Advances in ovarian cancer proteomics: The quest for biomarkers and improved therapeutic interventions

Expert Review of Proteomics

Volumn 5, Issue 4, 2008, Pages 551-560

  Jurisicova, Andrea ^b   Jurisica, Igor ^c,d,e   Kislinger, Thomas ^a,c,e  

^a Toronto Medical Discovery Tower ^*  (Canada)

^b MOUNT SINAI HOSPITAL   (Canada)

^c PRINCESS MARGARET HOSPITAL   (Canada)

^d UNIVERSITY OF TORONTO   (Canada)

^e UNIVERSITY OF TORONTO   (Canada)

Author keywords

Biomarker; Body fluid; Computational biology; Mouse model; Ovarian cancer; Proteomics

Indexed keywords

BETA CATENIN; BIOLOGICAL MARKER; CELL SURFACE PROTEIN; PHOSPHATIDYLINOSITOL 3,4,5 TRISPHOSPHATE 3 PHOSPHATASE; WNT PROTEIN;

BODY FLUID; CANCER CELL; CELL HETEROGENEITY; CHEMICAL ANALYSIS; EX VIVO STUDY; GLYCOSYLATION; HISTOPATHOLOGY; HUMAN; IN VITRO STUDY; LIQUID CHROMATOGRAPHY; MASS SPECTROMETRY; MATRIX ASSISTED LASER DESORPTION IONIZATION TIME OF FLIGHT MASS SPECTROMETRY; NONHUMAN; OVARY CANCER; PROGNOSIS; PROTEIN ANALYSIS; PROTEOMICS; REVIEW; SENSITIVITY AND SPECIFICITY; SURFACE ENHANCED LASER DESORPTION IONIZATION TIME OF FLIGHT MASS SPECTROMETRY; TECHNOLOGY; VALIDATION PROCESS;

ANIMALS; CA-125 ANTIGEN; FEMALE; HUMANS; OVARIAN NEOPLASMS; PROTEOMICS; TUMOR MARKERS, BIOLOGICAL;

EID: 51149116105     PISSN: 14789450     EISSN: 17448387     Source Type: Journal    
DOI: 10.1586/14789450.5.4.551     Document Type: Review

References (105)

