In the previous work of this RP, we discovered that global patterns of DNA copy number alterations (CNAs) in primary tumors were strongly associated with recurrence after radical prostatectomy. In this renewal we aim to determine the value of CNAs for predicting prostate cancer metastasis and death in men managed conservatively (Aim 3). In order to do so, we need to develop technology to measure CNAs in biopsy samples (Aim 2). We also need to refine our initial model of CNAs, which was developed using biochemical recurrence as an endpoint (Aim 1). By creating a CNA model in Aim 1 and testing it on an independent population sample in Aim 3, this research project will serve as a rigorous test of our CNA hypothesis, and fulfill the SPORE's goal for investigations into population science.
In Aim 1, we will further refine and confirm our initial model of CNAs, using metastasis and death from prostate cancer as endpoints rather than recurrence. We will also test the feasibility of using formalin-fixed paraffin-embedded tissue samples rather than frozen (as used in our prior CNA research).
In Aim 2, we will develop a """"""""miniaturized"""""""" CNA assay that can be conducted on a prostate biopsy sample by (a) determining the genomic regions that carry the most prognostic impact;(b) developing a miniaturized CNA detection platform to identify those regions, and (c) evaluating the concordance of CNA data between biopsy and radical prostatectomy samples, to establish the feasibility of our new assay.
In Aim 3, we will test the assay's success in predicting patient outcomes, using tissue samples from a large cohort of men whose prostate cancer was treated conservatively, and for whom we have a median 15-year follow-up. We are aiming to produce a biomarker which could be used to supply enough information to aid in the choice of Initial treatment, and thus ultimately reduce death from prostate cancer while also reducing unnecessary treatment of prostate cancer.

Public Health Relevance

Men newly diagnosed with low-risk prostate cancer must choose between active surveillance or aggressive curative treatment. The current methods for assessing risk level (ie, Gleason grade, PSA, and clinical stage) have limited accuracy, prompting many patients to choose aggressive treatment and thus leading to overtreatment In the population. Analyzing CNA patterns in tumor samples may provide prognostic value.

National Institute of Health (NIH)
National Cancer Institute (NCI)
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Special Emphasis Panel (ZCA1)
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