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Advances in Medicine
Volume 2014, Article ID 238045, 25 pages
http://dx.doi.org/10.1155/2014/238045
Review Article

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Office of Cancer Clinical Proteomics Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA

Received 23 March 2014; Accepted 30 June 2014; Published 8 September 2014

Academic Editor: Runjan Chetty

Copyright © 2014 Mehdi Mesri. 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. J. Potash and K. C. Anderson, “Announcing the AACR cancer progress report 2013,” Clinical Cancer Research, vol. 19, p. 5545, 2013. View at Google Scholar
  2. B. Pradet-Balade, F. Boulmé, H. Beug, E. W. Müllner, and J. A. Garcia-Sanz, “Translation control: bridging the gap between genomics and proteomics?” Trends in Biochemical Sciences, vol. 26, no. 4, pp. 225–229, 2001. View at Publisher · View at Google Scholar · View at Scopus
  3. L. A. Garraway and E. S. Lander, “Lessons from the cancer genome,” Cell, vol. 153, no. 1, pp. 17–37, 2013. View at Publisher · View at Google Scholar · View at Scopus
  4. L. Hood, “A personal journey of discovery: developing technology and changing biology,” Annual Review of Analytical Chemistry, vol. 1, pp. 1–43, 2008. View at Google Scholar
  5. B. Weir, X. Zhao, and M. Meyerson, “Somatic alterations in the human cancer genome,” Cancer Cell, vol. 6, no. 5, pp. 433–438, 2004. View at Publisher · View at Google Scholar · View at Scopus
  6. D. Hanahan and R. A. Weinberg, “Hallmarks of cancer: the next generation,” Cell, vol. 144, no. 5, pp. 646–674, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. E. R. Mardis, “Next-generation sequencing platforms,” Annual Review of Analytical Chemistry, vol. 6, pp. 287–303, 2013. View at Publisher · View at Google Scholar
  8. R. D. Hawkins, G. C. Hon, and B. Ren, “Next-generation genomics: an integrative approach,” Nature Reviews Genetics, vol. 11, no. 7, pp. 476–486, 2010. View at Publisher · View at Google Scholar · View at Scopus
  9. C. M. Perou, T. Sørile, M. B. Eisen et al., “Molecular portraits of human breast tumours,” Nature, vol. 406, no. 6797, pp. 747–752, 2000. View at Publisher · View at Google Scholar · View at Scopus
  10. A. M. Glas, A. Floore, L. J. M. J. Delahaye et al., “Converting a breast cancer microarray signature into a high-throughput diagnostic test,” BMC Genomics, vol. 7, article 278, 2006. View at Publisher · View at Google Scholar · View at Scopus
  11. L. A. Habel, S. Shak, M. K. Jacobs et al., “A population-based study of tumor gene expression and risk of breast cancer death among lymp node-negative patients,” Breast Cancer Research, vol. 8, no. 3, article R25, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. R. Salazar, P. Roepman, G. Capella et al., “Gene expression signature to improve prognosis prediction of stage II and III colorectal cancer,” Journal of Clinical Oncology, vol. 29, no. 1, pp. 17–24, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. H. Davies, G. R. Bignell, C. Cox et al., “Mutations of the BRAF gene in human cancer,” Nature, vol. 417, no. 6892, pp. 949–954, 2002. View at Publisher · View at Google Scholar · View at Scopus
  14. Y. Samuels, Z. Wang, A. Bardelli et al., “High frequency of mutations of the PIK3CA gene in human cancers,” Science, vol. 304, no. 5670, p. 554, 2004. View at Publisher · View at Google Scholar · View at Scopus
  15. T. J. Lynch, D. W. Bell, R. Sordella et al., “Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib,” The New England Journal of Medicine, vol. 350, no. 21, pp. 2129–2139, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. J. G. Paez, P. A. Jänne, J. C. Lee et al., “EGFR mutations in lung, cancer: correlation with clinical response to gefitinib therapy,” Science, vol. 304, no. 5676, pp. 1497–1500, 2004. View at Publisher · View at Google Scholar · View at Scopus
  17. W. Pao, V. Miller, M. Zakowski et al., “EGF receptor gene mutations are common in lung cancers from “never smokers” and are associated with sensitivity of tumors to gefitinib and erlotinib,” Proceedings of the National Academy of Sciences of the United States of America, vol. 101, no. 36, pp. 13306–13311, 2004. View at Publisher · View at Google Scholar · View at Scopus
  18. E. Boja, T. Hiltke, R. Rivers et al., “Evolution of clinical proteomics and its role in medicine,” Journal of Proteome Research, vol. 10, no. 1, pp. 66–84, 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. M. Bantscheff and B. Kuster, “Quantitative mass spectrometry in proteomics,” Analytical and Bioanalytical Chemistry, vol. 404, no. 4, pp. 937–938, 2012. View at Publisher · View at Google Scholar · View at Scopus
  20. P. Lescuyer, A. Farina, and D. F. Hochstrasser, “Proteomics in clinical chemistry: will it be long?” Trends in Biotechnology, vol. 28, no. 5, pp. 225–229, 2010. View at Publisher · View at Google Scholar · View at Scopus
  21. J. B. Fenn, M. Mann, C. K. Meng, S. F. Wong, and C. M. Whitehouse, “Electrospray ionization for mass spectrometry of large biomolecules,” Science, vol. 246, no. 4926, pp. 64–71, 1989. View at Publisher · View at Google Scholar · View at Scopus
  22. J. Lengqvist, J. Andrade, Y. Yang, G. Alvelius, R. Lewensohn, and J. Lehtiö, “Robustness and accuracy of high speed LC-MS separations for global peptide quantitation and biomarker discovery,” Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, vol. 877, no. 13, pp. 1306–1316, 2009. View at Publisher · View at Google Scholar · View at Scopus
  23. N. M. Griffin, J. Yu, F. Long et al., “Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis,” Nature Biotechnology, vol. 28, no. 1, pp. 83–89, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. J. Pan, H. Chen, Y. Sun, J. Zhang, and X. Luo, “Comparative proteomic analysis of non-small-cell lung cancer and normal controls using serum label-free quantitative shotgun technology,” Lung, vol. 186, no. 4, pp. 255–261, 2008. View at Publisher · View at Google Scholar · View at Scopus
  25. S. K. Huang, M. M. Darfler, M. B. Nicholl et al., “LC/MS-based quantitative proteomic analysis of paraffin-embedded archival melanomas reveals potential proteomic biomarkers associated with metastasis,” PLoS ONE, vol. 4, no. 2, Article ID e4430, 2009. View at Publisher · View at Google Scholar · View at Scopus
  26. M. C. Wiener, J. R. Sachs, E. G. Deyanova, and N. A. Yates, “Differential mass spectrometry: a label-free LC-MS method for finding significant differences in complex peptide and protein mixtures,” Analytical Chemistry, vol. 76, no. 20, pp. 6085–6096, 2004. View at Publisher · View at Google Scholar · View at Scopus
  27. R. E. Higgs, M. D. Knierman, V. Gelfanova, J. P. Butler, and J. E. Hale, “Comprehensive label-free method for the relative quantification of proteins from biological samples,” Journal of Proteome Research, vol. 4, no. 4, pp. 1442–1450, 2005. View at Publisher · View at Google Scholar · View at Scopus
