title: Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy.
abstract: 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.affiliation: US Food and Drug Administration-National Cancer Institute Clinical Proteomics Program, Office of Cellular and Gene Therapy, Center for Biologics Evaluation and Research, FDA, Bethesda, MD, USA. epetrico@gmu.edu
authors.forename: Emanuel F
authors.initials: EF
authors.lastname: Petricoin
authors.forename: Verena E
authors.initials: VE
authors.lastname: Bichsel
authors.forename: Valerie S
authors.initials: VS
authors.lastname: Calvert
authors.forename: Virginia
authors.initials: V
authors.lastname: Espina
authors.forename: Mary
authors.initials: M
authors.lastname: Winters
authors.forename: Lynn
authors.initials: L
authors.lastname: Young
authors.forename: Claudio
authors.initials: C
authors.lastname: Belluco
authors.forename: Bruce J
authors.initials: BJ
authors.lastname: Trock
authors.forename: Marc
authors.initials: M
authors.lastname: Lippman
authors.forename: David A
authors.initials: DA
authors.lastname: Fishman
authors.forename: Dennis C
authors.initials: DC
authors.lastname: Sgroi
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Munson
authors.forename: Laura J
authors.initials: LJ
authors.lastname: Esserman
authors.forename: Lance A
authors.initials: LA
authors.lastname: Liotta
mesh_terms: D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D003131:Combined Modality Therapy; D005260:Female; D005544:Forecasting; D020869:Gene Expression Profiling; D015316:Genetic Therapy / Q000379:methods; D006801:Humans; D007167:Immunotherapy / Q000379:methods; D008297:Male; D008495:Medical Oncology / Q000592:standards / Q000639:trends; D008967:Molecular Biology / Q000379:methods*; D009363:Neoplasm Proteins; D009369:Neoplasms / Q000235:genetics / Q000401:mortality / Q000628:therapy*; D040081:Protein Array Analysis; D040901:Proteomics / Q000379:methods*; D012680:Sensitivity and Specificity; D015398:Signal Transduction
chemical_list: D009363:Neoplasm Proteins