The overall goal of this application is to discover and validate multiple novel plasma protein biomarkers of human ovarian cancer. We will initially discover a substantial number of candidate biomarkers through parallel analysis of two complementary models of ovarian cancers and will subsequently validate the most promising candidate biomarkers in a human patient cohort.
In Aim 1, we will use a xenograft model where human ovarian cancer cell lines are injected into both ovaries of NOD/SCID/3c-/- (NOG) mice and human primary tumors are allowed to grow prior to collection of the plasma. Several existing early passage serous cancer cell lines will be used and additional early passage cell lines will be derived from human ovarian tumors for this study. Low abundance plasma proteins will be identified using a 4-D protein profiling method that is capable of detecting many proteins in the low ng/ml to pg/ml range in plasma. Proteins secreted or shed by the human tumors will be unambiguously identified using high mass accuracy mass spectrometry coupled with rigorous data analysis to distinguish human and mouse proteins based on species-specific sequence differences. Low abundance human proteins that can be identified with >99% confidence and where repeat targeted LC-MS/MS analysis of the fraction can confirm the protein identification will be considered as candidate biomarkers.
In Aim 2, we will analyze the secretome (shed and secreted proteins) from short term organ cultures using fresh ovarian tumors. The effects of normoxic and hypoxic conditions on protein shedding will be compared. In addition, the secretomes of short term organ culture, early passage established cultures from the same tumor and xenograft tumors from the same cell line will be compared to determine how different environmental and physiological context affects ovarian tumor cell protein shedding.
In Aim 3, we will select the most promising candidate biomarkers from Aims 1 and 2 for validation analyses. Candidate biomarkers from the discovery studies in Aims 1 and 2 will be prioritized based upon: abundance in normal human plasma;specificity for ovarian tumors: consistency of shedding by different ovarian tumors, and biological function. The highest priority candidate biomarkers will be subsequently validated using multiplexed multiple reaction monitoring (MRM) mass spectrometry assays to quantify biomarker levels in plasma of ovarian patients and controls. Individual biomarkers as well as groups of biomarkers will be evaluated for their capacity to predict early stage ovarian cancers
Survival rates of ovarian cancer patients are about 90% if the disease is confined to the ovaries at diagnosis. Unfortunately, early stage ovarian tumors are usually asymptomatic and about 75% of cases are diagnosed after the cancer has spread. Recently developed powerful mass spectrometry-based plasma proteome analysis methods coupled with mouse ovarian cancer models provide unique opportunities to systematically discover many new ovarian cancer biomarker candidates that will lead to improved early diagnosis and clinical management of this disease.
|Beer, Lynn A; Liu, Pengyuan; Ky, Bonnie et al. (2017) Efficient Quantitative Comparisons of Plasma Proteomes Using Label-Free Analysis with MaxQuant. Methods Mol Biol 1619:339-352|
|Beer, Lynn A; Ky, Bonnie; Barnhart, Kurt T et al. (2017) In-Depth, Reproducible Analysis of Human Plasma Using IgY 14 and SuperMix Immunodepletion. Methods Mol Biol 1619:81-101|
|Pestell, Timothy G; Jiao, Xuanmao; Kumar, Mukesh et al. (2017) Stromal cyclin D1 promotes heterotypic immune signaling and breast cancer growth. Oncotarget 8:81754-81775|
|Zhu, Hengrui; Le, Linh; Tang, Hsin-Yao et al. (2017) Detection of the Ubiquitinome in Cells Undergoing Oncogene-Induced Senescence. Methods Mol Biol 1534:127-137|
|Liu, Pengyuan; Beer, Lynn A; Ky, Bonnie et al. (2017) Quantitative Comparisons of Large Numbers of Human Plasma Samples Using TMT10plex Labeling. Methods Mol Biol 1619:319-337|
|Goldman, Aaron; Harper, Sandra; Speicher, David W (2016) Detection of Proteins on Blot Membranes. Curr Protoc Protein Sci 86:10.8.1-10.8.11|
|Fan, Ming-Hui; Zhu, Qiang; Li, Hui-Hua et al. (2016) Fibroblast Activation Protein (FAP) Accelerates Collagen Degradation and Clearance from Lungs in Mice. J Biol Chem 291:8070-89|
|Goldman, Aaron R; Bitler, Benjamin G; Schug, Zachary et al. (2016) The Primary Effect on the Proteome of ARID1A-mutated Ovarian Clear Cell Carcinoma is Downregulation of the Mevalonate Pathway at the Post-transcriptional Level. Mol Cell Proteomics 15:3348-3360|
|Bengsch, Fee; Tu, Zhigang; Tang, Hsin-Yao et al. (2015) Comprehensive analysis of the ubiquitinome during oncogene-induced senescence in human fibroblasts. Cell Cycle 14:1540-7|
|Goldman, Aaron; Ursitti, Jeanine A; Mozdzanowski, Jacek et al. (2015) Electroblotting from Polyacrylamide Gels. Curr Protoc Protein Sci 82:10.7.1-16|
Showing the most recent 10 out of 18 publications