  28. S. E. Ong, B. Blagoev, I. Kratchmarova et al., “Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics,” Molecular & Cellular Proteomics, vol. 1, no. 5, pp. 376–386, 2002. View at Google Scholar · View at Scopus
  29. M. Krüger, M. Moser, S. Ussar et al., “SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function,” Cell, vol. 134, no. 2, pp. 353–364, 2008. View at Publisher · View at Google Scholar · View at Scopus
  30. T. Geiger, J. Cox, P. Ostasiewicz, J. R. Wisniewski, and M. Mann, “Super-SILAC mix for quantitative proteomics of human tumor tissue,” Nature Methods, vol. 7, no. 5, pp. 383–385, 2010. View at Publisher · View at Google Scholar · View at Scopus
  31. T. A. Neubert and P. Tempst, “Super-SILAC for tumors and tissues,” Nature Methods, vol. 7, no. 5, pp. 361–362, 2010. View at Publisher · View at Google Scholar · View at Scopus
  32. G. W. Becker, “Stable isotopic labeling of proteins for quantitative proteomic applications,” Briefings in Functional Genomics and Proteomics, vol. 7, no. 5, pp. 371–382, 2008. View at Publisher · View at Google Scholar · View at Scopus
  33. M. Schnölzer, P. Jedrzejewski, and W. D. Lehmann, “Protease-catalyzed incorporation of 18O into peptide fragments and its application for protein sequencing by electrospray and matrix-assisted laser desorption/ionization mass spectrometry,” Electrophoresis, vol. 17, no. 5, pp. 945–953, 1996. View at Publisher · View at Google Scholar · View at Scopus
  34. X. Ye, B. Luke, T. Andresson, and J. Blonder, “18O stable isotope labeling in MS-based proteomics,” Briefings in Functional Genomics and Proteomics, vol. 8, no. 2, pp. 136–144, 2009. View at Publisher · View at Google Scholar · View at Scopus
  35. S. P. Gygi, B. Rist, S. A. Gerber, F. Turecek, M. H. Gelb, and R. Aebersold, “Quantitative analysis of complex protein mixtures using isotope-coded affinity tags,” Nature Biotechnology, vol. 17, no. 10, pp. 994–999, 1999. View at Publisher · View at Google Scholar · View at Scopus
  36. Y. Shiio and R. Aebersold, “Quantitative proteome analysis using isotope-coded affinity tags and mass spectrometry,” Nature Protocols, vol. 1, no. 1, pp. 139–145, 2006. View at Publisher · View at Google Scholar · View at Scopus
  37. M. Mesri, C. Birse, J. Heidbrink et al., “Identification and characterization of angiogenesis targets through proteomic profiling of endothelial cells in human cancer tissues,” PLoS ONE, vol. 8, no. 11, Article ID e78885, 2013. View at Publisher · View at Google Scholar
  38. P. L. Ross, Y. N. Huang, J. N. Marchese et al., “Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents,” Molecular and Cellular Proteomics, vol. 3, no. 12, pp. 1154–1169, 2004. View at Publisher · View at Google Scholar · View at Scopus
  39. A. Thompson, J. Schäfer, K. Kuhn et al., “Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS,” Analytical Chemistry, vol. 75, no. 8, pp. 1895–1904, 2003. View at Publisher · View at Google Scholar · View at Scopus
  40. M. M. Savitski, F. Fischer, T. Mathieson, G. Sweetman, M. Lang, and M. Bantscheff, “Targeted data acquisition for improved reproducibility and robustness of proteomic mass spectrometry assays,” Journal of the American Society for Mass Spectrometry, vol. 21, no. 10, pp. 1668–1679, 2010. View at Publisher · View at Google Scholar · View at Scopus
  41. N. A. Karp, W. Huber, P. G. Sadowski, P. D. Charles, S. V. Hester, and K. S. Lilley, “Addressing accuracy and precision issues in iTRAQ quantitation,” Molecular and Cellular Proteomics, vol. 9, no. 9, pp. 1885–1897, 2010. View at Publisher · View at Google Scholar · View at Scopus
  42. Y. O. Saw, M. Salim, J. Noirel, C. Evans, I. Rehman, and P. C. Wright, “iTRAQ underestimation in simple and complex mixtures: ‘The good, the bad and the ugly’,” Journal of Proteome Research, vol. 8, no. 11, pp. 5347–5355, 2009. View at Publisher · View at Google Scholar · View at Scopus
  43. L. V. DeSouza, A. D. Romaschin, T. J. Colgan, and K. W. M. Siu, “Absolute quantification of potential cancer markers in clinical tissue homogenates using multiple reaction monitoring on a hybrid triple quadrupole/linear ion trap tandem mass spectrometer,” Analytical Chemistry, vol. 81, no. 9, pp. 3462–3470, 2009. View at Publisher · View at Google Scholar · View at Scopus
  44. P. Mitchell, “Proteomics retrenches,” Nature Biotechnology, vol. 28, no. 7, pp. 665–670, 2010. View at Publisher · View at Google Scholar · View at Scopus
  45. M. Karas and F. Hillenkamp, “Laser desorption ionization of proteins with molecular masses exceeding 10,000 daltons,” Analytical Chemistry, vol. 60, no. 20, pp. 2299–2301, 1988. View at Publisher · View at Google Scholar · View at Scopus
  46. L. F. Marvin, M. A. Roberts, and L. B. Fay, “Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in clinical chemistry,” Clinica Chimica Acta, vol. 337, no. 1-2, pp. 11–21, 2003. View at Publisher · View at Google Scholar · View at Scopus
  47. 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
  48. T. W. Hutchens and T. T. Yip, “New desorption strategies for the mass spectrometric analysis of macromolecules,” Rapid Communications in Mass Spectrometry, vol. 7, no. 7, pp. 576–580, 1993. View at Google Scholar
  49. M. Zhou and T. D. Veenstra, “Mass spectrometry: m/z 1983–2008,” Biotechniques, vol. 44, no. 5, pp. 667–670, 2008. View at Publisher · View at Google Scholar · View at Scopus
  50. N. Tang, P. Tornatore, and S. R. Weinberger, “Current developments in SELDI affinity technology,” Mass Spectrometry Reviews, vol. 23, no. 1, pp. 34–44, 2004. View at Publisher · View at Google Scholar · View at Scopus
  51. J. Zou, G. Hong, X. Guo et al., “Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms,” PLoS ONE, vol. 6, no. 10, Article ID e26294, 2011. View at Publisher · View at Google Scholar · View at Scopus
  52. J. Li, N. White, Z. Zhang et al., “Detection of prostate cancer using serum proteomics pattern in a histologically confirmed population,” The Journal of Urology, vol. 171, no. 5, pp. 1782–1787, 2004. View at Publisher · View at Google Scholar · View at Scopus
  53. A. Xue, R. C. Gandy, L. Chung, R. C. Baxter, and R. C. Smith, “Discovery of diagnostic biomarkers for pancreatic cancer in immunodepleted serum by SELDI-TOF MS,” Pancreatology, vol. 12, no. 2, pp. 124–129, 2012. View at Publisher · View at Google Scholar · View at Scopus
  54. F. Navaglia, P. Fogar, D. Basso et al., “Pancreatic cancer biomarkers discovery by surface-enhanced laser desorption and ionization time-of-flight mass spectrometry,” Clinical Chemistry and Laboratory Medicine, vol. 47, no. 6, pp. 713–723, 2009. View at Publisher · View at Google Scholar · View at Scopus
  55. H. Gao, Z. Zheng, Z. Yue, F. Liu, L. Zhou, and X. Zhao, “Evaluation of serum diagnosis of pancreatic cancer by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry,” International Journal of Molecular Medicine, vol. 30, no. 5, pp. 1061–1068, 2012. View at Publisher · View at Google Scholar · View at Scopus
