Biomarker Discovery for Metastatic Disease

  • Gilbert S. Omenn
  • James D. Cavalcoli


Emerging knowledge about the many features of metastasis offers numerous possibilities for discovery and exploitation of diagnostic and prognostic biomarkers and targets for therapy. A systems biology approach that encompasses differential expression of mRNAs (gene expression), microRNAs (gene regulators), and proteins in primary and metastatic tumors, in proximal biofluids, and in the blood plasma generates potentially complementary molecular signatures. We illustrate the use of Oncomine and Molecular Concepts Maps and the biological amplification of tumor protein signals with immune responses that produce autoantibodies in relation to lung cancers.


Epidermal Growth Factor Receptor Lung Adenocarcinoma Epidermal Growth Factor Receptor Expression Epidermal Growth Factor Receptor Gene Epidermal Growth Factor Receptor TKIs 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by grants MEDC 687, NIH U54 DA02159, and SAIC/NCI 23X110A. We thank Denise Taylor-Moon for expert assistance with the manuscript.


  1. 1.
    Omenn, G.S. Strategies for plasma proteomic profiling of cancers. Proteomics 6: 5662–73, 2006.PubMedCrossRefGoogle Scholar
  2. 2.
    Henschke, C.I., D.F. Yankelevitz, D.M. Libby, M.W. Pasmantier, J.P. Smith, and O.S. Miettinen. Survival of patients with stage I lung cancer detected on CT screening. N Engl J Med 355: 1763–71, 2006.PubMedCrossRefGoogle Scholar
  3. 3.
    Omenn, G.S. Human lung cancer chemoprevention strategies: Parker B. Francis lecture. Chest 125: 123S–7S, 2004.PubMedCrossRefGoogle Scholar
  4. 4.
    Sporn, M.B. The war on cancer. Lancet 347: 1377–81, 1996.PubMedCrossRefGoogle Scholar
  5. 5.
    Hanahan, D. and R.A. Weinberg. The hallmarks of cancer. Cell 100: 57–70, 2000.PubMedCrossRefGoogle Scholar
  6. 6.
    Weinberg, R.A. Moving out: invasion and metastasis, in The Biology of Cancer (New York: Garland Science, Taylor & Francis Group, 2006).  Chapter 14, 587–654.Google Scholar
  7. 7.
    Padua, D., X.H. Zhang, Q. Wang, C. Nadal, W.L. Gerald, R.R. Gomis, and J. Massague. TGFbeta primes breast tumors for lung metastasis seeding through angiopoietin-like 4. Cell 133: 66–77, 2008.PubMedCrossRefGoogle Scholar
  8. 8.
    Dvorak, H.F., M. Detmar, K.P. Claffey, J.A. Nagy, L. van de Water, and D.R. Senger. Vascular permeability factor/vascular endothelial growth factor: an important mediator of angiogenesis in malignancy and inflammation. Int Arch Allergy Immunol 107: 233–5, 1995.PubMedCrossRefGoogle Scholar
  9. 9.
    Naumov, G.N., I.C. MacDonald, P.M. Weinmeister, N. Kerkvliet, K.V. Nadkarni, S.M. Wilson, V.L. Morris, A.C. Groom, and A.F. Chambers. Persistence of solitary mammary carcinoma cells in a secondary site: a possible contributor to dormancy. Cancer Res 62: 2162–8, 2002.PubMedGoogle Scholar
  10. 10.
    Simonson, A.B. and J.E. Schnitzer. Vascular proteomic mapping in vivo. J Thromb Haemost 5 Suppl 1: 183–7, 2007.PubMedCrossRefGoogle Scholar
  11. 11.
    Murphy, E.A., B.K. Majeti, L.A. Barnes, M. Makale, S.M. Weis, K. Lutu-Fuga, W. Wrasidlo, and D.A. Cheresh. Nanoparticle-mediated drug delivery to tumor vasculature suppresses metastasis. Proc Natl Acad Sci USA 105: 9343–8, 2008.PubMedCrossRefGoogle Scholar
  12. 12.
    Kosteva, J. and C. Langer. The changing landscape of the medical management of skeletal metastases in nonsmall cell lung cancer. Curr Opin Oncol 20: 155–61, 2008.PubMedCrossRefGoogle Scholar
  13. 13.
    Klein, C.A., T.J. Blankenstein, O. Schmidt-Kittler, M. Petronio, B. Polzer, N.H. Stoecklein, and G. Riethmuller. Genetic heterogeneity of single disseminated tumour cells in minimal residual cancer. Lancet 360: 683–9, 2002.PubMedCrossRefGoogle Scholar
  14. 14.