1. Jemal A, Siegel R, Ward E et al. Cancer statistics, 2006. CA Cancer J. Clin. 56(2), 106-130 (2006).
2. Markman M. The myth of measurable disease in ovarian cancer. J. Clin. Oncol. 21(16), 3013-3015 (2003).
3. Markman M. Limitations to the use of the CA-125 antigen level in ovarian cancer. Curr. Oncol. Rep. 5(4), 263-264 (2003).
4. McGuire WP III, Markman M. Primary ovarian cancer chemotherapy: current standards of care. Br. J. Cancer 89(Suppl. 3), S3-S8 (2003).
5. Kurman RJ, Visvanathan K, Roden R, Wu TC, Shih IeM. Early detection and treatment of ovarian cancer: shifting from early stage to minimal volume of disease based on a new model of carcinogenesis. Am. J. Obstet. Gynecol. 198(4), 351-356 (2008).
6. Baker PM, Oliva E. Immunohistochemistry as a tool in the differential diagnosis of ovarian tumors: an update. Int. J. Gynecol. Pathol. 24(1), 39-55 (2005).
7. Shih IeM, Kurman RJ. Ovarian tumorigenesis: a proposed model based on morphological and molecular genetic analysis. Am. J. Pathol. 164(5), 1511-1518 (2004).
8. Shih IeM, Kurman RJ. Molecular pathogenesis of ovarian borderline tumors: new insights and old challenges. Clin. Cancer Res. 11(20), 7273-7279 (2005).
9. Landen CN Jr, Birrer MJ, Sood AK. Early events in the pathogenesis of epithelial ovarian cancer. J. Clin. Oncol. 26(6), 995-1005 (2008).
10. Auersperg N, Ota T, Mitchell GW. Early events in ovarian epithelial carcinogenesis: progress and problems in experimental approaches. Int. J. Gynecol. Cancer 12(6), 691-703 (2002).
11. Colgan TJ. Challenges in the early diagnosis and staging of Fallopian-tube carcinomas associated with BRCA mutations. Int. J. Gynecol. Pathol. 22(2), 109-120 (2003).
12. Lee Y, Medeiros F, Kindelberger D et al. Advances in the recognition of tubal intraepithelial carcinoma: applications to cancer screening and the pathogenesis of ovarian cancer. Adv. Anat. Pathol. 13(1), 1-7 (2006).
13. Kislinger T, Cox B, Kannan A et al. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling. Cell 125(1), 173-186 (2006).
14. Washburn MP, Wolters D, Yates JR III. Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat. Biotechnol. 19(3), 242-247 (2001).
15. Cravatt BF, Simon GM, Yates JR III. The biological impact of mass-spectrometry-based proteomics. Nature 450(7172), 991-1000 (2007).
16. Bast RC Jr, Xu FJ, Yu YH et al. CA 125: the past and the future. Int. J. Biol. Markers 13(4), 179-187 (1998).
17. Hunter VJ, Daly L, Helms M et al. The prognostic significance of CA 125 half-life in patients with ovarian cancer who have received primary chemotherapy after surgical cytoreduction. Am. J. Obstet. Gynecol. 163(4 Pt 1), 1164-1167 (1990).
18. Hunter VJ, Weinberg JB, Haney AF et al. CA 125 in peritoneal fluid and serum from patients with benign gynecologic conditions and ovarian cancer. Gynecol. Oncol. 36(2), 161-165 (1990).
19. Visintin I, Feng Z, Longton G et al. Diagnostic markers for early detection of ovarian cancer. Clin. Cancer Res. 14(4), 1065-1072 (2008).
20. Gramolini A, Peterman S, Kislinger T. Mass spectrometry-based proteomics: a useful tool for biomarker discovery? Clin. Pharmacol. Ther. 83(5), 758-760 (2008).
21. Faca V, Krasnoselsky A, Hanash S. Innovative proteomic approaches for cancer biomarker discovery. Biotechniques 43(3), 279, 281-273, 285 (2007).
22. Pitteri SJ, Hanash SM. Proteomic approaches for cancer biomarker discovery in plasma. Expert Rev. Proteomics 4(5), 589-590 (2007).
23. Hanash SM, Pitteri SJ, Faca VM. Mining the plasma proteome for cancer biomarkers. Nature 452(7187), 571-579 (2008).
24. Adachi J, Kumar C, Zhang Y, Olsen JV, Mann M. The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins. Genome Biol. 7(9), R80 (2006). •• First comprehensive investigation of the human urine proteome.
25. Omenn GS, States DJ, Adamski M et al. Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 5(13), 3226-3245 (2005). •• First comprehensive investigation of the human plasma proteome.
26. States DJ, Omenn GS, Blackwell TW et al. Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study. Nat. Biotechnol. 24(3), 333-338 (2006).
27. Huang L, Fang X. Immunoaffinity fractionation of plasma proteins by chicken IgY antibodies. Methods Mol. Biol. 425, 41-51 (2008).
28. Faca V, Pitteri SJ, Newcomb L et al. Contribution of protein fractionation to depth of analysis of the serum and plasma proteomes. J. Proteome Res. 6(9), 3558-3565 (2007).