  56. Q. Song, W. Hu, P. Wang, Y. Yao, and H. Zeng, “Identification of serum biomarkers for lung cancer using magnetic bead-based SELDI-TOF-MS,” Acta Pharmacologica Sinica, vol. 32, no. 12, pp. 1537–1542, 2011. View at Publisher · View at Google Scholar · View at Scopus
  57. C. Şimşek, Ó. Sónmez, A. S. Yurdakul et al., “Importance of serum SELDI-TOF-MS analysis in the diagnosis of early lung cancer,” Asian Pacific Journal of Cancer Prevention, vol. 14, no. 3, pp. 2037–2042, 2013. View at Publisher · View at Google Scholar · View at Scopus
  58. X. Xiao, X. Wei, and D. He, “Proteomic approaches to biomarker discovery in lung cancers by SELDI technology,” Science in China C: Life Sciences, vol. 46, no. 5, pp. 531–537, 2003. View at Publisher · View at Google Scholar · View at Scopus
  59. L. Lei, X. Wang, Z. Zheng et al., “Identification of serum protein markers for breast cancer relapse with SELDI-TOF MS,” Anatomical Record, vol. 294, no. 6, pp. 941–944, 2011. View at Publisher · View at Google Scholar · View at Scopus
  60. A. W. van Winden, M.-C. W. Gast, J. H. Beijnen et al., “Validation of previously identified serum biomarkers for breast cancer with SELDI-TOF MS: a case control study,” BMC Medical Genomics, vol. 2, article 4, 2009. View at Publisher · View at Google Scholar · View at Scopus
  61. M. W. Gast, C. H. van Gils, L. F. A. Wessels et al., “Serum protein profiling for diagnosis of breast cancer using SELDI-TOF MS,” Oncology Reports, vol. 22, no. 1, pp. 205–213, 2009. View at Publisher · View at Google Scholar · View at Scopus
  62. L. L. Wilson, L. Tran, D. L. Morton, and D. S. B. Hoon, “Detection of differentially expressed proteins in early-stage melanoma patients using SELDI-TOF mass spectrometry,” Annals of the New York Academy of Sciences, vol. 1022, pp. 317–322, 2004. View at Publisher · View at Google Scholar · View at Scopus
  63. Z. Wang, K. Ding, J. Yu et al., “Proteomic analysis of primary colon cancer-associated fibroblasts using the SELDI-ProteinChip platform,” Journal of Zhejiang University: Science B, vol. 13, no. 3, pp. 159–167, 2012. View at Publisher · View at Google Scholar · View at Scopus
  64. N. Fan, C. Gao, and X. Wang, “Identification of regional lymph node involvement of colorectal cancer by serum SELDI proteomic patterns,” Gastroenterology Research and Practice, vol. 2011, Article ID 784967, 6 pages, 2011. View at Publisher · View at Google Scholar · View at Scopus
  65. I. Cadron, T. Van Gorp, P. Moerman, E. Waelkens, and I. Vergote, “Proteomic analysis of laser microdissected ovarian cancer tissue with SELDI-TOF MS,” Methods in Molecular Biology, vol. 755, pp. 155–163, 2011. View at Publisher · View at Google Scholar · View at Scopus
  66. H. Zhang, B. Kong, X. Qu, L. Jia, B. Deng, and Q. Yang, “Biomarker discovery for ovarian cancer using SELDI-TOF-MS,” Gynecologic Oncology, vol. 102, no. 1, pp. 61–66, 2006. View at Publisher · View at Google Scholar · View at Scopus
  67. S.-P. Wu, Y.-W. Lin, H.-C. Lai, T.-Y. Chu, Y.-L. Kuo, and H.-S. Liu, “SELDI-TOF MS profiling of plasma proteins in ovarian cancer,” Taiwanese Journal of Obstetrics and Gynecology, vol. 45, no. 1, pp. 26–32, 2006. View at Publisher · View at Google Scholar · View at Scopus
  68. C. Liu, “The application of SELDI-TOF-MS in clinical diagnosis of cancers,” Journal of Biomedicine and Biotechnology, vol. 2011, Article ID 245821, 6 pages, 2011. View at Publisher · View at Google Scholar · View at Scopus
  69. C. Melle, R. Kaufmann, M. Hommann et al., “Proteomic profiling in microdissected hepatocellular carcinoma tissue using ProteinChip technology,” International Journal of Oncology, vol. 24, no. 4, pp. 885–891, 2004. View at Google Scholar · View at Scopus
  70. M. Wisztorski, R. Lemaire, J. Stauber et al., “New developments in MALDI imaging for pathology proteomic studies,” Current Pharmaceutical Design, vol. 13, no. 32, pp. 3317–3324, 2007. View at Publisher · View at Google Scholar · View at Scopus
  71. R. M. Caprioli, T. B. Farmer, and J. Gile, “Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS,” Analytical Chemistry, vol. 69, no. 23, pp. 4751–4760, 1997. View at Publisher · View at Google Scholar · View at Scopus
  72. K. E. Burnum, D. S. Cornett, S. M. Puolitaival et al., “Spatial and temporal alterations of phospholipids determined by mass spectrometry during mouse embryo implantation,” Journal of Lipid Research, vol. 50, no. 11, pp. 2290–2298, 2009. View at Publisher · View at Google Scholar · View at Scopus
  73. O. Jardin-Mathé, D. Bonnel, J. Franck et al., “MITICS (MALDI Imaging Team Imaging Computing System): a new open source mass spectrometry imaging software,” Journal of Proteomics, vol. 71, no. 3, pp. 332–345, 2008. View at Publisher · View at Google Scholar · View at Scopus
  74. A. Mangé, P. Chaurand, H. Perrochia, P. Roger, R. M. Caprioli, and J. Solassol, “Liquid chromatography-tandem and MALDI imaging mass spectrometry analyses of RCL2/CS100-fixed, paraffin-embedded tissues: proteomics evaluation of an alternate fixative for biomarker discovery,” Journal of Proteome Research, vol. 8, no. 12, pp. 5619–5628, 2009. View at Publisher · View at Google Scholar · View at Scopus
  75. Y. Kimura, K. Tsutsumi, Y. Sugiura, and M. Setou, “Medical molecular morphology with imaging mass spectrometry,” Medical Molecular Morphology, vol. 42, no. 3, pp. 133–137, 2009. View at Publisher · View at Google Scholar · View at Scopus
  76. R. Mirnezami, K. Spagou, P. A. Vorkas et al., “Chemical mapping of the colorectal cancer microenvironment via MALDI imaging mass spectrometry (MALDI-MSI) reveals novel cancer-associated field effects,” Molecular Oncology, vol. 8, no. 1, pp. 39–49, 2014. View at Google Scholar
  77. G. Marko-Varga, T. E. Fehniger, M. Rezeli, B. Döme, T. Laurell, and Á. Végvári, “Drug localization in different lung cancer phenotypes by MALDI mass spectrometry imaging,” Journal of Proteomics, vol. 74, no. 7, pp. 982–992, 2011. View at Publisher · View at Google Scholar · View at Scopus
  78. X. Liu, J. L. Ide, I. Norton et al., “Molecular imaging of drug transit through the blood-brain barrier with MALDI mass spectrometry imaging,” Scientific Reports, vol. 3, article 2859, 2013. View at Publisher · View at Google Scholar
  79. S. C. C. Wong, C. M. L. Chan, B. B. Y. Ma et al., “Advanced proteomic technologies for cancer biomarker discovery,” Expert Review of Proteomics, vol. 6, no. 2, pp. 123–134, 2009. View at Publisher · View at Google Scholar · View at Scopus
  80. M. Andersson, M. R. Groseclose, A. Y. Deutch, and R. M. Caprioli, “Imaging mass spectrometry of proteins and peptides: 3D volume reconstruction,” Nature Methods, vol. 5, no. 1, pp. 101–108, 2008. View at Publisher · View at Google Scholar · View at Scopus
