Biomarker identification for prostate cancer and lymph node metastasis from microarray data and protein interaction network using gene prioritization method

The Scientific World Journal

Volumn 2012, Issue , 2012, Pages

  Arias, Carlos Roberto ^a,b   Yeh, Hsiang Yuan ^a   Soo, Von Wun ^a  

^a NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^b UNIVERSIDAD TECNOLÓGICA CENTROAMERICANA UNITEC   (Honduras)

Author keywords

[No Author keywords available]

Indexed keywords

2 5A DEPENDENT RIBONUCLEASE; ANDROGEN RECEPTOR; BRCA2 PROTEIN; CD82 ANTIGEN; CHECKPOINT KINASE 2; ELAC PROTEIN 2; EPHRIN RECEPTOR B2; HEREDITARY PROSTATE CANCER 1; HUNTINGTIN INTERACTING PROTEIN 1; KRUPPEL LIKE FACTOR 6; MACROPHAGE SCAVENGER RECEPTOR TYPE I AND II; MAX INTERACTING PROTEIN 1; MITOTIC SPINDLE ASSEMBLY CHECKPOINT PROTEIN MAD; PHOSPHATIDYLINOSITOL 3,4,5 TRISPHOSPHATE 3 PHOSPHATASE; PREDISPOSING FOR PROSTATE CANCER PROTEIN; TUMOR MARKER; UNCLASSIFIED DRUG;

ARTICLE; BIOINFORMATICS; DATA BASE; GENE PRIORITIZATION FROM MICROARRAY DATA BASED ON SHORTEST PATH EXTENDED WITH STRUCTURAL AND BIOLOGICAL PROPERTIES AND EDGE FLUX USING VOTING SCHEME; GENE TARGETING; LYMPH NODE METASTASIS; MICROARRAY ANALYSIS; PROSTATE CANCER; PROTEIN INTERACTION; QUALITY CONTROL; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETICS; HUMAN; MALE; METABOLISM; METHODOLOGY; PATHOPHYSIOLOGY; PHYSIOLOGY; PROSTATE TUMOR; PROTEIN PROTEIN INTERACTION; SYSTEMS BIOLOGY;

GENE EXPRESSION PROFILING; HUMANS; LYMPHATIC METASTASIS; MALE; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PROSTATIC NEOPLASMS; PROTEIN INTERACTION MAPS; SYSTEMS BIOLOGY; TUMOR MARKERS, BIOLOGICAL;

EID: 84862323263     PISSN: None     EISSN: 1537744X     Source Type: Journal    
DOI: 10.1100/2012/842727     Document Type: Article

References (59)

