We use a targeted approach to discover biomarkers for assay development. First, markers for cancer detection and disease stratification are identified by comparing the transcriptomes, or gene expression, of cell types within tumors to those of their normal counterpart. Cell type-specific transcriptomes are determined via cell isolation from tissue specimens using antibodies to cell surface CD antigens followed by expression analysis using Affymetrix DNA arrays. Second, tumor upregulated genes encoding extracellular/secreted proteins are selected. The gene AGR2 showed a comparatively high level of expression in prostate cancer cells, and the 17-kDa AGR2 protein was detected in tumor tissue preparations by Western blot analysis using a commercial mouse antibody 1C3. Third, tissue microarray analysis validated prostate tumor expression of AGR2, and non-cancer tissue showed little AGR2 expression. Fourth, new monoclonal antibodies are being generated against AGR2 for the development of a urine test to screen men with prostate cancer, where tumor secreted AGR2 protein might be present in voided urine at ?ng/ml levels. The 1C3 antibody, which was raised against a bacterially produced recombinant AGR2 protein, appeared not to recognize native AGR2 as secreted by the AGR2-I- prostate cancer cell line CL1. A novel procedure to obtain useful antibodies is also proposed to immunize mice with proteins in tumor tissue preparations. Tumor heterogeneity could be attributed to multiple cancer cell types: Gleason pattern 3 vs. Gleason pattern 4;CD10- vs. CD10+. Differentially expressed genes among these cell types are useful as risk assessment markers because pattern 4 and CD10+ cancer cells are associated with poor outcomes. In addition, markers could be derived from differentially expressed genes of tumor-associated stromal cells. One example is the ~29 kDa CD90/THY1 protein found released into tumor tissue preparations. A multi-marker analysis tool, multiple reactions monitoring (MRM) mass spectrometry, is being developed to measure multiple informative proteins simultaneously in urine. Cell transcriptomes allow the development of cancer cell type- specific signatures that consist of genes and their abundance (in transcript counts). These can be applied to diagnose tumors for the presence of specific cancer cell types, which will then provide prognostic information.

Public Health Relevance

Biomarkers are important for detecting cancer early when it is more treatable. They are also important for risk assessment so that patients can be stratified for different types of treatment. The informative biomarkers are the genes and proteins expressed by the different cell types in tumors. For prostate and bladder cancer testing for these markers in voided urine provides a very non-invasive means of cancer diagnosis.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA111244-08
Application #
8336904
Study Section
Special Emphasis Panel (ZCA1-SRLB-C (M1))
Program Officer
Kagan, Jacob
Project Start
2004-09-22
Project End
2015-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
8
Fiscal Year
2012
Total Cost
$445,763
Indirect Cost
$137,153
Name
University of Washington
Department
Urology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Shi, Tujin; Quek, Sue-Ing; Gao, Yuqian et al. (2017) Multiplexed targeted mass spectrometry assays for prostate cancer-associated urinary proteins. Oncotarget 8:101887-101898
Ahmad, Rumana; Nicora, Carrie D; Shukla, Anil K et al. (2016) An efficient method for native protein purification in the selected range from prostate cancer tissue digests. Chin Clin Oncol 5:78
Vitello, Elizabeth A; Quek, Sue-Ing; Kincaid, Heather et al. (2016) Cancer-secreted AGR2 induces programmed cell death in normal cells. Oncotarget 7:49425-49434
Ho, Melissa E; Quek, Sue-Ing; True, Lawrence D et al. (2016) Bladder cancer cells secrete while normal bladder cells express but do not secrete AGR2. Oncotarget 7:15747-56
Alavi, Mohammed; Mah, Vei; Maresh, Erin L et al. (2015) High expression of AGR2 in lung cancer is predictive of poor survival. BMC Cancer 15:655
Quek, Sue-Ing; Wong, Olivia M; Chen, Adeline et al. (2015) Processing of voided urine for prostate cancer RNA biomarker analysis. Prostate 75:1886-95
Shi, Tujin; Gao, Yuqian; Quek, Sue Ing et al. (2014) A highly sensitive targeted mass spectrometric assay for quantification of AGR2 protein in human urine and serum. J Proteome Res 13:875-82
Shi, Tujin; Sun, Xuefei; Gao, Yuqian et al. (2013) Targeted quantification of low ng/mL level proteins in human serum without immunoaffinity depletion. J Proteome Res 12:3353-61
Shi, Tujin; Fillmore, Thomas L; Gao, Yuqian et al. (2013) Long-gradient separations coupled with selected reaction monitoring for highly sensitive, large scale targeted protein quantification in a single analysis. Anal Chem 85:9196-203
Ho, Melissa E; Quek, Sue-Ing; True, Lawrence D et al. (2013) Prostate cancer cell phenotypes based on AGR2 and CD10 expression. Mod Pathol 26:849-59

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