Table of Contents
International Journal of Proteomics
Volume 2012 (2012), Article ID 926427, 10 pages
http://dx.doi.org/10.1155/2012/926427
Review Article

MALDI-MS-Based Profiling of Serum Proteome: Detection of Changes Related to Progression of Cancer and Response to Anticancer Treatment

Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska Curie Memorial Cancer Center and Institute of Oncology Gliwice Branch, Wybrzeże Armii Krajowej 15, 44-101 Gliwice, Poland

Received 23 February 2012; Revised 12 June 2012; Accepted 12 June 2012

Academic Editor: Vladimir Uversky

Copyright © 2012 Monika Pietrowska and Piotr Widłak. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. R. D. Riley, K. R. Abrams, A. J. Sutton et al., “Reporting of prognostic markers: current problems and development of guidelines for evidence-based practice in the future,” British Journal of Cancer, vol. 88, no. 8, pp. 1191–1198, 2003. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Duffy, “Predictive markers in breast and other cancers: a review,” Clinical Chemistry, vol. 51, no. 3, pp. 494–503, 2005. View at Publisher · View at Google Scholar · View at Scopus
  3. C. Han, J. Ma, J. Zhao, Y. Zhou, W. Jing, and H. Zou, “EGFR mutations, gene amplification, and protein expression and KRAS mutations in primary and metastatic tumors of nonsmall cell lung cancers and their clinical implications: a meta-analysis,” Cancer Investigation, vol. 29, no. 9, pp. 626–634, 2011. View at Google Scholar
  4. L. A. Liotta and E. F. Petricoin III, “The promise of proteomics,” Clinical Advances in Hematology and Oncology, vol. 1, no. 8, pp. 460–462, 2003. View at Google Scholar
  5. L. A. Liotta and E. F. Petricoin, “Mass spectrometry-based protein biomarker discovery: solving the remaining challenges to reach the promise of clinical benefit,” Clinical Chemistry, vol. 56, no. 10, pp. 1641–1642, 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. M. F. Lopez, A. Mikulskis, S. Kuzdzal et al., “A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples,” Clinical Chemistry, vol. 53, no. 6, pp. 1067–1074, 2007. View at Publisher · View at Google Scholar · View at Scopus
  7. L. A. Liotta and E. F. Petricoin, “Serum peptidome for cancer detection: spinning biologic trash into diagnostic gold,” The Journal of Clinical Investigation, vol. 116, no. 1, pp. 26–30, 2006. View at Publisher · View at Google Scholar · View at Scopus
  8. R. A. W. Johnstone and M. E. Rose, Spektrometria Mas, Wydawnictwo Naukowe PWN, Warszawa, Poland, 2001.
  9. R. Mazurkiewicz, “Spektrometria masowa,” w: Metody spektroskopowe i ich zastosowanie do identyfikacji związków organicznych, red. W. Zieliński, A. Rajca, WNT, Warszawa, pp. 436-537 [in polish], 2000.
