The overall goal of this project is to identify autoantibody biomarkers in sera that can be readily used for the early detection of cancer. Antibodies are induced by tumor-specific alterations in protein expression, mutation, degradation, or localization, with high specificity. We have developed a novel programmable protein microarray technology (NAPPA), which uses printed cDNA encoding tumor antigens that are translated in vitro. We have been funded for the past four years as an EDRN Biomarker Development Laboratory to develop NAPPA as a clinical research tool and to employ it for the detection of autoantibody biomarkers for breast cancer, and have screened over 700 sera and identified 32 novel breast and 23 ovarian biomarkers that have undergone blinded validation studies. Here, we propose to increase the feature density of NAPPA arrays in order to accommodate the increasing size of our cDNA collection, which now approaches 10,000 unique genes (Aim 1) and to develop a method for producing glycoproteome arrays (Aim 2). Both of these methods will enhance autoantibody biomarker discovery by increasing the number and quality of the antigens screened.
Aim 3 will use the results of Aims 1 and 2 to expand the top breast cancer biomarkers that have been identified to focus on particular subtypes of breast cancer that are more difficult to detect including Her2+ breast cancers, triple-negative (ER-PR-Her2-) breast cancers, and cancers that occur in the setting of high breast density. Association of antibody detection and tumor antigen expression will be explored.
Aim 4 will assess the performance characteristics of the combined set of top breast cancer biomarkers in Phase II studies using sera collected in multicenter clinical studies.
Aim 5 will focus on the utility of these biomarkers to detect disease prior to clinical diagnosis. At the end of these experiments, our goal is to identify autoantibody serum signatures that can be used by EDRN CEVCs in further Phase III independent validation studies for the early detection of breast cancer according to the EDRN biomarker discovery guideline.
In 2008, it is estimated that over 40,000 people will die of breast cancer, and over 500,000 will die of other cancers, with increased morbidity and mortality when cancers are detected at late stages. This project focuses on eariy detection biomarker discovery for breast cancer to complement mammographic screening, with an ultimate goal to reduce overall breast cancer morbidity and mortality.
|Yu, Xiaobo; Petritis, Brianne; Duan, Hu et al. (2018) Advances in cell-free protein array methods. Expert Rev Proteomics 15:1-11|
|Kaaks, Rudolf; Fortner, Renée Turzanski; Hüsing, Anika et al. (2018) Tumor-associated autoantibodies as early detection markers for ovarian cancer? A prospective evaluation. Int J Cancer 143:515-526|
|Anderson, Karen S; Wallstrom, Garrick; Langseth, Hilde et al. (2017) Pre-diagnostic dynamic HPV16 IgG seropositivity and risk of oropharyngeal cancer. Oral Oncol 73:132-137|
|Katchman, Benjamin A; Chowell, Diego; Wallstrom, Garrick et al. (2017) Autoantibody biomarkers for the detection of serous ovarian cancer. Gynecol Oncol 146:129-136|
|Yu, Xiaobo; Petritis, Brianne; LaBaer, Joshua (2016) Advancing translational research with next-generation protein microarrays. Proteomics 16:1238-50|
|Ewaisha, Radwa; Gawryletz, Chelsea D; Anderson, Karen S (2016) Crucial considerations for pipelines to validate circulating biomarkers for breast cancer. Expert Rev Proteomics 13:201-11|
|Katchman, Benjamin A; Smith, Joseph T; Obahiagbon, Uwadiae et al. (2016) Application of flat panel OLED display technology for the point-of-care detection of circulating cancer biomarkers. Sci Rep 6:29057|
|Katchman, Benjamin A; Barderas, Rodrigo; Alam, Rizwan et al. (2016) Proteomic mapping of p53 immunogenicity in pancreatic, ovarian, and breast cancers. Proteomics Clin Appl 10:720-31|
|Yu, Xiaobo; LaBaer, Joshua (2015) High-throughput identification of proteins with AMPylation using self-assembled human protein (NAPPA) microarrays. Nat Protoc 10:756-67|
|Anderson, Karen S; Cramer, Daniel W; Sibani, Sahar et al. (2015) Autoantibody signature for the serologic detection of ovarian cancer. J Proteome Res 14:578-86|
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