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The US Food and Drug Administration perspective on cancer biomarker development

Nature Reviews Cancer volume 6, pages 565–571 (2006)Cite this article

Abstract

Despite the intense interest in biomarker development for cancer management, few biomarker assays for diagnostic uses have been submitted to the US Food and Drug Administration (FDA). What challenges must researchers overcome to bring cancer-detection technologies to the market and, therefore, into clinical use?

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References

  1. Guttmacher, A. E. & Collins, F. S. Realizing the promise of genomics in biomedical research. JAMA 291, 1399–1402 (2005).

    Article  Google Scholar 

  2. Shak, S. et al. A multigene assay to predict recurrence of tamoxifen-treated, nod-negative breast cancer. N. Engl. J. Med. 351, 2817–2826 (2004).

    Article  Google Scholar 

  3. van de Vijver, M. J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009 (2002).

    Article  CAS  Google Scholar 

  4. Meyerson, M. & Carbone, D. Genomic and proteomic profiling of lung cancers: lung cancer classification in the age of targeted therapy. J. Clin. Oncol. 10, 3219–3226 (2005).

    Article  Google Scholar 

  5. Baruch, A. C., Shi, J., Feng, Y. & Nelson, M. A. New developments in the staging of melanomas. Cancer Invest. 23, 561–567 (2005).

    Article  Google Scholar 

  6. Zhou, G. et al. Proteomic analysis of global alteration of protein expression in squamous cell carcinoma of the esophagus. Proteomics 5, 2814–3821 (2005).

    Google Scholar 

  7. Chen, R. et al. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape. Gastroenterology 129, 1344–1347 (2005).

    Article  Google Scholar 

  8. US Food and Drugs Administration. Federal Food, Drug, And Cosmetic Act. US Food and Drugs Administration [online], (2004).

  9. Goehring, C., Perrier, A. & Morabia, A. Spectrum bias: a quantitative and graphical analysis of the variability of medical diagnostic test performance. Stat. Med. 15, 125–135 (2004).

    Article  Google Scholar 

  10. Punglia, R. S., Kuntz, K. M., Catalona, W. J. & D'Amico, A. Operating characteristics of prostate-specific antigen and verification bias. JAMA 294, 2698–2699 (2005).

    Article  CAS  Google Scholar 

  11. Zang, D. et al. Reliability of tissue microarrays in detecting protein expression and gene amplification in breast cancer. Mol. Pathol. 16, 79–84 (2004).

    Article  Google Scholar 

  12. US Food and Drugs Administration. 510(k) Premarket notification database. US Food and Drugs Administration [online], (2006).

  13. Pepe, M. S. et al. Phases of biomarker development for early detection of cancer. J. Natl Cancer Inst. 93, 1054–1061 (2001).

    Article  CAS  Google Scholar 

  14. US Food and Drugs Administration. Electronic code of federal regulations. US Food and Drugs Administration [online], (2006).

  15. US Food and Drugs Administration. Guidance on informed consent for in vitro diagnostic device studies using leftover human specimens that are not individually identifiable — guidance for sponsors, institutional review boards, clinical investigators and FDA staff. US Food and Drugs Administration [online], (2006).

  16. Bast, R.C. Jr. et al. Translational crossroads for biomarkers. Clin. Cancer Res. 11, 6103–6108 (2005).

    Article  Google Scholar 

  17. Ludwig, J. A., & Weinstein, J. N. Biomarkers in cancer staging, prognosis, and treatment selection. Nature Rev. Cancer 5, 845–856 (2005).

    Article  CAS  Google Scholar 

  18. US Food and Drugs Administration. Voluntary genomic data submissions: FDA Guidance. US Food and Drugs Administration [online], (2005).

  19. Ramakrishnan, R. et al. An assessment of Motorola CodeLink microarray performance for gene expression profiling applications. Nucleic Acid Res. 30, 1–12 (2002).

    Article  Google Scholar 

  20. Yudong, D. et al. Microarray standard data set and FIGS or merit for comparing data processing methods and experiment designs. Bioinformatics 19, 956–965 (2003).

    Article  Google Scholar 

  21. Pusztai, L. & Hess, K. R. Clinical trial design for microarray predictive marker discovery and assessment. Ann. Oncol. 15, 1731–1737 (2004).

    Article  CAS  Google Scholar 

  22. Gong, P., Harbers, G. M. & Grainger, D. W. Multi-technique comparison of immobilized and hybridized oligonucleotide surface density on commercial amine-reactive microarray slides. Anal. Chem. 78, 2342–2351 (2006).

    Article  CAS  Google Scholar 

  23. Dorris, D. R. et al. A highly reproducible, linear, and automated sample preparation method for DNA microarrays. Genome Res. 12, 976–984 (2006)

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  25. Ransohoff, D. E. Bias as a threat to the validity of cancer molecular-marker research. Nature Rev. Cancer 5, 142–149 (2005).

