In silico analysis of combinatorial microRNA activity reveals target genes and pathways associated with breast cancer metastasis

Cancer Informatics

Volumn 10, Issue , 2011, Pages 13-29

  Dombkowski, Alan A ^a   Sultana, Zakia ^b   Craig, Douglas B ^a   Jamil, Hasan ^b  

^a WAYNE STATE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b Wayne State University   (United States)

Author keywords

Bioinformatics; Cancer; Computational; Metastasis; microRNA

Indexed keywords

ACTIN RELATED PROTEIN 3; CYCLIN D1; FRUCTOSE BISPHOSPHATE ALDOLASE; FRUCTOSE BISPHOSPHATE ALDOLASE ISOENZYME; KERATIN; KERATIN 81; MICRORNA; MYC PROTEIN; OSTEOCLAST DIFFERENTIATION FACTOR; PLATELET DERIVED GROWTH FACTOR A; TRANSFORMING GROWTH FACTOR BETA1; UNCLASSIFIED DRUG;

3' UNTRANSLATED REGION; ARTICLE; BINDING SITE; BIOINFORMATICS; BREAST CANCER; CARCINOGENESIS; CELL ADHESION; CELL CYCLE REGULATION; COMBINATORIAL CHEMISTRY; COMPUTER ANALYSIS; COMPUTER MODEL; CONTROLLED STUDY; CYTOSKELETON; GENE ACTIVITY; GENE CONTROL; GENE OVEREXPRESSION; GENE TARGETING; GENOMIC INSTABILITY; HUMAN; HUMAN GENOME; IDENTIFICATION KEY; METASTASIS; MICROARRAY ANALYSIS; MICRORNA COMBINATORIAL ANALYSIS OF TARGETS; NONHUMAN; PROTEIN EXPRESSION; RNA TRANSLATION; TRANSCRIPTION REGULATION;

EID: 79952911456     PISSN: 11769351     EISSN: 11769351     Source Type: Journal    
DOI: 10.4137/CIN.S6631     Document Type: Article

References (96)