  10. R. Aebersold and M. Mann, “Mass spectrometry-based proteomics,” Nature, vol. 422, no. 6928, pp. 198–207, 2003. View at Publisher · View at Google Scholar · View at Scopus
  11. G. L. Hortin, “The MALDI-TOF mass spectrometric view of the plasma proteome and peptidome,” Clinical Chemistry, vol. 52, no. 7, pp. 1223–1237, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. N. S. Azad, N. Rasool, C. M. Annunziata, L. Minasian, G. Whiteley, and E. C. Kohn, “Proteomics in clinical trials and practice: present uses and future promise,” Molecular and Cellular Proteomics, vol. 5, no. 10, pp. 1819–1829, 2006. View at Publisher · View at Google Scholar · View at Scopus
  13. N. Ahmed, K. T. Oliva, G. Barker et al., “Proteomic tracking of serum protein isoforms as screening biomarkers of ovarian cancer,” Proteomics, vol. 5, no. 17, pp. 4625–4636, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. E. M. Posadas, F. Simpkins, L. A. Liotta, C. MacDonald, and E. C. Kohn, “Proteomic analysis for the early detection and rational treatment of cancer—realistic hope?” Annals of Oncology, vol. 16, no. 1, pp. 16–22, 2005. View at Publisher · View at Google Scholar · View at Scopus
  15. L. A. Liotta, M. Ferrari, and E. F. Petricoin, “Clinical proteomics: written in blood,” Nature, vol. 425, no. 6961, p. 905, 2003. View at Google Scholar · View at Scopus
  16. P. Findeisen and M. Neumaier, “Mass spectrometry-based clinical proteomics profiling: current status and future directions,” Expert Review of Proteomics, vol. 6, no. 5, pp. 457–459, 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. P. Findeisen and M. Neumaier, “Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective,” Clinical Chemistry and Laboratory Medicine, vol. 47, no. 6, pp. 666–684, 2009. View at Publisher · View at Google Scholar · View at Scopus
  18. J. Solassol, W. Jacot, L. Lhermitte, N. Boulle, T. Maudelonde, and A. Mangé, “Clinical proteomics and mass spectrometry profiling for cancer detection,” Expert Review of Proteomics, vol. 3, no. 3, pp. 311–320, 2006. View at Publisher · View at Google Scholar · View at Scopus
  19. E. F. Petricoin, A. M. Ardekani, B. A. Hitt et al., “Use of proteomic patterns in serum to identify ovarian cancer,” The Lancet, vol. 359, no. 9306, pp. 572–577, 2002. View at Publisher · View at Google Scholar · View at Scopus
  20. K. R. Kozak, M. W. Amneus, S. M. Pusey et al., “Identification of biomarkers for ovarian cancer using strong anion-exchange ProteinChips: potential use in diagnosis and prognosis,” Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 21, pp. 12343–12348, 2003. View at Publisher · View at Google Scholar · View at Scopus
  21. Z. Zhang, R. C. Bast, Y. Yu et al., “Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer,” Cancer Research, vol. 64, no. 16, pp. 5882–5890, 2004. View at Publisher · View at Google Scholar · View at Scopus
  22. K. R. Kozak, F. Su, J. P. Whitelegge, K. Faull, S. Reddy, and R. Farias-Eisner, “Characterization of serum biomarkers for detection of early stage ovarian cancer,” Proteomics, vol. 5, no. 17, pp. 4589–4596, 2005. View at Publisher · View at Google Scholar · View at Scopus
  23. M. S. Lowenthal, A. I. Mehta, K. Frogale et al., “Analysis of albumin-associated peptides and proteins from ovarian cancer patients,” Clinical Chemistry, vol. 51, no. 10, pp. 1933–1945, 2005. View at Publisher · View at Google Scholar · View at Scopus
  24. Y. W. Lin, C. Y. Lin, H. C. Lai et al., “Plasma proteomic pattern as biomarkers for ovarian cancer,” International Journal of Gynecological Cancer, vol. 16, supplement 1, pp. 139–146, 2006. View at Publisher · View at Google Scholar · View at Scopus
  25. J. T. Wadsworth, K. D. Somers, L. H. Cazares et al., “Serum protein profiles to identify head and neck cancer,” Clinical Cancer Research, vol. 10, no. 5, pp. 1625–1632, 2004. View at Publisher · View at Google Scholar · View at Scopus