1. Vogelstein B., Kinzler K. W., Cancer genes and the pathways they control Nature Medicine 2004 10 8 789 799 (Pubitemid 39070849)
2. Futreal P. A., Coin L., Marshall M., Down T., Hubbard T., Wooster R., Rahman N., Stratton M. R., A census of human cancer genes Nature Reviews Cancer 2004 4 3 177 183 (Pubitemid 38337497)
3. Huang S. M., Harari P. M., Epidermal growth factor receptor inhibition in cancer therapy: biology, rationale and preliminary clinical results Investigational New Drugs 1999 17 3 259 269 (Pubitemid 30037958)
4. Edwards A. M., Kus B., Jansen R., Greenbaum D., Greenblatt J., Gerstein M., Bridging structural biology and genomics: assessing protein interaction data with known complexes Trends in Genetics 2002 18 10 529 536 (Pubitemid 35287028)
5. Tiffin N., Kelso J. F., Powell A. R., Pan H., Bajic V. B., Hide W. A., Integration of text- and data-mining using ontologies successfully selects disease gene candidates Nucleic Acids Research 2005 33 5 1544 1552 (Pubitemid 41418383)
6. van Driel M. A., Cuelenaere K., Kemmeren P. P. C. W., Leunissen J. A. M., Brunner H. G., A new web-based data mining tool for the identification of candidate genes for human genetic disorders European Journal of Human Genetics 2003 11 1 57 63 (Pubitemid 36175784)
7. Piro R. M., Molineris I., Ala U., Provero P., di Cunto F., Candidate gene prioritization based on spatially mapped gene expression: an application to XLMR Bioinformatics 2010 26 18 i618 i624. in Proceedings of the 9th European Conference on Computational Biology, Ghent, Belgium, SEP 26-29, 2010
8. Lpez-Bigas N., Ouzounis C. A., Genome-wide identification of genes likely to be involved in human genetic disease Nucleic Acids Research 2004 32 10 3108 3114 (Pubitemid 39023002)
9. Adie E. A., Adams R. R., Evans K. L., Porteous D. J., Pickard B. S., Speeding disease gene discovery by sequence based candidate prioritization BMC Bioinformatics 2005 6, article 55
10. Adie E. A., Adams R. R., Evans K. L., Porteous D. J., Pickard B. S., SUSPECTS: enabling fast and effective prioritization of positional candidates Bioinformatics 2006 22 6 773 774
11. The Gene Ontology Consortium, The gene ontology project in 2008 Nucleic Acids Research 2008 36 440 444
12. Hunter S., Apweiler R., Attwood T. K., Bairoch A., Bateman A., Binns D., Bork P., Das U., Daugherty L., Duquenne L., Finn R. D., Gough J., Haft D., Hulo N., Kahn D., Kelly E., Laugraud A., Letunic I., Lonsdale D., Lopez R., Madera M., Maslen J., Mcanulla C., McDowall J., Mistry J., Mitchell A., Mulder N., Natale D., Orengo C., Quinn A. F., Selengut J. D., Sigrist C. J. A., Thimma M., Thomas P. D., Valentin F., Wilson D., Wu C. H., Yeats C., InterPro: the integrative protein signature database Nucleic Acids Research 2009 37 1 D211 D215
13. Schlicker A., Lengauer T., Albrecht M., Improving disease gene prioritization using the semantic similarity of gene ontology terms Bioinformatics 2010 26 18 i561 i567. in Proceedings of the 9th European Conference on Computational Biology, Ghent, Belgium, SEP 26-29, 2010
14. Schlicker A., Rahnenfhrer J., Albrecht M., Lengauer T., Domingues F. S., GOTax: investigating biological processes and biochemical activities along the taxonomic tree Genome Biology 2007 8 3, article R33
15. Ashburner M., Ball C. A., Blake J. A., Botstein D., Butler H., Cherry J. M., Davis A. P., Dolinski K., Dwight S. S., Eppig J. T., Harris M. A., Hill D. P., Issel-Tarver L., Kasarskis A., Lewis S., Matese J. C., Richardson J. E., Ringwald M., Rubin G. M., Sherlock G., Gene ontology: tool for the unification of biology Nature Genetics 2000 25 1 25 29 (Pubitemid 30257031)
16. Dolan M. E., Ni L., Camon E., Blake J. A., A procedure for assessing GO annotation consistency Bioinformatics 2005 21 1 i136 i143
17. Aerts S., Lambrechts D., Maity S., Van Loo P., Coessens B., De Smet F., Tranchevent L. C., De Moor B., Marynen P., Hassan B., Carmeliet P., Moreau Y., Gene prioritization through genomic data fusion Nature Biotechnology 2006 24 5 537 544
18. Chen J., Bardes E. E., Aronow B. J., Jegga A. G., Toppgene Suite for gene list enrichment analysis and candidate gene prioritization Nucleic Acids Research 2009 37 2 W305 W311
19. Ma X., Lee H., Wang L., Sun F., CGI: a new approach for prioritizing genes by combining gene expression and protein-protein interaction data Bioinformatics 2007 23 2 215 221 (Pubitemid 46189612)