29. Whiteaker JR, Zhang H, Eng JK et al. Head-to-head comparison of serum fractionation techniques. J. Proteome Res. 6(2), 828-836 (2007).
30. Anderson NL, Anderson NG. The human plasma proteome: history, character, and diagnostic prospects. Mol. Cell Proteomics 1(11), 845-867 (2002).
31. Anderson NL, Polanski M, Pieper R et al. The human plasma proteome: a nonredundant list developed by combination of four separate sources. Mol. Cell Proteomics 3(4), 311-326 (2004).
32. Zhang H, Li XJ, Martin DB, Aebersold R. Identification and quantification of N-linked glycoproteins using hydrazide chemistry, stable isotope labeling and mass spectrometry. Nat. Biotechnol. 21(6), 660-666 (2003). •• Elegant paper describing the selective isolation of glycoproteins as a subproteome.
33. Lowenthal MS, Mehta AI, Frogale K et al. Analysis of albumin-associated peptides and proteins from ovarian cancer patients. Clin. Chem. 51(10), 1933-1945 (2005).
34. Mehta AI, Ross S, Lowenthal MS et al. Biomarker amplification by serum carrier protein binding. Dis. Markers 19(1), 1-10 (2003).
35. Horth P, Miller CA, Preckel T, Wenz C. Efficient fractionation and improved protein identification by peptide OFFGEL electrophoresis. Mol. Cell Proteomics 5(10), 1968-1974 (2006).
36. Zhang H, Yi EC, Li XJ et al. High throughput quantitative analysis of serum proteins using glycopeptide capture and liquid chromatography mass spectrometry. Mol. Cell Proteomics 4(2), 144-155 (2005).
37. Zhou Y, Aebersold R, Zhang H. Isolation of N-linked glycopeptides from plasma. Anal. Chem. 79(15), 5826-5837 (2007).
38. Stahl-Zeng J, Lange V, Ossola R et al. High sensitivity detection of plasma proteins by multiple reaction monitoring of N-glycosites. Mol. Cell Proteomics 6(10), 1809-1817 (2007).
39. Petricoin EF, Ardekani AM, Hitt BA et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet 359(9306), 572-577 (2002).
40. Baggerly KA, Morris JS, Edmonson SR, Coombes KR. Signal in noise: evaluating reported reproducibility of serum proteomic tests for ovarian cancer. J. Natl Cancer Inst. 97(4), 307-309 (2005).
41. Check E. Proteomics and cancer: running before we can walk? Nature 429(6991), 496-497 (2004).
42. Liotta LA, Lowenthal M, Mehta A et al. Importance of communication between producers and consumers of publicly available experimental data. J. Natl Cancer Inst. 97(4), 310-314 (2005).
43. Lopez MF, Mikulskis A, Kuzdzal S et al. A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples. Clin. Chem. 53(6), 1067-1074 (2007).
44. Bast RC Jr, Badgwell D, Lu Z et al. New tumor markers: CA125 and beyond. Int. J. Gynecol. Cancer 15(Suppl. 3), 274-281 (2005).
45. Drukier AK, Ossetrova N, Schors E et al. High-sensitivity blood-based detection of breast cancer by multi photon detection diagnostic proteomics. J. Proteome Res. 5(8), 1906-1915 (2006).
46. Jackson D, Craven RA, Hutson RC et al. Proteomic profiling identifies afamin as a potential biomarker for ovarian cancer. Clin. Cancer Res. 13(24), 7370-7379 (2007).
47. Zhang Z, Bast RC Jr, Yu Y et al. Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res. 64(16), 5882-5890 (2004).
48. Zhang Z, Yu Y, Xu F et al. Combining multiple serum tumor markers improves detection of stage I epithelial ovarian cancer. Gynecol. Oncol. 107(3), 526-531 (2007).
49. Arshadi N, Jurisica I. Integrating case-based reasoning systems with data mining techniques for discovering and using disease biomarkers. IEEE Trans. Knowl. Data Eng. 17(8), 1127-1137 (2005).
50. Baggerly KA, Coombes KR, Neeley ES. Run batch effects potentially compromise the usefulness of genomic signatures for ovarian cancer. J. Clin. Oncol. 26(7), 1186-1187; author reply 1187-1188 (2008).
51. Baggerly KA, Edmonson SR, Morris JS, Coombes KR. High-resolution serum proteomic patterns for ovarian cancer detection. Endocr. Relat. Cancer 11(4), 583-584; author reply 585-587 (2004).
52. Baggerly KA, Morris JS, Coombes KR. Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments. Bioinformatics 20(5), 777-785 (2004).
53. Baggerly KA, Morris JS, Wang J et al. A comprehensive approach to the analysis of matrix-assisted laser desorption/ionization-time of flight proteomics spectra from serum samples. Proteomics 3(9), 1667-1672 (2003).
54. Coombes KR, Fritsche HA Jr, Clarke C et al. Quality control and peak finding for proteomics data collected from nipple aspirate fluid by surface-enhanced laser desorption and ionization. Clin. Chem. 49(10), 1615-1623 (2003).