  26. S. G. Soltys, Q. T. Le, G. Shi, R. Tibshirani, A. J. Giaccia, and A. C. Koong, “The use of plasma surface-enhanced laser desorption/ionization time-of-flight mass spectrometry proteomic patterns for detection of head and neck squamous cell cancers,” Clinical Cancer Research, vol. 10, no. 14, pp. 4806–4812, 2004. View at Publisher · View at Google Scholar · View at Scopus
  27. W. C. S. Cho, T. T. C. Yip, C. Yip et al., “Identification of serum amyloid A protein as a potentially useful biomarker to monitor relapse of nasopharyngeal cancer by serum proteomic profiling,” Clinical Cancer Research, vol. 10, no. 1, pp. 43–52, 2004. View at Publisher · View at Google Scholar · View at Scopus
  28. A. J. Cheng, L. C. Chen, K. Y. Chien et al., “Oral cancer plasma tumor marker identified with bead-based affinity-fractionated proteomic technology,” Clinical Chemistry, vol. 51, no. 12, pp. 2236–2244, 2005. View at Publisher · View at Google Scholar · View at Scopus
  29. D. W. Ho, Z. F. Yang, B. Y. Wong et al., “Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry serum protein profiling to identify nasopharyngeal carcinoma,” Cancer, vol. 107, no. 1, pp. 99–107, 2006. View at Publisher · View at Google Scholar · View at Scopus
  30. C. G. Gourin, Z. S. Xia, Y. Han et al., “Serum protein profile analysis in patients with head and neck squamous cell carcinoma,” Archives of Otolaryngology—Head and Neck Surgery, vol. 132, no. 4, pp. 390–397, 2006. View at Publisher · View at Google Scholar · View at Scopus
  31. L. Zhou, L. Cheng, L. Tao, X. Jia, Y. Lu, and P. Liao, “Detection of hypopharyngeal squamous cell carcinoma using serum proteomics,” Acta Oto-Laryngologica, vol. 126, no. 8, pp. 853–860, 2006. View at Publisher · View at Google Scholar · View at Scopus
  32. G. L. Freed, L. H. Cazares, C. E. Fichandler et al., “Differential capture of serum proteins for expression profiling and biomarker discovery in pre- and posttreatment head and neck cancer samples,” Laryngoscope, vol. 118, no. 1, pp. 61–68, 2008. View at Publisher · View at Google Scholar · View at Scopus
  33. C. G. Gourin, W. H. Moretz III, P. M. Weinberger et al., “Serum protein profile analysis following definitive treatment in patients with head and neck squamous cell carcinoma,” Archives of Otolaryngology—Head and Neck Surgery, vol. 133, no. 11, pp. 1125–1130, 2007. View at Publisher · View at Google Scholar · View at Scopus
  34. M. Pietrowska, J. Polańska, R. Suwiński et al., “Comparison of peptide cancer signatures identified by mass spectrometry in serum of patients with head and neck, lung and colorectal cancers: association with tumor progression,” International Journal of Oncology, vol. 40, no. 1, pp. 148–156, 2012. View at Publisher · View at Google Scholar
  35. P. Widłak, M. Pietrowska, K. Wojtkiewicz et al., “Radiation-related changes in serum proteome profiles detected by mass spectrometry in blood of patients treated with radiotherapy due to larynx cancer,” Journal of Radiation Research, vol. 52, no. 5, pp. 575–581, 2011. View at Publisher · View at Google Scholar · View at Scopus
  36. M. Pietrowska, J. Polańska, A. Walaszczyk et al., “Association between plasma proteome profiles analysed by mass spectrometry, a lymphocyte-based DNA-break repair assay and radiotherapy-induced acute mucosal reaction in head and neck cancer patients,” International Journal of Radiation Biology, vol. 87, no. 7, pp. 711–719, 2011. View at Publisher · View at Google Scholar · View at Scopus
  37. J. Li, Z. Zhang, J. Rosenzweig, Y. Y. Wang, and D. W. Chan, “Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer,” Clinical Chemistry, vol. 48, no. 8, pp. 1296–1304, 2002. View at Google Scholar · View at Scopus
  38. A. Gonçalves, B. Esterni, F. Bertucci et al., “Postoperative serum proteomic profiles may predict metastatic relapse in high-risk primary breast cancer patients receiving adjuvant chemotherapy,” Oncogene, vol. 25, no. 7, pp. 981–989, 2006. View at Publisher · View at Google Scholar · View at Scopus
  39. J. Villanueva, D. R. Shaffer, J. Philip et al., “Differential exoprotease activities confer tumor-specific serum peptidome patterns,” The Journal of Clinical Investigation, vol. 116, no. 1, pp. 271–284, 2006. View at Publisher · View at Google Scholar · View at Scopus