    Wu, J.M., M.J. Fackler, M.K. Halushka, D.W. Molavi, M.E. Taylor, W.W. Teo, C. Griffin, J. Fetting, N.E. Davidson, A.M. De Marzo, J.L. Hicks, D. Chitale, M. Ladanyi, S. Sukumar, and P. Argani. Heterogeneity of breast cancer metastases: comparison of therapeutic target expression and promoter methylation between primary tumors and their multifocal metastases. Clin Cancer Res 14: 1938–46, 2008.PubMedCrossRefGoogle Scholar
  15. 15.
    Mehrotra, J., M. Vali, M. McVeigh, S.L. Kominsky, M.J. Fackler, J. Lahti-Domenici, K. Polyak, N. Sacchi, E. Garrett-Mayer, P. Argani, and S. Sukumar. Very high frequency of hypermethylated genes in breast cancer metastasis to the bone, brain, and lung. Clin Cancer Res 10: 3104–9, 2004.PubMedCrossRefGoogle Scholar
  16. 16.
    Barrett, T., T.O. Suzek, D.B. Troup, S.E. Wilhite, W.C. Ngau, P. Ledoux, D. Rudnev, A.E. Lash, W. Fujibuchi, and R. Edgar. NCBI GEO: mining millions of expression profiles – database and tools. Nucleic Acids Res 33: D562–6, 2005.PubMedCrossRefGoogle Scholar
  17. 17.
    Parkinson, H., U. Sarkans, M. Shojatalab, N. Abeygunawardena, S. Contrino, R. Coulson, A. Farne, G.G. Lara, E. Holloway, M. Kapushesky, P. Lilja, G. Mukherjee, A. Oezcimen, T. Rayner, P. Rocca-Serra, A. Sharma, S. Sansone, and A. Brazma. ArrayExpress – a public repository for microarray gene expression data at the EBI. Nucleic Acids Res 33: D553–5, 2005.PubMedCrossRefGoogle Scholar
  18. 18.
    van 't Veer, L.J., H. Dai, M.J. van de Vijver, Y.D. He, A.A. Hart, M. Mao, H.L. Peterse, K. van der Kooy, M.J. Marton, A.T. Witteveen, G.J. Schreiber, R.M. Kerkhoven, C. Roberts, P.S. Linsley, R. Bernards, and S.H. Friend. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415: 530–6, 2002.PubMedCrossRefGoogle Scholar
  19. 19.
    Rhodes, D.R., S. Kalyana-Sundaram, V. Mahavisno, R. Varambally, J. Yu, B.B. Briggs, T.R. Barrette, M.J. Anstet, C. Kincead-Beal, P. Kulkarni, S. Varambally, D. Ghosh, and A.M. Chinnaiyan. Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia 9: 166–80, 2007.PubMedCrossRefGoogle Scholar
  20. 20.
    Rhodes, D.R. and A.M. Chinnaiyan. Integrative analysis of the cancer transcriptome. Nat Genet 37 Suppl: S31–7, 2005.PubMedCrossRefGoogle Scholar
  21. 21.
    Tomlins, S.A., D.R. Rhodes, S. Perner, S.M. Dhanasekaran, R. Mehra, X.W. Sun, S. Varambally, X. Cao, J. Tchinda, R. Kuefer, C. Lee, J.E. Montie, R.B. Shah, K.J. Pienta, M.A. Rubin, and A.M. Chinnaiyan. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 310: 644–8, 2005.PubMedCrossRefGoogle Scholar
  22. 22.
    Rhodes, D.R., J. Yu, K. Shanker, N. Deshpande, R. Varambally, D. Ghosh, T. Barrette, A. Pandey, and A.M. Chinnaiyan. Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. Proc Natl Acad Sci USA 101: 9309–14, 2004.PubMedCrossRefGoogle Scholar
  23. 23.
    Varambally, S., S.M. Dhanasekaran, M. Zhou, T.R. Barrette, C. Kumar-Sinha, M.G. Sanda, D. Ghosh, K.J. Pienta, R.G. Sewalt, A.P. Otte, M.A. Rubin, and A.M. Chinnaiyan. The polycomb group protein EZH2 is involved in progression of prostate cancer. Nature 419: 624–9, 2002.PubMedCrossRefGoogle Scholar
  24. 24.