20. Hutz J. E., Kraja A. T., McLeod H. L., Province M. A., CANDID: a flexible method for prioritizing candidate genes for complex human traits Genetic Epidemiology 2008 32 8 779 790
21. Mani K. M., Lefebvre C., Wang K., Lim W. K., Basso K., Dalla-Favera R., Califano A., A systems biology approach to prediction of oncogenes and molecular perturbation targets in B-cell lymphomas Molecular Systems Biology 2008 4, article 169
22. Erten S., Koyuturk M., Pizzuti C., Ritchie M., Giacobini M., Role of centrality in network-based prioritization of disease genes Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics 2010 6023 Berlin, Germany Springer 13 25 Lecture Notes in Computer Science
23. Benson M., Breitling R., Network theory to understand microarray studies of complex diseases Current Molecular Medicine 2006 6 6 695 701 (Pubitemid 44377768)
24. Perez-Iratxeta C., Bork P., Andrade-Navarro M. A., Update of the G2D tool for prioritization of gene candidates to inherited diseases Nucleic Acids Research 2007 35 W212 216
25. Wu X., Jiang R., Zhang M. Q., Li S., Network-based global inference of human disease genes Molecular Systems Biology 2008 4, article 189
26. Lage K., Karlberg E. O., Strling Z. M., lason P.., Pedersen A. G., Rigina O., Hinsby A. M., Tmer Z., Pociot F., Tommerup N., Moreau Y., Brunak S., A human phenome-interactome network of protein complexes implicated in genetic disorders Nature Biotechnology 2007 25 3 309 316 (Pubitemid 46402863)
27. Han J. D. J., Berlin N., Hao T., Goldberg D. S., Berriz G. F., Zhang L. V., Dupuy D., Walhout A. J.M., Cusick M. E., Roth F. P., Vidal M., Evidence for dynamically organized modularity in the yeast protein-protein interaction network Nature 2004 430 6995 88 93 (Pubitemid 38915230)
28. Erten S., Bebek G., Koyutuerk M., Bafna V., Sahinalp S., Disease gene prioritization based on topological similarity inprotein-protein interaction networks Research in Computational Biology 2011 6577 Berlin, Germany Springer 54 68 Lecture Notes in Bioinformatics. in Proceedings of the 15th Annual International Conference on Research in Computational Molecular Biology, Simon Fraser University, Lab for Computational Biology, Vancouver, Canada, 2011
29. zgr A., Vu T., Erkan G., Radev D. R., Identifying gene-disease associations using centrality on a literature mined gene-interaction network Bioinformatics 2008 24 13 i277 i285
30. Karni S., Soreq H., Sharan R., A network-based method for predicting disease-causing genes Journal of Computational Biology 2009 16 2 181 189
31. Cai J. J., Borenstein E., Petrov D. A., Broker genes in human disease Genome Biology and Evolution 2010 2 815 825
32. Junker B. H., Schreiber F., Analysis of Biological Networks 2008 Hoboken, NJ, USA John Wiley Sons Wiley Series on Bioinformatics: Computational Techniques and Engineering
33. Prieto C., Rivas J. D. L., APID: agile protein interaction DataAnalyzer Nucleic Acids Research 2006 34 W298 W302
34. Liu H.-C., Arias C. R., Soo V.-W., Bioir: an approach to public domain resource integration of humanprotein-protein interaction Proceeding of the 7th Asia Pacific Bioinformatics Conference 2009
35. Lapointe J., Li C., Higgins J. P., Van De Rijn M., Bair E., Montgomery K., Ferrari M., Egevad L., Rayford W., Bergerheim U., Ekman P., DeMarzo A. M., Tibshiran R., Botstein D., Brown P. O., Brooks J. D., Pollack J. R., Gene expression profiling identifies clinically relevant subtypes of prostate cancer Proceedings of the National Academy of Sciences of the United States of America 2004 101 3 811 816 (Pubitemid 38121040)
36. Hamosh A., Scott A. F., Amberger J. S., Bocchini C. A., McKusick V. A., Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders Nucleic Acids Research 2005 33 D514 D517
37. zgr A., Vu T., Erkan G., Radev D. R., Identifying gene-disease associations using centrality on a literature mined gene-interaction network Bioinformatics 2008 24 13 i277 i285
38. Kanehisa M., Goto S., Kawashima S., Okuno Y., Hattori M., The KEGG resource for deciphering the genome Nucleic Acids Research 2004 32 D277 D280
39. Li L. C., Zhao H., Shiina H., Kane C. J., Dahiya R., PGDB: a curated and integrated database of genes related to the prostate Nucleic Acids Research 2003 31 1 291 293 (Pubitemid 36150387)
40. Goh K. I., Cusick M. E., Valle D., Childs B., Vidal M., Barabsi A. L., The human disease network Proceedings of the National Academy of Sciences of the United States of America 2007 104 21 8685 8690 (Pubitemid 47175372)