  40. L. Pusztai, B. W. Gregory, K. A. Baggerly et al., “Pharmacoproteomic analysis of prechemotherapy and postchemotherapy plasma samples from patients receiving neoadjuvant or adjuvant chemotherapy for breast carcinoma,” Cancer, vol. 100, no. 9, pp. 1814–1822, 2004. View at Publisher · View at Google Scholar · View at Scopus
  41. Y. Heike, M. Hosokawa, S. Osumi et al., “Identification of serum proteins related to adverse effects induced by docetaxel infusion from protein expression profiles of serum using SELDI ProteinChip system,” Anticancer Research, vol. 25, no. 2, pp. 1197–1203, 2005. View at Google Scholar · View at Scopus
  42. M. Pietrowska, J. Polanska, L. Marczak et al., “Mass spectrometry-based analysis of therapy-related changes in serum proteome patterns of patients with early-stage breast cancer,” Journal of Translational Medicine, vol. 8, article 66, 2010. View at Publisher · View at Google Scholar · View at Scopus
  43. M. Pietrowska, L. Marczak, J. Polanska et al., “Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer,” Journal of Translational Medicine, vol. 7, article 60, 2009. View at Publisher · View at Google Scholar · View at Scopus
  44. J. Solassol, P. Rouanet, P. J. Lamy et al., “Serum protein signature may improve detection of ductal carcinoma in situ of the breast,” Oncogene, vol. 29, no. 4, pp. 550–560, 2010. View at Publisher · View at Google Scholar · View at Scopus
  45. E. F. Petricoin, D. K. Ornstein, C. P. Paweletz et al., “Serum proteomic patterns for detection of prostate cancer,” Journal of the National Cancer Institute, vol. 94, no. 20, pp. 1576–1578, 2002. View at Google Scholar · View at Scopus
  46. B. L. Adam, Y. Qu, J. W. Davis et al., “Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men,” Cancer Research, vol. 62, no. 13, pp. 3609–3614, 2002. View at Google Scholar · View at Scopus
  47. D. K. Ornstein, W. Rayford, V. A. Fusaro et al., “Serum proteomic profiling can discriminate prostate cancer from benign prostates in men with total prostate specific antigen levels between 2.5 and 15.0 ng/ml,” Journal of Urology, vol. 172, no. 4, pp. 1302–1305, 2004. View at Publisher · View at Google Scholar · View at Scopus
  48. L. Le, K. Chi, S. Tyldesley et al., “Identification of serum amyloid A as a biomarker to distinguish prostate cancer patients with bone lesions,” Clinical Chemistry, vol. 51, no. 4, pp. 695–707, 2005. View at Publisher · View at Google Scholar · View at Scopus
  49. L. R. Zhu, W. Y. Zhang, L. Yu, Y. H. Zheng, J. Z. Zhang, and Q. P. Liao, “Serum proteomic features for detection of endometrial cancer,” International Journal of Gynecological Cancer, vol. 16, no. 3, pp. 1374–1378, 2006. View at Publisher · View at Google Scholar · View at Scopus
  50. S. Yang, X. Xiao, W. Zhang et al., “Application of serum SELDI proteomic patterns in diagnosis of lung cancer,” BMC Cancer, vol. 5, article 83, 2005. View at Publisher · View at Google Scholar · View at Scopus
  51. X. P. Liu, J. Shen, Z. F. Li, L. Yan, and J. Gu, “A serum proteomic pattern for the detection of colorectal adenocarcinoma using surface enhanced laser desorption and ionization mass spectrometry,” Cancer Investigation, vol. 24, no. 8, pp. 747–753, 2006. View at Publisher · View at Google Scholar · View at Scopus
  52. J. Koopmann, Z. Zhang, N. White et al., “Serum diagnosis of pancreatic adenocarcinoma using surface-enhanced laser desorption and ionization mass spectrometry,” Clinical Cancer Research, vol. 10, no. 3, pp. 860–868, 2004. View at Publisher · View at Google Scholar · View at Scopus
  53. J. Villanueva, A. J. Martorella, K. Lawlor et al., “Serum peptidome patterns that distinguish metastatic thyroid carcinoma from cancer-free controls are unbiased by gender and age,” Molecular and Cellular Proteomics, vol. 5, no. 10, pp. 1840–1852, 2006. View at Publisher · View at Google Scholar · View at Scopus