    Article  CAS  Google Scholar 

  26. Diamandis, E. Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems. J. Natl Cancer Inst. 96, 353–356 (2004).

    Article  Google Scholar 

  27. Saah, A. J. & Hoover, D. R. Sensitivity and specificity reconsidered: the meaning of these terms in analytical and diagnostic settings. Ann. Intern. Med. 1126, 91–84 (1997).

    Article  Google Scholar 

  28. Gutman, S. & Meyer, D. Lexicon for laboratories — scaling the Tower of Babel. Arch. Pathol. Lab. Med. 127, 625–626 (2003).

    PubMed  Google Scholar 

  29. Hagdu, A. The discrepancy in discrepant resolution. Lancet 348, 592–593 (1996).

    Article  Google Scholar 

  30. Bossuyt, P. M. et al. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Standards for Reporting of Diagnostic Accuracy. Clin. Chem. 49, 19–20 (2003).

    Article  Google Scholar 

  31. McShane, L. M., et al. Reporting recommendations for tumour MARKer prognostics studies (REMARK). Br. J. Cancer 93, 387–391 (2005).

    Article  CAS  Google Scholar 

  32. Schatzkin, A., Connor, R. J., Taylor, P. R. & Bunag, B. Comparing new and old screening tests when a reference procedure cannot be performed on all screenees. Example of automated cytometry for early detection of cervical cancer. Am. J. Epidemiol. 125, 672–678 (1987).

    Article  CAS  Google Scholar 

  33. US Food and Drugs Administration. Statistical Guidance on reporting results from studies evaluating diagnostic tests; draft guidance for industry and FDA reviewers. US Food and Drugs Administration [online], (2003).

  34. Clinical Laboratory Standards Institute. Assessment of the clinical accuracy of laboratory tests using receiver operating characteristics (ROC) plots, approved guideline. Clinical Laboratory Standards Institute (1995).

  35. Dobbin, K. & Simon, R. Sample size determination in microarray experiments for class comparison and prognostic classification. Biostatistics 6, 27–38 (2005).

    Article  Google Scholar 

  36. Campbell, G. Some statistical and regulatory issues in the evaluation of genetic and genomic tests. J. Biopharm. Stat. 14, 529–552 (2004).

    Article  Google Scholar 

  37. Paik, S. et al. Real-world performance of HER2 testing — National Surgical Adjuvant Breast and Bowel Project experience. J. Natl Cancer Inst. 94, 852–854 (2002).

    Article  Google Scholar 

  38. Roche, P. C. et al. Concordance between local and central laboratory HER2 testing in the breast intergroup trial N9831. J. Natl Cancer Inst. 94, 855–857 (2002).

    Article  Google Scholar 

  39. US Food and Drugs Administration. Medical devices, part 820: quality system regulation. US Food and Drugs Administration [online], (2005).

  40. US Food and Drugs Administration. Draft guidance for industry and FDA staff — pharmacogenetic tests and genetic tests for heritable markers. US Food and Drugs Administration [online], (2006).

Download references

Acknowledgements

The opinions expressed in this article are those of the authors and are not to be construed as official or as representing the opinion of the US Food and Drug Administration.

Author information

Authors and Affiliations

  1. Steven Gutman and Larry Kessler are at the Office of in vitro Diagnostic Devices and the Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, NFZ-440, 2098 Gaither Road, Rockville, 20857, Maryland, USA

    Steven Gutman & Larry G. Kessler

Authors
  1. Steven Gutman
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  2. Larry G. Kessler
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Corresponding author

Correspondence to Steven Gutman.

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Competing interests

The authors declare no competing financial interests.

Related links

Related links

DATABASES

National Cancer Institute

breast cancer

bladder cancer

cervical cancer

colon cancer

liver cancer

lung cancer

melanoma

oesophageal cancer

ovarian cancer

pancreatic cancer

prostate cancer

testicular cancer

FURTHER INFORMATION

International Organization for Standardization (ISO)

The FDA website

Current information on the FDA's review products for in vitro diagnostic (laboratory tests) biomarkers for clinical use

Interagency Oncology Task Force (IOTF)

Current information on the FDA's review of genomic tests as part of drug discovery and development

Guidance document on voluntary pharmacogenomic data submissions (VGDS) for the use of pharmacogenomic data in new drug development

Information on best practices for the VGDS process

Information on the preliminary thinking of the FDA about the co-development of diagnostics and drugs

Special controls for the first FDA-cleared microarray

Special controls for the first FDA-cleared microarray reader

Draft guidance for industry and FDA staff on pharmacogenetics tests and genetic tests for heritable markers

Regulations citing quality system regulation requirements and explaining corrective and preventive action processes

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Gutman, S., Kessler, L. The US Food and Drug Administration perspective on cancer biomarker development. Nat Rev Cancer 6, 565–571 (2006). https://doi.org/10.1038/nrc1911

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