41. Rhodes D. R., Chinnaiyan A. M., Integrative analysis of the cancer transcriptome Nature Genetics 2005 37 6 S31 S37
42. Komurov K., White M. A., Ram P. T., Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data PLoS Computational Biology 2010 6 8
43. Grigoriev A., A relationship between gene expression and protein interactions on the proteome scale: analysis of the bacteriophage T7 and the yeast Saccharomyces cerevisiae Nucleic Acids Research 2001 29 17 3513 3519 (Pubitemid 32898765)
44. de Borda J. C., Memoire sur les Elections au Scrutin 1781 Paris, France Histoire de l'Academie Royale des Sciences
45. van Erp M., Schomaker L., Zhang B., Ding D., Zhang L., Variants of the borda count method for combining ranked classifier hypotheses Proceedings of the 7th International Workshop of Frontiers in Handwriting Recognition 2000 443 452 The Learning Methodology Inspired by Human's Intelligence
46. Chen X., Yan G., Ren W., Qu J.-B., Modularized random walk with restart for candidate diseasegenes prioritization Systems Biology 2009 353 360
47. Edwards J., Bartlett J. M. S., The androgen receptor and signal-transduction pathways in hormone-refractory prostate cancer. Part 1: modifications to the androgen receptor BJU International 2005 95 9 1320 1326 (Pubitemid 40799454)
48. Festuccia C., Gravina G. L., Biordi L., D'Ascenzo S., Dolo V., Ficorella C., Ricevuto E., Tombolini V., Effects of EGFR tyrosine kinase inhibitor erlotinib in prostate cancer cells in vitro Prostate 2009 69 14 1529 1537
49. Gurel B., Iwata T., Koh C. M., Jenkins R. B., Lan F., Van Dang C., Hicks J. L., Morgan J., Cornish T. C., Sutcliffe S., Isaacs W. B., Luo J., De Marzo A. M., Nuclear MYC protein overexpression is an early alteration in human prostate carcinogenesis Modern Pathology 2008 21 9 1156 1167
50. Vandenberg C., Guan X., Vonhoff D., DNA-sequence amplification in human prostate-cancer identified by chromosome microdissectionpotential prognostic implications Clinical Cancer Research 1995 1 1 11 18
51. Bubendorf L., Kononen J., Koivisto P., Schraml P., Moch H., Gasser T. C., Willi N., Mihatsch M. J., Sauter G., Kallioniemi O. P., Survey of gene amplifications during prostate cancer progression by high-throughput fluorescence in situ hybridization on tissue microarrays Cancer Research 1999 59 4 803 806 (Pubitemid 29086730)
52. Abate-Shen C., Shen M. M., Molecular genetics of prostate cancer Genes and Development 2000 14 19 2410 2434
53. Yeh H. Y., Cheng S. W., Lin Y. C., Yeh C. Y., Lin S. F., Soo V. W., Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency BMC Medical Genomics 2009 2, article 70
54. Keller E. T., Fu Z., Brennan M., The biology of a prostate cancer metastasis suppressor protein: raf kinase inhibitor protein Journal of Cellular Biochemistry 2005 94 2 273 278 (Pubitemid 41420306)
55. Bedolla R. G., Wang Y., Asuncion A., Chamie K., Siddiqui S., Mudryj M. M., Prihoda T. J., Siddiqui J., Chinnaiyan A. M., Mehra R., De Vere White R. W., Ghosh P. M., Nuclear versus cytoplasmic localization of filamin a in prostate cancer: immunohistochemical correlation with metastases Clinical Cancer Research 2009 15 3 788 796
56. Wong C.-Y. A., Wuriyanghan H., Xie Y., Epigenetic regulation of phosphatidylinositol 3,4,5-triphosphate-dependent rac exchanger 1 gene expression in prostate cancer cells Journal of Biological Chemistry 2011 286 25813 25822
57. Bratland A., Boender P. J., Hoifodt H. K., Osteoblast-induced EGFR/ERBB2 signaling in androgen-sensitiveprostate carcinoma cells characterized by multiplex kinase activity profiling Clinical Experimental Metastasis 2009 26 485 496
58. Ding Z., Wu C. J., Chu G. C., Xiao Y., Ho D., Zhang J., Perry S. R., Labrot E. S., Wu X., Lis R., Hoshida Y., Hiller D., Hu B., Jiang S., Zheng H., Stegh A. H., Scott K. L., Signoretti S., Bardeesy N., Wang Y. A., Hill D. E., Golub T. R., Stampfer M. J., Wong W. H., Loda M., Mucci L., Chin L., Depinho R. A., SMAD4-dependent barrier constrains prostate cancer growth and metastatic progression Nature 2011 470 7333 269 276
59. Serk I. P., Zhang J., Phillips K. A., Araujo J. C., Najjar A. M., Volgin A. Y., Gelovani J. G., Kim S. J., Wang Z., Gallick G. E., Targeting Src family kinases inhibits growth and lymph node metastases of prostate cancer in an orthotopic nude mouse model Cancer Research 2008 68 9 3323 3333