    Kirmizis, A., S.M. Bartley, A. Kuzmichev, R. Margueron, D. Reinberg, R. Green, and P.J. Farnham. Silencing of human polycomb target genes is associated with methylation of histone H3 Lys 27. Genes Dev 18: 1592–605, 2004.PubMedCrossRefGoogle Scholar
  25. 25.
    Yu, J., D.R. Rhodes, S.A. Tomlins, X. Cao, G. Chen, R. Mehra, X. Wang, D. Ghosh, R.B. Shah, S. Varambally, K.J. Pienta, and A.M. Chinnaiyan. A polycomb repression signature in metastatic prostate cancer predicts cancer outcome. Cancer Res 67: 10657–63, 2007.PubMedCrossRefGoogle Scholar
  26. 26.
    Garber, M.E., O.G. Troyanskaya, K. Schluens, S. Petersen, Z. Thaesler, M. Pacyna-Gengelbach, M. van de Rijn, G.D. Rosen, C.M. Perou, R.I. Whyte, R.B. Altman, P.O. Brown, D. Botstein, and I. Petersen. Diversity of gene expression in adenocarcinoma of the lung. Proc Natl Acad Sci USA 98: 13784–9, 2001.PubMedCrossRefGoogle Scholar
  27. 27.
    Tomlins, S.A., R. Mehra, D.R. Rhodes, X. Cao, L. Wang, S.M. Dhanasekaran, S. Kalyana-Sundaram, J.T. Wei, M.A. Rubin, K.J. Pienta, R.B. Shah, and A.M. Chinnaiyan. Integrative molecular concept modeling of prostate cancer progression. Nat Genet 39: 41–51, 2007.PubMedCrossRefGoogle Scholar
  28. 28.
    Beer, D.G., S.L. Kardia, C.C. Huang, T.J. Giordano, A.M. Levin, D.E. Misek, L. Lin, G. Chen, T.G. Gharib, D.G. Thomas, M.L. Lizyness, R. Kuick, S. Hayasaka, J.M. Taylor, M.D. Iannettoni, M.B. Orringer, and S. Hanash. Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat Med 8: 816–24, 2002.PubMedGoogle Scholar
  29. 29.
    Bhattacharjee, A., W.G. Richards, J. Staunton, C. Li, S. Monti, P. Vasa, C. Ladd, J. Beheshti, R. Bueno, M. Gillette, M. Loda, G. Weber, E.J. Mark, E.S. Lander, W. Wong, B.E. Johnson, T.R. Golub, D.J. Sugarbaker, and M. Meyerson. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl Acad Sci USA 98: 13790–5, 2001.PubMedCrossRefGoogle Scholar
  30. 30.
    Jayapandian, M., A. Chapman, V.G. Tarcea, C. Yu, A. Elkiss, A. Ianni, B. Liu, A. Nandi, C. Santos, P. Andrews, B. Athey, D. States, and H.V. Jagadish. Michigan Molecular Interactions (MiMI): putting the jigsaw puzzle together. Nucleic Acids Res 35: D566–71, 2007.PubMedCrossRefGoogle Scholar
  31. 31.
    Bader, G.D. and C.W. Hogue. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4: 2, 2003.PubMedCrossRefGoogle Scholar
  32. 32.
    Talbot, S.G., C. Estilo, E. Maghami, I.S. Sarkaria, D.K. Pham, P. Oc, N.D. Socci, I. Ngai, D. Carlson, R. Ghossein, A. Viale, B.J. Park, V.W. Rusch, and B. Singh. Gene expression profiling allows distinction between primary and metastatic squamous cell carcinomas in the lung. Cancer Res 65: 3063–71, 2005.PubMedGoogle Scholar
  33. 33.
    Bild, A.H., G. Yao, J.T. Chang, Q. Wang, A. Potti, D. Chasse, M.B. Joshi, D. Harpole, J.M. Lancaster, A. Berchuck, J.A. Olson, Jr., J.R. Marks, H.K. Dressman, M. West, and J.R. Nevins. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 439: 353–7, 2006.PubMedCrossRefGoogle Scholar
  34. 34.
    Bittner, M. A window on the dynamics of biological switches. Nat Biotechnol 23: 183–4, 2005.PubMedCrossRefGoogle Scholar
  35. 35.
    Chen, H.Y., S.L. Yu, C.H. Chen, G.C. Chang, C.Y. Chen, A. Yuan, C.L. Cheng, C.H. Wang, H.J. Terng, S.F. Kao, W.K. Chan, H.N. Li, C.C. Liu, S. Singh, W.J. Chen, J.J. Chen, and P.C. Yang. A five-gene signature and clinical outcome in non-small-cell lung cancer. N Engl J Med 356: 11–20, 2007.PubMedCrossRefGoogle Scholar
  36. 36.
