Identification of modulatory functions of TP53, estrogen signaling, and 14q32.31 miRNA cluster on CHRNA5 knock-down expression profile and development of syneRgy APP
Date
Authors
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Print ISSN
Electronic ISSN
Publisher
Volume
Issue
Pages
Language
Type
Journal Title
Journal ISSN
Volume Title
Attention Stats
Usage Stats
views
downloads
Series
Abstract
Cholinergic receptor subunit alpha 5 (CHRNA5) is a ligand-gated ion channel expressed in not only the nervous system but also other tissues. Differential expression and the polymorphisms of CHRNA5 have been associated with addiction, particularly nicotine and various cancer types. The tumor-suppressive properties of CHRNA5 depletion, i.e., decrease in cell proliferation, induction of DNA damage response, and drug sensitivity, have been identified in breast cancer cell lines. This thesis focuses on identifying critical factors modulating or modulated by the knock-down of CHRNA5 in breast cancer cell lines using both wet-lab and bioinformatics approaches. Here I have first found the significant correlation between CHRNA5 and DNA damage response in breast cancer tumor datasets. Moreover, I discovered that the introduction of siTP53 antagonized the actions of siCHRNA5 and reverted the siCHRNA5-mediated cell cycle inhibition and drug sensitivity in the MCF7 breast cancer cell line.
Furthermore, siCHRNA5 was found to inhibit the secondary signaling of estrogen/ESR1 in time and dosage-dependent manners. CHRNA5 depletion also downregulated the conserved 14q32.31 miRNA cluster expression. Among those miRNAs, miR495-3p appeared to be the most prominent candidate, exhibiting a similar expression profile with selective estrogen degraders and partially with siCHRNA5. However, the inhibitory effect of the combinatorial treatment with siCHRNA5 and miR495-3p on the secondary targets of estrogen signaling indicated that siCHRNA5 and miR495-3p might target converging pathways, evidenced by the antagonism (rather than addictiveness) between them.
In addition, the Shiny-based syneRgy app was developed to analyze the transcriptome-based synergy between treatments and/or genetic modifications. As a case study, syneRgy analysis using novel MDM2 inhibitor and/or temozolomide treated neuroblastoma cell lines revealed that although the tumor-suppressor effect of combination therapy was more than each individual treatment, it was less than additive. syneRgy was applied to understand the combinatorial treatment of siCHRNA5 with siTP53 as well as siCHRNA5 with miR495-3p mimic and enhanced our understanding of the TFs that might have a role in the crosstalk. To our knowledge, syneRgy is the first-ever online tool to perform statistical synergy analysis using RNAseq count or logFC transcriptomic data and synreg, i.e. our novel methodology allowing for statistical tests of TF target enrichment using regression models.