title: Clinical proteomics: from biomarker discovery and cell signaling profiles to individualized personal therapy.
abstract: The discovery of new highly sensitive and specific biomarkers for early disease detection and risk stratification coupled with the development of personalized "designer" therapies holds the key to future treatment of complex diseases such as cancer. Mounting evidence confirms that the low molecular weight (LMW) range of the circulatory proteome contains a rich source of information that may be able to detect early stage disease and stratify risk. Current mass spectrometry (MS) platforms can generate a rapid and high resolution portrait of the LMW proteome. Emerging novel nanotechnology strategies to amplify and harvest these LMW biomarkers in vivo or ex vivo will greatly enhance our ability to discover and characterize molecules for early disease detection, subclassification and prognostic capability of current proteomics modalities. Ultimately genetic mutations giving rise to disease are played out and manifested on a protein level, involving derangements in protein function and information flow within diseased cells and the interconnected tissue microenvironment. Newly developed highly sensitive, specific and linearly dynamic reverse phase protein microarray systems are now able to generate circuit maps of information flow through phosphoprotein networks of pure populations of microdissected tumor cells obtained from patient biopsies. We postulate that this type of enabling technology will provide the foundation for the development of individualized combinatorial therapies of molecular inhibitors to target tumor-specific deranged pathways regulating key biologic processes including proliferation, differentiation, apoptosis, immunity and metastasis. Hence future therapies will be tailored to the specific deranged molecular circuitry of an individual patient's disease. The successful transition of these groundbreaking proteomic technologies from research tools to integrated clinical diagnostic platforms will require ongoing continued development, and optimization with rigorous standardization development and quality control procedures.
authors.affiliation: Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. calvok@mail.nih.gov
authors.forename: Katherine R
authors.initials: KR
authors.lastname: Calvo
authors.forename: Lance A
authors.initials: LA
authors.lastname: Liotta
authors.forename: Emanuel F
authors.initials: EF
authors.lastname: Petricoin
mesh_terms: D015415:Biomarkers / Q000737:chemistry*; D014408:Biomarkers, Tumor; D003131:Combined Modality Therapy / Q000379:methods; D019295:Computational Biology / Q000379:methods; D023281:Genomics / Q000379:methods / Q000639:trends; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods; D036103:Nanotechnology / Q000379:methods; D040081:Protein Array Analysis / Q000379:methods; D020543:Proteome; D040901:Proteomics / Q000379:methods* / Q000639:trends; D015398:Signal Transduction
chemical_list: D015415:Biomarkers; D014408:Biomarkers, Tumor; D020543:Proteome