   Moore, Jason H ^a  

^a DARTMOUTH MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ESTROGEN RECEPTOR; LETROZOLE;

ARTICLE; BREAST BIOPSY; BREAST TUMOR; DRUG RESPONSE; GENE EXPRESSION; GENE IDENTIFICATION; HUMAN; PRIORITY JOURNAL; TRANSCRIPTOMICS;

ANTINEOPLASTIC AGENTS; BREAST NEOPLASMS; COMPUTATIONAL BIOLOGY; FEMALE; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HUMANS; NITRILES; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; TIME FACTORS; TRIAZOLES; TUMOR MARKERS, BIOLOGICAL;

EID: 84877357986     PISSN: None     EISSN: 17558794     Source Type: Journal    
DOI: 10.1186/1755-8794-6-S2-S2     Document Type: Article

References (47)

1. Systems Biology and Genomics of Breast Cancer. Perou C, Børresen-Dale A, Cold Spring Harb Perspect Biol 2011 3 ii: a003293 doi: 10.1101/cshperspect.a003293 21047916
2. Gene-expression signatures in breast cancer. Sotiriou C, Pusztai L, N Engl J Med 2009 360 790 800 10.1056/NEJMra0801289 19228622
3. From molecular to modular cell biology. Hartwell LH, et al. Nature 1999 402 47 C52 10.1038/35011540 10591225
4. Systematic survey reveals general applicability of «guilt-by- association» within gene coexpression networks. Wolfe C, Kohane I, Butte A, BMC Bioinformatics 2005 6 227 10.1186/1471-2105-6-227 16162296 (Pubitemid 41372439)
5. Mechanisms of estrogen receptor signaling: convergence of genomic and nongenomic actions on target genes. Björnström L, Sjöberg M, Mol Endocrinol 2005 19 833 842 10.1210/me.2004-0486 15695368 (Pubitemid 40397050)
6. ACOSOG Z1031: a randomized phase II trial comparing exemestane, letrozole, and anastrozole in postmenopausal women with clinical stage II/III estrogen receptor-positive breast cancer. Ellis M, Buzdar A, Unzeitig G, Esserman L, Leitch A, Deshyrver K, et al. J Clin Oncol (ASCO Meeting Abstracts) 2010 28 7s
7. Sequential changes in gene expression profiles in breast cancers during treatment with the aromatase inhibitor, letrozole. Miller W, Larionov A, Anderson T, Evans D, Dixon J, Pharmacogenomics J 2010 12 10 21 20697427
8. Changes in breast cancer transcriptional profiles after treatment with the aromatase inhibitor, letrozole. Miller W, Larionov A, Renshaw L, Anderson T, White S, Murray J, Murray E, Hampton G, Walker J, Ho S, et al. Pharmacogenet Genomics 2007 17 10 813 826 10.1097/FPC.0b013e32820b853a 17885619 (Pubitemid 47462295)
9. Gene expression profiles differentiating between breast cancers clinically responsive or resistant to letrozole. Miller W, et al. J Clin Oncol 2009 27 9 1382 1387 10.1200/JCO.2008.16.8849 19224856
10. Proliferation, steroid receptors and clinical/pathological response in breast cancer treated with letrozole. Miller W, et al. Br J Cancer 2006 94 7 1051 1056 10.1038/sj.bjc.6603001 16538221
11. Which patients benefit most from adjuvant aromatase inhibitors? Results using a composite measure of prognostic risk in the BIG 1-98 randomized trial. Viale G, Regan M, Dell'Orto P, Mastropasqua M, Maiorano E, Rasmussen B, MacGrogan G, Forbes J, Paridaens R, Colleoni M, et al. Ann Oncol 2011 22 10 2201 2207 10.1093/annonc/mdq738 21335417
12. Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Dai M, Wang P, Boyd A, Kostov G, Athey B, Jones E, Bunney W, Myers R, Speed T, Akil H, et al. Nucleic Acids Res 2005 33 20 175 e175 10.1093/nar/gni179 16284200 (Pubitemid 41806403)
13. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Irizarry R, Hobbs B, Collin F, Beazer-Barclay Y, Antonellis K, Scherf U, Speed T, Biostatistics 2003 4 2 249 264 10.1093/biostatistics/4.2.249 12925520
14. Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data. Jeffery I, Higgins D, Culhane A, BMC Bioinformatics 2006 7 359 10.1186/1471-2105-7-359 16872483
15. Smyth G, Limma: linear models for microarray data Springer 2005
16. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Sherman B, Lempicki R, et al. Nucleic Acids Res 2009 37 1 13 10.1093/nar/gkn923 19033363
17. Discovery of meaningful associations in genomic data using partial correlation coefficients. de la Fuente A, Bing N, Hoeschele I, Mendes P, Bioinformatics 2004 20 18 3565 3574 10.1093/bioinformatics/bth445 15284096 (Pubitemid 40136792)
18. The igraph software package for complex network research. Csardi G, Nepusz T, InterJournal 2006 Complex Systems 1695 http://igraph.sf.net
19. R Core Team, R: A Language and Environment for Statistical Computing R Foundation for Statistical Computing, Vienna, Austria 2012 http://www.R-project. org [ISBN 3-900051-07-0]
20. Rank of correlation coefficient as a comparable measure for biological significance of gene coexpression. Obayashi T, Kinoshita K, DNA Res 2009 16 249 260 10.1093/dnares/dsp016 19767600
21. Network biology: understanding the cell's functional organization. Barabási A, Oltvai Z, Nat Rev Genet 2004 5 101 113 10.1038/nrg1272 14735121 (Pubitemid 38160277)
22. Wasserman S, Faust K, Social network analysis: Methods and applications, Volume 8 Cambridge University Press 1994
23. Collective dynamics of «small-world» networks. Watts D, Strogatz S, Nature 1998 393 440 442 10.1038/30918 9623998 (Pubitemid 28292183)
24. The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics. Yu H, et al. PLoS Comput Biol 2007 3 0713 0720
25. Lethality and centrality in protein networks. Jeong H, Mason S, Barabasi A, Oltvai Z, Nature 2001 411 41 42 10.1038/35075138 11333967 (Pubitemid 32428180)
26. Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality. Zotenko E, Mestre J, O'Leary D, Przytycka T, PLoS Comput Biol 2008 4 1000140 10.1371/journal.pcbi.1000140 18670624
27. Towards a knowledge-based human protein atlas. Uhlen M, Oksvold P, Fagerberg L, Lundberg E, Jonasson K, Forsberg M, Zwahlen M, Kampf C, Wester K, Hober S, et al. Nat Biotechnol 2010 28 1248 1250 10.1038/nbt1210-1248 21139605
28. The expression patterns of ER, PR, HER2, CK5/6, EGFR, Ki-67 and AR by immunohistochemical analysis in breast cancer cell lines. Subik K, Lee J, Baxter L, Strzepek T, Costello D, Crowley P, Xing L, Hung M, Bonfiglio T, Hicks D, et al. Breast Cancer (Auckl) 2010 4 35 41 20697531
29. A single nucleotide polymorphism-derived regulatory gene network underlying puberty in 2 tropical breeds of beef cattle. Fortes M, Reverter A, Nagaraj S, Zhang Y, Jonsson N, Barris W, Lehnert S, Boe-Hansen G, Hawken R, J Anim Sci 2011 89 1669 1683 10.2527/jas.2010-3681 21357453
30. A homeodomain-zinc finger protein, ZFHX4, is expressed in neuronal differentiation manner and suppressed in muscle differentiation manner. Hemmi K, Ma D, Miura Y, Kawaguchi M, Sasahara M, Hashimoto-Tamaoki T, Tamaoki T, Sakata N, Tsuchiya K, Biol Pharm Bull 2006 29 1830 1835 10.1248/bpb.29.1830 16946494 (Pubitemid 44338403)
31. Genome-wide scan of 500,000 single-nucleotide polymorphisms among responders and nonresponders to interferon beta therapy in multiple sclerosis. Comabella M, Craig D, Morcillo-Suárez C, Rio J, Navarro A, Fernández M, Martin R, Montalban X, Arch Neurol 2009 66 972 978 10.1001/archneurol.2009.150 19667218
