Adjuvant dendritic cell therapy in stage IIIB/C melanoma: the MIND-DC randomized phase III trial

Autologous natural dendritic cells (nDCs) treatment can induce tumor-specific immune responses and clinical responses in cancer patients. In this phase III clinical trial (NCT02993315), 148 patients with resected stage IIIB/C melanoma were randomized to adjuvant treatment with nDCs (n = 99) or placebo (n = 49). Active treatment consisted of intranodally injected autologous CD1c+ conventional and plasmacytoid DCs loaded with tumor antigens. The primary endpoint was the 2-year recurrence-free survival (RFS) rate, whereas the secondary endpoints included median RFS, 2-year and median overall survival, adverse event profile, and immunological response The 2-year RFS rate was 36.8% in the nDC treatment group and 46.9% in the control group (p = 0.31). Median RFS was 12.7 months vs 19.9 months, respectively (hazard ratio 1.25; 90% CI: 0.88-1.79; p = 0.29). Median overall survival was not reached in both treatment groups (hazard ratio 1.32; 90% CI: 0.73-2.38; p = 0.44). Grade 3-4 study-related adverse events occurred in 5% and 6% of patients. Functional antigen-specific T cell responses could be detected in 67.1% of patients tested in the nDC treatment group vs 3.8% of patients tested in the control group (p < 0.001). In conclusion, while adjuvant nDC treatment in stage IIIB/C melanoma patients generated specific immune responses and was well tolerated, no benefit in RFS was observed.

Detection of dendritic cell subsets in the tumor microenvironment by multiplex immunohistochemistry

Dendritic cells (DCs) are essential in antitumor immunity. In humans, three main DC subsets are defined: two types of conventional DCs (cDC1s and cDC2s) and plasmacytoid DCs (pDCs). To study DC subsets in the tumor microenvironment (TME), it is important to correctly identify them in tumor tissues. Tumor-derived DCs are often analyzed in cell suspensions in which spatial information about DCs which can be important to determine their function within the TME is lost. Therefore, we developed the first standardized and optimized multiplex immunohistochemistry panel, simultaneously detecting cDC1s, cDC2s, and pDCs within their tissue context. We report on this panel's development, validation, and quantitative analysis. A multiplex immunohistochemistry panel consisting of CD1c, CD303, X-C motif chemokine receptor 1, CD14, CD19, a tumor marker, and DAPI was established. The ImmuNet machine learning pipeline was trained for the detection of DC subsets. The performance of ImmuNet was compared with conventional cell phenotyping software. Ultimately, frequencies of DC subsets within several tumors were defined. In conclusion, this panel provides a method to study cDC1s, cDC2s, and pDCs in the spatial context of the TME, which supports unraveling their specific roles in antitumor immunity.

Identifiability of causal effects in test-negative design studies

Causal directed acyclic graphs (DAGs) are often used to select variables in a regression model to identify causal effects. Outcome-based sampling studies, such as the 'test-negative design' used to assess vaccine effectiveness, present unique challenges that are not addressed by the common back-door criterion. Here we discuss intuitive, graphical approaches to explain why the common back-door criterion cannot be used for identification of population average causal effects with outcome-based sampling studies. We also describe graphical rules that can be used instead in outcome-based sampling studies when the objective is limited to determining if the causal odds ratio is identifiable, and illustrate recent changes to the free online software Dagitty which incorporate these principles.

Machine learning analysis of the T cell receptor repertoire identifies sequence features of self-reactivity

The T cell receptor (TCR) determines specificity and affinity for both foreign and self-peptides presented by the major histocompatibility complex (MHC). Although the strength of TCR interactions with self-pMHC impacts T cell function, it has been challenging to identify TCR sequence features that predict T cell fate. To discern patterns distinguishing TCRs from naive CD4+ T cells with low versus high self-reactivity, we used data from 42 mice to train a machine learning (ML) algorithm that identifies population-level differences between TCRβ sequence sets. This approach revealed that weakly self-reactive T cell populations were enriched for longer CDR3β regions and acidic amino acids. We tested our ML predictions of self-reactivity using retrogenic mice with fixed TCRβ sequences. Extrapolating our analyses to independent datasets, we predicted high self-reactivity for regulatory T cells and slightly reduced self-reactivity for T cells responding to chronic infections. Our analyses suggest a potential trade-off between TCR repertoire diversity and self-reactivity. A record of this paper's transparent peer review process is included in the supplemental information.

