Spectroscopy and spectrometry approaches to elucidating the anti-cancer immune response
Lead Research Organisation:
Swansea University
Department Name: Institute of Life Science Medical School
Abstract
Hypothesis: Tissue scanning Raman spectroscopy and mass spectrometry imaging coupled to biological informatics can reveal functional differences in immune checkpoint pathways and their role in the tumour microenvironment.
Objectives: 1. To use Raman spectroscopy and biological informatics of single cancer and immune cells to prepare an atlas of characteristic immune checkpoint molecular and chemical signatures. 2. To use this atlas to identify the immune checkpoints active in tumour tissue by adopting a combined Raman imaging and mathematical biology approach. 3. To use mass spectrometry imaging to annotate the Raman-generated spectral fingerprint from tumour tissues on a cell-by-cell basis.
Overview: This project proposes the use of tissue scanning and imaging modalities - specifically Raman spectroscopy and mass spectrometry - to elucidate key molecular and chemical pathways operational within tumour tissue that can be aligned to specific immune checkpoint strategies co-opted to counteract any beneficial anti-cancer immune response. The overarching goal is to overcome the limitations of the need to disrupt tumour tissue to understand cellular and chemical interactions between cancer, immune and other cells. This would improve our understanding of the role of the tumour microenvironment in regulating the anti-tumour immune response for detrimental or beneficial effect. Tissue scanning and imaging techniques coupled to biological informatics will enable the whole tissue section approach proposed here. By providing information about the spatial relationship of cells and the molecular and cellular pathways active within intact tumour tissue from patients with pancreatic cancer, new approaches to the design and development of immunotherapeutics can be pursued. Additional to the scanning/imaging and bioinformatic techniques proposed, complementary cellular, molecular and chemical analysis approaches will be used. Firstly, a mathematical biology approach will be used to create an atlas of response patterns linked to activation of different immune checkpoint pathways. These measures will be generated in vitro using cancer cell lines and primary human T cells interrogated with Raman spectroscopy and data processed using AI-based machine learning strategies. This atlas will then be used to inform analysis and interpretation of data from tumour tissue sections interrogated using scanning/imaging Raman spectroscopy to detect active immune checkpoint pathways in tumours ex vivo. This is a novel use for Raman spectroscopy. Identification and annotation of pathway components will be made by mass spectrometry imaging. The spatial alignment of Raman spectroscopy and mass spectrometry data from tissue sections can only be achieved through an AI-based bioinformatic approach. The Raman spectroscopy atlas generated as pivotal to this project will be disseminated for use by other investigators and could be applied to a wider variety of solid tumour types beyond pancreatic cancer as to be studied here.
Outcomes: The proposed project will enhance our understanding of the anti-tumour capacity of the tumour microenvironment to inform developments in immunotherapy and precision medicine. It will exploit analytical science approaches that have their foundations in the physical sciences and now are utilised at the interface between chemical biology and clinical technologies.
EPSRC Research Areas
Analytical science
Biological informatics
Chemical biology and biological chemistry
Clinical technologies
Mathematical biology
Objectives: 1. To use Raman spectroscopy and biological informatics of single cancer and immune cells to prepare an atlas of characteristic immune checkpoint molecular and chemical signatures. 2. To use this atlas to identify the immune checkpoints active in tumour tissue by adopting a combined Raman imaging and mathematical biology approach. 3. To use mass spectrometry imaging to annotate the Raman-generated spectral fingerprint from tumour tissues on a cell-by-cell basis.
Overview: This project proposes the use of tissue scanning and imaging modalities - specifically Raman spectroscopy and mass spectrometry - to elucidate key molecular and chemical pathways operational within tumour tissue that can be aligned to specific immune checkpoint strategies co-opted to counteract any beneficial anti-cancer immune response. The overarching goal is to overcome the limitations of the need to disrupt tumour tissue to understand cellular and chemical interactions between cancer, immune and other cells. This would improve our understanding of the role of the tumour microenvironment in regulating the anti-tumour immune response for detrimental or beneficial effect. Tissue scanning and imaging techniques coupled to biological informatics will enable the whole tissue section approach proposed here. By providing information about the spatial relationship of cells and the molecular and cellular pathways active within intact tumour tissue from patients with pancreatic cancer, new approaches to the design and development of immunotherapeutics can be pursued. Additional to the scanning/imaging and bioinformatic techniques proposed, complementary cellular, molecular and chemical analysis approaches will be used. Firstly, a mathematical biology approach will be used to create an atlas of response patterns linked to activation of different immune checkpoint pathways. These measures will be generated in vitro using cancer cell lines and primary human T cells interrogated with Raman spectroscopy and data processed using AI-based machine learning strategies. This atlas will then be used to inform analysis and interpretation of data from tumour tissue sections interrogated using scanning/imaging Raman spectroscopy to detect active immune checkpoint pathways in tumours ex vivo. This is a novel use for Raman spectroscopy. Identification and annotation of pathway components will be made by mass spectrometry imaging. The spatial alignment of Raman spectroscopy and mass spectrometry data from tissue sections can only be achieved through an AI-based bioinformatic approach. The Raman spectroscopy atlas generated as pivotal to this project will be disseminated for use by other investigators and could be applied to a wider variety of solid tumour types beyond pancreatic cancer as to be studied here.
Outcomes: The proposed project will enhance our understanding of the anti-tumour capacity of the tumour microenvironment to inform developments in immunotherapy and precision medicine. It will exploit analytical science approaches that have their foundations in the physical sciences and now are utilised at the interface between chemical biology and clinical technologies.
EPSRC Research Areas
Analytical science
Biological informatics
Chemical biology and biological chemistry
Clinical technologies
Mathematical biology