1. Jackson RJ, Standart N. How do microRNAs regulate gene expression? Sci STKE. 2007;2007(367):re1.
2. Wu L, Belasco JG. Let me count the ways: mechanisms of gene regulation by miRNAs and siRNAs. Molecular Cell. 2008;29(1):1-7.
3. Bartel DP. microRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116(2):281-97.
4. Wu L, Fan J, Belasco JG. microRNAs direct rapid deadenylation of mRNA. Proceedings of the National Academy of Sciences of the United States of America. 2006;103(11):4034-9.
5. Giraldez AJ, Mishima Y, Rihel J, et al. Zebrafish MiR-430 promotes deadenylation and clearance of maternal mRNAs. Science. 2006;312 (5770):75-9.
6. Doench JG, Sharp PA. Specificity of microRNA target selection in translational repression. Genes and Development. 2004;18(5):504-11.
7. Krek A, Grun D, Poy MN, et al. Combinatorial microRNA target predictions. 2005;37(5):495-500.
8. Enright A, John B, Gaul U, Tuschl T, Sander C, Marks D. microRNA targets in Drosophila. Genome Biology. 2003;5(1):R1.
9. Hu Z. Insight into microRNA regulation by analyzing the characteristics of their targets in humans. BMC Genomics. 2009;10:594.
10. Forrest AR, Kanamori-Katayama M, Tomaru Y, et al. Induction of microRNAs, mir-155, mir-222, mir-424 and mir-503, promotes monocytic differentiation through combinatorial regulation. Leukemia. 2009 3.
11. Takagi T, Iio A, Nakagawa Y, Naoe T, Tanigawa N, Akao Y. Decreased expression of microRNA-143 and -145 in human gastric cancers. Oncology. 2009;77(1):12-21.
12. Xin M, Small EM, Sutherland LB, et al. microRNAs miR-143 and miR- 145 modulate cytoskeletal dynamics and responsiveness of smooth muscle cells to injury. Genes Dev. 2009 23(18):2166-78.
13. Gusev Y. Computational methods for analysis of cellular functions and pathways collectively targeted by differentially expressed microRNA: microRNAs: Part B. Methods. 2008;44(1):61-72.
14. Wang X. miRDB: A microRNA target prediction and functional annotation database with a wiki interface. RNA. 2008;14(6):1012-7.
15. Nam S, Kim B, Shin S, Lee S. miRGator: an integrated system for functional annotation of microRNAs. Nucl Acids Res. 2008/1/11 2008;36(suppl_1): D159-64.
16. Chiromatzo AO, Oliveira TY, Pereira G, et al. miRNApath: a database of miRNAs, target genes and metabolic pathways. Genet Mol Res. 2007;6(4): 859-65.
17. Li L, Xu J, Yang D, Tan X, Wang H. Computational approaches for microRNA studies: a review. Mamm Genome. 2009 Dec 15.
18. Tavazoie SF, Alarcon C, Oskarsson T, et al. Endogenous human microRNAs that suppress breast cancer metastasis. 2008;451(7175):147-52.
19. Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ. miRBase: microRNA sequences, targets and gene nomenclature. Nucl Acids Res. 2006;34(Suppl_1):D140-4.
20. John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS. Human microRNA Targets. 2004;2(11):e363.
21. Betel D, Wilson M, Gabow A, Marks DS, Sander C. The microRNA.org resource: targets and expression. Nucleic Acids Res. 2008 Jan;36(Database issue):D149-53.
22. Dennis G, Sherman B, Hosack D, et al. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biology. 2003;4(5):P3.
23. De Hoon MJ, Imoto S, Nolan J, Miyano S. Open source clustering software. Bioinformatics. 2004;20(9):1453-4.
24. Saldanha AJ. Java Treeview--extensible visualization of microarray data. Bioinformatics. 2004;20(17):3246-8.
25. Zubarev RA, Nielsen ML, Fung EM, et al. Identification of dominant signaling pathways from proteomics expression data. J Proteomics. 2008;71(1):89-96.
26. Warburg O. On the origin of cancer cells. Science. 1956;123(3191): 309-14.
27. Schade AL. Enzymic studies on ascitic tumors and their host's blood plasmas. Biochim Biophys Acta. 1953;12(1-2):163-71.
28. Shadidi M, Sorensen D, Dybwad A, Furset G, Sioud M. Mucosal vaccination with phage-displayed tumour antigens identified through proteomics-based strategy inhibits the growth and metastasis of 4T1 breast adenocarcinoma. Int J Oncol. 2008;32(1):241-7.
29. Asaka M, Alpert E. Subunit-specific radioimmunoassay for aldolase A, B, and C subunits: clinical significance. Ann N Y Acad Sci. 1983;417:359-67.
