Periodic Reporting for period 2 - QuanTII (Quantitative T cell Immunology and Immunotherapy)
Reporting period: 2020-09-01 to 2023-08-31
Health and disease are regulated, to a large extent, by our immune system. The immune system not only protects the body from infectious disease, but is involved in a number of conditions of increasing incidence and morbidity. In cancer, the immune system can be both cause and cure; it contributes to chronic inflammation that promotes tumour development, but it can also provide the ultimate weapon against metastatic disease. Thus, the development of ways to harness, direct or restrain immune responses has great potential for enhancing human health. QuanTII will address the need for new quantitative approaches to query immune cell function in lymphoid organs and tissues by developing novel quantitative methods of (1) the compartmentalisation and dynamics of T cells, (2) T cell receptor (TCR) repertoires in health and disease, in blood and tissues, and (3) T cell immunotherapies. Results from this project will improve our understanding of immunological memory, the variety of immune responses evoked by a single pathogen (immune repertoire), and the molecular and cellular mechanisms at the heart of cancer immunotherapies, such as adoptive cell transfer.
The specific training objectives of QuanTII are to provide an inspiring and supportive environment for the training of 15 ESRs, and to establish a broad programme of challenging research projects that are multidisciplinary and intersectoral, and lead to lasting, fruitful collaboration between ETN partners.
ESRs carried out research projects in immunological memory, immune repertoires, cancer and immunotherapies. Experimental approaches included sequencing and labelling of thymocytes and stem-cell memory T cells. Theoretical approaches included deterministic models of signalling, of T-cell subsets in exhaustion, and of the effect of checkpoint inhibitors. ESRs developed stochastic models of cell division and death, of the correlation structure of cell fates, and of the maintenance of product cell populations from progenitor cells, probabilistic repertoire models and agent-based models of heterogeneous populations. Modern algebraic and statistical techniques including Bayesian analysis were a feature. Once travel restrictions were relaxed, ESRs were able to undertake secondments and attend network meetings again. We are grateful that all QuanTII academic and industrial partners remained with the network from start to finish, participating in supervision of training and research, organising network events and hosting secondments.
The specific training objectives of QuanTII are to provide an inspiring and supportive environment for the training of 15 ESRs, and to establish a broad programme of challenging research projects that are multidisciplinary and intersectoral, and lead to lasting, fruitful collaboration between ETN partners.
ESRs carried out research projects in immunological memory, immune repertoires, cancer and immunotherapies. Experimental approaches included sequencing and labelling of thymocytes and stem-cell memory T cells. Theoretical approaches included deterministic models of signalling, of T-cell subsets in exhaustion, and of the effect of checkpoint inhibitors. ESRs developed stochastic models of cell division and death, of the correlation structure of cell fates, and of the maintenance of product cell populations from progenitor cells, probabilistic repertoire models and agent-based models of heterogeneous populations. Modern algebraic and statistical techniques including Bayesian analysis were a feature. Once travel restrictions were relaxed, ESRs were able to undertake secondments and attend network meetings again. We are grateful that all QuanTII academic and industrial partners remained with the network from start to finish, participating in supervision of training and research, organising network events and hosting secondments.
ESR 1 performed labelling and sequencing measurements that were analysed to understand the development of T cells from hematopoietic stem cells and thymocytes, and the connection to acute T cell lymphoblastic leukaemia.
ESR 2 was involved in modelling normal and autonomous thymii, seeding rates of thymic progenitors, and Bayesian computation to determine mutation and selection parameters from sequencing data.
ESR 3 has made use of novel algebraic methods to study IL-7R binding models to obtain analytical expressions of the steady state, amplitude and EC50 of the dose response.
ESR 4 obtained murine data from bone marrow and skin, and by studying memory T cells in human and a more natural mouse model they found relations and similarities between both species.
ESR 5 quantified antigen-specific CD8 T memory subpopulations from combined skin and muscle HIV trial vaccine study samples, and found the correlation between the T stem cell memory pool generated at early timepoints and the rate of decay of memory.
ESR 6 studied mathematical models for the cell cycle, with a particular interest in multi-stage representation for cell proliferation via Erlang distributions.
ESR 7 investigated the lifespan and maintenance of memory T cells in human bone marrow and skin, adipose tissues, and blood by using in vivo heavy water labelling.
ESR 8 made improvements to the differential equations models used to estimate the life span of T cells in the human body from heavy-water labelling experiments.
ESR 9 performed an analysis to predict immunogenicity of somatic mutations that arise from different cancer mutation signatures.
ESR 10 developed a stochastic model of T-cell populations in homeostasis including cross-reactivity and multiple self-pMHC complexes.
ESR 11 validated a computational model of TCR probability in the periphery, and also applied the method to B cell receptors to check its wide applicability.
ESR 12 studied the relevance of the iKIR-HLA receptor-ligand system in cancer and autoimmunity and analyse the mechanisms by which iKIRs influence T cells.
ESR 13 considered the maintenance of 'product' cell populations from 'progenitor' cells via a sequence of one or more cell types, or compartments, where each cell's fate is chosen stochastically. ESR 13 defined an ODE model of T-cell exhaustion states and studied structural identifiability.
