The evolutionary events that cause colorectal adenomas (benign) to progress to carcinomas (malignant) remain largely undetermined. Using multi-region genome and exome sequencing of 24 benign and malignant colorectal tumours, we investigate the evolutionary fitness landscape occupied by these neoplasms. Unlike carcinomas, advanced adenomas frequently harbour sub-clonal driver mutations-considered to be functionally important in the carcinogenic process-that have not swept to fixation, and have relatively high genetic heterogeneity. Carcinomas are distinguished from adenomas by widespread aneusomies that are usually clonal and often accrue in a 'punctuated' fashion. We conclude that adenomas evolve across an undulating fitness landscape, whereas carcinomas occupy a sharper fitness peak, probably owing to stabilizing selection.
The Hybrid Automata Library (HAL) is a Java Library developed for use in mathematical oncology modeling. It is made of simple, efficient, generic components that can be used to model complex spatial systems. HAL's components can broadly be classified into: on-and off-lattice agent containers, finite difference diffusion fields, a GUI building system, and additional tools and utilities for computation and data collection. These components are designed to operate independently and are standardized to make them easy to interface with one another. As a demonstration of how modeling can be simplified using our approach, we have included a complete example of a hybrid model (a spatial model with interacting agent-based and PDE components). HAL is a useful asset for researchers who wish to build performant 1D, 2D and 3D hybrid models in Java, while not starting entirely from scratch. It is available on GitHub at https://github.com/MathOnco/HAL under the MIT License. HAL requires the Java JDK version 1.8 or later to compile and run the source code.
Most ovarian cancers are infiltrated by prognostically relevant activated T cells1–3, yet exhibit low response rates to immune checkpoint inhibitors4. Memory B cell and plasma cell infiltrates have previously been associated with better outcomes in ovarian cancer5,6, but the nature and functional relevance of these responses are controversial. Here, using 3 independent cohorts that in total comprise 534 patients with high-grade serous ovarian cancer, we show that robust, protective humoral responses are dominated by the production of polyclonal IgA, which binds to polymeric IgA receptors that are universally expressed on ovarian cancer cells. Notably, tumour B-cell-derived IgA redirects myeloid cells against extracellular oncogenic drivers, which causes tumour cell death. In addition, IgA transcytosis through malignant epithelial cells elicits transcriptional changes that antagonize the RAS pathway and sensitize tumour cells to cytolytic killing by T cells, which also contributes to hindering malignant progression. Thus, tumour-antigen-specific and -antigen-independent IgA responses antagonize the growth of ovarian cancer by governing coordinated tumour cell, T cell and B cell responses. These findings provide a platform for identifying targets that are spontaneously recognized by intratumoural B-cell-derived antibodies, and suggest that immunotherapies that augment B cell responses may be more effective than approaches that focus on T cells, particularly for malignancies that are resistant to checkpoint inhibitors.
Cancers accumulate mutations that lead to neoantigens, novel peptides that elicit an immune response, and consequently undergo evolutionary selection. Here we establish how the clonal structure of neoantigens in a growing cancer is shaped by negative selection, by constructing a mathematical model of neoantigen evolution. The model predicts that, without immune escape, tumour neoantigens are either clonal or absent from large subclones, and hyper-mutated tumours can only establish following the evolution of immune evasion. Strong negative selection on neoantigens leads to an increased number of neutrally-evolving tumours, as a consequence of selective pressure for immune escape. The clone size distribution under negative selection is effectivelyneutral, and becomes more neutral-like under stronger negative selection. These results are consistent with the analysis of neoantigen clone sizes and immune escape in exome and RNA sequencing data from colon, stomach and endometrial cancers. 4 RESULTS Mathematical model of tumour growth predicts distinct antigen-hot and -cold tumoursWe created a mathematical model of neoantigen evolution during tumour growth, based on a stochastic branching process (Figure 1a and Methods). At each step, tumour cells of lineage i produced two surviving offspring at birth rate b=1 per unit time or died with death rate determined by the strength of negative selection against the cumulative antigenicity of neoantigens in the lineage. Neoantigens accumulated at rate µ per cell per division, and had antigenicity s drawn from a pre-specified distribution. s can be interpreted as the effectiveness of immune predation against an antigen: s=0 indicates no selection pressure (neutral evolution), and s<0 strong negative selection (following ref 34 ). Tumour growth was simulated until the tumour reached a predefined population size (approximating a clinically detectable size) or until a sufficiently long time elapsed without tumour establishment (corresponding to no cancer formation within a person's lifetime).We first examined the temporal neoantigen burden in simulated tumours. We defined the 'antigen score' of a tumour as the proportion of tumour cells carrying cumulative antigenicity ≥ ! . Tumours simulated with identical parameters separated into two distinct groups: 'antigen-hot' and 'antigen-cold'. Antigen-hot tumours had an antigen score close to 1, corresponding to every tumour cell in the population being highly antigenic, whereas in antigen-cold tumours the majority of cells lacked immunogenic mutations (Figure 1b&c). The proportion of antigen-hot tumours depended on the selection strength (Figure S1a): increased negative selection for neoantigens decreased the probability of observing antigen-hot tumours. In antigen-cold tumours, the proportion of neoantigen-carrying cells also decreased inversely with negative selection.
BackgroundTumours rapidly ferment glucose to lactic acid even in the presence of oxygen, and coupling high glycolysis with poor perfusion leads to extracellular acidification. We hypothesise that acidity, independent from lactate, can augment the pro-tumour phenotype of macrophages.MethodsWe analysed publicly available data of human prostate cancer for linear correlation between macrophage markers and glycolysis genes. We used zwitterionic buffers to adjust the pH in series of in vitro experiments. We then utilised subcutaneous and transgenic tumour models developed in C57BL/6 mice as well as computer simulations to correlate tumour progression with macrophage infiltration and to delineate role of acidity.ResultsActivating macrophages at pH 6.8 in vitro enhanced an IL-4-driven phenotype as measured by gene expression, cytokine profiling, and functional assays. These results were recapitulated in vivo wherein neutralising intratumoural acidity reduced the pro-tumour phenotype of macrophages, while also decreasing tumour incidence and invasion in the TRAMP model of prostate cancer. These results were recapitulated using an in silico mathematical model that simulate macrophage responses to environmental signals. By turning off acid-induced cellular responses, our in silico mathematical modelling shows that acid-resistant macrophages can limit tumour progression.ConclusionsThis study suggests that tumour acidity contributes to prostate carcinogenesis by altering the state of macrophage activation.
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