The development of biomarkers for earlier detection of ovarian cancer will greatly improve survival. Most women present with advanced stage disease with survival rates of roughly 20%. Advances in the field of proteomics now provide the tools necessary to effectively analyze the serum proteome, and the application of such technologies holds great promise for determining novel biomarkers. This proposal outlines methods to comprehensively discover, identify, quantify, and validate a panel of specific and sensitive ovarian cancer biomarkers for early detection. We propose the following Specific Aims: 1. Determine candidate ovarian cancer biomarkers defined by comprehensive biomarker analysis of serum. Emphasis will be placed on refining the most effective overall analytical strategy for comprehensive and reproducible measurements. Spectral peaks that most accurately distinguish cancer vs. control will be identified using high-resolving power technology. Biostatistics and bioinformatics will be used to prioritize candidate markers (according to specificity, sensitivity and predictive value) for further characterization. 2. Identification and absolute quantification of the candidate biomarkers. This will improve reliability and high-throughput capabilities in subsequent validation testing, and the identification of these proteins will contribute further to research into the biologic basis of the disease. We will use accurate mass measurements, tandem mass spectrometry, and non-redundant protein and genome databases applied to distinct selected controls. Furthermore, we will determine the range of values for both normal and cancer serum samples using stable isotope labeled internal standards. 3. Clinical validation of a panel of biomarkers in specific groups of women. Sera from defined cohorts of women will be used to accurately determine the sensitivity, specificity, and predictive values of individual and combinations of candidate markers in all aspects of disease (early/late stage, familial, remission and recurrence) and in large numbers of non-cancer controls.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants Phase II (R33)
Project #
5R33CA105295-02
Application #
6896409
Study Section
Special Emphasis Panel (ZCA1-SRRB-C (O1))
Program Officer
Lively, Tracy (LUGO)
Project Start
2004-05-21
Project End
2005-06-30
Budget Start
2005-05-04
Budget End
2005-06-30
Support Year
2
Fiscal Year
2005
Total Cost
$5,712
Indirect Cost
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905
Dixon, R Brent; Bereman, Michael S; Petitte, James N et al. (2011) One-Year Plasma N-linked Glycome Intra-individual and Inter-individual Variability in the Chicken Model of Spontaneous Ovarian Adenocarcinoma. Int J Mass Spectrom 305:79-86
Bereman, Michael S; Muddiman, David C (2010) The effects of abundant plasma protein depletion on global glycan profiling using nanoLC FT-ICR mass spectrometry. Anal Bioanal Chem 396:1473-9
Williams Jr, D Keith; Kovach, Alexander L; Muddiman, David C et al. (2009) Utilizing artificial neural networks in MATLAB to achieve parts-per-billion mass measurement accuracy with a fourier transform ion cyclotron resonance mass spectrometer. J Am Soc Mass Spectrom 20:1303-10
Williams, D Keith; Muddiman, David C (2009) Absolute quantification of C-reactive protein in human plasma derived from patients with epithelial ovarian cancer utilizing protein cleavage isotope dilution mass spectrometry. J Proteome Res 8:1085-90
Bereman, Michael S; Young, Douglas D; Deiters, Alexander et al. (2009) Development of a robust and high throughput method for profiling N-linked glycans derived from plasma glycoproteins by NanoLC-FTICR mass spectrometry. J Proteome Res 8:3764-70
Bereman, Michael S; Williams, Taufika Islam; Muddiman, David C (2009) Development of a nanoLC LTQ orbitrap mass spectrometric method for profiling glycans derived from plasma from healthy, benign tumor control, and epithelial ovarian cancer patients. Anal Chem 81:1130-6
Sampson, Jason S; Murray, Kermit K; Muddiman, David C (2009) Intact and top-down characterization of biomolecules and direct analysis using infrared matrix-assisted laser desorption electrospray ionization coupled to FT-ICR mass spectrometry. J Am Soc Mass Spectrom 20:667-73
Hawkridge, Adam M; Muddiman, David C (2009) Mass spectrometry-based biomarker discovery: toward a global proteome index of individuality. Annu Rev Anal Chem (Palo Alto Calif) 2:265-77
Williams Jr, D Keith; Comins, Daniel L; Whitten, Jerry L et al. (2009) Evaluation of the ALiPHAT method for PC-IDMS and correlation of limits-of-detection with nonpolar surface area. J Am Soc Mass Spectrom 20:2006-12
Sampson, Jason S; Hawkridge, Adam M; Muddiman, David C (2008) Construction of a versatile high precision ambient ionization source for direct analysis and imaging. J Am Soc Mass Spectrom 19:1527-34

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