  54. J. Tolson, R. Bogumil, E. Brunst et al., “Serum protein profilling by SELDI mass spectrometry: detection of multiple variants of serum amyloid alpha in renal cancer patients,” Laboratory Investigation, vol. 84, no. 9, pp. 845–856, 2004. View at Publisher · View at Google Scholar · View at Scopus
  55. H. Hong, Y. Dragan, J. Epstein et al., “Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS),” BMC Bioinformatics, vol. 6, supplement 2, article S5, 2005. View at Publisher · View at Google Scholar · View at Scopus
  56. M. Aivado, D. Spentzos, U. Germing et al., “Serum proteome profiling detects myelodysplastic syndromes and identifies CXC chemokine ligands 4 and 7 as markers for advanced disease,” Proceedings of the National Academy of Sciences of the United States of America, vol. 104, no. 4, pp. 1307–1312, 2007. View at Publisher · View at Google Scholar · View at Scopus
  57. M. Z. Zhang, Z. C. Sun, X. R. Fu et al., “Analysis of serum proteome profiles of non-Hodgkin lymphoma for biomarker identification,” Journal of Proteomics, vol. 72, no. 6, pp. 952–959, 2009. View at Publisher · View at Google Scholar · View at Scopus
  58. N. L. Anderson and N. G. Anderson, “The human plasma proteome: history, character, and diagnostic prospects,” Molecular & Cellular Proteomics, vol. 1, no. 11, pp. 845–867, 2002. View at Google Scholar · View at Scopus
  59. K. Honda, Y. Hayashida, T. Umaki et al., “Possible detection of pancreatic cancer by plasma protein profiling,” Cancer Research, vol. 65, no. 22, pp. 10613–10622, 2005. View at Publisher · View at Google Scholar · View at Scopus
  60. J. Koomen, L. Shih, K. Coombes et al., “Plasma protein profiling for diagnosis of pancreatic cancer reveals the presence of host response proteins,” Clinical Cancer Research, vol. 11, no. 3, pp. 1110–1118, 2005. View at Google Scholar · View at Scopus
  61. M. Pietrowska, L. Marczak, J. Polanska et al., “Optimizing of MALDI-ToF-based low-molecular-weight serum proteome pattern analysis in detection of breast cancer patients; the effect of albumin removal on classification performance,” Neoplasma, vol. 57, no. 6, pp. 537–544, 2010. View at Google Scholar · View at Scopus
  62. J. L. Luque-Garcia and T. A. Neubert, “Sample preparation for serum/plasma profiling and biomarker identification by mass spectrometry,” Journal of Chromatography A, vol. 1153, no. 1-2, pp. 259–276, 2007. View at Publisher · View at Google Scholar · View at Scopus
  63. J. Whiteaker, H. Zhang, J. Eng et al., “Head-to-head comparison of serum fractionation techniques,” Journal of Proteome Research, vol. 6, no. 2, pp. 828–836, 2007. View at Publisher · View at Google Scholar · View at Scopus
  64. M. Lopez, A. Mikulskis, S. Kuzdzal et al., “A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples,” Clinical Chemistry, vol. 53, no. 6, pp. 1067–1074, 2007. View at Publisher · View at Google Scholar · View at Scopus
  65. N. Zolotarjova, J. Martosella, G. Nicol, J. Bailey, B. E. Boyes, and W. C. Barrett, “Differences among techniques for high-abundant protein depletion,” Proteomics, vol. 5, no. 13, pp. 3304–3313, 2005. View at Publisher · View at Google Scholar · View at Scopus
  66. S. Camerini, M. L. Polci, L. A. Liotta, E. F. Petricoin, and W. Zhou, “A method for the selective isolation and enrichment of carrier protein-bound low-molecular weight proteins and peptides in the blood,” Proteomics—Clinical Applications, vol. 1, no. 2, pp. 176–184, 2007. View at Publisher · View at Google Scholar · View at Scopus
  67. D. H. Geho, A. Luchini, E. Garaci, C. Belluco, E. Petricoin, and L. A. Liotta, “Nanotechnology in clinical proteomics,” Nanomedicine, vol. 2, no. 1, pp. 1–5, 2007. View at Publisher · View at Google Scholar · View at Scopus
  68. A. Luchini, D. H. Geho, B. Bishop et al., “Smart hydrogel particles: biomarker harvesting: one-step affinity purification, size exclusion, and protection against degradation,” Nano Letters, vol. 8, no. 1, pp. 350–361, 2008. View at Publisher · View at Google Scholar · View at Scopus
