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Immune biomarkers: the promises and pitfalls of personalized medicine

Abstract

Substantial progress in molecular immunology, coupled with an increasing focus on translational research and an enthusiasm for personalized medicine, has resulted in a rapid expansion in the field of immune biomarkers in recent years. In this Science and Society article, we provide a conceptual overview of the field and discuss the progress that has been made so far, as well as the future potential in the context of the scientific, logistical, financial, legal and ethical framework within which this research is being carried out and translated into clinical use.

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Figure 1: Volume of immune biomarker publications.
Figure 2: Comparison of different medical approaches.
Figure 3: Timelines for treatment efficacy in allograft rejection.
Figure 4: The immune biomarker workstream.
Figure 5: Decreasing costs of genome sequencing.

References

  1. Sanderson, J., Ansari, A., Marinaki, T. & Duley, J. Thiopurine methyltransferase: should it be measured before commencing thiopurine drug therapy? Ann. Clin. Biochem. 41, 294–302 (2004).

    Article  CAS  PubMed  Google Scholar 

  2. Goldman, J. M. & Melo, J. V. Chronic myeloid leukemia — advances in biology and new approaches to treatment. New. Engl. J. Med. 349, 1451–1464 (2003).

    Article  CAS  PubMed  Google Scholar 

  3. Soverini, S. et al. Drug resistance and BCR–ABL kinase domain mutations in Philadelphia chromosome-positive acute lymphoblastic leukaemia from the imatinib to the second-generation tyrosine kinase inhibitor era: the main changes are in the type of mutations, but not in the frequency of mutation involvement. Cancer 120, 1002–1009 (2014).

    Article  CAS  PubMed  Google Scholar 

  4. Maini, R. et al. Infliximab (chimeric anti-tumour necrosis factor-α monoclonal antibody) versus placebo in rheumatoid arthritis patients receiving concomitant methotrexate: a randomised phase III trial. ATTRACT Study group. Lancet 354, 1932–1939 (1999).

    Article  CAS  PubMed  Google Scholar 

  5. National institute for Health and Care Excellence. Rheumatoid Arthritis. The Management of Rheumatoid Arthritis in Adults. (NICE, 2013).

  6. Plant, D., Wilson, A. G. & Barton, A. Genetic and epigenetic predictors of responsiveness to treatment in RA. Nature Rev. Rheumatol. 10, 329–337 (2014).

    Article  CAS  Google Scholar 

  7. Kalos, M. et al. T cells with chimeric antigen receptors have potent antitumour effects and can establish memory in patients with advanced leukemia. Sci. Transl. Med. 3, 95ra73 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Geissler, E. K. & Hutchinson, J. A. Cell therapy as a strategy to minimize maintenance immunosuppression in solid organ transplant recipients. Curr. Opin. Organ. Transplant. 18, 408–415 (2013).

    CAS  PubMed  Google Scholar 

  9. Masteller, E. L., Tang, Q. & Bluestone, J. A. Antigen-specific regulatory T cells: ex vivo expansion and therapeutic potential. Semin. Immunol. 18, 103–110 (2006).

    Article  CAS  PubMed  Google Scholar 

  10. Leslie, M. Regulatory T cells get their chance to shine. Science 332, 1020–1021 (2011).

    Article  CAS  PubMed  Google Scholar 

  11. Naidoo, J., Page, D. B. & Wolchok, J. D. Immune modulation for cancer therapy. Br. J. Cancer 111, 2214–2219 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Ku, G. Y. et al. Single institution experience with ipilimumab in advanced melanoma patients in the compassionate use setting: lymphocyte count after two doses correlates with survival. Cancer 116, 1767–1775 (2010).

    Article  CAS  PubMed  Google Scholar 

  13. Postow, M. A. et al. Evaluation of the absolute lymphocyte count as a biomarker for melanoma patients treated with the commercially available dose of ipilimumab (3mg/kg). J. Clin. Oncol. 30, 8575 (2012).

    Google Scholar 

  14. Topalian, S. L. et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N. Engl. J. Med. 366, 2443–2453 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Goris, A. & Liston, A. The immunogenetic architecture of autoimmune disease. Cold Spring Harb. Perspect. Biol. 4, a007260 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Hartono, C., Muthukumar, T. & Suthanthiran, M. Noninvasive diagnosis of acute rejection of renal allografts. Curr. Opin. Organ. Transplant. 15, 35–41 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Zhang, B. et al. Proteogenomic characterisation of human colon and rectal cancer. Nature 513, 382–387 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. O'Connell, R. M., Rao, D. S., Chaudhuri, A. A. & Baltimore, D. Physiological and pathological roles for microRNAs in the immune system. Nature Rev. Immunol. 10, 111–122 (2010).

    Article  CAS  Google Scholar 

  19. Pauley, K. M., Cha, S. & Chan, E. K. MicroRNA in autoimmunity and autoimmune diseases. J. Autoimmun. 32, 189–194 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Mitchell, P. S. et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc. Natl. Acad. Sci. USA 105, 10513–10518 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kroh, E. M., Parkin, R. K., Mitchell, P. S. & Tewari, M. Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR. Methods 50, 298–301 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ma, Y. et al. Genome-wide sequencing of cellular microRNAs identifies a combinatorial expression signature diagnostic of sepsis. PLoS ONE 8, e75918 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Buffie, C. G. et al. Precision microbiome reconstruction restores bile acid mediated resistance to Clostridium difficile. Nature 517, 205–208 (2015).