30. Asaka M, Nagase K, Miyazaki T, Alpert E. Radioimmunoassay of aldolase A. Determination of normal serum levels and increased serum concentration in cancer patients. Cancer. 1983;51(10):1873-8.
31. Castaldo G, Calcagno G, Sibillo R, et al. Quantitative analysis of aldolase A mRNA in liver discriminates between hepatocellular carcinoma and cirrhosis. Clin Chem. 2000;46(7):901-6.
32. Gure AO, Altorki NK, Stockert E, Scanlan MJ, Old LJ, Chen YT. Human lung cancer antigens recognized by autologous antibodies: definition of a novel cDNA derived from the tumor suppressor gene locus on chromosome 3p21.3. Cancer Res. 1998;58(5):1034-41.
33. Hamaguchi T, Iizuka N, Tsunedomi R, et al. Glycolysis module activated by hypoxia-inducible factor 1alpha is related to the aggressive phenotype of hepatocellular carcinoma. Int J Oncol. 2008 Oct;33(4):725-31.
34. Tanaka H. Determination of aldolase A by radioimmunoassay. Experimental and clinical studies on the diagnosis of cancer of the digestive tract. Hokkaido Igaku Zasshi. 1983 Jul;58(4):363-75.
35. Esau C, Davis S, Murray SF, et al. miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting. Cell Metab. 2006;3(2):87-98.
36. Fabani MM, Gait MJ. miR-122 targeting with LNA/2'-O-methyl oligonucleotide mixmers, peptide nucleic acids (PNA), and PNA-peptide conjugates. RNA. 2008;14(2):336-46.
37. Elmen J, Lindow M, Silahtaroglu A, et al. Antagonism of microRNA-122 in mice by systemically administered LNA-antimiR leads to up-regulation of a large set of predicted target mRNAs in the liver. Nucleic Acids Res. 2008;36(4):1153-62.
38. Tu K, Yu H, Hua YJ, et al. Combinatorial network of primary and secondary microRNA-driven regulatory mechanisms. Nucleic Acids Res. 2009; 37(18):5969-80.
39. Yue H, Yang B, Zhang H, et al. Clinical significance of TGF- beta1 and beta- glucuronidase synchronous detection in human pancreatic cancer. Hepatobiliary Pancreat Dis Int. 2002;1(2):309-11.
40. Tang J, Zhou HW, Jiang JL, et al. BetaIg-h3 is involved in the HAb18G/ CD147-mediated metastasis process in human hepatoma cells. Exp Biol Med (Maywood). 2007 232(3):344-52.
41. Ma C, Rong Y, Radiloff DR, et al. Extracellular matrix protein betaig-h3/ TGFBI promotes metastasis of colon cancer by enhancing cell extravasation. Genes Dev. 2008;22(3):308-21.
42. Wong FH, Huang CY, Su LJ, et al. Combination of microarray profiling and protein-protein interaction databases delineates the minimal discriminators as a metastasis network for esophageal squamous cell carcinoma. Int J Oncol. 2009;34(1):117-28.
43. Joshi A, Cao D. TGF-beta signaling, tumor microenvironment and tumor progression: the butterfly effect. Front Biosci. 15:180-94.
44. Glick AB. TGFbeta1, back to the future: revisiting its role as a transforming growth factor. Cancer Biol Ther. 2004;3(3):276-83.
45. Ivanovic V, Demajo M, Krtolica K, et al. Elevated plasma TGF-beta1 levels correlate with decreased survival of metastatic breast cancer patients. Clin Chim Acta. 2006;371(1-2):191-3.
46. Moore LD, Isayeva T, Siegal GP, Ponnazhagan S. Silencing of transforming growth factor-beta1 in situ by RNA interference for breast cancer: implications for proliferation and migration in vitro and metastasis in vivo. Clin Cancer Res. 2008;14(15):4961-70.
47. Mills GB, Schmandt R, McGill M, et al. Expression of TTK, a novel human protein kinase, is associated with cell proliferation. J Biol Chem. 1992;267(22):16000-6.
48. Kasbek C, Yang CH, Fisk HA. Mps1 as a link between centrosomes and genomic instability. Environ Mol Mutagen. 2009;50(8):654-65.
49. Yuan B, Xu Y, Woo JH, et al. Increased expression of mitotic checkpoint genes in breast cancer cells with chromosomal instability. Clin Cancer Res. 2006;12(2):405-10.
50. Park WR, Nakamura Y. p53CSV, a novel p53-inducible gene involved in the p53-dependent cell-survival pathway. Cancer Res. 2005;65(4): 1197-206.
51. Felix RS, Colleoni GW, Caballero OL, et al. SAGE analysis highlights the importance of p53csv, ddx5, mapkapk2 and ranbp2 to multiple myeloma tumorigenesis. Cancer Lett. 2009;278(1):41-8.