  69. R. G. Harper, S. R. Workman, S. Schuetzner, A. T. Timperman, and J. N. Sutton, “Low-molecular-weight human serum proteome using ultrafiltration, isoelectric focusing, and mass spectrometry,” Electrophoresis, vol. 25, no. 9, pp. 1299–1306, 2004. View at Publisher · View at Google Scholar · View at Scopus
  70. X. Zheng, H. Baker, and W. S. Hancock, “Analysis of the low molecular weight serum peptidome using ultrafiltration and a hybrid ion trap-Fourier transform mass spectrometer,” Journal of Chromatography A, vol. 1120, no. 1-2, pp. 173–184, 2006. View at Publisher · View at Google Scholar · View at Scopus
  71. M. Zhou, D. A. Lucas, K. C. Chan et al., “An investigation into the human serum ‘interactome’,” Electrophoresis, vol. 25, no. 9, pp. 1289–1298, 2004. View at Publisher · View at Google Scholar · View at Scopus
  72. S. Ayache, M. Panelli, F. M. Marincola, and D. F. Stroncek, “Effects of storage time and exogenous protease inhibitors on plasma protein levels,” American Journal of Clinical Pathology, vol. 126, no. 2, pp. 174–184, 2006. View at Publisher · View at Google Scholar · View at Scopus
  73. A. S. Schrohl, S. Würtz, E. Kohn et al., “Banking of biological fluids for studies of disease-associated protein biomarkers,” Molecular and Cellular Proteomics, vol. 7, no. 10, pp. 2061–2066, 2008. View at Publisher · View at Google Scholar · View at Scopus
  74. D. Geho, M. M. Cheng, K. Killian et al., “Fractionation of serum components using nanoporous substrates,” Bioconjugate Chemistry, vol. 17, no. 3, pp. 654–661, 2006. View at Publisher · View at Google Scholar · View at Scopus
  75. A. Luchini, C. Fredolini, B. H. Espina et al., “Nanoparticle technology: addressing the fundamental roadblocks to protein biomarker discovery,” Current Molecular Medicine, vol. 10, no. 2, pp. 133–141, 2010. View at Publisher · View at Google Scholar · View at Scopus
  76. I. Eidhammer, K. Flikka, L. Martens, and S. Mikalsen, Computational Methods for Mass Spectrometry Proteomics, John Wiley & Sons, 2007.
  77. J. Morris, K. R. Coombes, J. Koomen, K. A. Baggerly, and R. Kobayashi, “Feature extraction and quantification for mass spectrometry in biomedical applications using the mean spectrum,” Bioinformatics, vol. 21, no. 9, pp. 1764–1775, 2005. View at Publisher · View at Google Scholar · View at Scopus
  78. K. A. Baggerly, J. Morris, J. Wang, D. Gold, L. C. Xiao, and K. R. Coombes, “A comprehensive approach to the analysis of matrix-assisted laser desorption/ionization-time of flight proteomics spectra from serum samples,” Proteomics, vol. 3, no. 9, pp. 1667–1672, 2003. View at Publisher · View at Google Scholar · View at Scopus
  79. S. Q. Zhang, X. Zhou, H. Wang et al., “Peak detection with chemical noise removal using short-time FFT for a kind of MALDI data, proceedings of OSB,” Lecture Notes in Operations Research, vol. 7, pp. 222–231, 2007. View at Google Scholar
  80. E. Coche, M. Lonneux, and X. Geets, “Lung cancer: morphological and functional approach to screening, staging and treatment planning,” Future Oncology, vol. 6, no. 3, pp. 367–380, 2010. View at Publisher · View at Google Scholar · View at Scopus
  81. S. M. Cowherd, “Tumor staging and grading: a primer,” Methods in Molecular Biology, vol. 823, pp. 1–18, 2012. View at Google Scholar
  82. R. J. Hicks, “Use molecular targeted agents for the diagnosis, staging and therapy of neuroendocrine malignancy,” Cancer Imaging, vol. 10, no. 1, pp. S83–S91, 2010. View at Google Scholar
  83. D. Planchard and C. Le Pechoux, “Small cell lung cancer: new clinical recommendiations and current status of biomarker assessment,” European Journal of Cancer, vol. 47, supplement 3, pp. S272–S283, 2011. View at Google Scholar
  84. C. G. Berman and R. A. Clark, “Diagnostic imaging in cancer,” Primary Care, vol. 19, no. 4, pp. 677–713, 1992. View at Google Scholar · View at Scopus
  85. G. Maneti, C. Ciccio, E. Squillaci et al., “Role of combined DWIBS/3D-CE-T1w whole-body MRI in tumor staging: comparison with PET-CT,” European Journal of Radiology. In press.