    Article  CAS  PubMed  Google Scholar 

  24. Taur, Y. et al. The effects of intestinal tract bacterial diversity on mortality following allogeneic hematopoietic stem cell transplantation. Blood 124, 1174–1182 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Roedder, S., Gao, X. & Sarwal, M. The pits and pearls in translating operational tolerance biomarkers into clinical practice. Curr. Opin. Organ. Transplant. 17, 655–662 (2012).

    Article  PubMed  Google Scholar 

  26. Sagoo, P. et al. Development of a cross-platform biomarker signature to detect renal transplant tolerance in humans. J. Clin. Invest. 120, 1848–1861 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Sattlecker, M. et al. Alzheimer's disease biomarker discovery using SOMAscan multiplexed protein technology. Alzheimers Dement. 10, 724–734 (2014).

    Article  PubMed  Google Scholar 

  28. Mehan, M. R. et al. Validation of a blood protein signature for non-small cell lung cancer. Clin. Proteom. 11, 32 (2014).

    Article  Google Scholar 

  29. Menni, C. et al. Circulating proteomic signatures of chronological age. J. Gerontol. A. Biol. Sci. Med. Sci. http://dx.doi.org/10.1093/gerona/glu121 (2014).

  30. Hill, A. B. The environment and disease: association or causation? Proc. R. Soc. Med. 58, 295–300 (1965).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Tsoi, L. C. et al. Identification of 15 new psoriasis susceptibility loci highlights the role of innate immunity. Nature Genet. 44, 1341–1348 (2012).

    Article  CAS  PubMed  Google Scholar 

  32. Papp, K. A. et al. Brodalumab, an interleukin-17-receptor antibody for psoriasis. N. Engl. J. Med. 366, 1181–1189 (2012).

    Article  CAS  PubMed  Google Scholar 

  33. Lennon, V. A., Kryzer, T. J., Pittock, S. J., Verkman, A. S. & Hinson, S. R. IgG marker of optic-spinal multiple sclerosis binds to the aquaporin-4 water channel. J. Exp. Med. 202, 473–477 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Kitley, J. et al. Prognostic factors and disease course in aquaporin-4 antibody-positive patients with neuromyelitis optica spectrum disorder from the United Kingdom and Japan. Brain 135, 1834–1849 (2012).

    Article  PubMed  Google Scholar 

  35. Lee, D. W. et al. Current concepts in the diagnosis and management of cytokine release syndrome. Blood 124, 188–195 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kennedy, G. A. et al. Addition of interleukin-6 inhibition to standard graft-versus host disease prophylaxis after allogeneic stem cell transplantation: a phase 1/2 trial. Lancet Oncol. 15, 1451–1459 (2014).

    Article  CAS  PubMed  Google Scholar 

  37. Lo, D. J., Kaplan, B. & Kirk, A. Biomarkers for kidney transplant rejection. Nature Rev. Neph. 10, 215–225 (2014).

    Article  CAS  Google Scholar 

  38. Narang, V. et al. Systems immunology: a survey of modelling formalisms, applications and simulation tools. Immunol. Res. 53, 251–265 (2012).

    Article  CAS  PubMed  Google Scholar 

  39. Villanova, F. et al. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery. PLoS ONE 8, e65485 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Dendrou, C. A., Bell, J. I. & Fugger, L. Weighing in on autoimmune disease: big data tip the scale. Nature Med. 19, 138–139 (2013).

    Article  CAS  PubMed  Google Scholar 

  41. EMBL-European Bioinformatics Institute. EMBL-EBI Annual Scientific Report 2013. (EMBL-EBI, 2013).

  42. Pepe, M. S., Janes, H. & Li, C. I. Net risk reclassification p values: valid or misleading? J. Natl. Cancer Inst. 106, dju041 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Pepe, M. S., Feng, Z., Janes, H., Bossuyt, P. M, & Potter, J. D. Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. J. Natl Cancer Inst. 100, 1432–1438 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Fellner, C. Ipilimumab (Yervoy) prolongs survival in advanced melanoma. P. T. 37, 503–511 (2012).

    PubMed  PubMed Central  Google Scholar 

  45. Roep, B. O. & Peakman, M. Surrogate end points in the design of immunotherapy trials: emerging lessons from type 1 diabetes. Nature Rev. Immunol. 10, 145–152 (2010).

    Article  CAS  Google Scholar 

  46. U.S. Food and Drug Adminstration. Innovation or stagnation? Challenge and opportunity on the critical path to new medical products. U.S. Department of Health and Human Services [online], (2004).

  47. Organisation for Economic Co-operation and Development. Policy Issues for the Development and Use of Biomarkers in Health. OECD Directorate for Science, Technology and Industry (DSTI) [online], (2011).

  48. Greenbaum, D., Sboner, A., Mu, X. J. & Gerstein, M. Genomics and privacy: implications of the new reality of closed data for the field. PLoS Comput. Biol. 7, e1002278 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Sharp, R. R. Downsizing genomic medicine: approaching the ethical complexity of whole-genome sequencing by starting small. Genet. Med. 13, 191–194 (2011).

    Article  PubMed  Google Scholar 

  50. Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69, 89–95 (2001).

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Acknowledgements

The authors would like to acknowledge support from grants awarded by the Medical Research Council, UK (M003493), and the British Heart Foundation, UK (PG/12/36/29444). G.M.L. is also supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' National Health Service (NHS) Foundation Trust and King's College London, UK. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.

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Correspondence to Graham M. Lord.

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Willis, J., Lord, G. Immune biomarkers: the promises and pitfalls of personalized medicine. Nat Rev Immunol 15, 323–329 (2015). https://doi.org/10.1038/nri3820

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