  81. J. Franck, K. Arafah, M. Elayed et al., “MALDI imaging mass spectrometry: state of the art technology in clinical proteomics,” Molecular and Cellular Proteomics, vol. 8, no. 9, pp. 2023–2033, 2009. View at Publisher · View at Google Scholar · View at Scopus
  82. G. L. Wright Jr., “Two dimensional acrylamide gel electrophoresis of cancer patient serum proteins,” Annals of Clinical and Laboratory Science, vol. 4, no. 4, pp. 281–293, 1974. View at Google Scholar · View at Scopus
  83. D. Hariharan, M. E. Weeks, and T. Crnogorac-Jurcevic, “Application of proteomics in cancer gene profiling: two-dimensional difference in gel electrophoresis (2D-DIGE),” Methods in Molecular Biology, vol. 576, pp. 197–211, 2010. View at Google Scholar · View at Scopus
  84. R. Deng, Z. Lu, Y. Chen, L. Zhou, and X. Lu, “Plasma proteomic analysis of pancreatic cancer by 2-dimensional gel electrophoresis,” Pancreas, vol. 34, no. 3, pp. 310–317, 2007. View at Publisher · View at Google Scholar · View at Scopus
  85. P. Alfonso, A. Núñez, J. Madoz-Gurpide, L. Lombardia, L. Sánchez, and J. I. Casal, “Proteomic expression analysis of colorectal cancer by two-dimensional differential gel electrophoresis,” Proteomics, vol. 5, no. 10, pp. 2602–2611, 2005. View at Publisher · View at Google Scholar · View at Scopus
  86. P. Gromov, I. Gromova, J. Bunkenborg et al., “Up-regulated proteins in the fluid bathing the tumour cell microenvironment as potential serological markers for early detection of cancer of the breast,” Molecular Oncology, vol. 4, no. 1, pp. 65–89, 2010. View at Publisher · View at Google Scholar · View at Scopus
  87. J. Sasse and S. R. Gallagher, “Chapter 8: Unit 8.9. Staining proteins in gels,” in Current Protocols in Immunology, 2004. View at Publisher · View at Google Scholar
  88. T. H. Steinberg, “Chapter 31 protein gel staining methods: an introduction and overview,” Methods in Enzymology, vol. 463, pp. 541–563, 2009. View at Publisher · View at Google Scholar · View at Scopus
  89. T. Kondo and S. Hirohashi, “Application of 2D-DIGE in cancer proteomics toward personalized medicine,” Methods in Molecular Biology, vol. 577, pp. 135–154, 2009. View at Publisher · View at Google Scholar · View at Scopus
  90. J. Koo, K. Kim, B. Min, and G. M. Lee, “Differential protein expression in human articular chondrocytes expanded in serum-free media of different medium osmolalities by DIGE,” Journal of Proteome Research, vol. 9, no. 5, pp. 2480–2487, 2010. View at Publisher · View at Google Scholar · View at Scopus
  91. Z. Ma, S. Dasari, M. C. Chambers et al., “IDPicker 2.0: improved protein assembly with high discrimination peptide identification filtering,” Journal of Proteome Research, vol. 8, no. 8, pp. 3872–3881, 2009. View at Publisher · View at Google Scholar · View at Scopus
  92. R. Ummanni, F. Mundt, H. Pospisil et al., “Identification of clinically relevant protein targets in prostate cancer with 2D-DIGE coupled mass spectrometry and systems biology network platform,” PLoS ONE, vol. 6, no. 2, Article ID e16833, 2011. View at Publisher · View at Google Scholar · View at Scopus
  93. J. L. López, “Two-dimensional electrophoresis in proteome expression analysis,” Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, vol. 849, no. 1-2, pp. 190–202, 2007. View at Publisher · View at Google Scholar · View at Scopus
  94. P. L. Roulhac, J. M. Ward, J. W. Thompson et al., “Microproteomics: quantitative proteomic profiling of small numbers of laser-captured cells,” Cold Spring Harbor Protocols, vol. 6, no. 2, 2011. View at Publisher · View at Google Scholar · View at Scopus
  95. Y. Zhang, Y. Ye, D. Shen et al., “Identification of transgelin-2 as a biomarker of colorectal cancer by laser capture microdissection and quantitative proteome analysis,” Cancer Science, vol. 101, no. 2, pp. 523–529, 2010. View at Publisher · View at Google Scholar · View at Scopus
  96. H. Yao, Z. Zhang, Z. Xiao et al., “Identification of metastasis associated proteins in human lung squamous carcinoma using two-dimensional difference gel electrophoresis and laser capture microdissection,” Lung Cancer, vol. 65, no. 1, pp. 41–48, 2009. View at Publisher · View at Google Scholar · View at Scopus
  97. L. F. Waanders, K. Chwalek, M. Monetti, C. Kumar, E. Lammert, and M. Mann, “Quantitative proteomic analysis of single pancreatic islets,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 45, pp. 18902–18907, 2009. View at Publisher · View at Google Scholar · View at Scopus
  98. M. S. Scicchitano, D. A. Dalmas, R. W. Boyce, H. C. Thomas, and K. S. Frazier, “Protein extraction of formalin-fixed, paraffin-embedded tissue enables robust proteomic profiles by mass spectrometry,” Journal of Histochemistry and Cytochemistry, vol. 57, no. 9, pp. 849–860, 2009. View at Publisher · View at Google Scholar · View at Scopus
  99. Y. Nan, S. Yang, Y. Tian et al., “Analysis of the expression protein profiles of lung squamous carcinoma cell using shot-gun proteomics strategy,” Medical Oncology, vol. 26, no. 2, pp. 215–221, 2009. View at Publisher · View at Google Scholar · View at Scopus
  100. Z. Daohai and E. S. Koay, “Analysis of laser capture microdissected cells by 2-dimensional gel electrophoresis,” Methods in Molecular Biology, vol. 428, pp. 77–91, 2007. View at Google Scholar · View at Scopus
  101. D. J. Johann, S. Mukherjee, D. A. Prieto, T. D. Veenstra, and J. Blonder, “Profiling solid tumor heterogeneity by LCM and biological MS of fresh-frozen tissue sections,” Methods in Molecular Biology, vol. 755, pp. 95–106, 2011. View at Publisher · View at Google Scholar · View at Scopus
  102. K. Uleberg, A. C. Munk, C. Brede et al., “Discrimination of grade 2 and 3 cervical intraepithelial neoplasia by means of analysis of water soluble proteins recovered from cervical biopsies,” Proteome Science, vol. 9, article 36, 2011. View at Publisher · View at Google Scholar · View at Scopus
  103. C. Mueller, A. C. deCarvalho, T. Mikkelsen et al., “Glioblastoma cell enrichment is critical for analysis of phosphorylated drug targets and proteomic-genomic correlations,” Cancer Research, vol. 74, no. 3, pp. 818–828, 2014. View at Publisher · View at Google Scholar
  104. L. Melton, “Proteomics in multiplex,” Nature, vol. 429, no. 6987, pp. 101–107, 2004. View at Google Scholar · View at Scopus
  105. P. Moore and J. Clayton, “To affinity and beyond,” Nature, vol. 426, no. 6967, pp. 725–731, 2003. View at Google Scholar · View at Scopus
  106. L. A. Liotta, V. Espina, A. I. Mehta et al., “Protein microarrays: meeting analytical challenges for clinical applications,” Cancer Cell, vol. 3, no. 4, pp. 317–325, 2003. View at Publisher · View at Google Scholar · View at Scopus
  107. C. P. Pjaweletz, L. Charboneau, V. E. Bichsel et al., “Reverse phase protein microarrays which capture disease progression show activation of pro-survival pathways at the cancer invasion front,” Oncogene, vol. 20, no. 16, pp. 1981–1989, 2001. View at Publisher · View at Google Scholar · View at Scopus
