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Mapping Molecular Networks Using Proteomics: A Vision for Patient-Tailored Combination Therapy

From the US Food and Drug Administration (FDA) –National Cancer Institute (NCI) Clinical Proteomics Program, Office of Cellular and Gene Therapy, Center for Biologics Evaluation and Research (CBER), FDA; FDA-NCI Clinical Proteomics Program, Laboratory of Pathology, NCI, Center for Cancer Research (CCR)/National Institutes of Health (NIH); Biostatistics Section, Mathematical and Statistical Computing Laboratory, Center for Information Technology, NIH, Bethesda; Johns Hopkins University, Department of Urology, Baltimore, MD; University of Padova, Department of Oncological and Surgical Science, Padova, Italy; University of Michigan, Department of Internal Medicine, Ann Arbor, MI; Department of Obstetrics and Gynecology, New York University School of Medicine, New York, NY; Massachusetts General Hospital Cancer Center and Harvard Medical School, Charlestown, MA; and Departments of Surgery and Radiology, University of California, San Francisco, San Francisco, CA

Address reprint requests to Emanuel F. Petricoin III, PhD, Center for Applied Proteomics and Molecular Medicine, George Mason University, 10900 University Boulevard, MS 4E3, Manassas, VA 20110; e-mail: epetrico{at}gmu.edu

Mapping tumor cell protein networks in vivo will be critical for realizing the promise of patient-tailored molecular therapy. Cancer can be defined as a dysregulation or hyperactivity in the network of intracellular and extracellular signaling cascades. These protein signaling circuits are the ultimate targets of molecular therapy. Each patient's tumor may be driven by a distinct series of molecular pathogenic defects. Thus, for any single molecular targeted therapy, only a subset of cancer patients may respond. Individualization of therapy, which tailors a therapeutic regimen to a tumor molecular portrait, may be the solution to this dilemma. Until recently, the field lacked the technology for molecular profiling at the genomic and proteomic level. Emerging proteomic technology, used concomitantly with genomic analysis, promises to meet this need and bring to reality the clinical adoption of molecular stratification. The activation state of kinase-driven signal networks contains important information relative to cancer pathogenesis and therapeutic target selection. Proteomic technology offers a means to quantify the state of kinase pathways, and provides post-translational phosphorylation data not obtainable by gene arrays. Case studies using clinical research specimens are provided to show the feasibility of generating the critical information needed to individualize therapy. Such technology can reveal potential new pathway interconnections, including differences between primary and metastatic lesions. We provide a vision for individualized combinatorial therapy based on proteomic mapping of phosphorylation end points in clinical tissue material.

Authors' disclosures of potential conflicts of interest are found at the end of this article.

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