Recommendations for Biomarker Identification and Qualification in Clinical Proteomics
Recommendations about structuring proteomic biomarker studies should increase the probability that such markers will be clinically useful.
Science Translational Medicine
25 Aug 2010
Vol 2, Issue 46
p. 46ps42
Abstract
Clinical proteomics has yielded some early positive results—the identification of potential disease biomarkers—indicating the promise for this analytical approach to improve the current state of the art in clinical practice. However, the inability to verify some candidate molecules in subsequent studies has led to skepticism among many clinicians and regulatory bodies, and it has become evident that commonly encountered shortcomings in fundamental aspects of experimental design mainly during biomarker discovery must be addressed in order to provide robust data. In this Perspective, we assert that successful studies generally use suitable statistical approaches for biomarker definition and confirm results in independent test sets; in addition, we describe a brief set of practical and feasible recommendations that we have developed for investigators to properly identify and qualify proteomic biomarkers, which could also be used as reporting requirements. Such recommendations should help put proteomic biomarker discovery on the solid ground needed for turning the old promise into a new reality.
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Published In
Science Translational Medicine
Volume 2 | Issue 46
August 2010
August 2010
Copyright
Copyright © 2010, American Association for the Advancement of Science.
Acknowledgments
Funding: This initiative was supported in part by the EuroKUP COST-Action (BM0702; www.eurokup.org), by the European Community’s 6th Framework Programme, grant agreement LSHM-CT-2006-037093 (InGenious HyperCare), and by the European Community’s 7th Framework Programme, grant agreement HEALTH-F2-2009-241544 (SysKID). A.F.D. wishes to acknowledge support of the British Heart Foundation Chair and Programme Grants (BHF RG/07/005/23633). B.A.J. and J.N. acknowledge their support in part from NIH grants DK075868, DK078244, DK082753, DK083663, and DK080301. B.M. and J.P.S. acknowledge the support from the Agence Nationale pour la Recherche (ANR-07-PHYSIO-004-01), the Fondation pour la Recherche Médicale “Grands Equipements pour la Recherche Biomédicale,” and the CPER2007-2013 program. J.J. was supported by a grant from Federal Ministry of Education and Research (01GR0807). W.H. acknowledges support by NCI grant CA 128427 and Korean WCU grant R31-2008-000-10086-0. A.V. and J.G. acknowledge support from FP7 DECanBio (grant agreement 201333). O.J.S. acknowledges support from NIH/NCI CA CA085067. Competing interests: H.M. is the co-founder and co-owner of Mosaiques-Diagnostics. W.B.M. is the founder and principal of PharmPoint Consulting. The other authors declare that they have no competing interests.
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