The components contributing to cancer progression, especially the transition from early to invasive are unknown. Consequently, the biological reasons are unclear as to why some patients diagnosed with atypia and ductal carcinoma in situ (DCIS) never progress into invasive breast cancer. The “one gene at a time” approach does not sufficiently predict progression. To elucidate the early stage progression to invasive ductal cancer, expression signature of transcripts and transposable elements in micropunched samples of formalin-fixed, paraffin embedded (FFPE) tissue was conducted. A bioinformatics pipeline to analyze poor quality, short reads (>36 nts) from RNA-Seq data was created to compare the most common tools for alignment and differential expression. Most samples from patients prepared for RNA-seq analysis are acquired through archived FFPE tissue collections, which have low RNA quality. The pipeline analytics revealed that STAR alignment software outperformed others. Furthermore, our comparison revealed both DESeq2 and edgeR, with the estimateDisp function applied, both perform well when analyzing greater than 12 replicates. Transcriptome analysis revealed progressive diversification into known oncogenic pathways, a few novel biochemical pathways, in addition to antiviral and interferon activation. Furthermore, the transposable element (TE) signature during breast cancer progression at early stages indicated long terminal repeat (LTRs) as the most abundantly differentially expressed TEs. LTRs belong to endogenous retroviruses (ERV), a subclass of TEs. The retroviral and innate immune response activity in DCIS, which indirectly corroborates the increase in ERV expression in this pre-malignant stage. Finally, to demonstrate the potential role of TEs in the transition from pre-malignant to malignant breast cancer we used pharmacological approaches to alter global TE expression and inhibit retrotransposition activity in control and breast cancer cell lines. It was expected that dysregulation of TEs be associated with increased invasiveness and growth. However, our results indicated that DNA methyltransferase inhibitor 5-Azacytidine (AZA) consistently retarded cell migration and growth. While unexpected, these findings corroborate recent studies that AZA may induce an interferon response in cancer via increased ERV expression. This body of work illustrates the importance of understanding bioinformatics methods used in RNA-seq analysis of common clinical samples. These studies suggest the potential for TEs as biomarkers for disease progression and novel therapeutic approach to investigate in additional model systems.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-9097 |
| Date | 25 April 2019 |
| Creators | Raplee, Isaac D. |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
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