Textbook of Personalized Medicine - Second Edition [2015]

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Role of Reverse-Phase Protein Microarray in Drug Discovery


Reverse-phase protein microarray (RPMA) is a technology platform designed for
quantitative, multiplexed analysis of specifi c phosphorylated, cleaved, or total
(phosphorylated and nonphosphorylated) forms of cellular proteins from a limited
amount of sample. This class of microarray can be used to interrogate cellular sam-
ples, serum or body fl uids. RPMA has been applied for translational research and
therapeutic drug target discovery (VanMeter et al. 2007 ). It is particularly suited for
oncology. Mapping of protein signaling networks within tumors can identify new
targets for therapy and provide a means to stratify patients for individualized ther-
apy. Kinases are important drug targets as such kinase network information could
become the basis for development of therapeutic strategies for improving treatment
outcome. An urgent clinical goal is to identify functionally important molecular
networks associated with subpopulations of patients that may not respond to con-
ventional combination chemotherapy.


Dynamic Proteomics for Targeting Disease Pathways


Dynamic proteomics is the study of dynamics (synthesis, breakdown, transport,
storage, etc.) of all proteins in an organism and to translate them into drug discov-
ery, biomarkers and diagnostics. This approach combines the power of liquid chro-
matography (LC)/mass spectrometry (MS) methods to characterize thousands of
proteins in a single sample with kinetic fl ux analysis for interrogating complex bio-
logic systems to report on those that drive the initiation, progression and reversal of
common diseases. Advantages of this approach are:



  • Focus on causes rather than symptoms: generating pivotal knowledge for devel-
    oping blockbuster drugs, by targeting underlying biochemical causes.

  • Systems biology approach: insight into intact living systems, rather than simpli-
    fi ed models, ensures that drug effects are understood in their intended biological
    context.

  • Reduction of late-stage attrition: early, decision-relevant metrics of drug activity
    separate winners from losers and reduce losses from later failures.

  • Powerful assays of disease state: custom-developed assays to create companion
    diagnostic tests for personalized medicine.


Target Identifi cation and Validation


The genomics revolution has led to a fl ood of potential targets but genomic data, by
itself, is not be suffi cient for validating drug targets. Because most drugs act on
proteins, proteins are likely to be more signifi cant therapeutic targets than DNA in


6 Pharmacoproteomics
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