  86. P. Findeisen, M. Zapatka, T. Peccerella et al., “Serum amyloid A as a prognostic marker in melanoma identified by proteomic profiling,” Journal of Clinical Oncology, vol. 27, no. 13, pp. 2199–2208, 2009. View at Publisher · View at Google Scholar · View at Scopus
  87. B. L. Pierce, R. Ballard-Barbash, L. Bernstein et al., “Elevated biomarkers of inflammation are associated with reduced survival among breast cancer patients,” Journal of Clinical Oncology, vol. 27, no. 21, pp. 3437–3444, 2009. View at Publisher · View at Google Scholar · View at Scopus
  88. B. L. Pierce, M. L. Neuhouser, M. H. Wener et al., “Correlates of circulating C-reactive protein and serum amyloid A concentrations in breast cancer survivors,” Breast Cancer Research and Treatment, vol. 114, no. 1, pp. 155–167, 2009. View at Publisher · View at Google Scholar · View at Scopus
  89. N. Janikashvili, B. Bonnotte, E. Katsanis, and N. Larmonier, “The dendritic cell-regulatory T lymphocyte crosstalk contributes to tumor-induced tolerance,” Clinical and Developmental Immunology, vol. 2011, Article ID 430394, 14 pages, 2011. View at Publisher · View at Google Scholar
  90. L. E. Kandalaft, G. T. Motz, J. Duraiswamy, and G. Coukos, “Tumor immune surveillance and ovarian cancer: lessons on immune mediated tumor rejection or tolerance,” Cancer and Metastasis Reviews, vol. 30, no. 1, pp. 141–151, 2011. View at Publisher · View at Google Scholar · View at Scopus
  91. A. Ramankulov, M. Lein, M. Johannsen et al., “Serum amyloid A as indicator of distant metastases but not as early tumor marker in patients with renal cell carcinoma,” Cancer Letters, vol. 269, no. 1, pp. 85–92, 2008. View at Publisher · View at Google Scholar · View at Scopus
  92. A. Stojanovic and A. Cerwenka, “Natural killer cells and solid tumors,” Journal of Innate Immunity, vol. 3, no. 4, pp. 355–364, 2011. View at Publisher · View at Google Scholar · View at Scopus
  93. B. F. Zamarron and W. Chen, “Dual roles of immune cells and their factors in cancer development and progression,” International Journal of Biological Sciences, vol. 7, no. 5, pp. 651–658, 2011. View at Google Scholar · View at Scopus
  94. E. Cocco, S. Bellone, K. El-Sahwi et al., “Serum amyloid A: a novel biomarker for endometrial cancer,” Cancer, vol. 116, no. 4, pp. 843–851, 2010. View at Publisher · View at Google Scholar · View at Scopus
  95. M. Cremona, E. Calabrò, G. Randi et al., “Elevated levels of the acute-phase serum amyloid are associated with heightened lung cancer risk,” Cancer, vol. 116, no. 5, pp. 1326–1335, 2010. View at Publisher · View at Google Scholar · View at Scopus
  96. E. Malle, S. Sodin-Semrl, and A. Kovacevic, “Serum amyloid A: an acute-phase protein involved in tumour pathogenesis,” Cellular and Molecular Life Sciences, vol. 66, no. 1, pp. 9–26, 2009. View at Publisher · View at Google Scholar · View at Scopus
  97. T. Edgell, G. Martin-Roussety, G. Barker et al., “Phase II biomarker trial of a multimarker diagnostic for ovarian cancer,” Journal of Cancer Research and Clinical Oncology, vol. 136, no. 7, pp. 1079–1088, 2010. View at Publisher · View at Google Scholar · View at Scopus
