Biomarkers for Early Detection of Aggressive Prostate Cancer

Abbreviated Name: Aggressive PCa Biomarkers

Protocol ID: 478

Lead Investigator: Liu, Tao — Pacific Northwest National Laboratory

Coordinating Investigator: Liu, Tao — Pacific Northwest National Laboratory

Involved Investigator Sites:

Chesnut, Gregory — Center for Prostate Disease Research Uniformed Services University of the Health Sciences and the Walter Reed National Military Medical Center
Feng, Ziding — Fred Hutchinson Cancer Research Center
Liu, Tao — Pacific Northwest National Laboratory

Biomarker Name: AKT1 AMACR ANXA2 AR AURKA BRAF CAMKK2 CCND1 CDN1A CRISP3 EGFR ERG ETV1 EZH2 FGFR1 FOLH1 HIF1A HOXC6 HPN HSPB1 KLK11 KLK2 KLK3 MMP2 MMP9 MUC1 MUC6 MYC MYCN MYO6 NCOA2 NPY ODC1 OR51E2 PDGFRB PIK3CA PLA2G7 RAF1 SERPINI1 SMAD4 SPARC SPINK1 SPP1 STAT3 TFF3 TGFB1 TMPRSS2 TP53 TPM2 TWIST1 VEGFA

Design: No design specified.

Field(s) of Research: Proteomics

Collaborative Group: Prostate and Urologic Cancers Research Group

Phased Status:

Abstract:

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. The objective of this collaborative study is to identify protein biomarkers for early detection of aggressive disease. Such biomarkers have the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance.

Aims: 1. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we will use targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. 2. Protein classifiers will be identified and evaluated with or without combining with existing clinical and pathological standard of care variables to demonstrate significant improvement in predicting distant metastasis or biochemical recurrence, in a training/testing analysis. 3. We will validate the findings in another independent cohort.

Analytic Method: The application of our antibody-independent PRISM-SRM method, which utilizes offline chromatographic separation and “intelligent” fraction selection via monitoring the heavy isotope-labeled peptide internal standards, allows for much higher sample loading (e.g., 70-fold in the current study), highly effective peptide enrichment, and significantly reduced sample complexity that provided much higher sensitivity and is thus well suited for the detection of protein biomarker candidates in a broad concentration range. Using synthetic peptides with and without heavy isotope labeling of C-terminal lysine or arginine, highly sensitive, precise, and multiplex PRISM-SRM assays were developed in our laboratory using procedures we previously established.

Comments:

Biomarkers:

Datasets:

No datasets are currently associated with this protocol.