Al-Omari, A, 2019. Identification of distinct markers to differentiate natural and induced T regulatory cells in cancer. PhD, Nottingham Trent University.
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Abstract
Regulatory T cells (Tregs) are a distinct subset of CD4+ T cells that play a vital role in maintaining immune homeostasis and peripheral tolerance, thereby preventing autoimmunity. Tregs are generally categorised into two main subsets; natural and induced Tregs. In cancer, Tregs are found extremely enriched in the tumour microenvironment and contribute to the inhibition of anti-tumour response and tumour progression. The origin of tumour-infiltrating Tregs (whether it is nTregs or iTregs) is still enigmatic, since there are no distinct biomarkers which can differentiate between the two subsets. Therefore, the aim of this study is to identify cell surface biomarkers that can differentiate phenotypic features of iTregs from nTregs in the context of cancer. With this aim, an in vitro murine model was successfully developed to generate CD4+CD25++Foxp3+ iTregs from purely sorted naïve CD4+CD25-Foxp3- T cells in the presence of TGF-β1. The induction of iTregs was assessed using flow cytometry. Methylation status of Foxp3-TSDR and Foxp3 stability was assessed. Naïve CD4+CD25-Foxp3- T cells and CD4+CD25+Foxp3+ nTregs were purely sorted using cell sorting. Five biologically different subsets of CD4+ cells including naïve CD4+CD25-Foxp3- T cells, activated CD4+CD25-Foxp3- T cells, naïve CD4+CD25+Foxp3+ nTregs, activated CD4+CD25+Foxp3+ nTregs and CD4+CD25++Foxp3+ iTregs were subjected to quantitative proteomic profiling using SWATH-MS. Subcellular fractionation methods were employed to isolate membrane and cytoplasmic proteins from each of the subsets. Quantitative proteomic data were analysed using artificial neural networks. The results revealed that 4 distinct membrane biomarkers (PLP2, ITIH4, HEM6 and MAVS) were differentially upregulated in iTregs compared to other subsets. EPHX1 (HYEP) was identified upregulated only in naïve nTregs and downregulated in iTregs and other subsets. The biomarkers were further tested. Pathway enrichment analysis of iTregs showed a distinct metabolic pathway enrichment in iTregs indicating a mechanistic insight into the iTreg development. Once validated in humans these proteins could be used as a biomarker for iTreg or as a drug target for the selective depletion for better immunotherapeutic outcome in cancer patients.
Item Type: | Thesis |
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Creators: | Al-Omari, A. |
Date: | November 2019 |
Rights: | This work is the intellectual property of the author. You may copy up to 5% of this work for private study, or personal, non-commercial research. Any re-use of the information contained within this document should be fully referenced, quoting the author, title, university, degree level and pagination. Queries or requests for any other use, or if a more substantial copy is required, should be directed in the owner(s) of the Intellectual Property Rights. |
Divisions: | Schools > School of Science and Technology |
Record created by: | Jeremy Silvester |
Date Added: | 05 Jul 2020 21:17 |
Last Modified: | 31 May 2021 15:19 |
URI: | https://irep.ntu.ac.uk/id/eprint/40163 |
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