Multiplex Immunohistochemical Analysis of the Spatial Immune Cell Landscape of the Tumor Microenvironment

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. Multiplex immunohistochemistry is a valuable tool to visualize and identify different types of immune cells in tumor tissues while retaining its spatial information. Here we provide detailed protocols to analyze lymphocyte, myeloid, and dendritic cell populations in tissue sections. Starting from cutting formalin-fixed paraffin-embedded sections, automatic multiplex staining procedures on an automated platform, scanning of the slides on a multispectral imaging microscope, to the analysis of images using an in-house-developed machine learning algorithm ImmuNet. These protocols can be applied to a variety of tumor specimens by simply switching tumor markers to analyze immune cells in different compartments of the sample (tumor versus invasive margin) and apply nearest-neighbor analysis. This analysis is not limited to tumor samples but can also be applied to other (non-)pathogenic tissues. Improvements to the equipment and workflow over the past few years have significantly shortened throughput times, which facilitates the future application of this procedure in the diagnostic setting.

Flow rate resonance of actively deforming particles

Lymphoid organs are unusual multicellular tissues: they are densely packed, but the lymphocytes trafficking through them are actively moving. We hypothesize that the intriguing ability of lymphocytes to avoid jamming and clogging is in part attributable to the dynamic shape changes that cells undergo when they move. In this work, we test this hypothesis by investigating an idealized system, namely, the flow of self-propelled, oscillating particles passing through a narrow constriction in two dimensions (2D), using numerical simulations. We found that deformation allows particles with these properties to flow through a narrow constriction in conditions when non-deformable particles would not be able to do so. Such a flowing state requires the amplitude and frequency of oscillations to exceed threshold values. Moreover, a resonance leading to the maximum flow rate was found when the oscillation frequency matched the natural frequency of the particle related to its elastic stiffness. To our knowledge, this phenomenon has not been described previously. Our findings could have important implications for understanding and controlling flow in a variety of systems in addition to lymphoid organs, such as granular flows subjected to vibration.

In silico cancer immunotherapy trials uncover the consequences of therapy-specific response patterns for clinical trial design and outcome

Late-stage cancer immunotherapy trials often lead to unusual survival curve shapes, like delayed curve separation or a plateauing curve in the treatment arm. It is critical for trial success to anticipate such effects in advance and adjust the design accordingly. Here, we use in silico cancer immunotherapy trials - simulated trials based on three different mathematical models - to assemble virtual patient cohorts undergoing late-stage immunotherapy, chemotherapy, or combination therapies. We find that all three simulation models predict the distinctive survival curve shapes commonly associated with immunotherapies. Considering four aspects of clinical trial design - sample size, endpoint, randomization rate, and interim analyses - we demonstrate how, by simulating various possible scenarios, the robustness of trial design choices can be scrutinized, and possible pitfalls can be identified in advance. We provide readily usable, web-based implementations of our three trial simulation models to facilitate their use by biomedical researchers, doctors, and trialists.

Tumor microenvironment shows an immunological abscopal effect in patients with NSCLC treated with pembrolizumab-radiotherapy combination

Background

Immunotherapy is currently part of the standard of care for patients with advanced-stage non-small cell lung cancer (NSCLC). However, many patients do not respond to this treatment, therefore combination strategies are being explored to increase clinical benefit. The PEMBRO-RT trial combined the therapeutic programmed cell death 1 (PD-1) antibody pembrolizumab with stereotactic body radiation therapy (SBRT) to increase the overall response rate and study the effects on the tumor microenvironment (TME).

Methods

Here, immune infiltrates in the TME of patients included in the PEMBRO-RT trial were investigated. Tumor biopsies of patients treated with pembrolizumab alone or combined with SBRT (a biopsy of the non-irradiated site) at baseline and during treatment were stained with multiplex immunofluorescence for CD3, CD8, CD20, CD103 and FoxP3 for lymphocytes, pan-cytokeratin for tumors, and HLA-ABC expression was determined.

Results

The total number of lymphocytes increased significantly after 6 weeks of treatment in the anti-PD-1 group (fold change: 1.87, 95% CI: 1.06 to 3.29) and the anti-PD-1+SBRT group (fold change: 2.29, 95% CI: 1.46 to 3.60). The combination of SBRT and anti-PD-1 induced a 4.87-fold increase (95% CI: 2.45 to 9.68) in CD103⁺ cytotoxic T-cells 6 weeks on treatment and a 2.56-fold increase (95% CI: 1.03 to 6.36) after anti-PD-1 therapy alone. Responders had a significantly higher number of lymphocytes at baseline than non-responders (fold difference 1.85, 95% CI: 1.04 to 3.29 for anti-PD-1 and fold change 1.93, 95% CI: 1.08 to 3.44 for anti-PD-1+SBRT).