    Gordon, G.J., R.V. Jensen, L.L. Hsiao, S.R. Gullans, J.E. Blumenstock, S. Ramaswamy, W.G. Richards, D.J. Sugarbaker, and R. Bueno. Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma. Cancer Res 62: 4963–7, 2002.PubMedGoogle Scholar
  37. 37.
    Larsen, J.E., S.J. Pavey, L.H. Passmore, R. Bowman, B.E. Clarke, N.K. Hayward, and K.M. Fong. Expression profiling defines a recurrence signature in lung squamous cell carcinoma. Carcinogenesis 28: 760–6, 2007.PubMedCrossRefGoogle Scholar
  38. 38.
    Minn, A.J., G.P. Gupta, P.M. Siegel, P.D. Bos, W. Shu, D.D. Giri, A. Viale, A.B. Olshen, W.L. Gerald, and J. Massague. Genes that mediate breast cancer metastasis to lung. Nature 436: 518–24, 2005.PubMedCrossRefGoogle Scholar
  39. 39.
    Nielsen, T.O., R.B. West, S.C. Linn, O. Alter, M.A. Knowling, J.X. O'Connell, S. Zhu, M. Fero, G. Sherlock, J.R. Pollack, P.O. Brown, D. Botstein, and M. van de Rijn. Molecular characterisation of soft tissue tumours: a gene expression study. Lancet 359: 1301–7, 2002.PubMedCrossRefGoogle Scholar
  40. 40.
    Powell, C.A., A. Spira, A. Derti, C. DeLisi, G. Liu, A. Borczuk, S. Busch, S. Sahasrabudhe, Y. Chen, D. Sugarbaker, R. Bueno, W.G. Richards, and J.S. Brody. Gene expression in lung adenocarcinomas of smokers and nonsmokers. Am J Respir Cell Mol Biol 29: 157–62, 2003.PubMedCrossRefGoogle Scholar
  41. 41.
    Ramaswamy, S., P. Tamayo, R. Rifkin, S. Mukherjee, C.H. Yeang, M. Angelo, C. Ladd, M. Reich, E. Latulippe, J.P. Mesirov, T. Poggio, W. Gerald, M. Loda, E.S. Lander, and T.R. Golub. Multiclass cancer diagnosis using tumor gene expression signatures. Proc Natl Acad Sci USA 98: 15149–54, 2001.PubMedCrossRefGoogle Scholar
  42. 42.
    Raponi, M., Y. Zhang, J. Yu, G. Chen, G. Lee, J.M. Taylor, J. Macdonald, D. Thomas, C. Moskaluk, Y. Wang, and D.G. Beer. Gene expression signatures for predicting prognosis of squamous cell and adenocarcinomas of the lung. Cancer Res 66: 7466–72, 2006.PubMedCrossRefGoogle Scholar
  43. 43.
    Su, A.I., J.B. Welsh, L.M. Sapinoso, S.G. Kern, P. Dimitrov, H. Lapp, P.G. Schultz, S.M. Powell, C.A. Moskaluk, H.F. Frierson, Jr., and G.M. Hampton. Molecular classification of human carcinomas by use of gene expression signatures. Cancer Res 61: 7388–93, 2001.PubMedGoogle Scholar
  44. 44.
    Stearman, R.S., L. Dwyer-Nield, L. Zerbe, S.A. Blaine, Z. Chan, P.A. Bunn, Jr., G.L. Johnson, F.R. Hirsch, D.T. Merrick, W.A. Franklin, A.E. Baron, R.L. Keith, R.A. Nemenoff, A.M. Malkinson, and M.W. Geraci. Analysis of orthologous gene expression between human pulmonary adenocarcinoma and a carcinogen-induced murine model. Am J Pathol 167: 1763–75, 2005.PubMedCrossRefGoogle Scholar
  45. 45.
    Tomida, S., K. Koshikawa, Y. Yatabe, T. Harano, N. Ogura, T. Mitsudomi, M. Some, K. Yanagisawa, T. Takahashi, and H. Osada. Gene expression-based, individualized outcome prediction for surgically treated lung cancer patients. Oncogene 23: 5360–70, 2004.PubMedCrossRefGoogle Scholar
  46. 46.
    Wachi, S., K. Yoneda, and R. Wu. Interactome-transcriptome analysis reveals the high centrality of genes differentially expressed in lung cancer tissues. Bioinformatics 21: 4205–8, 2005.PubMedCrossRefGoogle Scholar
  47. 47.
