Proteomic Analysis for Biomarkers in Early Detection of Cancer

Proteomic Analysis for Biomarkers in Early Detection of Cancer

Proteomic Analysis for Biomarkers in Early Detection of Cancer Sherry Funston Emily Faerber Brandon Lesniak 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 Why use plasma? Easily obtained Widely used clinically Contains many proteins (a good

representation of the bodys proteome) Plasma has already been used in the diagnosis of many other diseases Plasma vs Serum Plasma:

Add anti-coagulant (EDTA) Centrifuge Remove plasma, leave cells behind Serum: Allow blood to clot Remove supernatant = serum Variable results

Biomarkers potentially useful in cancer diagnosis Biomarker Cancer type References Apolipoprotein A1 Ovarian, pancreatic Zhang et al., 2004; Kozak et al., 2005

Heptaglobin -subunitsubunit Ovarian, pancreatic, lung Ye et al., 2003 Transthyretin fragment Ovarian Kozak et al., 2005 Inter-subunitalpha-subunittrypsin inhibitor fragment

Ovarian, pancreatic Zhang et al., 2004 Vitamin D-subunitbinding 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 1-subunitantitrypsin and 1-subunit antichymotrypsin Pancreatic Orchekowski et al., 2005; Yu et al., 2005 Osteopontin Ovarian, prostate

Khodavirdi et al., 2006 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

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 MALDI-TOF-MS/MS SELDI-TOF-MS

Sample depletion/enrichment Sample depletion/enrichment Sample depletion/enrichment Sample fractionation/separation 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 Problems to Overcome Finding biomarkers that are:

Tumor specific Tissue specific Sample complexity Correlation to population in vivo vs. in vitro behavior Clinical Applications

Provides improved patient treatment Targeted treatment Reduced cost Reliable results Early diagnosis Identification of proper treatment

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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