32. The BMP2/7 heterodimer inhibits the human breast cancer stem cell subpopulation and bone metastases formation. Buijs J, van der Horst G, van den Hoogen C, Cheung H, de Rooij B, Kroon J, Petersen M, van Overveld P, Pelger R, van der Pluijm G, Oncogene 2011 31 2164 2174 21996751
33. Cross-talk between bone morphogenic proteins and estrogen receptor signaling. Yamamoto T, Saatcioglu F, Matsuda T, Endocrinology 2002 143 2635 2642 10.1210/en.143.7.2635 12072396 (Pubitemid 34701327)
34. Entrez Gene: gene-centered information at NCBI. Maglott D, Ostell J, Pruitt K, Tatusova T, Nucleic Acids Res 2005 33 54 D58 10.1093/nar/gni052 15608257 (Pubitemid 41748351)
35. Disabled-2 downregulation promotes epithelial-to-mesenchymal transition. Martin J, Herbert B, Hocevar B, BJC 2010 103 1716 1723 10.1038/sj.bjc.6605975 21063401
36. Identification of Fat4 as a candidate tumor suppressor gene in breast cancers. Qi C, Zhu Y, Hu L, Zhu Y, Int J Cancer 2009 124 793 798 10.1002/ijc.23775 19048595
37. A genome-scale protein interaction profile of Drosophila p53 uncovers additional nodes of the human p53 network. Lunardi A, Di Minin G, Provero P, Dal Ferro M, Carotti M, Del Sal G, Collavin L, PNAS 2010 107 6322 6327 10.1073/pnas.1002447107 20308539
38. CAV1 siRNA Reduces Membrane Estrogen Receptor-α Levels and Attenuates Sexual Receptivity. Christensen A, Micevych P, Endocrinology 2012 153 3872 3877 10.1210/en.2012-1312 22669893
39. Biomechanical remodeling of the microenvironment by stromal caveolin-1 favors tumor invasion and metastasis. Goetz J, Minguet S, Navarro-Lérida I, Lazcano J, Samaniego R, Calvo E, Tello M, Osteso-Ibáñez T, Pellinen T, Echarri A, et al. Cell 2011 146 148 163 10.1016/j.cell.2011.05.040 21729786
40. Estrogen-induced redox sensitive Id3 signaling controls the growth of vascular cells. Felty Q, Porther N, Atherosclerosis 2008 198 12 21 10.1016/j.atherosclerosis.2007.12.048 18281048
41. Acquired Resistance to Tamoxifen Is Associated with Loss of the Type I Insulin-like Growth Factor Receptor: Implications for Breast Cancer Treatment. Fagan D, Uselman R, Sachdev D, Yee D, Cancer Res 2012 72 3372 3380 10.1158/0008-5472.CAN-12-0684 22573715
42. Identification of TACC1, NOV, and PTTG1 as new candidate genes associated with endocrine therapy resistance in breast cancer. Ghayad S, Vendrell J, Bieche I, Spyratos F, Dumontet C, Treilleux I, Lidereau R, Cohen P, J Mol Endocrinol 2009 42 87 103 18984771
43. Cancer susceptibility and the functions of BRCA1 and BRCA2. Venkitaraman A, et al. Cell 2002 108 171 182 10.1016/S0092-8674(02)00615-3 11832208 (Pubitemid 34161138)
44. β-Catenin independent cross-control between the estradiol and Wnt pathways in osteoblasts. McCarthy T, Kallen C, Centrella M, Gene 2011 479 16 28 10.1016/j.gene.2011.02.002 21335072
45. Rewiring of genetic networks in response to DNA damage. Bandyopadhyay S, Mehta M, Kuo D, Sung M, Chuang R, Jaehnig E, Bodenmiller B, Licon K, Copeland W, Shales M, et al. Science 2010 330 1385 1389 10.1126/science.1195618 21127252
46. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Han J, Bertin N, Hao T, Goldberg D, Berriz G, Zhang L, Dupuy D, Walhout A, Cusick M, Roth F, et al. Nature 2004 430 88 93 10.1038/nature02555 15190252 (Pubitemid 38915230)
47. Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets. Gandhi T, Zhong J, Mathivanan S, Karthick L, Chandrika K, Mohan S, Sharma S, Pinkert S, Nagaraju S, Periaswamy B, et al. Nat Genet 2006 38 285 293 10.1038/ng1747 16501559