    Wigle, D.A., I. Jurisica, N. Radulovich, M. Pintilie, J. Rossant, N. Liu, C. Lu, J. Woodgett, I. Seiden, M. Johnston, S. Keshavjee, G. Darling, T. Winton, B.J. Breitkreutz, P. Jorgenson, M. Tyers, F.A. Shepherd, and M.S. Tsao. Molecular profiling of non-small cell lung cancer and correlation with disease-free survival. Cancer Res 62: 3005–8, 2002.PubMedGoogle Scholar
  48. 48.
    Yamagata, N., Y. Shyr, K. Yanagisawa, M. Edgerton, T.P. Dang, A. Gonzalez, S. Nadaf, P. Larsen, J.R. Roberts, J.C. Nesbitt, R. Jensen, S. Levy, J.H. Moore, J.D. Minna, and D.P. Carbone. A training-testing approach to the molecular classification of resected non-small cell lung cancer. Clin Cancer Res 9: 4695–704, 2003.PubMedGoogle Scholar
  49. 49.
    Weiss, G.J., L.T. Bemis, E. Nakajima, M. Sugita, D.K. Birks, W.A. Robinson, M. Varella-Garcia, P.A. Bunn, Jr., J. Haney, B.A. Helfrich, H. Kato, F.R. Hirsch, and W.A. Franklin. EGFR regulation by microRNA in lung cancer: correlation with clinical response and survival to gefitinib and EGFR expression in cell lines. Ann Oncol 19: 1053–9, 2008.PubMedCrossRefGoogle Scholar
  50. 50.
    Boyerinas, B., S.M. Park, N. Shomron, M.M. Hedegaard, J. Vinther, J.S. Andersen, C. Feig, J. Xu, C.B. Burge, and M.E. Peter. Identification of let-7-regulated oncofetal genes. Cancer Res 68: 2587–91, 2008.PubMedCrossRefGoogle Scholar
  51. 51.
    Omenn, G.S., D.J. States, M. Adamski, T.W. Blackwell, R. Menon, H. Hermjakob, R. Apweiler, B.B. Haab, R.J. Simpson, J.S. Eddes, E.A. Kapp, R.L. Moritz, D.W. Chan, A.J. Rai, A. Admon, R. Aebersold, J. Eng, W.S. Hancock, S.A. Hefta, H. Meyer, Y.K. Paik, J.S. Yoo, P. Ping, J. Pounds, J. Adkins, X. Qian, R. Wang, V. Wasinger, C.Y. Wu, X. Zhao, R. Zeng, A. Archakov, A. Tsugita, I. Beer, A. Pandey, M. Pisano, P. Andrews, H. Tammen, D.W. Speicher, and S.M. Hanash. 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: 3226–45, 2005.PubMedCrossRefGoogle Scholar
  52. 52.
    Chen, G., T.G. Gharib, H. Wang, C.C. Huang, R. Kuick, D.G. Thomas, K.A. Shedden, D.E. Misek, J.M. Taylor, T.J. Giordano, S.L. Kardia, M.D. Iannettoni, J. Yee, P.J. Hogg, M.B. Orringer, S.M. Hanash, and D.G. Beer. Protein profiles associated with survival in lung adenocarcinoma. Proc Natl Acad Sci USA 100: 13537–42, 2003.PubMedCrossRefGoogle Scholar
  53. 53.
    Warburg, O. The Chemical Constitution of Respiration Ferment. Science 68: 437–43, 1928.PubMedCrossRefGoogle Scholar
  54. 54.
    Yanagisawa, K., S. Tomida, Y. Shimada, Y. Yatabe, T. Mitsudomi, and T. Takahashi. A 25-signal proteomic signature and outcome for patients with resected non-small-cell lung cancer. J Natl Cancer Inst 99: 858–67, 2007.PubMedCrossRefGoogle Scholar
  55. 55.
    Soltermann, A., R. Ossola, S. Kilgus-Hawelski, A. von Eckardstein, T. Suter, R. Aebersold, and H. Moch. N-glycoprotein profiling of lung adenocarcinoma pleural effusions by shotgun proteomics. Cancer 114: 124–33, 2008.PubMedCrossRefGoogle Scholar
  56. 56.
    Tyan, Y.C., H.Y. Wu, W.C. Su, P.W. Chen, and P.C. Liao. Proteomic analysis of human pleural effusion. Proteomics 5: 1062–74, 2005.PubMedCrossRefGoogle Scholar
  57. 57.
