Glycoprotein Biomarkers for the Early Detection of Aggressive Prostate Cancer
No involved investigator sites defined.
The Early Detection Research Network of the NCI is charged with the discovery, development and validation of biomarkers for early detection and prognosis related to neoplastic disease. Our laboratory is an NCI EDRN (U01CA152813) working on "Glycoprotein biomarkers for the early detection of aggressive prostate cancer". This EDRN administratiVE! supplement is a collaboration with Robert Veltri on his project to identify men with very low risk (indolent) prostate cancer (CaP) at the diagnostic biopsy at selection for active surveillance (AS). We will assess biopsy tissue using quantitative nuclear histomorphometric measurements and molecular biomarkers to predict an unexpected catastrophic CaP in such men with indolent CaP. At Johns Hopkins Hospital w1e use the Epstein criteria that includes; PSA density (PSAD) <0.15 ng/mVcm3, Gleason score SS, S2 cons involved with cancer, and ::;;SO% of any core involved with cancer to select AS. Our approach will study 140 AS men (70 with a expected outcome and 70 with a disastrous outcome) using nuclear histomorphometry and pre-qualified biomarkers quantified by digital microscopy. Previously, our laboratory combined measurements of DNA content and (-2)pPSA in the serum and (-5,-?)pPSA in biopsy tissue to identify 7/10 men that would fail surveillance based on the primary diagnostic biopsy. We now will devHiop a clinical, morphological and biomarker 'signature' for identifying severe aggressive disease from a AS diagnostic biopsy. Our approach will combine nuclear morphometry measured by digital microscopy with a unique biopsy tissue biomarker profile (DNA content, Ki67, Her2neu, CACND1 and periostin). Fcr the molecular targets we will use a multiplex tissue blot (MTB) immunohistochemistry method. The Aims o'f our work include 1) to utilize retrospective archival biopsy material from 70 AS cases where the outcome was unexpected and disastrous and collect an equal number of AS cases (n=140) and perform assays for morphology and biomarker targi ts proposed, 2) and predict failure using Cox proportional hazards statistical modeling.
There are currently no biomarkers annotated for this protocol.
No datasets are currently associated with this protocol.