Cancer is a complex disease that starts with mutations of key genes in one cell or a small group of cells at a primary site in the body. If these cancer cells continue to grow successfully and, at some later stage, invade the surrounding tissue and acquire a vascular network, they can spread to distant secondary sites in the body. This process, known as metastatic spread , is responsible for around 90% of deaths from cancer and is one of the so-called hallmarks of cancer . To shed light on the metastatic process, we present a mathematical modelling framework that captures for the first time the interconnected processes of invasion and metastatic spread of individual cancer cells in a spatially explicit manner—a multigrid, hybrid, individual-based approach. This framework accounts for the spatiotemporal evolution of mesenchymal- and epithelial-like cancer cells, membrane-type-1 matrix metalloproteinase (MT1-MMP) and the diffusible matrix metalloproteinase-2 (MMP-2), and for their interactions with the extracellular matrix. Using computational simulations, we demonstrate that our model captures all the key steps of the invasion-metastasis cascade, i.e. invasion by both heterogeneous cancer cell clusters and by single mesenchymal-like cancer cells; intravasation of these clusters and single cells both via active mechanisms mediated by matrix-degrading enzymes (MDEs) and via passive shedding; circulation of cancer cell clusters and single cancer cells in the vasculature with the associated risk of cell death and disaggregation of clusters; extravasation of clusters and single cells; and metastatic growth at distant secondary sites in the body. By faithfully reproducing experimental results, our simulations support the evidence-based hypothesis that the membrane-bound MT1-MMP is the main driver of invasive spread rather than diffusible MDEs such as MMP-2.

Cancer is a complex disease that starts with mutations of key genes in one cell or a small group of cells at a primary site in the body. If these cancer cells continue to grow successfully and, at some later stage, invade the surrounding tissue and acquire a vascular network (tumour-induced angiogenesis), they can spread to distant secondary sites in the body. This process, known as metastatic spread, is responsible for around 90% of deaths from cancer and is one of the so-called hallmarks of cancer.To shed light on the metastatic process, we present a mathematical modelling framework that captures for the first time the interconnected processes of invasion and metastatic spread of individual cancer cells in a spatially explicit manner -a multi-grid, hybrid, individual-based approach. This framework accounts for the spatio-temporal evolution of mesenchymal-and epithelial-like cancer cells, as well as MT1-MMP and MMP-2 dynamics, and interactions with the extracellular matrix.Using computational simulations, we demonstrate that our model captures all the key steps of the invasion-metastasis cascade, i.e. invasion by both heterogeneous cancer cell clusters and by single mesenchymal-like cancer cells; intravasation of these clusters and single cells both via active mechanisms mediated by matrix degrading enzymes (MDEs) and via passive shedding; circulation of cancer cell clusters and single cancer cells in the vasculature with the associated risk of cell death and disaggregation of clusters; extravasation of clusters and single cells; and metastatic growth at distant secondary sites in the body. By faithfully reproducing experimental results, our simulations support the evidence-based hypothesis that the membrane-bound MT1-MMP is the main driver of invasive spread rather than diffusible MDEs like MMP-2.Keywords Metastatic spread · Mathematical oncology · Tumour microenvironment · Individual-based model · Multi-grid framework LCF is funded by the Engineering and Physical Sciences Research Council (EPSRC). MAJC gratefully acknowledges the support of EPSRC Grant

Immunogenicity, defined as the ability to provoke an immune response, can be either wanted (i.e., vaccines) or unwanted. The latter refers to an immune response to protein or peptide therapeutics, characterized by the production of anti-drug antibodies, which may affect the efficacy and/or the safety profiles of these drugs. Consequently, evaluation of the risk of immunogenicity early in the development of biotherapeutics is of critical importance for defining their efficacy and safety profiles. Here, we describe and validate a fit-for-purpose FluoroSpot-based in vitro assay for the evaluation of drug-specific T cell responses. A panel of 24 biotherapeutics with a wide range of clinical anti-drug antibody response rates were tested in this assay. We demonstrated that using suitable cutoffs and donor cohort sizes, this assay could identify most of the compounds with high clinical immunogenicity rates (71% and 78% for sensitivity and specificity, respectively) while we characterized the main sources of assay variability. Overall, these data indicate that the dendritic cell and CD4+ T cell restimulation assay published herein could be a valuable tool to assess the risk of drug-specific T cell responses and contribute to the selection of clinical candidates in early development.

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