  108. S. Sundaresh, D. L. Doolan, S. Hirst et al., “Identification of humoral immune responses in protein microarrays using DNA microarray data analysis techniques,” Bioinformatics, vol. 22, no. 14, pp. 1760–1766, 2006. View at Publisher · View at Google Scholar · View at Scopus
  109. H. Chandra and S. Srivastava, “Cell-free synthesis-based protein microarrays and their applications,” Proteomics, vol. 10, no. 4, pp. 717–730, 2010. View at Publisher · View at Google Scholar · View at Scopus
  110. N. Ramachandran, J. V. Raphael, E. Hainsworth et al., “Next-generation high-density self-assembling functional protein arrays,” Nature Methods, vol. 5, no. 6, pp. 535–538, 2008. View at Publisher · View at Google Scholar · View at Scopus
  111. R. Spera, J. Labaer, and C. Nicolini, “MALDI-TOF characterization of NAPPA-generated proteins,” Journal of Mass Spectrometry, vol. 46, no. 9, pp. 960–965, 2011. View at Publisher · View at Google Scholar · View at Scopus
  112. L. Melton, “Pharmacogenetics and genotyping: on the trail of SNPs,” Nature, vol. 422, no. 6934, pp. 917–923, 2003. View at Google Scholar · View at Scopus
  113. B. Houser, “Bio-rad's Bio-Plex suspension array system, xMAP technology overview,” Archives of Physiology and Biochemistry, vol. 118, no. 4, pp. 192–196, 2012. View at Publisher · View at Google Scholar · View at Scopus
  114. S. M. Hanash, S. J. Pitteri, and V. M. Faca, “Mining the plasma proteome for cancer biomarkers,” Nature, vol. 452, no. 7187, pp. 571–579, 2008. View at Publisher · View at Google Scholar · View at Scopus
  115. G. Poste, “Bring on the biomarkers,” Nature, vol. 469, no. 7329, pp. 156–157, 2011. View at Publisher · View at Google Scholar · View at Scopus
  116. M. Polanski and N. L. Anderson, “A list of candidate cancer biomarkers for targeted proteomics,” Biomark Insights, vol. 1, pp. 1–48, 2007. View at Google Scholar
  117. S. Ohtsuki, Y. Uchida, Y. Kubo, and T. Terasaki, “Quantitative targeted absolute proteomics-based ADME research as a new path to drug discovery and development: methodology, advantages, strategy, and prospects,” Journal of Pharmaceutical Sciences, vol. 100, no. 9, pp. 3547–3559, 2011. View at Publisher · View at Google Scholar · View at Scopus
  118. E. S. Boja and H. Rodriguez, “Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins,” Proteomics, vol. 12, no. 8, pp. 1093–1110, 2012. View at Publisher · View at Google Scholar · View at Scopus
  119. D. C. Liebler and L. J. Zimmerman, “Targeted quantitation of proteins by mass spectrometry,” Biochemistry, vol. 52, no. 22, pp. 3797–3806, 2013. View at Publisher · View at Google Scholar · View at Scopus
  120. P. Picotti and R. Aebersold, “Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions,” Nature Methods, vol. 9, no. 6, pp. 555–566, 2012. View at Publisher · View at Google Scholar · View at Scopus
  121. S. Pan, R. Aebersold, R. Chen et al., “Mass spectrometry based targeted protein quantification: methods and applications,” Journal of Proteome Research, vol. 8, no. 2, pp. 787–797, 2009. View at Publisher · View at Google Scholar · View at Scopus
  122. H. Rodriguez, R. Rivers, C. Kinsinger et al., “Reconstructing the pipeline by introducing multiplexed multiple reaction monitoring mass spectrometry for cancer biomarker verification: an NCI-CPTC initiative perspective,” Proteomics: Clinical Applications, vol. 4, no. 12, pp. 904–914, 2010. View at Publisher · View at Google Scholar · View at Scopus
  123. B. Domon and R. Aebersold, “Mass spectrometry and protein analysis,” Science, vol. 312, no. 5771, pp. 212–217, 2006. View at Publisher · View at Google Scholar · View at Scopus
  124. H. Schupke, R. Hempel, R. Eckardt, and T. Kronbach, “Identification of talinolol metabolites in urine of man, dog, rat and mouse after oral administration by high-performance liquid chromatography-thermospray tandem mass spectrometry,” Journal of Mass Spectrometry, vol. 31, pp. 1371–1381, 1996. View at Google Scholar
  125. R. Kostiainen, T. Kotiaho, T. Kuuranne, and S. Auriola, “Liquid chromatography/atmospheric pressure ionization-mass spectrometry in drug metabolism studies,” Journal of Mass Spectrometry, vol. 38, no. 4, pp. 357–372, 2003. View at Publisher · View at Google Scholar · View at Scopus
  126. S. S.-C. Tai, D. M. Bunk, E. White V, and M. J. Welch, “Development and evaluation of a reference measurement procedure for the determination of total 3,3′,5-triiodothyronine in human serum using isotope-dilution liquid chromatography-tandem mass spectrometry,” Analytical Chemistry, vol. 76, no. 17, pp. 5092–5096, 2004. View at Publisher · View at Google Scholar · View at Scopus
  127. N. Ahmed and P. J. Thornalley, “Quantitative screening of protein biomarkers of early glycation, advanced glycation, oxidation and nitrosation in cellular and extracellular proteins by tandem mass spectrometry multiple reaction monitoring,” Biochemical Society Transactions, vol. 31, no. 6, pp. 1417–1422, 2003. View at Publisher · View at Google Scholar · View at Scopus
  128. A. Sannino, L. Bolzoni, and M. Bandini, “Application of liquid chromatography with electrospray tandem mass spectrometry to the determination of a new generation of pesticides in processed fruits and vegetables,” Journal of Chromatography A, vol. 1036, no. 2, pp. 161–169, 2004. View at Publisher · View at Google Scholar · View at Scopus
  129. M. A. Kuzyk, D. Smith, J. Yang et al., “Multiple reaction monitoring-based, multiplexed, absolute quantitation of 45 proteins in human plasma,” Molecular and Cellular Proteomics, vol. 8, no. 8, pp. 1860–1877, 2009. View at Publisher · View at Google Scholar · View at Scopus
  130. Z. Meng and T. D. Veenstra, “Targeted mass spectrometry approaches for protein biomarker verification,” Journal of Proteomics, vol. 74, no. 12, pp. 2650–2659, 2011. View at Publisher · View at Google Scholar · View at Scopus
  131. H. Keshishian, T. Addona, M. Burgess, E. Kuhn, and S. A. Carr, “Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution,” Molecular and Cellular Proteomics, vol. 6, no. 12, pp. 2212–2229, 2007. View at Publisher · View at Google Scholar · View at Scopus
  132. H. Keshishian, T. Addona, M. Burgess et al., “Quantification of cardiovascular biomarkers in patient plasma by targeted mass spectrometry and stable isotope dilution,” Molecular and Cellular Proteomics, vol. 8, no. 10, pp. 2339–2349, 2009. View at Publisher · View at Google Scholar · View at Scopus
  133. A. N. Hoofnagle, J. O. Becker, M. H. Wener, and J. W. Heinecke, “Quantification of thyroglobulin, a low-abundance serum protein, by immunoaffinity peptide enrichment and tandem mass spectrometry,” Clinical Chemistry, vol. 54, no. 11, pp. 1796–1804, 2008. View at Publisher · View at Google Scholar · View at Scopus
  134. “Method of the year 2012,” Nature Methods, vol. 10, no. 1, 2013. View at Publisher · View at Google Scholar
