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Review
. 2011 Nov 18;74(12):2632-41.
doi: 10.1016/j.jprot.2011.04.023. Epub 2011 May 4.

Proteomics and biomarkers in clinical trials for drug development

Affiliations
Review

Proteomics and biomarkers in clinical trials for drug development

Jung-min Lee et al. J Proteomics. .

Abstract

Proteomics allows characterization of protein structure and function, protein-protein interactions, and peptide modifications. It has given us insight into the perturbations of signaling pathways within tumor cells and has improved the discovery of new therapeutic targets and possible indicators of response to and duration of therapy. The discovery, verification, and validation of novel biomarkers are critical in streamlining clinical development of targeted compounds, and directing rational treatments for patients whose tumors are dependent upon select signaling pathways. Studies are now underway in many diseases to examine the immune or inflammatory proteome, vascular proteome, cancer or disease proteome, and other subsets of the specific pathology microenvironment. Successful assay verification and biological validation of such biomarkers will speed development of potential agents to targetable dominant pathways and lead to selection of individuals most likely to benefit. Reconsideration of analytical and clinical trials methods for acquisition, examination, and translation of proteomics data must occur before we march further into future of drug development.

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Figures

Figure 1
Figure 1. The decision-making process of drug development incorporating proteomics
Proteomic profiling has been applied for identification of predictive markers and therapeutic targets through retrospective analyses. The discovery and validation of biomarkers would lead to development of new potential drugs via prospective clinical trials stratified by biomarker for more effective targeted therapy in recurrent cancers.
Figure 2
Figure 2. Prospective and retrospective approaches for identification of potential biomarkers
A biomarker-forward, focused, target-associated prospective approach specifically address biomarkers to select patients for therapy. Alternatively, an agnostic, trial-backwards, retrospective approach would apply biased selection with biological validation of translational endpoints against patient outcome in targeted agents’ trials.

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