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Vaccine and immunomodulatory strategies to target the cancer mutanome

Vaccine and immunomodulatory strategies to target the cancer mutanome
Vaccine and immunomodulatory strategies to target the cancer mutanome
Cancers are characterised by uncontrolled cell growth driven primarily by acquired somatic mutations in the genome. Antigens derived from these mutations may be ideal targets for cancer immunotherapy as they induce a tumour-specific immune response in patients. The cancer mutanome has been successfully targeted using peptide and RNA vaccines in preclinical models and promising results from trials in patients are also emerging. Here we explore the use of DNA vaccines, a more stable and malleable antigen delivery system, to induce immune responses against mutanome-derived antigens. We have developed a translatable bioinformatics pipeline to identify targetable mutations in solid and haematological tumours with a low neoantigen load. We first demonstrated the use of DNA-based vaccines to target mutanome-derived neoantigens in a murine model of HNSCC (TC-1), where we induced tumour-specific T-cell responses that resulted in improved survival and delayed tumour progression. We also demonstrated the successful induction of mutanome-specific T-cell responses in a murine model of MM (5T33) and used our bioinformatics pipeline to identify targetable mutations in an index myeloma patient. In addition to mutated neoantigens, we have also examined the scope of targeting CTA at different stages in MM and have interrogated the integrity of antigen processing and presentation machinery to help stratify patients for cancer vaccination. The work described in this thesis adds to our growing understanding of cancer vaccination, especially in the context of low tumour mutation burden.
University of Southampton
Short, Cinderella Claudia
88411dcb-ea57-49eb-98eb-d04aaa1e4383
Short, Cinderella Claudia
88411dcb-ea57-49eb-98eb-d04aaa1e4383
Savelyeva, Natalia
804c3e15-d260-4717-9b7c-15c16ba87fc7

Short, Cinderella Claudia (2022) Vaccine and immunomodulatory strategies to target the cancer mutanome. University of Southampton, Doctoral Thesis, 285pp.

Record type: Thesis (Doctoral)

Abstract

Cancers are characterised by uncontrolled cell growth driven primarily by acquired somatic mutations in the genome. Antigens derived from these mutations may be ideal targets for cancer immunotherapy as they induce a tumour-specific immune response in patients. The cancer mutanome has been successfully targeted using peptide and RNA vaccines in preclinical models and promising results from trials in patients are also emerging. Here we explore the use of DNA vaccines, a more stable and malleable antigen delivery system, to induce immune responses against mutanome-derived antigens. We have developed a translatable bioinformatics pipeline to identify targetable mutations in solid and haematological tumours with a low neoantigen load. We first demonstrated the use of DNA-based vaccines to target mutanome-derived neoantigens in a murine model of HNSCC (TC-1), where we induced tumour-specific T-cell responses that resulted in improved survival and delayed tumour progression. We also demonstrated the successful induction of mutanome-specific T-cell responses in a murine model of MM (5T33) and used our bioinformatics pipeline to identify targetable mutations in an index myeloma patient. In addition to mutated neoantigens, we have also examined the scope of targeting CTA at different stages in MM and have interrogated the integrity of antigen processing and presentation machinery to help stratify patients for cancer vaccination. The work described in this thesis adds to our growing understanding of cancer vaccination, especially in the context of low tumour mutation burden.

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Published date: May 2022

Identifiers

Local EPrints ID: 475908
URI: http://eprints.soton.ac.uk/id/eprint/475908
PURE UUID: 41c919e5-08f0-467e-981a-27a5eed79de4

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Date deposited: 30 Mar 2023 16:38
Last modified: 17 Mar 2024 01:20

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Contributors

Author: Cinderella Claudia Short
Thesis advisor: Natalia Savelyeva

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