Networks in proteomics analysis of cancer

Current Opinion in Biotechnology

Volumn 24, Issue 6, 2013, Pages 1122-1128

  Goh, Wilson Wen Bin ^a,b   Wong, Limsoon ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL INFORMATION; BIOLOGICAL NETWORKS; COMPLEX RELATIONSHIPS; CONTEXTUALIZATION; NETWORK-BASED; NETWORK-BASED ANALYSIS; PROTEOMIC IDENTIFICATION; QUALITY DATA;

COMPLEX NETWORKS; DISEASES; HARDWARE; MOLECULAR BIOLOGY; PROTEINS;

QUALITY CONTROL;

TUMOR MARKER;

CANCER DIAGNOSIS; CARCINOGENESIS; CAUSAL ATTRIBUTION; DISEASE ASSOCIATION; HUMAN; MALIGNANT NEOPLASTIC DISEASE; MOLECULAR DIAGNOSIS; MOLECULAR PATHOLOGY; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEOMICS; REVIEW; SIGNAL TRANSDUCTION;

GENOMICS; HUMANS; MODELS, BIOLOGICAL; NEOPLASMS; PROTEIN INTERACTION MAPS; PROTEINS; PROTEOMICS; TUMOR MARKERS, BIOLOGICAL;

EID: 84887625418     PISSN: 09581669     EISSN: 18790429     Source Type: Journal    
DOI: 10.1016/j.copbio.2013.02.011     Document Type: Review

References (54)