    Jagirdar, J. Application of immunohistochemistry to the diagnosis of primary and metastatic carcinoma to the lung. Arch Pathol Lab Med 132: 384–96, 2008.PubMedGoogle Scholar
  58. 58.
    Opitz, I., A. Soltermann, M. Abaecherli, M. Hinterberger, N. Probst-Hensch, R. Stahel, H. Moch, and W. Weder. PTEN expression is a strong predictor of survival in mesothelioma patients. Eur J Cardiothorac Surg 33: 502–6, 2008.PubMedCrossRefGoogle Scholar
  59. 59.
    Rahman, S.M., Y. Shyr, P.B. Yildiz, A.L. Gonzalez, H. Li, X. Zhang, P. Chaurand, K. Yanagisawa, B.S. Slovis, R.F. Miller, M. Ninan, Y.E. Miller, W.A. Franklin, R.M. Caprioli, D.P. Carbone, and P.P. Massion. Proteomic patterns of preinvasive bronchial lesions. Am J Respir Crit Care Med 172: 1556–62, 2005.PubMedCrossRefGoogle Scholar
  60. 60.
    Amann, J.M., P. Chaurand, A. Gonzalez, J.A. Mobley, P.P. Massion, D.P. Carbone, and R.M. Caprioli. Selective profiling of proteins in lung cancer cells from fine-needle aspirates by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin Cancer Res 12: 5142–50, 2006.PubMedCrossRefGoogle Scholar
  61. 61.
    Taguchi, F., B. Solomon, V. Gregorc, H. Roder, R. Gray, K. Kasahara, M. Nishio, J. Brahmer, A. Spreafico, V. Ludovini, P.P. Massion, R. Dziadziuszko, J. Schiller, J. Grigorieva, M. Tsypin, S.W. Hunsucker, R. Caprioli, M.W. Duncan, F.R. Hirsch, P.A. Bunn, Jr., and D.P. Carbone. Mass spectrometry to classify non-small-cell lung cancer patients for clinical outcome after treatment with epidermal growth factor receptor tyrosine kinase inhibitors: a multicohort cross-institutional study. J Natl Cancer Inst 99: 838–46, 2007.PubMedCrossRefGoogle Scholar
  62. 62.
    Yildiz, P.B., Y. Shyr, J.S. Rahman, N.R. Wardwell, L.J. Zimmerman, B. Shakhtour, W.H. Gray, S. Chen, M. Li, H. Roder, D.C. Liebler, W.L. Bigbee, J.M. Siegfried, J.L. Weissfeld, A.L. Gonzalez, M. Ninan, D.H. Johnson, D.P. Carbone, R.M. Caprioli, and P.P. Massion. Diagnostic accuracy of MALDI mass spectrometric analysis of unfractionated serum in lung cancer. J Thorac Oncol 2: 893–901, 2007.PubMedCrossRefGoogle Scholar
  63. 63.
    Gao, W.M., R. Kuick, R.P. Orchekowski, D.E. Misek, J. Qiu, A.K. Greenberg, W.N. Rom, D.E. Brenner, G.S. Omenn, B.B. Haab, and S.M. Hanash. Distinctive serum protein profiles involving abundant proteins in lung cancer patients based upon antibody microarray analysis. BMC Cancer 5: 110, 2005.PubMedCrossRefGoogle Scholar
  64. 64.
    Han, K.Q., G. Huang, C.F. Gao, X.L. Wang, B. Ma, L.Q. Sun, and Z.J. Wei. Identification of lung cancer patients by serum protein profiling using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Am J Clin Oncol 31: 133–9, 2008.PubMedCrossRefGoogle Scholar
  65. 65.
    Heo, S.H., S.J. Lee, H.M. Ryoo, J.Y. Park, and J.Y. Cho. Identification of putative serum glycoprotein biomarkers for human lung adenocarcinoma by multilectin affinity chromatography and LC-MS/MS. Proteomics 7: 4292–302, 2007.PubMedCrossRefGoogle Scholar
  66. 66.
    Maciel, C.M., M. Junqueira, M.E. Paschoal, M.T. Kawamura, R.L. Duarte, G. Carvalho Mda, and G.B. Domont. Differential proteomic serum pattern of low molecular weight proteins expressed by adenocarcinoma lung cancer patients. J Exp Ther Oncol 5: 31–8, 2005.PubMedGoogle Scholar
  67. 67.
