Ayse Cemek

Date of Award

2024

Document Type

Thesis

Degree Name

Bachelors

Department

Natural Sciences

First Advisor

Walstrom, Katherine

Area of Concentration

Biochemistry with Computer Science

Abstract

Prostate cancer (PCa) is the most commonly diagnosed cancer for men worldwide. According to the National Cancer Institute, in 2020 alone, 3,343,976 men were diagnosed with PCa in the United States, with an estimated death rate of 34,700 per year, and the estimated number of new diagnosed cases being 288,300 in 2023. Currently, the prostate-specific antigen (PSA) test is the main method of screening for PCa: a blood sample is taken to measure levels of a protein that is generated by both healthy and cancerous cells of the prostate gland. However, the PSA test is not PCa-specific, but instead prostate gland-specific, which results in many inaccurate diagnoses of PCa. Additionally, depending on the age of the individual, PSA levels can be elevated even when no PCa is present, resulting in high false-positive rates. Because of this, a positive PSA test is usually followed by a tissue biopsy to confirm the diagnosis of PCa. Given the heterogeneity of PCa, biopsies can be imprecise and may result in complications. These biopsies are used to stratify patients into PCa risk groups based on Gleason score, stage, and prostate-specific antigen (PSA) levels and guide PCa treatment based on the risk for recurrence and metastases. In the era of precision medicine, there is a compelling need for more precise, minimally invasive methods such as liquid biopsies to improve the prediction of who may be at risk for recurrence or progression at diagnosis, during, and following treatment. Liquid biopsies, which can detect nucleic acids in plasma or serum, hold great promise for determining the risk for recurrence and metastatic spread in cancer patients. For many cancers, it has been hypothesized that increasing levels of circulating cell-free (ccf) DNA may be associated with adverse outcomes. Therefore, the objective of this study was to determine whether ccfDNA quantity was associated with the PCa risk group. Our methods included isolating ccfDNA from serum, determining the quantity in each sample over time, and performing descriptive, inferential, and associational statistical analyses to determine its association with the risk group. Specifically, PCa patients who were eligible for the study volunteered to have their blood taken for pre-radiation therapy as well as 2 and 4 weeks after the radiation therapy. Our results indicated that increasing ccfDNA quantity was not associated with a PCa risk group.

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