1. Tan H.T., Lee Y.H., Chung M.C. Cancer proteomics. Mass Spectrom Rev 2012, 31:583-605.
2. Hanash S., Taguchi A. The grand challenge to decipher the cancer proteome. Nat Rev Cancer 2010, 10:652-660.
3. White F.M. The potential cost of high-throughput proteomics. Sci Signal 2011, 4:pe8.
4. Pe'er D., Hacohen N. Principles and strategies for developing network models in cancer. Cell 2011, 144:864-873.
5. Kreeger P.K., Lauffenburger D.A. Cancer systems biology: a network modeling perspective. Carcinogenesis 2010, 31:2-8.
6. Goh W.W., Lee Y.H., Chung M., Wong L. How advancement in biological network analysis methods empowers proteomics. Proteomics 2012, 12:550-563.
7. Bell A.W., Deutsch E.W., Au C.E., Kearney R.E., Beavis R., Sechi S., Nilsson T., Bergeron J.J., Group H.T.S.W. A HUPO test sample study reveals common problems in mass spectrometry-based proteomics. Nat Methods 2009, 6:423-430.
8. Nagaraj N., Wisniewski J.R., Geiger T., Cox J., Kircher M., Kelso J., Paabo S., Mann M. Deep proteome and transcriptome mapping of a human cancer cell line. Mol Syst Biol 2011, 7:548.
9. Beck M., Schmidt A., Malmstroem J., Claassen M., Ori A., Szymborska A., Herzog F., Rinner O., Ellenberg J., Aebersold R. The quantitative proteome of a human cell line. Mol Syst Biol 2011, 7:549.
10. Goh W.W., Lee Y.H., Ramdzan Z.M., Chung M.C., Wong L., Sergot M.J. A network-based maximum link approach towards MS identifies potentially important roles for undetected ARRB1/2 and ACTB in liver cancer progression. Int J Bioinform Res Appl 2012, 8:155-170.
11. Ostlund G., Lindskog M., Sonnhammer E.L. Network-based identification of novel cancer genes. Mol Cell Proteomics 2010, 9:648-655.
12. Goh W.W., Lee Y.H., Zubaidah R.M., Jin J., Dong D., Lin Q., Chung M.C., Wong L. Network-based pipeline for analyzing MS data: an application toward liver cancer. J Proteome Res 2011, 10:2261-2272.
13. Gillet L.C., Navarro P., Tate S., Rost H., Selevsek N., Reiter L., Bonner R., Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics 2012, 11. O111.016717.
14. Goh W.W., Lee Y.H., Ramdzan Z.M., Sergot M.J., Chung M., Wong L. Proteomics signature profiling (PSP): a novel contextualization approach for cancer proteomics. J Proteome Res 2012, 11:1571-1581.
15. Albrethsen J., Bogebo R., Moller C.H., Olsen J.A., Raskov H.H., Gammeltoft S. Candidate biomarker verification: critical examination of a serum protein pattern for human colorectal cancer. Proteomics Clin Appl 2012, 6:182-189.
16. Lund H., Lovsletten K., Paus E., Halvorsen T.G., Reubsaet L. Immuno-MS based targeted proteomics: highly specific, sensitive, and reproducible human chorionic gonadotropin determination for clinical diagnostics and doping analysis. Anal Chem 2012, 84:7926-7932.
17. Venet D., Dumont J.E., Detours V. Most random gene expression signatures are significantly associated with breast cancer outcome. PLoS Comput Biol 2011, 7:e1002240.
18. Ng C., Weigelt B., Grigoriadis A., Reis-Filho J.S. Prognostic signatures in breast cancer: correlation does not imply causation. Breast Cancer Res 2012, 14:313.
19. Shi M., Beauchamp R.D., Zhang B. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients. PLoS One 2012, 7:e41292.
20. Vandin F., Clay P., Upfal E., Raphael B.J. Discovery of mutated subnetworks associated with clinical data in cancer. Pac Symp Biocomput 2012, 55-66.
21. Vandin F., Upfal E., Raphael B.J. Finding driver pathways in cancer: models and algorithms. Algorithms Mol Biol 2012, 7:23.
22. Vandin F., Upfal E., Raphael B.J. De novo discovery of mutated driver pathways in cancer. Genome Res 2012, 22:375-385.
23. Imielinski M., Cha S., Rejtar T., Richardson E.A., Karger B.L., Sgroi D.C. Integrated proteomic, transcriptomic, and biological network analysis of breast carcinoma reveals molecular features of tumorigenesis and clinical relapse. Mol Cell Proteomics 2012, 11. M111.014910.
24. Yu Y., Shen H., Yu H., Zhong F., Zhang Y., Zhang C., Zhao J., Li H., Chen J., Liu Y., et al. Systematic proteomic analysis of human hepotacellular carcinoma cells reveals molecular pathways and networks involved in metastasis. Mol Biosyst 2011, 7:1908-1916.
25. Wu C.C., Hsu C.W., Chen C.D., Yu C.J., Chang K.P., Tai D.I., Liu H.P., Su W.H., Chang Y.S., Yu J.S. Candidate serological biomarkers for cancer identified from the secretomes of 23 cancer cell lines and the human protein atlas. Mol Cell Proteomics 2010, 9:1100-1117.
26. Andersen J.N., Sathyanarayanan S., Di Bacco A., Chi A., Zhang T., Chen A.H., Dolinski B., Kraus M., Roberts B., Arthur W., et al. Pathway-based identification of biomarkers for targeted therapeutics: personalized oncology with PI3K pathway inhibitors. Sci Transl Med 2010, 2:43ra55.
27. Moritz A., Li Y., Guo A., Villen J., Wang Y., MacNeill J., Kornhauser J., Sprott K., Zhou J., Possemato A., et al. Akt-RSK-S6 kinase signaling networks activated by oncogenic receptor tyrosine kinases. Sci Signal 2010, 3:ra64.
