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Proteomic and genomic technologies for biomarker discovery


  1. 1

    Etzioni, R., Urban, N., Ramsey, S., et al. (2003) The case for early detection. Nat. Rev. Cancer 3, 243–252.

  2. 2

    Bast, R. C., Jr., Klug, T. L., St. John, E., et al. (1983) A radioimmunoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer. N. Engl. J. Med. 309, 883–887.

  3. 3

    Celis, A., Rasmussen, H. H., Celis, P., et al. (1999) Short-term culturing of low-grade superficial bladder transitional cell carcinomas leads to changes in the expression levels of several proteins involved in key cellular activities. Electrophoresis 20, 355–361.

  4. 4

    Kageyama, S., Isono, T., Iwaki, H., et al. (2004) Identification by proteomic analysis of calreticulin as a marker for bladder cancer and evaluation of the diagnostic accuracy of its detection in urine. Clin. Chem. 50, 857–866.

  5. 5

    Wang, X., Yu, J., Sreekumar, A., et al. (2005) Autoantibody signatures in prostate cancer. N. Engl. J. Med. 353, 1224–1235.

  6. 6

    Petricoin, E. F., Ardekani, A. M., Hitt, B. A., et al. (2002) Use of proteomic patterns in serum to identify ovarian cancer. Lancet 359, 572–577.

  7. 7

    Caprioli, R. M. (2005) Deciphering protein molecular signatures in cancer tissues to aid in diagnosis, prognosis, and therapy. Cancer Res. 65, 10,642–10,645.

  8. 8

    Yanagisawa, K., Shyr, Y., Xu, B. J., et al. (2003) Proteomic patterns of tumor subsets in non-small-cell lung cancer. Lancet 362, 433–439.

  9. 9

    Martin, D. B., Gifford, D. R., Wright, M. E., et al. (2004) Quantitative proteomic analysis of proteins released by neoplastic prostate epithelium. Cancer Res. 64, 347–355.

  10. 10

    Perou, C. M., Sorlie, T., Eisen, M. B., et al. (2000) Molecular portraits of human breast tumors. Nature 406, 747–752.

  11. 11

    Alizadeh, A. A., Ross, D. T., Perous, C. M., and van de Rijn, M. (2001) Towards a novel classification of human malignancies based on gene expression patterns. J. Pathol. 195, 41–52.

  12. 12

    Weigelt, B., Hu, Z., He, X., et al. (2005) Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. Cancer Res. 65, 9144–9158.

  13. 13

    Alizadeh, A. A., Eisen, M. B., Davis, R. E., et al. (2000) Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503–511.

  14. 14

    Rosenwald, A., Wright, G., Chan, W. C., et al. (2002) Lymphoma/leukemia molecular profiling project: The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N. Engl. J. Med. 346, 1937–1947.

  15. 15

    Bhattacharjee, A., Richards, W. G., Staunton, J., et al. (2001) Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Natl. Acad. Sci. USA 98, 13,790–13,795.

  16. 16

    Ramaswamy, S., Ross, K. N., Lander, E. S., and Golub, T. R. (2003) A molecular signature of metastasis in primary solid tumors. Nat. Genet. 33, 49–54.

  17. 17

    Pemeroy, S. L., Tamayo, P., Gaasenbeek, M., et al. (2002) Prediction of central nervous system embryonal tumor outcome based on gene expression. Nature 415, 436–442.

  18. 18

    Iizuka, N., Hammoto, Y., and Oka, M. (2004) Predicting individual outcomes in hepatocellular carcinoma. Lancet 364, 1837–1839.

  19. 19

    van de Vijver, M. J., He, Y. D., van't Veer, I. J., et al. (2002) A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009.

  20. 20

    van't Veer, I. J. and Weigelt, B. (2003) Road map to metastasis. Nat. Med. 9, 999–1000.

  21. 21

    Lossos, I. S., Czerwinski, D. K., Alizadeh, A. A., et al. (2004) Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes. N. Engl. J. Med. 350, 1828–1837.

  22. 22

    Cronin, M., Pho, M., Dutta, D., et al. (2004) Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. Am. J. Pathol. 164, 35–42.

  23. 23

    Bast, R. C., Jr., Ravdin, P., Hayes, D. F., et al. (2000) Update of recommendations for the use of tumor markers in breast and colorectal cancer: clinical practice guidelines of the American Society of Clinical Oncology. J. Clin. Oncol. 19, 1865–1878.

  24. 24

    Finne, P., Finne, R., Auvinen, A., et al. (2000) Predicting the outcome of prostate biopsy in screen-positive men by a multilayer perceptron network. Urology 56, 418–422.

  25. 25

    Stephan, C., Cammann, H., Semjonow, A., et al. (2002) Multicenter evaluation of an artificial neural network to increase the prostate cancer detection rate and reduce unnecessary biopsies. Clin. Chem. 48, 1279–1287.

  26. 26

    Diamandis, E. P. (2003) Point: proteomic patterns in biological fluids: do they represent the future of cancer diagnostics? Clin. Chem. 49, 1272–1275.

  27. 27

    Diamandis, E. P. (2003) Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems. J. Natl. Cancer Inst. 96, 353–356.

  28. 28

    Karsan, A., Eigl, B. J., Fibotte, S., et al. (2005) Analytical and preanalytical biases in serum proteomic pattern analysis for breast cancer diagnosis. Clin. Chem. 51, 1525–1528.

  29. 29

    Banks, R. E., Stanley, A. J., Cairns, D. A., et al. (2005) Influences of blood sample processing on low-molecular-weight-proteome identified by surface-enhanced laser desorption/ionization mass spectrometry. Clin. Chem. 51, 1637–1649.

  30. 30

    Baggerly, K. A., Morris, J. S., Edmonson, S. R., and Coombes, K. R. (2005) Signal in noise: evaluating reported reproducibility of serum proteomic tests for ovarian cancer. J. Natl. Cancer Inst. 97, 307–309.

  31. 31

    Ransohoff, D. F. (2005) Lessons from controversy: ovarian cancer screening and serum proteomics. J. Natl. Cancer Inst. 97, 315–319.

  32. 32

    Elias, J. E., Haas, W., Faherty, B. K., and Gygi, S. P. (2005) Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations. Nat. Methods 2, 667–675.

  33. 33

    Michiels, S., Koscielny, S., and Hill, C. (2005) Prediction of cancer outcome with microarrays: a multiple random validation strategy. Lancet 365, 488–492.

  34. 34

    Ioannidis, J. P. (2005) Microarrays and molecular research: noise discovery? Lancet 365, 454–455.

  35. 35

    Branca, M. A. (2005) Omic diagnostics trip up on way to clinic. Nat Biotechnol. 23, 769.

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Correspondence to Eleftherios P. Diamandis.

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