DOI

https://doi.org/10.25772/GT2Q-MW21

Defense Date

2015

Document Type

Thesis

Degree Name

Master of Science

Department

Biochemistry

First Advisor

Zendra Z. Zehner

Second Advisor

Michael W. Holmes

Third Advisor

Carmen Sato- Bigbee

Abstract

Prostate cancer is the most common noncutaneous cancer among men, yet current diagnostic methods are insufficient and more reliable diagnostic markers need to be developed. The answer that can bridge this gap and enable more efficient diagnoses may lie in microRNAs. These small, single stranded RNA molecules impact protein expression at the translational level and regulate important cellular pathways. Dysregulation of these small RNA molecules can have tumorigenic effects on cells and lead to many types of cancers.

Currently the Prostate-Stimulating Antigen (PSA) is used as a diagnostic marker for prostate cancer. However, many factors can elevate PSA levels such as infections and certain medications, consequently leading to false positive diagnoses and unnecessary concern and over treatment with dire outcomes for the patient. Even worse, are the chances of false negative diagnoses, which result in prostate cancer not being diagnosed until its later stages. Therefore, although the use of the PSA level has had its uses in the clinic, it has failed to sufficiently bridge the gap or to distinguish indolent from aggressive disease.

It has long been suggested in the literature that microRNAs are drastically altered throughout the course of cancer progression. Here, RNA sequencing was used to identify changes in miR expression profiles diagnostic for prostate cancer patients compared to non-patient controls. The RNA sequencing results were also used to identify normalization miRs to be used as endogenous controls. Confirmatory qRT-PCR was then used to corroborate these results for the top seven dysregulated miRs found from the RNA sequencing data. Data analysis of the Area Under the Curve (AUC) of the Receiver Operating Curves (ROC) of the selected miRs exhibited a better correlation with prostate cancer (AUC Range= 0.819- 0.950) than PSA (AUC of PSA=0.667). In summary, a panel of seven miRs are proposed, many of which have prostate specific targets, which would represent a significant improvement over current testing methods.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

8-5-2015

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