28. Bodenmiller B., Wanka S., Kraft C., Urban J., Campbell D., Pedrioli P.G., Gerrits B., Picotti P., Lam H., Vitek O., et al. Phosphoproteomic analysis reveals interconnected system-wide responses to perturbations of kinases and phosphatases in yeast. Sci Signal 2010, 3:rs4.
29. Muller T., Schrotter A., Loosse C., Helling S., Stephan C., Ahrens M., Uszkoreit J., Eisenacher M., Meyer H.E., Marcus K. Sense and nonsense of pathway analysis software in proteomics. J Proteome Res 2011, 10:5398-5408.
30. Soh D., Dong D., Guo Y., Wong L. Consistency, comprehensiveness, and compatibility of pathway databases. BMC Bioinformatics 2010, 11:449.
31. Stobbe M.D., Houten S.M., Jansen G.A., van Kampen A.H., Moerland P.D. Critical assessment of human metabolic pathway databases: a stepping stone for future integration. BMC Syst Biol 2011, 5:165.
32. Ideker T., Krogan N.J. Differential network biology. Mol Syst Biol 2012, 8:565.
33. Geistlinger L., Csaba G., Kuffner R., Mulder N., Zimmer R. From sets to graphs: towards a realistic enrichment analysis of transcriptomic systems. Bioinformatics 2011, 27:i366-i373.
34. Zampieri M., Legname G., Segre D., Altafini C. A system-level approach for deciphering the transcriptional response to prion infection. Bioinformatics 2011, 27:3407-3414.
35. Chindelevitch L., Ziemek D., Enayetallah A., Randhawa R., Sidders B., Brockel C., Huang E.S. Causal reasoning on biological networks: interpreting transcriptional changes. Bioinformatics 2012, 28:1114-1121.
36. Higareda-Almaraz J.C., Enriquez-Gasca Mdel R., Hernandez-Ortiz M., Resendis-Antonio O., Encarnacion-Guevara S. Proteomic patterns of cervical cancer cell lines, a network perspective. BMC Syst Biol 2011, 5:96.
37. 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 Comput Biol 2010, 6.
38. Bandyopadhyay S., Mehta M., Kuo D., Sung M.K., Chuang R., Jaehnig E.J., Bodenmiller B., Licon K., Copeland W., Shales M., et al. Rewiring of genetic networks in response to DNA damage. Science 2010, 330:1385-1389.
39. Moulick K., Ahn J.H., Zong H., Rodina A., Cerchietti L., Gomes DaGama E.M., Caldas-Lopes E., Beebe K., Perna F., Hatzi K., et al. Affinity-based proteomics reveal cancer-specific networks coordinated by Hsp90. Nat Chem Biol 2011, 7:818-826.
40. Wu M., Li X.L., Kwoh C.K., Ng S.K., Wong L. Discovery of protein complexes with core-attachment structures from tandem affinity purification (TAP) data. J Comput Biol 2012, 19:1027-1042.
41. Bisson N., James D.A., Ivosev G., Tate S.A., Bonner R., Taylor L., Pawson T. Selected reaction monitoring mass spectrometry reveals the dynamics of signaling through the GRB2 adaptor. Nat Biotechnol 2011, 29:653-658.
42. Bensimon A., Heck A.J., Aebersold R. Mass spectrometry-based proteomics and network biology. Annu Rev Biochem 2012, 81:379-405.
43. Lee M.J., Ye A.S., Gardino A.K., Heijink A.M., Sorger P.K., MacBeath G., Yaffe M.B. Sequential application of anticancer drugs enhances cell death by rewiring apoptotic signaling networks. Cell 2012, 149:780-794.
44. Nibbe R.K., Koyuturk M., Chance M.R. An integrative-omics approach to identify functional sub-networks in human colorectal cancer. PLoS Comput Biol 2010, 6:e1000639.
45. D'Aguanno S., D'Agnano I., De Canio M., Rossi C., Bernardini S., Federici G., Urbani A. Shotgun proteomics and network analysis of neuroblastoma cell lines treated with curcumin. Mol Biosyst 2012, 8:1068-1077.
46. Graumann J., Scheltema R.A., Zhang Y., Cox J., Mann M. A framework for intelligent data acquisition and real-time database searching for shotgun proteomics. Mol Cell Proteomics 2012, 11. M111.013185.
47. Pierobon M., Vanmeter A.J., Moroni N., Galdi F., Petricoin E.F. Reverse-phase protein microarrays. Methods Mol Biol 2012, 823:215-235.
48. Kozuka-Hata H., Tasaki S., Oyama M. Phosphoproteomics-based systems analysis of signal transduction networks. Front Physiol 2011, 2:113.
49. Lee Y.Y., McKinney K.Q., Ghosh S., Iannitti D.A., Martinie J.B., Caballes F.R., Russo M.W., Ahrens W.A., Lundgren D.H., Han D.K., et al. Subcellular tissue proteomics of hepatocellular carcinoma for molecular signature discovery. J Proteome Res 2011, 10:5070-5083.
50. Wei Y., Tong J., Taylor P., Strumpf D., Ignatchenko V., Pham N.A., Yanagawa N., Liu G., Jurisica I., Shepherd F.A., et al. Primary tumor xenografts of human lung adeno and squamous cell carcinoma express distinct proteomic signatures. J Proteome Res 2011, 10:161-174.
51. Zhu W., Fang C., Gramatikoff K., Niemeyer C.C., Smith J.W. Proteins and an inflammatory network expressed in colon tumors. J Proteome Res 2011, 10:2129-2139.
52. Huttenhain R., Soste M., Selevsek N., Rost H., Sethi A., Carapito C., Farrah T., Deutsch E.W., Kusebauch U., Moritz R.L., et al. Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics. Sci Transl Med 2012, 4:142ra194.
53. Wen J.J., Zago M.P., Nunez S., Gupta S., Burgos F.N., Garg N.J. Serum proteomic signature of human chagasic patients for the identification of novel potential protein biomarkers of disease. Mol Cell Proteomics 2012, 11:435-452.
54. Hilger M., Mann M. Triple SILAC to determine stimulus specific interactions in the Wnt pathway. J Proteome Res 2012, 11:982-994.