  135. T. A. Addona, S. E. Abbatiello, B. Schilling et al., “Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma,” Nature Biotechnology, vol. 27, pp. 633–641, 2009. View at Publisher · View at Google Scholar · View at Scopus
  136. R. Aebersold, A. L. Burlingame, and R. A. Bradshaw, “Western blots versus selected reaction monitoring assays: time to turn the tables?” Molecular & Cellular Proteomics, vol. 12, no. 9, pp. 2381–2382, 2013. View at Publisher · View at Google Scholar
  137. J. J. Kennedy, S. E. Abbatiello, K. Kim, and et al, “Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins,” Nature Methods, vol. 11, pp. 149–155, 2014. View at Publisher · View at Google Scholar
  138. S. A. Carr, S. E. Abbatiello, B. L. Ackermann et al., “Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach,” Molecular & Cellular Proteomics, vol. 13, no. 3, pp. 907–917, 2014. View at Publisher · View at Google Scholar
  139. E. Kuhn, T. Addona, H. Keshishian et al., “Developing multiplexed assays for troponin I and interleukin-33 in plasma by peptide immunoaffinity enrichment and targeted mass spectrometry,” Clinical Chemistry, vol. 55, no. 6, pp. 1108–1117, 2009. View at Publisher · View at Google Scholar · View at Scopus
  140. T. Fortin, A. Salvador, J. P. Charrier et al., “Clinical quantitation of prostate-specific antigen biomarker in the low nanogram/milliliter range by conventional bore liquid chromatography-tandem mass spectrometry (multiple reaction monitoring) coupling and correlation with ELISA tests,” Molecular and Cellular Proteomics, vol. 8, no. 5, pp. 1006–1015, 2009. View at Publisher · View at Google Scholar · View at Scopus
  141. M. Hossain, D. T. Kaleta, E. W. Robinson et al., “Enhanced sensitivity for selected reaction monitoring mass spectrometry-based targeted proteomics using a dual stage electrodynamic ion funnel interface,” Molecular & Cellular Proteomics, vol. 10, no. 2, Article ID M000062-MCP201, 2011. View at Publisher · View at Google Scholar · View at Scopus
  142. T. Fortin, A. Salvador, J. P. Charrier et al., “Multiple reaction monitoring cubed for protein quantification at the low nanogram/milliliter level in nondepleted human serum,” Analytical Chemistry, vol. 81, no. 22, pp. 9343–9352, 2009. View at Publisher · View at Google Scholar · View at Scopus
  143. T. Shi, T. L. Fillmore, X. Sun et al., “Antibody-free, targeted mass-spectrometric approach for quantification of proteins at low picogram per milliliter levels in human plasma/serum,” Proceedings of the National Academy of Sciences of the United States of America, vol. 109, no. 38, pp. 15395–15400, 2012. View at Publisher · View at Google Scholar · View at Scopus
  144. A. C. Peterson, J. D. Russell, D. J. Bailey, M. S. Westphall, and J. J. Coon, “Parallel reaction monitoring for high resolution and high mass accuracy quantitative, targeted proteomics,” Molecular and Cellular Proteomics, vol. 11, no. 11, pp. 1475–1488, 2012. View at Publisher · View at Google Scholar · View at Scopus
  145. A. Doerr, “Targeting with PRM,” Nature Methods, vol. 9, no. 10, p. 950, 2012. View at Google Scholar
  146. J. Sherman, M. J. McKay, K. Ashman, and M. P. Molloy, “How specific is my SRM?: the issue of precursor and product ion redundancy,” Proteomics, vol. 9, no. 5, pp. 1120–1123, 2009. View at Publisher · View at Google Scholar · View at Scopus
  147. L. C. Gillet, P. Navarro, S. Tate et al., “Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis,” Molecular & Cellular Proteomics, vol. 11, no. 6, 2012. View at Publisher · View at Google Scholar · View at Scopus
  148. K. P. Law and Y. P. Lim, “Recent advances in mass spectrometry: data independent analysis and hyper reaction monitoring,” Expert Review of Proteomics, vol. 10, pp. 551–566, 2013. View at Publisher · View at Google Scholar
  149. N. Rifai, M. A. Gillette, and S. A. Carr, “Protein biomarker discovery and validation: the long and uncertain path to clinical utility,” Nature Biotechnology, vol. 24, no. 8, pp. 971–983, 2006. View at Publisher · View at Google Scholar · View at Scopus
  150. D. Nedelkov, “Mass spectrometry-based protein assays for in vitro diagnostic testing,” Expert Review of Molecular Diagnostics, vol. 12, no. 3, pp. 235–239, 2012. View at Publisher · View at Google Scholar · View at Scopus
  151. G. R. Nicol, M. Han, J. Kim et al., “Use of an immunoaffinity-mass spectrometry-based approach for the quantification of protein biomarkers from serum samples of lung cancer patients,” Molecular & Cellular Proteomics, vol. 7, no. 10, pp. 1974–1982, 2008. View at Publisher · View at Google Scholar · View at Scopus
  152. V. Kulasingam, C. R. Smith, I. Batruch, A. Buckler, D. A. Jeffery, and E. P. Diamandis, “‘Product ion monitoring’ assay for prostate-specific antigen in serum using a linear ion-trap,” Journal of Proteome Research, vol. 7, no. 2, pp. 640–647, 2008. View at Publisher · View at Google Scholar · View at Scopus
  153. M. J. Berna, Y. Zhen, D. E. Watson, J. E. Hale, and B. L. Ackermann, “Strategic use of immunoprecipitation and LC/MS/MS for trace-level protein quantification: myosin light chain 1, a biomarker of cardiac necrosis,” Analytical Chemistry, vol. 79, no. 11, pp. 4199–4205, 2007. View at Publisher · View at Google Scholar · View at Scopus
  154. E. E. Niederkofler, D. A. Phillips, B. Krastins et al., “Targeted selected reaction monitoring mass spectrometric immunoassay for insulin-like growth factor 1,” PLoS ONE, vol. 8, Article ID e81125, 2013. View at Google Scholar
  155. V. Brun, C. Masselon, J. Garin, and A. Dupuis, “Isotope dilution strategies for absolute quantitative proteomics,” Journal of Proteomics, vol. 72, no. 5, pp. 740–749, 2009. View at Publisher · View at Google Scholar · View at Scopus
  156. D. Lebert, A. Dupuis, J. Garin, C. Bruley, and V. Brun, “Production and use of stable isotope-labeled proteins for absolute quantitative proteomics,” Methods in Molecular Biology, vol. 753, pp. 93–115, 2011. View at Publisher · View at Google Scholar · View at Scopus
  157. G. Picard, D. Lebert, M. Louwagie et al., “PSAQ standards for accurate MS-based quantification of proteins: from the concept to biomedical applications,” Journal of Mass Spectrometry, vol. 47, no. 10, pp. 1353–1363, 2012. View at Publisher · View at Google Scholar · View at Scopus
  158. R. W. Nelson, D. Nedelkov, K. A. Tubbs, and U. A. Kiernan, “Quantitative mass spectrometric immunoassay of insulin like growth factor 1,” Journal of Proteome Research, vol. 3, no. 4, pp. 851–855, 2004. View at Publisher · View at Google Scholar · View at Scopus
  159. M. R. Stratton, P. J. Campbell, and P. A. Futreal, “The cancer genome,” Nature, vol. 458, no. 7239, pp. 719–724, 2009. View at Publisher · View at Google Scholar · View at Scopus
  160. G. R. Bignell, C. D. Greenman, H. Davies et al., “Signatures of mutation and selection in the cancer genome,” Nature, vol. 463, no. 7283, pp. 893–898, 2010. View at Publisher · View at Google Scholar · View at Scopus