55. Coombes KR, Morris JS, Hu J, Edmonson SR, Baggerly KA. Serum proteomics profiling - a young technology begins to mature. Nat. Biotechnol. 23(3), 291-292 (2005).
56. Coombes KR, Tsavachidis S, Morris JS et al. Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform. Proteomics 5(16), 4107-4117 (2005).
57. Gortzak-Uzan L, Ignatchenko A, Evangelou AI et al. A proteome resource of ovarian cancer ascites: integrated proteomic and bioinformatic analyses to identify putative biomarkers. J. Proteome Res. 7(1), 339-351 (2008). • First comprehensive investigation of the human ovarian cancer ascites proteome.
58. Mills GB, May C, McGill M, Roifman CM, Mellors A. A putative new growth factor in ascitic fluid from ovarian cancer patients: identification, characterization, and mechanism of action. Cancer Res. 48(5), 1066-1071 (1988).
59. Whiteaker JR, Zhang H, Zhao L et al. Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer. J. Proteome Res. 6(10), 3962-3975 (2007). •• Elegant paper describing the usefulness of a mouse model of breast cancer for biomarker discovery.
60. Wolf-Yadlin A, Hautaniemi S, Lauffenburger DA, White FM. Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks. Proc. Natl Acad. Sci. USA 104(14), 5860-5865 (2007).
61. Rossant J, McKerlie C. Mouse-based phenogenomics for modelling human disease. Trends Mol. Med. 7(11), 502-507 (2001).
62. Xing D, Orsulic S. A mouse model for the molecular characterization of BRCA1-associated ovarian carcinoma. Cancer Res. 66(18), 8949-8953 (2006).
63. Connolly DC, Bao R, Nikitin AY et al. Female mice chimeric for expression of the simian virus 40 TAg under control of the MISIIR promoter develop epithelial ovarian cancer. Cancer Res. 63(6), 1389-1397 (2003).
64. Dinulescu DM, Ince TA, Quade BJ et al. Role of K-ras and Pten in the development of mouse models of endometriosis and endometrioid ovarian cancer. Nat. Med. 11(1), 63-70 (2005).
65. Roby KF, Taylor CC, Sweetwood JP et al. Development of a syngeneic mouse model for events related to ovarian cancer. Carcinogenesis 21(4), 585-591 (2000).
66. Greenaway J, Moorehead R, Shaw P, Petrik J. Epithelial-stromal interaction increases cell proliferation, survival and tumorigenicity in a mouse model of human epithelial ovarian cancer. Gynecol. Oncol. 108(2), 385-394 (2008).
67. Urzua U, Frankenberger C, Gangi L et al. Microarray comparative genomic hybridization profile of a murine model for epithelial ovarian cancer reveals genomic imbalances resembling human ovarian carcinomas. Tumour Biol. 26(5), 236-244 (2005).
68. Urzua U, Roby KF, Gangi LM et al. Transcriptomic analysis of an in vitro murine model of ovarian carcinoma: functional similarity to the human disease and identification of prospective tumoral markers and targets. J. Cell Physiol. 206(3), 594-602 (2006).
69. Wang H, Kachman MT, Schwartz DR, Cho KR, Lubman DM. Comprehensive proteome analysis of ovarian cancers using liquid phase separation, mass mapping and tandem mass spectrometry: a strategy for identification of candidate cancer biomarkers. Proteomics 4(8), 2476-2495 (2004).
70. Wang H, Kachman MT, Schwartz DR, Cho KR, Lubman DM. A protein molecular weight map of ES2 clear cell ovarian carcinoma cells using a two-dimensional liquid separations/mass mapping technique. Electrophoresis 23(18), 3168-3181 (2002).
71. Wang Y, Wu R, Cho KR et al. Classification of cancer cell lines using an automated two-dimensional liquid mapping method with hierarchical clustering techniques. Mol. Cell Proteomics 5(1), 43-52 (2006).
72. Kim H, Lubman DM. Micro-proteome analysis using micro-chromatofocusing in intact protein separations. J. Chromatogr. A (2008).
73. Zhu Y, Wu R, Sangha N et al. Classifications of ovarian cancer tissues by proteomic patterns. Proteomics 6(21), 5846-5856 (2006).
74. Castronovo V, Kischel P, Guillonneau F et al. Identification of specific reachable molecular targets in human breast cancer using a versatile ex vivo proteomic method. Proteomics 7(8), 1188-1196 (2007).
75. Castronovo V, Waltregny D, Kischel P et al. A chemical proteomics approach for the identification of accessible antigens expressed in human kidney cancer. Mol. Cell Proteomics 5(11), 2083-2091 (2006).
76. Roesli C, Neri D, Rybak JN. In vitro protein biotinylation and sample preparation for the proteomic identification of organ- and disease-specific antigens accessible from the vasculature. Nat. Protoc. 1(1), 192-199 (2006).