ESR 14 explored agent-based and stochastic models and their combination with ordinary differential equations, to model heterogeneity of cancer cell populations, the effect of different therapeutic options and the tumour-immune cell interaction. The reinforcement algorithm was employed to optimize parameters.
ESR 15 developed the Cyton2 model, that encapsulates features of inheritance correlation structure of cell fates.
ESR 2 was involved in modelling normal and autonomous thymii, seeding rates of thymic progenitors, and Bayesian computation to determine mutation and selection parameters from sequencing data.
ESR 3 has made use of novel algebraic methods to study IL-7R binding models to obtain analytical expressions of the steady state, amplitude and EC50 of the dose response.
ESR 4 obtained murine data from bone marrow and skin, and by studying memory T cells in human and a more natural mouse model they found relations and similarities between both species.
ESR 5 quantified antigen-specific CD8 T memory subpopulations from combined skin and muscle HIV trial vaccine study samples, and found the correlation between the T stem cell memory pool generated at early timepoints and the rate of decay of memory.
ESR 6 studied mathematical models for the cell cycle, with a particular interest in multi-stage representation for cell proliferation via Erlang distributions.
ESR 7 investigated the lifespan and maintenance of memory T cells in human bone marrow and skin, adipose tissues, and blood by using in vivo heavy water labelling.
ESR 8 made improvements to the differential equations models used to estimate the life span of T cells in the human body from heavy-water labelling experiments.
ESR 9 performed an analysis to predict immunogenicity of somatic mutations that arise from different cancer mutation signatures.
ESR 10 developed a stochastic model of T-cell populations in homeostasis including cross-reactivity and multiple self-pMHC complexes.
ESR 11 validated a computational model of TCR probability in the periphery, and also applied the method to B cell receptors to check its wide applicability.
ESR 12 studied the relevance of the iKIR-HLA receptor-ligand system in cancer and autoimmunity and analyse the mechanisms by which iKIRs influence T cells.
ESR 13 considered the maintenance of 'product' cell populations from 'progenitor' cells via a sequence of one or more cell types, or compartments, where each cell's fate is chosen stochastically. ESR 13 defined an ODE model of T-cell exhaustion states and studied structural identifiability.
ESR 14 explored agent-based and stochastic models and their combination with ordinary differential equations, to model heterogeneity of cancer cell populations, the effect of different therapeutic options and the tumour-immune cell interaction. The reinforcement algorithm was employed to optimize parameters.
ESR 15 developed the Cyton2 model, that encapsulates features of inheritance correlation structure of cell fates.
In work package 1, the success of new vaccination strategies that are currently being developed to trigger responses at the site of pathogen entry, and the success of T cell therapies that aim for a long-lasting effect in cancer patients, depend on the long-term maintenance of naive and memory T cells at appropriate locations in the body. T cells reside in various compartments where they protect against infection. Their major sites of production are lymphoid tissues, and yet the vast majority of human data on how these T cells are maintained come from blood samples. ESRs in WP1 have worked towards an improved quantitative understanding of the in vivo dynamics of the different naive and memory T cell populations throughout the human body and the relationships between them, which is needed to obtain the best clinical outcome.
In work package 2, T cell clonotypes can be identified by their unique TCRs, and with current NGS technologies, T cell repertoires can be identified in various tissues for naive and memory T cell subsets. An improved quantitative understanding of the in vivo TCR repertoire diversity and clonal distributions of the different naive and memory T cell populations in blood and tissues, in health and disease, as well as the overlap between and cross-reactivity of these TCR repertoires is needed, and ESRs in WP2 have worked to obtain the best clinical outcome, and also to tailor individual patient T cell immunotherapies.
ESRs in WP3 have worked to improve our current quantitative understanding of T cell based immunotherapies, by carrying out research projects to develop novel theoretical methods. Adoptive T cell therapies for the treatment of cancer and immunodeficiencies rely on appropriate selection of T cells from the patient, ex vivo clonal expansion through the provision of activating stimuli and, possibly, ex vivo genetic modifications that result in T cells expressing chimeric antigen receptors (CARs). In trials, these CARs are directly engineered to possess a cancer specificity, although some ground-breaking ideas that involve using the natural diversity of other host's TCRs have been proposed.
In work package 2, T cell clonotypes can be identified by their unique TCRs, and with current NGS technologies, T cell repertoires can be identified in various tissues for naive and memory T cell subsets. An improved quantitative understanding of the in vivo TCR repertoire diversity and clonal distributions of the different naive and memory T cell populations in blood and tissues, in health and disease, as well as the overlap between and cross-reactivity of these TCR repertoires is needed, and ESRs in WP2 have worked to obtain the best clinical outcome, and also to tailor individual patient T cell immunotherapies.
ESRs in WP3 have worked to improve our current quantitative understanding of T cell based immunotherapies, by carrying out research projects to develop novel theoretical methods. Adoptive T cell therapies for the treatment of cancer and immunodeficiencies rely on appropriate selection of T cells from the patient, ex vivo clonal expansion through the provision of activating stimuli and, possibly, ex vivo genetic modifications that result in T cells expressing chimeric antigen receptors (CARs). In trials, these CARs are directly engineered to possess a cancer specificity, although some ground-breaking ideas that involve using the natural diversity of other host's TCRs have been proposed.