Improving Prostate Cancer Outcome Prediction Through Noninvasive exRNA Assessment

Abbreviated Name: PASS: Ref Set App: Cooperberg miRNA (2018)

Protocol ID: 445

Lead Investigator: Carroll, Peter R. — University of California San Francisco

Coordinating Investigator:

No coordinating investigator defined.

Involved Investigator Sites:

Carroll, Peter R. — University of California San Francisco

Biomarker Name:

Design: No design specified.

Field(s) of Research: Genomics

Collaborative Group: Prostate and Urologic Cancers Research Group

Phased Status: 2

Abstract:

Our goal is to identify and validate across multiple clinical scenarios a novel circulating biomarker signature that can refine patient stratification, enabling the delivery of aggressive interventional therapy to the subset of patients who are most likely to benefit. We hypothesize that plasma micro-RNAs (miRNA) will help identify such patients. Recently published data from others and us strongly support this hypothesis.4 Importantly, due to their relatively long half-lives, miRNA provide a less noisy signature than messenger RNA; and plasma is less susceptible to sampling error than tissue.

Aims: The objective of this aim is to leverage this remarkable resource to follow plasma miRNAs during the course of observation. In PASS, plasma samples have been collected every 6 months for the whole cohort. We hypothesize that we will be able to validate the miRNA signature at diagnosis and/or during the course of AS to predict disease course and thus identify the subset of patients that will eventually show clear disease progression. To explore this hypothesis, we will measure miRNAs in semiannual plasma specimens over a 2.5 year period. To our knowledge, this study would be the first time in any cancer where consecutive miRNA measurements are made to follow a disease course. The rationale for performing such a study is that successful identification of a signature could alter treatment course. One exciting possibility is that such a signature could allow the intensity of surveillance to be customized, specifically allowing many men to minimize the frequency of follow-up via invasive and expensive biopsies. Conversely, earlier detection of progression could lead to intervention before the disease becomes incurable.

Analytic Method:

Comments: Cooperberg is the actual PI

Biomarkers:

There are currently no biomarkers annotated for this protocol.

Datasets:

No datasets are currently associated with this protocol.