  161. Q. Wang, R. Chaerkady, J. Wu et al., “Mutant proteins as cancer-specific biomarkers,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 6, pp. 2444–2449, 2011. View at Publisher · View at Google Scholar · View at Scopus
  162. D. P. Little, A. Braun, M. J. O'Donnell, and H. Koster, “Mass spectrometry from miniaturized arrays for full comparative DNA analysis,” Nature Medicine, vol. 3, no. 12, pp. 1413–1416, 1997. View at Publisher · View at Google Scholar · View at Scopus
  163. N. L. Anderson, N. G. Anderson, L. R. Haines, D. B. Hardie, R. W. Olafson, and T. W. Pearson, “Mass spectrometric quantitation of peptides and proteins using Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA),” Journal of Proteome Research, vol. 3, no. 2, pp. 235–244, 2004. View at Publisher · View at Google Scholar · View at Scopus
  164. J. R. Whiteaker, L. Zhao, H. Y. Zhang et al., “Antibody-based enrichment of peptides on magnetic beads for mass-spectrometry-based quantification of serum biomarkers,” Analytical Biochemistry, vol. 362, no. 1, pp. 44–54, 2007. View at Publisher · View at Google Scholar · View at Scopus
  165. N. L. Anderson, A. Jackson, D. Smith, D. Hardie, C. Borchers, and T. W. Pearson, “SISCAPA peptide enrichment on magnetic beads using an in-line bead trap device,” Molecular & Cellular Proteomics, vol. 8, no. 5, pp. 995–1005, 2009. View at Publisher · View at Google Scholar · View at Scopus
  166. J. R. Whiteaker, L. Zhao, L. Anderson, and A. G. Paulovich, “An automated and multiplexed method for high throughput peptide immunoaffinity enrichment and multiple reaction monitoring mass spectrometry-based quantification of protein biomarkers,” Molecular and Cellular Proteomics, vol. 9, no. 1, pp. 184–196, 2010. View at Publisher · View at Google Scholar · View at Scopus
  167. R. M. Schoenherr, L. Zhao, J. R. Whiteaker et al., “Automated screening of monoclonal antibodies for SISCAPA assays using a magnetic bead processor and liquid chromatography-selected reaction monitoring-mass spectrometry,” Journal of Immunological Methods, vol. 353, no. 1-2, pp. 49–61, 2010. View at Publisher · View at Google Scholar · View at Scopus
  168. M. Razavi, M. E. Pope, M. V. Soste et al., “MALDI Immunoscreening (MiSCREEN): a method for selection of anti-peptide monoclonal antibodies for use in immunoproteomics,” Journal of Immunological Methods, vol. 364, no. 1-2, pp. 50–64, 2011. View at Publisher · View at Google Scholar · View at Scopus
  169. J. D. Reid, D. T. Holmes, D. R. Mason, B. Shah, and C. H. Borchers, “Towards the development of an immuno MALDI (iMALDI) mass spectrometry assay for the diagnosis of hypertension,” Journal of the American Society for Mass Spectrometry, vol. 21, no. 10, pp. 1680–1686, 2010. View at Publisher · View at Google Scholar · View at Scopus
  170. J. Jiang, C. E. Parker, K. A. Hoadley, C. M. Perou, G. Boysen, and C. H. Borchers, “Development of an immuno tandem mass spectrometry (iMALDI) assay for EGFR diagnosis,” Proteomics: Clinical Applications, vol. 1, no. 12, pp. 1651–1659, 2007. View at Publisher · View at Google Scholar · View at Scopus
  171. M. H. Elliott, D. S. Smith, C. E. Parker, and C. Borchers, “Current trends in quantitative proteomics,” Journal of Mass Spectrometry, vol. 44, no. 12, pp. 1637–1660, 2009. View at Publisher · View at Google Scholar · View at Scopus
  172. J. R. Whiteaker, C. Lin, J. Kennedy et al., “A targeted proteomics-based pipeline for verification of biomarkers in plasma,” Nature Biotechnology, vol. 29, no. 7, pp. 625–634, 2011. View at Publisher · View at Google Scholar · View at Scopus
  173. S. A. Agger, L. C. Marney, and A. N. Hoofnagle, “Simultaneous quantification of apolipoprotein A-I and apolipoprotein B by liquid-chromatography-multiple-reaction-monitoring mass spectrometry,” Clinical Chemistry, vol. 56, no. 12, pp. 1804–1813, 2010. View at Publisher · View at Google Scholar · View at Scopus
  174. B. MacLean, D. M. Tomazela, N. Shulman et al., “Skyline: an open source document editor for creating and analyzing targeted proteomics experiments,” Bioinformatics, vol. 26, no. 7, pp. 966–968, 2010. View at Publisher · View at Google Scholar · View at Scopus
  175. D. B. Martin, T. Holzman, D. May et al., “MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments,” Molecular and Cellular Proteomics, vol. 7, no. 11, pp. 2270–2278, 2008. View at Publisher · View at Google Scholar · View at Scopus
  176. M.-Y. K. Brusniak, S.-T. Kwok, M. Christiansen et al., “ATAQS: a computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry,” BMC Bioinformatics, vol. 12, article 78, 2011. View at Publisher · View at Google Scholar · View at Scopus
  177. L. Reiter, O. Rinner, P. Picotti et al., “MProphet: automated data processing and statistical validation for large-scale SRM experiments,” Nature Methods, vol. 8, no. 5, pp. 430–435, 2011. View at Publisher · View at Google Scholar · View at Scopus
  178. P. Picotti, H. Lam, D. Campbell et al., “A database of mass spectrometric assays for the yeast proteome,” Nature Methods, vol. 5, no. 11, pp. 913–914, 2008. View at Publisher · View at Google Scholar · View at Scopus
  179. S. E. Abbatiello, D. R. Mani, H. Keshishian, and S. A. Carr, “Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry,” Clinical Chemistry, vol. 56, no. 2, pp. 291–305, 2010. View at Publisher · View at Google Scholar · View at Scopus
  180. M. Mann, “Comparative analysis to guide quality improvements in proteomics,” Nature Methods, vol. 6, no. 10, pp. 717–719, 2009. View at Publisher · View at Google Scholar · View at Scopus
  181. E. F. Petricoin III, A. M. Ardekani, and B. A. Hitt, “Use of proteomic patterns in serum to identify ovarian cancer,” The Lancet, vol. 364, no. 9434, p. 582, 2004. View at Publisher · View at Google Scholar · View at Scopus
  182. E. P. Diamandis, “Cancer biomarkers: can we turn recent failures into success?” Journal of the National Cancer Institute, vol. 102, no. 19, pp. 1462–1467, 2010. View at Publisher · View at Google Scholar · View at Scopus
  183. E. P. Diamandis, “Proteomic patterns in biological fluids: do they represent the future of cancer diagnostics?” Clinical Chemistry, vol. 49, no. 8, pp. 1272–1275, 2003. View at Publisher · View at Google Scholar · View at Scopus
  184. E. P. Diamandis, “Mass spectrometry as a diagnostic and a cancer biomarker discovery tool: opportunities and potential limitations,” Molecular and Cellular Proteomics, vol. 3, no. 4, pp. 367–378, 2004. View at Publisher · View at Google Scholar · View at Scopus
  185. E. P. Diamandis, “Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems,” Journal of the National Cancer Institute, vol. 96, no. 5, pp. 353–356, 2004. View at Publisher · View at Google Scholar · View at Scopus