52. Musgrove EA, Hamilton JA, Lee CS, Sweeney KJ, Watts CK, Sutherland RL. Growth factor, steroid, and steroid antagonist regulation of cyclin gene expression associated with changes in T-47D human breast cancer cell cycle progression. Mol Cell Biol. 1993;13(6):3577-87.
53. Schraml P, Kononen J, Bubendorf L, et al. Tissue microarrays for gene amplification surveys in many different tumor types. Clin Cancer Res. 1999;5(8):1966-75.
54. Bieche I, Olivi M, Nogues C, Vidaud M, Lidereau R. Prognostic value of CCND1 gene status in sporadic breast tumours, as determined by real-time quantitative PCR assays. Br J Cancer. 2002;86(4):580-6.
55. Loden M, Stighall M, Nielsen NH, et al. The cyclin D1 high and cyclin E high subgroups of breast cancer: separate pathways in tumorogenesis based on pattern of genetic aberrations and inactivation of the pRb node. Oncogene. 2002;21(30):4680-90.
56. Al-Kuraya K, Schraml P, Torhorst J, et al. Prognostic relevance of gene amplifications and coamplifications in breast cancer. Cancer Res. 2004;64(23):8534-40.
57. Kendall SD, Linardic CM, Adam SJ, Counter CM. A network of genetic events sufficient to convert normal human cells to a tumorigenic state. Cancer Res. 2005;65(21):9824-28.
58. Wang Y, Thakur A, Sun Y, et al. Synergistic effect of cyclin D1 and c-Myc leads to more aggressive and invasive mammary tumors in severe combined immunodeficient mice. Cancer Res. 2007;67(8):3698-707.
59. Quackenbush J. Computational analysis of microarray data. Nat Rev Genet. 2001 2(6):418-27.
60. Moretti S, Wilm A, Higgins DG, Xenarios I, Notredame C. R-Coffee: a web server for accurately aligning noncoding RNA sequences. Nucleic Acids Res. 2008 Jul 1;36(Web Server issue):W10-3.
61. Brennecke J, Stark A, Russell RB, Cohen SM. Principles of microRNAtarget recognition. PLoS Biol. 2005;3(3):e85.
62. Varani G, McClain WH. The G ×U wobble base pair. A fundamental building block of RNA structure crucial to RNA function in diverse biological systems. EMBO Rep. 2000 1(1):18-23.
63. Machesky LM. Lamellipodia and filopodia in metastasis and invasion: Nuclear Dynamics and Cytoskeleton Signaling. FEBS Letters. 2008; 582(14):2102-11.
64. Kedrin D, van Rheenen J, Hernandez L, Condeelis J, Segall JE. Cell motility and cytoskeletal regulation in invasion and metastasis. J Mammary Gland Biol Neoplasia. 2007;12(2-3):143-52.
65. Loisel TP, Boujemaa R, Pantaloni D, Carlier M-F. Reconstitution of actin- based motility of Listeria and Shigella using pure proteins. Nature. 1999;401(6753):613-6.
66. Wang W, Goswami S, Lapidus K, et al. Identification and testing of a gene expression signature of invasive carcinoma cells within primary mammary tumors. Cancer Res. 2004 64(23):8585-94.
67. Weaver AM. Invadopodia: specialized cell structures for cancer invasion. Clin Exp Metastasis. 2006;23(2):97-105.
68. Yamaguchi H, Lorenz M, Kempiak S, et al. Molecular mechanisms of invadopodium formation: the role of the N-WASP-Arp2/3 complex pathway and cofilin. J Cell Biol. 2005 168(3):441-52.
69. Albiges-Rizo C, Destaing O, Fourcade B, Planus E, Block MR. Actin machinery and mechanosensitivity in invadopodia, podosomes and focal adhesions. J Cell Sci. 2009 122(17):3037-49.
70. Wang WS, Chen PM, Hsiao HL, Wang HS, Liang WY, Su Y. Overexpression of the thymosin beta-4 gene is associated with increased invasion of SW480 colon carcinoma cells and the distant metastasis of human colorectal carcinoma. Oncogene. 2004;23(39):6666-71.
71. Kobayashi T, Okada F, Fujii N, et al. Thymosin-beta4 regulates motility and metastasis of malignant mouse fibrosarcoma cells. Am J Pathol. 2002; 160(3):869-82.
72. Nummela P, Yin M, Kielosto M, Leaner V, Birrer MJ, Holtta E. Thymosin beta4 is a determinant of the transformed phenotype and invasiveness of S-adenosylmethionine decarboxylase-transfected fibroblasts. Cancer Res. 2006;66(2):701-12.
73. Cha HJ, Jeong MJ, Kleinman HK. Role of thymosin beta4 in tumor metastasis and angiogenesis. J Natl Cancer Inst. 2003;95(22):1674-80.
