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Proteomic Analysis for Biomarkers in Early Detection of Cancer Sherry Funston Emily Faerber Brandon Lesniak
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Protein Biomarkers  Proteins used as an indicator of a specific state (such as a disease)  Changes in protein expression or state can be “biomarkers” for risk or progression of a disease
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Why use plasma?     Easily obtained Widely used clinically Contains many proteins (a good representation of the body’s proteome) Plasma has already been used in the diagnosis of many other diseases
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Plasma vs Serum  Plasma:     Add anti-coagulant (EDTA) Centrifuge Remove plasma, leave cells behind Serum:    Allow blood to clot Remove supernatant = serum Variable results
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Biomarkers potentially useful in cancer diagnosis Biomarker Cancer type References Apolipoprotein A1 Ovarian, pancreatic Zhang et al., 2004; Kozak et al., 2005 Heptaglobin α-subunit Ovarian, pancreatic, lung Ye et al., 2003 Transthyretin fragment Ovarian Kozak et al., 2005 Inter-alpha-trypsin inhibitor fragment Ovarian, pancreatic Zhang et al., 2004 Vitamin D-binding protein Prostate, breast Corder et al., 1993; Pawlik et al., 2006 Serum amyloid A Nasopharyngeal, pancreatic, ovarian Orchekowski et al., 2005; Moshkovskii et al., 2005 α1-antitrypsin and α1antichymotrypsin Pancreatic Orchekowski et al., 2005; Yu et al., 2005 Osteopontin Ovarian, prostate Khodavirdi et al., 2006
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Why use proteomic analysis?  Proteomics    The “protein complement of a given genome” (Dr. Marc Wilkins) Basically, all proteins that are being expressed by a cell, tissue, or genome Proteomic analysis reveals which proteins are being expressed with accuracy, speed, and resolution  Has the potential to diagnose diseases, disease states, and effect of treatment of those diseases
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 Approaches to Biomarker Discovery Target Specific     Antibodies Requires previous knowledge of proteins Low-throughput Global/Nondirected    Profiling of unidentified proteins Generate profiles of identified proteins High-throughput
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Slide #10.

MALDI-TOF-MS/MS
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SELDI-TOF-MS
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Sample depletion/enrichment
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Sample depletion/enrichment
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Sample depletion/enrichment
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Sample fractionation/separation
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Research    Research has focused on ovarian, prostate, and breast cancer SELDI-TOF-MS has identified biomarker profiles with 100% sensitivity and 95% specificity Studies have successfully:      Identified patients with tumors Identified type of tumor Distinguished between benign and malignant Identified possible treatments Distinguished response/no response to treatment
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Problems to Overcome  Finding biomarkers that are:      Tumor specific Tissue specific Sample complexity Correlation to population in vivo vs. in vitro behavior
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Clinical Applications  Provides improved patient treatment      Targeted treatment Reduced cost Reliable results Early diagnosis Identification of proper treatment
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References Davis, Michael A., Hanash, Samir. High-throughput genomic technology in reaserach and clinical management in early detection and t herapy. Breast Cancer Research 2006, 8:217. 18 December 2006. Reddy, Guru and Dalmasso, Enrique A. SELDI® Array Technology: Protein-Based Predictive Medicine and Drug Discovery Applications. Journal of Biomedicine and Biotechnology v. 2003(4): 237-241. Alaoui-Jamali, Moulay A., Xu, Ying-jie. Proteomic technology for biomarker profiling in cancer: an update. Joural of Zhejian University SCIENCE v. 7 (6): 411-420. Verrills, Nicole M. Clinical Proteomics: Present and Future Prospects. Clinical Biochemist Reviews v. 27 (2): 99-116.
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