    Okano, T., T. Kondo, T. Kakisaka, K. Fujii, M. Yamada, H. Kato, T. Nishimura, A. Gemma, S. Kudoh, and S. Hirohashi. Plasma proteomics of lung cancer by a linkage of multi-dimensional liquid chromatography and two-dimensional difference gel electrophoresis. Proteomics 6: 3938–48, 2006.PubMedCrossRefGoogle Scholar
  68. 68.
    Mahanta, S., S.P. Fessler, J. Park, and C. Bamdad. A minimal fragment of MUC1 mediates growth of cancer cells. PLoS ONE 3: e2054, 2008.PubMedCrossRefGoogle Scholar
  69. 69.
    Stockert, E., E. Jager, Y.T. Chen, M.J. Scanlan, I. Gout, J. Karbach, M. Arand, A. Knuth, and L.J. Old. A survey of the humoral immune response of cancer patients to a panel of human tumor antigens. J Exp Med 187: 1349–54, 1998.PubMedCrossRefGoogle Scholar
  70. 70.
    Hanash, S. Harnessing immunity for cancer marker discovery. Nat Biotechnol 21: 37–8, 2003.PubMedCrossRefGoogle Scholar
  71. 71.
    Brichory, F., D. Beer, F. Le Naour, T. Giordano, and S. Hanash. Proteomics-based identification of protein gene product 9.5 as a tumor antigen that induces a humoral immune response in lung cancer. Cancer Res 61: 7908–12, 2001.PubMedGoogle Scholar
  72. 72.
    Brichory, F.M., D.E. Misek, A.M. Yim, M.C. Krause, T.J. Giordano, D.G. Beer, and S.M. Hanash. An immune response manifested by the common occurrence of annexins I and II autoantibodies and high circulating levels of IL-6 in lung cancer. Proc Natl Acad Sci USA 98: 9824–9, 2001.PubMedCrossRefGoogle Scholar
  73. 73.
    Pereira-Faca, S.R., R. Kuick, E. Puravs, Q. Zhang, A.L. Krasnoselsky, D. Phanstiel, J. Qiu, D.E. Misek, R. Hinderer, M. Tammemagi, M.T. Landi, N. Caporaso, R. Pfeiffer, C. Edelstein, G. Goodman, M. Barnett, M. Thornquist, D. Brenner, and S.M. Hanash. Identification of 14-3-3 theta as an antigen that induces a humoral response in lung cancer. Cancer Res 67: 12000–6, 2007.PubMedCrossRefGoogle Scholar
  74. 74.
    Qiu, J., G. Choi, L. Lin, H. Wang, S.J. Pitteri, S.R. Pereira-Faca, A.L. Krasnoselsky, T.W. Randolph, C. Edelstein, M. Barnett, M. Thornquist, G. Goodman, G.S. Omenn, D. Brenner, Z. Feng, and S.M. Hanash. Occurrence of autoantibodies to annexin 1, 14-3-3 theta and LAMR1 in pre diagnostic lung cancer sera. J Clin Oncol 26: 5060–6, 2008.PubMedCrossRefGoogle Scholar
  75. 75.
    Omenn, G.S., G.E. Goodman, M.D. Thornquist, J. Balmes, M.R. Cullen, A. Glass, J.P. Keogh, F.L. Meyskens, B. Valanis, J.H. Williams, S. Barnhart, and S. Hammar. Effects of a combination of beta carotene and vitamin A on lung cancer and cardiovascular disease. N Engl J Med 334: 1150–5, 1996.PubMedCrossRefGoogle Scholar
  76. 76.
    Chen, G., X. Wang, J. Yu, S. Varambally, D.G. Thomas, M.Y. Lin, P. Vishnu, Z. Wang, R. Wang, J. Fielhauer, D. Ghosh, T.J. Giordano, D. Giacherio, A.C. Chang, M.B. Orringer, T. El-Hefnawy, W.L. Bigbee, D.G. Beer, and A.M. Chinnaiyan. Autoantibody profiles reveal ubiquilin 1 as a humoral immune response target in lung adenocarcinoma. Cancer Res 67: 3461–7, 2007.PubMedCrossRefGoogle Scholar
  77. 77.
    Keshamouni, V.G., G. Michailidis, C.S. Grasso, S. Anthwal, J.R. Strahler, A. Walker, D.A. Arenberg, R.C. Reddy, S. Akulapalli, V.J. Thannickal, T.J. Standiford, P.C. Andrews, and G.S. Omenn. Differential protein expression profiling by iTRAQ-2DLC-MS/MS of lung cancer cells undergoing epithelial-mesenchymal transition reveals a migratory/invasive phenotype. J Proteome Res 5: 1143–54, 2006.PubMedCrossRefGoogle Scholar
  78. 78.