74. Fili S, Karalaki M, Schaller B. Mechanism of bone metastasis: the role of osteoprotegerin and of the host-tissue microenvironment-related survival factors. Cancer Lett. 2009 28;283(1):10-9.
75. Ohshiba T, Miyaura C, Inada M, Ito A. Role of RANKL-induced osteoclast formation and MMP-dependent matrix degradation in bone destruction by breast cancer metastasis. Br J Cancer. 2003;88(8):1318-26.
76. Michigami T, Ihara-Watanabe M, Yamazaki M, Ozono K. Receptor activator of nuclear factor kappaB ligand (RANKL) is a key molecule of osteoclast formation for bone metastasis in a newly developed model of human neuroblastoma. Cancer Res. 2001 15;61(4):1637-44.
77. Canon JR, Roudier M, Bryant R, et al. Inhibition of RANKL blocks skeletal tumor progression and improves survival in a mouse model of breast cancer bone metastasis. Clin Exp Metastasis. 2008;25(2):119-29.
78. Hofbauer LC, Rachner T, Singh SK. Fatal attraction: why breast cancer cells home to bone. Breast Cancer Res. 2008;10(1):101.
79. Santini D, Fratto ME, Vincenzi B, et al. Denosumab: the era of targeted therapies in bone metastatic diseases. Curr Cancer Drug Targets. 2009; 9(7):834-42.
80. Mikami S, Katsube K, Oya M, et al. Increased RANKL expression is related to tumour migration and metastasis of renal cell carcinomas. J Pathol. 2009;218(4):530-9.
81. Jones DH, Nakashima T, Sanchez OH, et al. Regulation of cancer cell migration and bone metastasis by RANKL. Nature. 2006;440(7084):692-6.
82. Park HR, Min SK, Cho HD, Kim DH, Shin HS, Park YE. Expression of osteoprotegerin and RANK ligand in breast cancer bone metastasis. J Korean Med Sci. 2003;18(4):541-6.
83. Thomas RJ, Guise TA, Yin JJ, et al. Breast cancer cells interact with osteoblasts to support osteoclast formation. Endocrinology. 1999;140(10):4451-8.
84. Nicolin V, Narducci P. Soluble TRAIL could enhance bone destruction acting on Rank-ligand in estrogen-independent human breast cancer cell line MDA-MB-231. Acta Histochem. Mar;112(2):189-92.
85. Minn AJ, Gupta GP, Siegel PM, et al. Genes that mediate breast cancer metastasis to lung. Nature. 2005;436(7050):518-24.
86. Anan K, Morisaki T, Katano M, et al. Vascular endothelial growth factor and platelet-derived growth factor are potential angiogenic and metastatic factors in human breast cancer. Surgery. 1996;119(3):333-9.
87. Ariad S, Seymour L, Bezwoda WR. Platelet-derived growth factor (PDGF) in plasma of breast cancer patients: correlation with stage and rate of progression. Breast Cancer Res Treat. 1991;20(1):11-7.
88. Seymour L, Dajee D, Bezwoda WR. Tissue platelet derived-growth factor (PDGF) predicts for shortened survival and treatment failure in advanced breast cancer. Breast Cancer Res Treat. 1993;26(3):247-52.
89. Lev DC, Kim SJ, Onn A, et al. Inhibition of platelet-derived growth factor receptor signaling restricts the growth of human breast cancer in the bone of nude mice. Clin Cancer Res. 2005;11(1):306-14.
90. Regnier CH, Boulay A, Asch PH, et al. Expression of a truncated form of hHb1 hair keratin in human breast carcinomas. Br J Cancer. 1998;78(12):1640-4.
91. Nishikawa J, Kiss C, Imai S, et al. Upregulation of the truncated basic hair keratin 1(hHb1-DeltaN) in carcinoma cells by Epstein-Barr virus (EBV). Int J Cancer. 2003;107(4):597-602.
92. Boulay A, Regnier CH, Anglard P, Stoll I, Tomasetto C, Rio MC. Transcription regulation and protein subcellular localization of the truncated basic hair keratin hHb1-DeltaN in human breast cancer cells. J Biol Chem. 2001;276(25):22954-64.
93. Ptitsyn AA, Weil MM, Thamm DH. Systems biology approach to identification of biomarkers for metastatic progression in cancer. BMC Bioinformatics. 2008;9 Suppl 9:S8.
94. Hurst DR, Edmonds MD, Welch DR. Metastamir: the field of metastasis- regulatory microRNA is spreading. Cancer Res. 2009;69(19):7495-8.
95. Baranwal S, Alahari SK. miRNA control of tumor cell invasion and metastasis. Int J Cancer. Mar 15;126(6):1283-90.
96. Trang P, Weidhaas JB, Slack FJ. microRNAs as potential cancer therapeutics. Oncogene. 2008 Dec;27 Suppl 2:S52-7.