Bai, Yulong
(2023)
Elucidating the role of alternative polyadenylation in cancer by integrated transcriptomic analysis.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Alternative polyadenylation (APA) is an essential messenger RNA (mRNA) maturation mechanism that causes nascent transcripts from the same gene to have distinct lengths of 3' untranslated region (3' UTR). While widespread APA events have been reported in several types of cancer, its role in post-transcriptional regulation remains unclear. This dissertation aims to address two challenges to improve our understanding of the role of APA in cancer.
The first challenge is to quantify APA events specific to each cell type faithfully. In this dissertation, we developed scMAPA to improve current cell-type-specific APA identification in several aspects. First, scMAPA is compatible with both types of scRNA-Seq techniques, 3' captured and full-length, by formulating a change-point detection problem. Second, the APA gene identification module of scMAPA can adjust for undesired sources of variation, which potentially introduces noise to the identification of cell-type-specific APA genes. Third, in our novel simulation pipeline and data derived from biological samples, scMAPA outperformed existing methods in sensitivity and robustness of APA gene identification and accuracy of pA site detection.
For the second challenge, although previous studies have demonstrated the association between APA and cancer hallmarks, it is unclear through what molecular mechanism APA contributes to cancer regulation. By utilizing our published bioinformatics tool, PRIMATA-APA, we conducted the first pan-cancer analysis to computationally characterize the APA-mediated microRNA target site profiles in diverse cancer types. Findings from the pan-cancer analysis demonstrated that our novel feature, number of miRNA target sites (numTS), successfully classified tumors by their cancer type, whereas miRNA and mRNA profiles were inaccurate in distinguishing the same samples. We also extended PRIMATA-APA with a biomarker training module and a feature selection module. Through these modules, we demonstrated that numTS of selected miRNAs could be an effective biomarker for various cancer hallmarks, including immune and proliferation status, tumor-infiltrating immune cell abundance, and overall survival.
The bioinformatics tools presented in this dissertation advanced our understanding of APA in post-transcriptional regulation. These results highlight the role of APA in cancer and provide insights into the potential clinical application of miRNA biomarkers in cancer treatment, making this study of public health significance.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
9 May 2023 |
| Date Type: |
Publication |
| Defense Date: |
9 January 2023 |
| Approval Date: |
9 May 2023 |
| Submission Date: |
22 January 2023 |
| Access Restriction: |
2 year -- Restrict access to University of Pittsburgh for a period of 2 years. |
| Number of Pages: |
133 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Public Health > Human Genetics |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Alternative Polyadenylation, single-cell RNA-Sequencing, miRNA binding activity, Post-transcriptional regulation |
| Related URLs: |
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| Date Deposited: |
10 May 2023 01:33 |
| Last Modified: |
10 May 2023 01:33 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/44131 |
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