77. Sun B, Ranish JA, Utleg AG et al. Shotgun glycopeptide capture approach coupled with mass spectrometry for comprehensive glycoproteomics. Mol. Cell Proteomics 6(1), 141-149 (2007).
78. Faca VM, Ventura AP, Fitzgibbon MP et al. Proteomic analysis of ovarian cancer cells reveals dynamic processes of protein secretion and shedding of extra-cellular domains. PLoS ONE 3(6), e2425 (2008). • One of the first papers extensively analyzing several proteome fractions of ovarian cancer cells.
79. Kulasingam V, Diamandis EP. Proteomics analysis of conditioned media from three breast cancer cell lines: a mine for biomarkers and therapeutic targets. Mol. Cell Proteomics 6(11), 1997-2011 (2007).
80. Sardana G, Marshall J, Diamandis EP. Discovery of candidate tumor markers for prostate cancer via proteomic analysis of cell culture-conditioned medium. Clin. Chem. 53(3), 429-437 (2007).
81. Chen JY, Yan Z, Shen C, Fitzpatrick DP, Wang M. A systems biology approach to the study of cisplatin drug resistance in ovarian cancers. J. Bioinform. Comput. Biol. 5(2a), 383-405 (2007).
82. Le Moguen K, Lincet H, Deslandes E et al. Comparative proteomic analysis of cisplatin sensitive IGROV1 ovarian carcinoma cell line and its resistant counterpart IGROV1-R10. Proteomics 6(19), 5183-5192 (2006).
83. Le Moguen K, Lincet H, Marcelo P et al. A proteomic kinetic analysis of IGROV1 ovarian carcinoma cell line response to cisplatin treatment. Proteomics 7(22), 4090-4101 (2007).
84. Stewart JJ, White JT, Yan X et al. Proteins associated with cisplatin resistance in ovarian cancer cells identified by quantitative proteomic technology and integrated with mRNA expression levels. Mol. Cell Proteomics 5(3), 433-443 (2006).
85. Gagne JP, Ethier C, Gagne P et al. Comparative proteome analysis of human epithelial ovarian cancer. Proteome Sci. 5, 16 (2007).
86. Sheehan KM, Calvert VS, Kay EW et al. Use of reverse phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma. Mol. Cell Proteomics 4(4), 346-355 (2005).
87. Su D, Xu SH, Gu LH. [Comparative proteomics analysis of differentially expressed metastasis-associated proteins in human ovarian cancer cell lines]. Zhonghua Fu Chan Ke Za Zhi 40(9), 619-622 (2005).
88. Wulfkuhle JD, Aquino JA, Calvert VS et al. Signal pathway profiling of ovarian cancer from human tissue specimens using reverse-phase protein microarrays. Proteomics 3(11), 2085-2090 (2003).
89. Sodek KL, Evangelou AI, Ignatchenko A et al. Identification of pathways associated with invasive behavior by ovarian cancer cells using multidimensional protein identification technology (MudPIT). Mol. BioSyst. 4(7), 762-773 (2008). • One of the first papers extensively analyzing the proteome of diverse ovarian cancer cells.
90. Cowherd SM, Espina VA, Petricoin EF III, Liotta LA. Proteomic analysis of human breast cancer tissue with laser-capture microdissection and reverse-phase protein microarrays. Clin. Breast Cancer 5(5), 385-392 (2004).
91. Espina V, Heiby M, Pierobon M, Liotta LA. Laser capture microdissection technology. Expert Rev. Mol. Diagn. 7(5), 647-657 (2007).
92. Jones MB, Krutzsch H, Shu H et al. Proteomic analysis and identification of new biomarkers and therapeutic targets for invasive ovarian cancer. Proteomics 2(1), 76-84 (2002).
93. Legge F, Ferrandina G, Scambia G. From bio-molecular and technology innovations to clinical practice: focus on ovarian cancer. Ann. Oncol. 17(Suppl. 7), vii46-vii48 (2006).
94. Rodriguez AS, Espina BH, Espina V, Liotta LA. Automated laser capture microdissection for tissue proteomics. Methods Mol. Biol. 441, 71-90 (2008).
95. HUPO Human Antibody Initiative www.hupo.org/research/hai
96. Human Protein Atlas www.proteinatlas.org
97. The Gene Ontology www.geneontology.org
98. KEGG: Kyoto Encyclopedia of Genes and Genomes www.kegg.jp
99. Welcome to the Worldwide Protein Data Bank www.wwpdb.org
100. ExPASy - UniProt Knowledgebase: Swiss-Prot and TrEMBL http://ca.expasy.org/sprot
101. Oncomine (Research) - Cancer Profiling Database www.oncomine.org
102. Weka 3 - Data Mining with Open Source Machine Learning Software in Java www.cs.waikato.ac.nz/ml/weka
103. The R Project for Statistical Computing www.r-project.org
104. Cytoscape: Analyzing and Visualizing Network Data www.cytoscape.org
105. NAViGaTOR (Network Analysis, Visualization, & Graphing TORonto) http://ophid.utoronto.ca/navigator