  186. E. F. Petricoin, K. C. Zoon, E. C. Kohn, J. C. Barrett, and L. A. Liotta, “Clinical proteomics: translating benchside promise into bedside reality,” Nature Reviews Drug Discovery, vol. 1, no. 9, pp. 683–695, 2002. View at Publisher · View at Google Scholar · View at Scopus
  187. K. Chapman, “The ProteinChip biomarker system from ciphergen biosystems: a novel proteomics platform for rapid biomarker discovery and validation,” Biochemical Society Transactions, vol. 30, no. 2, pp. 82–87, 2002. View at Google Scholar · View at Scopus
  188. D. McLerran, W. E. Grizzle, Z. Feng et al., “SELDI-TOF MS whole serum proteomic profiling with IMAC surface does not reliably detect prostate cancer,” Clinical Chemistry, vol. 54, no. 1, pp. 53–60, 2008. View at Publisher · View at Google Scholar · View at Scopus
  189. A. W. Bell, E. W. Deutsch, C. E. Au et al., “A HUPO test sample study reveals common problems in mass spectrometry-based proteomics,” Nature Methods, vol. 6, no. 6, pp. 423–430, 2009. View at Publisher · View at Google Scholar
  190. D. B. Friedman, T. M. Andacht, M. K. Bunger et al., “The ABRF Proteomics Research Group Studies: Educational exercises for qualitative and quantitative proteomic analyses,” Proteomics, vol. 11, no. 8, pp. 1371–1381, 2011. View at Publisher · View at Google Scholar · View at Scopus
  191. A. G. Paulovich, D. Billheimer, A. L. Ham et al., “Interlaboratory study characterizing a yeast performance standard for benchmarking LC-MS platform performance,” Molecular and Cellular Proteomics, vol. 9, no. 2, pp. 242–254, 2010. View at Publisher · View at Google Scholar · View at Scopus
  192. P. A. Rudnick, K. R. Clauser, L. E. Kilpatrick et al., “Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses,” Molecular and Cellular Proteomics, vol. 9, no. 2, pp. 225–241, 2010. View at Publisher · View at Google Scholar · View at Scopus
  193. D. L. Tabb, L. Vega-Montoto, P. A. Rudnick et al., “Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry,” Journal of Proteome Research, vol. 9, no. 2, pp. 761–776, 2010. View at Publisher · View at Google Scholar · View at Scopus
  194. A. Beasley-Green, D. Bunk, P. Rudnick, L. Kilpatrick, and K. Phinney, “A proteomics performance standard to support measurement quality in proteomics,” Proteomics, vol. 12, no. 7, pp. 923–931, 2012. View at Publisher · View at Google Scholar · View at Scopus
  195. S. E. Abbatiello, D. R. Mani, B. Schilling et al., “Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS),” Molecular & Cellular Proteomics, vol. 12, pp. 2623–2639, 2013. View at Google Scholar
  196. J. D. Theis, S. Dasari, J. A. Vrana, P. J. Kurtin, and A. Dogan, “Shotgun-proteomics-based clinical testing for diagnosis and classification of amyloidosis,” Journal of Mass Spectrometry, vol. 48, pp. 1067–1077, 2013. View at Publisher · View at Google Scholar
  197. Z. Zhang and D. W. Chan, “The road from discovery to clinical diagnostics: lessons learned from the first FDA-cleared in vitro diagnostic multivariate index assay of proteomic biomarkers,” Cancer Epidemiology Biomarkers and Prevention, vol. 19, no. 12, pp. 2995–2999, 2010. View at Publisher · View at Google Scholar · View at Scopus
  198. F. E. Regnier, S. J. Skates, M. Mesri et al., “Protein-based multiplex assays: Mock presubmissions to the US food and drug administration,” Clinical Chemistry, vol. 56, no. 2, pp. 165–171, 2010. View at Publisher · View at Google Scholar · View at Scopus
  199. H. A. Yeong, Y. L. Ji, Y. L. Ju, Y. Kim, H. K. Jeong, and S. Y. Jong, “Quantitative analysis of an aberrant glycoform of TIMP1 from colon cancer serum by L-PHA-enrichment and SISCAPA with MRM mass spectrometry,” Journal of Proteome Research, vol. 8, no. 9, pp. 4216–4224, 2009. View at Publisher · View at Google Scholar · View at Scopus
  200. B. Wollscheid, D. Bausch-Fluck, C. Henderson et al., “Mass-spectrometric identification and relative quantification of N-linked cell surface glycoproteins,” Nature Biotechnology, vol. 27, no. 4, pp. 378–386, 2009. View at Publisher · View at Google Scholar · View at Scopus
  201. S. Decramer, S. Wittke, H. Mischak et al., “Predicting the clinical outcome of congenital unilateral ureteropelvic junction obstruction in newborn by urinary proteome analysis,” Nature Medicine, vol. 12, no. 4, pp. 398–400, 2006. View at Publisher · View at Google Scholar · View at Scopus
  202. N. L. Anderson, N. G. Anderson, T. W. Pearson et al., “A human proteome detection and quantitation project,” Molecular and Cellular Proteomics, vol. 8, no. 5, pp. 883–886, 2009. View at Publisher · View at Google Scholar · View at Scopus
  203. J. Munoz, T. Y. Low, Y. J. Kok et al., “The quantitative proteomes of human-induced pluripotent stem cells and embryonic stem cells,” Molecular Systems Biology, vol. 7, article 550, 2011. View at Publisher · View at Google Scholar · View at Scopus
  204. N. Nagaraj, J. R. Wisniewski, T. Geiger et al., “Deep proteome and transcriptome mapping of a human cancer cell line,” Molecular Systems Biology, vol. 7, article 548, 2011. View at Publisher · View at Google Scholar · View at Scopus
  205. R. M. Branca, L. M. Orre, H. J. Johansson et al., “HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics,” Nature Methods, vol. 11, pp. 59–62, 2014. View at Google Scholar
  206. T. Y. Low, S. van Heesch, H. van den Toorn, and et al, “Quantitative and qualitative proteome characteristics extracted from in-depth integrated genomics and proteomics analysis,” Cell Reports, vol. 5, pp. 1469–1478, 2013. View at Google Scholar
  207. A. F. M. Altelaar, J. Munoz, and A. J. R. Heck, “Next-generation proteomics: towards an integrative view of proteome dynamics,” Nature Reviews Genetics, vol. 14, no. 1, pp. 35–48, 2013. View at Publisher · View at Google Scholar · View at Scopus
  208. W. W. Soon, M. Hariharan, and M. P. Snyder, “High-throughput sequencing for biology and medicine,” Molecular Systems Biology, vol. 9, article 640, 2013. View at Publisher · View at Google Scholar · View at Scopus
  209. K. Ning, D. Fermin, and A. I. Nesvizhskii, “Comparative analysis of different label-free mass spectrometry based protein abundance estimates and their correlation with RNA-Seq gene expression data,” Journal of Proteome Research, vol. 11, no. 4, pp. 2261–2271, 2012. View at Publisher · View at Google Scholar · View at Scopus
  210. E. Venter, R. D. Smith, and S. H. Payne, “Proteogenomic analysis of bacteria and archaea: a 46 organism case study,” PLoS ONE, vol. 6, no. 11, Article ID e27587, 2011. View at Publisher · View at Google Scholar · View at Scopus
  211. S. Renuse, R. Chaerkady, and A. Pandey, “Proteogenomics,” Proteomics, vol. 11, no. 4, pp. 620–630, 2011. View at Publisher · View at Google Scholar · View at Scopus
  212. J. Cox and M. Mann, “Quantitative, high-resolution proteomics for data-driven systems biology,” Annual Review of Biochemistry, vol. 80, pp. 273–299, 2011. View at Publisher · View at Google Scholar · View at Scopus