51
IRUS Total
Downloads

Assessing the safety profile of antisense therapeutics through a novel computational and analytical framework

File Description SizeFormat 
Kamola-PJ-2015-PhD-Thesis.pdfThesis2.9 MBAdobe PDFView/Open
Title: Assessing the safety profile of antisense therapeutics through a novel computational and analytical framework
Authors: Kamola, Piotr
Item Type: Thesis or dissertation
Abstract: With many safety and technical limitations partly mitigated through chemical modifications, antisense oligonucleotides (ASOs) are gaining recognition as therapeutic entities. The increased potency realised by ‘third generation chemistries’ may, however, simultaneously increase affinity to unintended targets with partial sequence complementarity. Hybridisation-dependent off-target effects (OTEs), a risk historically regarded as low, are not being adequately investigated. My data shows an unexpectedly high OTEs confirmation rate for locked nucleic acid gapmer ASOs, showing a wide range of mismatch (MM) and gap patterns. Critically, hybridisation predicted against intronic regions of pre-mRNAs was tested and confirmed. This dramatically increases the ASO-binding landscape which, together with the high potency of such interactions, is a serious safety concern. OTEs were also found to translate in vivo in the mouse and highly correlate with observed hepatotoxcity. With base pairing-driven target recognition it is possible to predict the putative off-targets and a novel software pipeline (‘RNArcher’) was developed to address several challenges faced during ASO drug discovery. While the presence of chemical modifications limited the thermodynamics analysis of ASOs, the concept was applied to siRNAs. A correlation was found between the sequence composition of siRNA non-seed region (and its target sites) and seed-dependent OTEs that can be used to increase specificity of this modality. Overall, the hybridisation-mediated exonic and intronic OTEs are a significant safety concern for ASOs with 3rd generation chemistry. The ASO and siRNA-based guidelines and computational solutions developed throughout this project will aid the community in designing more specific molecular biology tools and safer therapeutics.
Content Version: Open Access
Issue Date: Sep-2015
Date Awarded: Nov-2015
URI: http://hdl.handle.net/10044/1/61019
DOI: https://doi.org/10.25560/61019
Supervisor: Gooderham, Nigel
Sponsor/Funder: Engineering and Physical Sciences Research Council
GlaxoSmithKline
Funder's Grant Number: EP/J502017/1
Department: Department of Surgery & Cancer
Publisher: Imperial College London
Qualification Level: Doctoral
Qualification Name: Doctor of Philosophy (PhD)
Appears in Collections:Department of Surgery and Cancer PhD Theses



Unless otherwise indicated, items in Spiral are protected by copyright and are licensed under a Creative Commons Attribution NonCommercial NoDerivatives License.

Creative Commons