  98. S. A. Moshkovskii, M. V. Serebryakova, K. B. Kuteykin-Teplyakov et al., “Ovarian cancer marker of 11.7 kDa detected by proteomics is a serum amyloid A1,” Proteomics, vol. 5, no. 14, pp. 3790–3797, 2005. View at Publisher · View at Google Scholar · View at Scopus
  99. W. C. S. Cho, T. T. Yip, W. W. Cheng, and J. S. K. Au, “Serum amyloid A is elevated in the serum of lung cancer patients with poor prognosis,” British Journal of Cancer, vol. 102, no. 12, pp. 1731–1735, 2010. View at Publisher · View at Google Scholar · View at Scopus
  100. T. W. Li, B. R. Zheng, Z. X. Huang et al., “Screening disease-associated proteins from sera of patients with rheumatoid arthritis: a comparative proteomic study,” Chinese Medical Journal, vol. 123, no. 5, pp. 537–543, 2010. View at Publisher · View at Google Scholar · View at Scopus
  101. V. Abbasciano, D. Tassinari, S. Sartori et al., “Usefulness of coagulation markers in staging of gastric cancer,” Cancer Detection and Prevention, vol. 19, no. 4, pp. 331–336, 1995. View at Google Scholar · View at Scopus
  102. B. Bottasso, D. Mari, R. Coppola, N. Santoro, M. Vaglini, and P. M. Mannucci, “Hypercoagulability and hyperfibrinolysis in patients with melanoma,” Thrombosis Research, vol. 81, no. 3, pp. 345–352, 1996. View at Publisher · View at Google Scholar · View at Scopus
  103. J. Y. Engwegen, N. Mehra, J. B. Haanen et al., “Validation of SELDI-TOF MS serum protein profiles for renal cell carcinoma in new populations,” Laboratory Investigation, vol. 87, no. 2, pp. 161–172, 2007. View at Publisher · View at Google Scholar · View at Scopus
  104. H. Roelofsen, G. Alvarez-Llamas, M. Dijkstra et al., “Analyses of intricate kinetics of the serum proteome during and after colon surgery by protein expression time series,” Proteomics, vol. 7, no. 17, pp. 3219–3228, 2007. View at Publisher · View at Google Scholar · View at Scopus
  105. P. B. Yildiz, Y. Shyr, J. S. M. Rahman et al., “Diagnostic accuracy of MALDI mass spectrometric analysis of unfractionated serum in lung cancer,” Journal of Thoracic Oncology, vol. 2, no. 10, pp. 893–901, 2007. View at Publisher · View at Google Scholar · View at Scopus
  106. C. Laronga, S. Becker, P. Watson et al., “SELDI-TOF serum profiling for prognostic and diagnostic classification of breast cancers,” Disease Markers, vol. 19, no. 4-5, pp. 229–238, 2003. View at Google Scholar · View at Scopus
  107. F. M. Smith, W. M. Gallagher, E. Fox et al., “Combination of SELDI-TOF-MS and data mining provides early-stage response prediction for rectal tumors undergoing multimodal neoadjuvant therapy,” Annals of Surgery, vol. 245, no. 2, pp. 259–266, 2007. View at Publisher · View at Google Scholar · View at Scopus
  108. C. Ménard, D. Johann, M. Lowenthal et al., “Discovering clinical biomarkers of ionizing radiation exposure with serum proteomic analysis,” Cancer Research, vol. 66, no. 3, pp. 1844–1850, 2006. View at Publisher · View at Google Scholar · View at Scopus