Introduction to Predictive Biomarkers: Definitions and Characteristics

  • Clive R. Taylor


The concept of “biomarkers” as indicators of health or disease is not new. This introductory chapter is focused on the utilization of “biomarkers” that can be detected directly in tissues from cancer patients. Within this context, biomarkers include proteins and nucleic acids and derivatives and parts thereof. The main methods of biomarker detection in cancer are reviewed, together with definitions and requirements set forth by regulatory organizations. The major challenges that this constellation of new test modalities presents to pathologists and clinicians are discussed, along with critical aspects of test cost and resultant test availability.

“Precision” or “personalized medicine” appears to be an irresistible force, in turn requiring a new level of “precision pathology.” This enhanced level of assay performance may only be achieved by further refinement and development of the methods, following approaches described in this opening chapter. Already these new performance demands have radically changed the practice of pathology, particularly with reference to the diagnosis and management of malignant disease. Today we stand only at the end of the beginning of a new era of pathology practice; the ultimate end none of us as yet can foresee.


Companion diagnostic Precision medicine Biomarkers Predictive biomarkers Immunohistochemistry In situ proteomics Quantifiable internal reference standards Immunohistochemistry controls Digital pathology Cancer diagnosis 


  1. 1.
    Van den Tweel J, Jiang J, Taylor CR. From magic to molecules: an illustrated history of disease: Beijing University Press; 2016.Google Scholar
  2. 2.
    Taylor CR. Quantitative in situ proteomics; a proposed pathway for quantification of immunohistochemistry at the light-microscopic level. Cell Tissue Res. 2015;360:109–20.CrossRefPubMedGoogle Scholar
  3. 3.
    Cheung CC, D’Arrigo C, Dietel M, et al.; From the International Society for Immunohistochemistry and Molecular Morphology (ISIMM) and International Quality Network for Pathology (IQN Path). Evolution of quality assurance for clinical immunohistochemistry in the era of precision medicine: part 4: tissue tools for quality assurance in immunohistochemistry. Appl Immunohistochem Mol Morphol. 2017;25: 227–230.CrossRefGoogle Scholar
  4. 4.
    Nass SJ, Phillips J, Patlak. Policy issues in the development and adoption of biomarkers for molecularly targeted cancer therapies. National Cancer Policy Forum. Workshop Summary. The National Academies Press. 2015. Scholar
  5. 5.
    European Parliament. Directive 98/79/EC of the European Parliament and of the Council of 27 October 1998 on in vitro diagnostic medical devices. 1998.
  6. 6.
    U.S. Food and Drug Administration. List of cleared or approved companion diagnostic devices (in vitro and imaging tools). 2016. Other nucleic acid based tests are listed separately under an included link. Updated 6/09/16.
  7. 7.
    U.S. Food and Drug Administration. Guidance for industry and FDA staff. In vitro diagnostic (IVD) device studies – frequently asked questions. 2010.
  8. 8.
    Mahoney K, Atkins MB. Prognostic and predictive markers for the new immunotherapies. Oncology. 2014;28(suppl 3):39–48.PubMedGoogle Scholar
  9. 9.
    Gu J, Taylor CR. Practicing pathology in the era of big data and personalized medicine. Appl Immunohistochem Mol Morphol. 2014;22:1–9.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Taylor CR. Predictive biomarkers and companion diagnostics. The future of immunohistochemistry: “in situ proteomics,” or just a “stain”? Appl Immunohistochem Mol Morphol. 2014;22:555–61.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Taylor CR, Becker KF. “Liquid morphology”: immunochemical analysis of proteins extracted from formalin fixed paraffin embedded tissues: combining proteomics with immunohistochemistry. Appl Immunohistochem Mol Morphol. 2011;19:1–9.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Yuan J, Hegde PS, Clynes R, et al. Novel technologies and emerging biomarkers for personalized cancer immunotherapy. J Immunol Ther Cancer. 2016;4:3.CrossRefGoogle Scholar
  13. 13.
    Gaule P, Smithy JW, Toki M, et al. A quantitative comparison of antibodies to programmed cell death 1 ligand 1. JAMA Oncol. 2016; Published online August 18, 2016.CrossRefGoogle Scholar
  14. 14.
    Murphy DA, Ely HA, Shoemaker R, et al. Detecting gene rearrangements in patient populations through a 2-step diagnostic test comprised of rapid IHC enrichment followed by sensitive next generation sequencing. Appl Immunohistochem Mol Morphol. 2017;25: 513–523.CrossRefGoogle Scholar
  15. 15.
    Yaziji H, Taylor CR. PD-L1 assessment for targeted therapy testing in Cancer: urgent need for realistic economic and practice expectations. Appl Immunohistochem Mol Morphol. 2017;25(1):1–3.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Taylor CR. Quality assurance and standardization in immunohistochemistry. A proposal for the annual meeting of the Biological Stain Commission. Biotech Histochem. 1992;67:110–7.CrossRefPubMedGoogle Scholar
  17. 17.
    Shi S-R, Liu C, Balgley BM, Lee C, Taylor CR. Protein extraction from Formalin-fixed, paraffin-embedded tissue sections: quality evaluation by mass spectrometry. J Histochem Cytochem. 2006;54:739–43.CrossRefPubMedGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Clive R. Taylor
    • 1
  1. 1.Department of PathologyUniversity of Southern CaliforniaLos AngelesUSA

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