Bioinformatic Analysis and Validation of Novel Urinary Biomarkers for Bladder Cancer and Prostate Cancer
| dc.contributor.advisor | Mohan, Chandra | |
| dc.contributor.committeeMember | Wu, Tianfu | |
| dc.contributor.committeeMember | Zhang, Yingchun | |
| dc.creator | Castillo, Jessica Ashley | |
| dc.date.accessioned | 2023-01-01T23:02:53Z | |
| dc.date.created | August 2022 | |
| dc.date.issued | 2022-08-09 | |
| dc.date.updated | 2023-01-01T23:02:54Z | |
| dc.description.abstract | Urological cancers, including bladder cancer and prostate cancer are highly prominent cancers diagnosed both globally and in the United States alone. Bladder and prostate cancer rank among the top 10 most common cancers worldwide. Both cancers currently have assays approved by the United States Food and Drug Administration. However, they cannot be used as the sole measure of diagnosis and surveillance due to low specificity values and false positives. As a result, there is a need for better biomarkers for both bladder and prostate cancer. In this study, an aptamer-based SOMAscan screening was conducted of 1,317 unique proteins using urine samples from a bladder cancer, prostate cancer, and a urological control cohort. Analysis of the data identified both significant and significantly upregulated proteins. Multiple machine learning techniques identified highly discriminatory proteins. Functional pathway enrichment identified significant processes, functions, and pathways associated with each cancer. Regulatory molecules of each cancer were also identified. Following analysis, bladder cancer urine proteins of interest were validated by an enzyme-linked immunosorbent assay (ELISA) in two independent cohorts of differing ethnicity. In total, 21 urine proteins significantly discriminated bladder cancer from urology controls. Nine urine proteins distinguished bladder cancer stage T1-T4 from stage Ta-Tis. Novel proteins of prostate cancer were also identified for further validation through the use of data analysis and machine learning techniques. The study aims to successfully identify novel urinary biomarkers of both bladder and prostate cancer through the use of an aptamer-based SOMAscan, data analysis measures, including machine learning techniques, and ELISAs. Further validation may aid in early diagnosis, surveillance, and long-term survival of those with bladder and prostate cancer. The work done can potentially pave the way to engineering point-of-care tests for both bladder and prostate cancer. | |
| dc.description.department | Biomedical Engineering, Department of | |
| dc.format.digitalOrigin | born digital | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/10657/13249 | |
| dc.language.iso | eng | |
| dc.rights | The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s). | |
| dc.subject | Biomarkers | |
| dc.subject | Bladder cancer | |
| dc.subject | Prostate cancer | |
| dc.title | Bioinformatic Analysis and Validation of Novel Urinary Biomarkers for Bladder Cancer and Prostate Cancer | |
| dc.type.dcmi | Text | |
| dc.type.genre | Thesis | |
| dcterms.accessRights | The full text of this item is not available at this time because the student has placed this item under an embargo for a period of time. The Libraries are not authorized to provide a copy of this work during the embargo period. | |
| local.embargo.lift | 2024-08-01 | |
| local.embargo.terms | 2024-08-01 | |
| thesis.degree.college | Cullen College of Engineering | |
| thesis.degree.department | Biomedical Engineering, Department of | |
| thesis.degree.discipline | Biomedical Engineering | |
| thesis.degree.grantor | University of Houston | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science in Biomedical Engineering |