UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma.

Although clonal neo-antigen burden is associated with improved response to immune therapy, the functional basis for this remains unclear. Here we study this question in a novel controlled mouse melanoma model that enables us to explore the effects of intra-tumor heterogeneity (ITH) on tumor aggressiveness and immunity independent of tumor mutational burden. Induction of UVB-derived mutations yields highly aggressive tumors with decreased anti-tumor activity. However, single-cell-derived tumors with reduced ITH are swiftly rejected. Their rejection is accompanied by increased T cell reactivity and a less suppressive microenvironment. Using phylogenetic analyses and mixing experiments of single-cell clones, we dissect two characteristics of ITH: the number of clones forming the tumor and their clonal diversity. Our analysis of melanoma patient tumor data recapitulates our results in terms of overall survival and response to immune checkpoint therapy. These findings highlight the importance of clonal mutations in robust immune surveillance and the need to quantify patient ITH to determine the response to checkpoint blockade.

Interactions between immune cell types facilitate the evolution of immune traits.

An essential prerequisite for evolution by natural selection is variation among individuals in traits that affect fitness1. The ability of a system to produce selectable variation, known as evolvability2, thus greatly affects the rate of evolution. The immune system belongs to the fastest evolving components in mammals3, yet the sources of variation in immune traits remain largely unknown4,5. Here, we show that an important determinant of the immune system's evolvability is its organisation into interacting modules represented by different immune cell types. By profiling immune cell variation in bone marrow of 54 genetically diverse mouse strains from the Collaborative Cross6, we found that variation in immune cell frequencies is polygenic and that many associated genes are involved in homeostatic balance through cell-intrinsic functions of proliferation, migration and cell death. However, we also found genes associated with the frequency of a particular cell type, which are expressed in a different cell type, exerting their effect in what we term cyto-trans. Vertebrate evolutionary record shows that genes associated in cyto-trans have faced weaker negative selection, thus increasing the robustness and hence evolvability2,7,8 of the immune system. This phenomenon is similarly observable in human blood. Our findings suggest that interactions between different components of the immune system provide a phenotypic space where mutations can produce variation without much detriment, underscoring the role of modularity in the evolution of complex systems9.

Alignment of single-cell trajectories to compare cellular expression dynamics.

Single-cell RNA sequencing and high-dimensional cytometry can be used to generate detailed trajectories of dynamic biological processes such as differentiation or development. Here we present cellAlign, a quantitative framework for comparing expression dynamics within and between single-cell trajectories. By applying cellAlign to mouse and human embryonic developmental trajectories, we systematically delineate differences in the temporal regulation of gene expression programs that would otherwise be masked.

A personalized network framework reveals predictive axis of anti-TNF response across diseases.

Personalized treatment of complex diseases has been mostly predicated on biomarker identification of one drug-disease combination at a time. Here, we use a computational approach termed Disruption Networks to generate a data type, contextualized by cell-centered individual-level networks, that captures biology otherwise overlooked when performing standard statistics. This data type extends beyond the "feature level space", to the "relations space", by quantifying individual-level breaking or rewiring of cross-feature relations. Applying Disruption Networks to dissect high-dimensional blood data, we discover and validate that the RAC1-PAK1 axis is predictive of anti-TNF response in inflammatory bowel disease. Intermediate monocytes, which correlate with the inflammatory state, play a key role in the RAC1-PAK1 responses, supporting their modulation as a therapeutic target. This axis also predicts response in rheumatoid arthritis, validated in three public cohorts. Our findings support blood-based drug response diagnostics across immune-mediated diseases, implicating common mechanisms of non-response.

Mass cytometry analysis of immune cells in the brain.

Immune cells comprise a diverse and dynamic cell population that is responsible for a broad range of immunological activities. They act in concert with other immune and nonimmune cells via cytokine-mediated communication and direct cell-cell interactions. Understanding the complex immune network requires a broad characterization of its individual cellular components. This is especially relevant for the brain compartment, which is an active immunological site, composed of resident and infiltrating immune cells that affect brain development, tissue homeostasis and neuronal activity. Mass cytometry, or CyTOF (cytometry by time-of-flight), uses metal-conjugated antibodies to enable a high-dimensional description of tens of markers at the single-cell level, thereby providing a bird's-eye view of the immune system. This technique has been successfully applied to the discovery of novel immune populations in humans and rodents. Here, we provide a step-by-step description of a mass cytometry approach for the analysis of the mouse brain compartment. The different stages of the procedure include brain perfusion, extraction of the brain tissue and its dissociation into a single-cell suspension, followed by cell staining with metal-tagged antibodies, sample reading using a mass cytometer, and data analysis using SPADE and viSNE. This procedure takes <5 h (excluding data analysis) and can be applied to study modifications in the brain's immune populations under normal and pathological conditions.

Immune-centric network of cytokines and cells in disease context identified by computational mining of PubMed.

Cytokines are signaling molecules secreted and sensed by immune and other cell types, enabling dynamic intercellular communication. Although a vast amount of data on these interactions exists, this information is not compiled, integrated or easily searchable. Here we report immuneXpresso, a text-mining engine that structures and standardizes knowledge of immune intercellular communication. We applied immuneXpresso to PubMed to identify relationships between 340 cell types and 140 cytokines across thousands of diseases. The method is able to distinguish between incoming and outgoing interactions, and it includes the effect of the interaction and the cellular function involved. These factors are assigned a confidence score and linked to the disease. By leveraging the breadth of this network, we predicted and experimentally verified previously unappreciated cell-cytokine interactions. We also built a global immune-centric view of diseases and used it to predict cytokine-disease associations. This standardized knowledgebase (http://www.immunexpresso.org) opens up new directions for interpretation of immune data and model-driven systems immunology.

High-dimensional, single-cell characterization of the brain's immune compartment.

The brain and its borders create a highly dynamic microenvironment populated with immune cells. Yet characterization of immune cells within the naive brain compartment remains limited. In this study, we used CyTOF mass cytometry to characterize the immune populations of the naive mouse brain using 44 cell surface markers. By comparing immune cell composition and cell profiles between the brain compartment and blood, we were able to characterize previously undescribed cell subsets of CD8 T cells, B cells, NK cells and dendritic cells in the naive brain. Using flow cytometry, we show differential distributions of immune populations between meninges, choroid plexus and parenchyma. We demonstrate the phenotypic ranges of resident myeloid cells and identify CD44 as a marker for infiltrating immune populations. This study provides an approach for a system-wide view of immune populations in the brain and is expected to serve as a resource for understanding brain immunity.

Activation of the reward system boosts innate and adaptive immunity.

Positive expectations contribute to the clinical benefits of the placebo effect. Such positive expectations are mediated by the brain's reward system; however, it remains unknown whether and how reward system activation affects the body's physiology and, specifically, immunity. Here we show that activation of the ventral tegmental area (VTA), a key component of the reward system, strengthens immunological host defense. We used 'designer receptors exclusively activated by designer drugs' (DREADDs) to directly activate dopaminergic neurons in the mouse VTA and characterized the subsequent immune response after exposure to bacteria (Escherichia coli), using time-of-flight mass cytometry (CyTOF) and functional assays. We found an increase in innate and adaptive immune responses that were manifested by enhanced antibacterial activity of monocytes and macrophages, reduced in vivo bacterial load and a heightened T cell response in the mouse model of delayed-type hypersensitivity. By chemically ablating the sympathetic nervous system (SNS), we showed that the reward system's effects on immunity are, at least partly, mediated by the SNS. Thus, our findings establish a causal relationship between the activity of the VTA and the immune response to bacterial infection.