    Keshamouni, V.G., Jagtap, P., Michailidi, G., Strahler, J.R., Kuick, R., Reka, A.K., Papoulias, P., Krishnapuram, R., Srirangam, A., Standiford, T.J., Andrews, P.C., Omenn, G.S. Temporal quantitative proteomics by iTRAQ 2D-LC-MS/MS and corresponding mRNA expression analysis identify post-transcriptional modulation of action-cytoskeleton regulators during TGF-beta-induced epithelial-mesenchymal transition. J Proteome Res 8: 35–47, 2009. PMID: 19118450.Google Scholar
  79. 79.
    Whiteaker, J.R., H. Zhang, L. Zhao, P. Wang, K.S. Kelly-Spratt, R.G. Ivey, B.D. Piening, L.C. Feng, E. Kasarda, K.E. Gurley, J.K. Eng, L.A. Chodosh, C.J. Kemp, M.W. McIntosh, and A.G. Paulovich. Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer. J Proteome Res 6: 3962–75, 2007.PubMedCrossRefGoogle Scholar
  80. 80.
    Faca, V.M., K.S. Song, H. Wang, Q. Zhang, A.L. Krasnoselsky, L.F. Newcomb, R.R. Plentz, S. Gurumurthy, M.S. Redston, S.J. Pitteri, S.R. Pereira-Faca, R.C. Ireton, H. Katayama, V. Glukhova, D. Phanstiel, D.E. Brenner, M.A. Anderson, D. Misek, N. Scholler, N.D. Urban, M.J. Barnett, C. Edelstein, G.E. Goodman, M.D. Thornquist, M.W. McIntosh, R.A. DePinho, N. Bardeesy, and S.M. Hanash. A mouse to human search for plasma proteome changes associated with pancreatic tumor development. PLoS Med 5: e123, 2008.PubMedCrossRefGoogle Scholar
  81. 81.
    Fermin, D., B.B. Allen, T.W. Blackwell, R. Menon, M. Adamski, Y. Xu, P. Ulintz, G.S. Omenn, and D.J. States. Novel gene and gene model detection using a whole genome open reading frame analysis in proteomics. Genome Biol 7: R35, 2006.PubMedCrossRefGoogle Scholar
  82. 82.
    Menon, R., Zhang, Q., Zhang, Y., Fermin, D., Bardeesy, N., DePinho, R.A., Lu, C., Hanash, S.M., Omenn, G.S., States, D.J. Identification of novel alternative splice isoforms of circulating proteins iin a mouse model of human pancreatic cancer. Cancer Res 69: 300–9, 2009. PMID: 19118015.Google Scholar
  83. 83.
    Sreekumar, A., Poisson, L.M., Rajendiran, T.M., Khan, A.P., Cao, Q., Yu, J., Laxman, B., Mehra, R., Loniga, R.J., Li., Y., Nyati, M.K., Ahsan, A., Kalyana-Sundaram, S., Han, B., Cao, X., Byun, J., Omenn, G.S., Ghosh, D., Pennathur, S., Alexander, D.C., Berger, A., Shuster, J.R., Wei, J.T., Varambally, S., Beecher, C., Chinnaiyan, A.M. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature, 457: 910–4, 2009. PMID: 19212411.Google Scholar
  84. 84.
    Anderson, L. and C.L. Hunter. Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins. Mol Cell Proteomics 5: 573–88, 2006.PubMedGoogle Scholar
  85. 85.
    Barker, P.E., P.D. Wagner, S.E. Stein, D.M. Bunk, S. Srivastava, and G.S. Omenn. Standards for plasma and serum proteomics in early cancer detection: a needs assessment report from the national institute of standards and technology – National Cancer Institute Standards, Methods, Assays, Reagents and Technologies Workshop, August 18–19, 2005. Clin Chem 52: 1669–74, 2006.PubMedCrossRefGoogle Scholar
  86. 86.
    Liu, J., J. Stevens, C.A. Rote, H.J. Yost, Y. Hu, K.L. Neufeld, R.L. White, and N. Matsunami. Siah-1 mediates a novel beta-catenin degradation pathway linking p53 to the adenomatous polyposis coli protein. Mol Cell 7: 927–36, 2001.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Internal Medicine, Human Genetics, Public Health, and Center for Computational Medicine and BioinformaticsUniversity of MichiganAnn ArborUSA

Personalised recommendations