Conclusion

This explorative study shows that that lymphocyte infiltration in general, instead of the infiltration of a specific lymphocyte subset, is associated with response to therapy in patients with NSCLC.

Furthermore, anti-PD-1+SBRT combination therapy induces an immunological abscopal effect in the TME represented by a superior infiltration of cytotoxic T cells as compared with anti-PD-1 monotherapy.

Paired primary and metastatic lesions of patients with ipilimumab-treated melanoma: high variation in lymphocyte infiltration and HLA-ABC expression whereas tumor mutational load is similar and correlates with clinical outcome

BACKGROUND

Immune checkpoint inhibitors (ICI) can lead to long-term responses in patients with metastatic melanoma. Still many patients with melanoma are intrinsically resistant or acquire secondary resistance. Previous studies have used primary or metastatic tumor tissue for biomarker assessment. Especially in melanoma, metastatic lesions are often present at different anatomical sites such as skin, lymph nodes, and visceral organs. The anatomical site may directly affect the tumor microenvironment (TME). To evaluate the impact of tumor evolution on the TME and on ICI treatment outcome, we directly compared paired primary and metastatic melanoma lesions for tumor mutational burden (TMB), HLA-ABC status, and tumor infiltrating lymphocytes (TILs) of patients that received ipilimumab.

METHODS

TMB was analyzed by sequencing primary and metastatic melanoma lesions using the TruSight Oncology 500 assay. Tumor tissues were subjected to multiplex immunohistochemistry to assess HLA-ABC status and for the detection of TIL subsets (B cells, cytotoxic T cells, helper T cells, and regulatory T cells), by using a machine-learning algorithm.

RESULTS

While we observed a very good agreement between TMB of matched primary and metastatic melanoma lesions (intraclass coefficient=0.921), such association was absent for HLA-ABC status, TIL density, and subsets thereof. Interestingly, analyses of different metastatic melanoma lesions within a single patient revealed that TIL density and composition agreed remarkably well, rejecting the hypothesis that the TME of different anatomical sites affects TIL infiltration. Similarly, the HLA-ABC status between different metastatic lesions within patients was also comparable. Furthermore, high TMB, of either primary or metastatic melanoma tissue, directly correlated with response to ipilimumab, whereas lymphocyte density or composition did not. Loss of HLA-ABC in the metastatic lesion correlated to a shorter progression-free survival on ipilimumab.

CONCLUSIONS

We confirm the link between TMB and HLA-ABC status and the response to ipilimumab-based immunotherapy in melanoma, but no correlation was found for TIL density, neither in primary nor metastatic lesions. Our finding that TMB between paired primary and metastatic melanoma lesions is highly stable, demonstrates its independency of the time point and location of acquisition. TIL and HLA-ABC status in metastatic lesions of different anatomical sites are highly similar within an individual patient.

Pre-existing chromatin accessibility and gene expression differences among naive CD4+ T cells influence effector potential

CD4+ T cells have a remarkable potential to differentiate into diverse effector lineages following activation. Here, we probe the heterogeneity present among naive CD4+ T cells before encountering their cognate antigen to ask whether their effector potential is modulated by pre-existing transcriptional and chromatin landscape differences. Single-cell RNA sequencing shows that key drivers of variability are genes involved in T cell receptor (TCR) signaling. Using CD5 expression as a readout of the strength of tonic TCR interactions with self-peptide MHC, and sorting on the ends of this self-reactivity spectrum, we find that pre-existing transcriptional differences among naive CD4+ T cells impact follicular helper T (TFH) cell versus non-TFH effector lineage choice. Moreover, our data implicate TCR signal strength during thymic development in establishing differences in naive CD4+ T cell chromatin landscapes that ultimately shape their effector potential.

CelltrackR: An R package for fast and flexible analysis of immune cell migration data

Visualization of cell migration via time-lapse microscopy has greatly advanced our understanding of the immune system. However, subtle differences in migration dynamics are easily obscured by biases and imaging artifacts. While several analysis methods have been suggested to address these issues, an integrated tool implementing them is currently lacking. Here, we present celltrackR, an R package containing a diverse set of state-of-the-art analysis methods for (immune) cell tracks. CelltrackR supports the complete pipeline for track analysis by providing methods for data management, quality control, extracting and visualizing migration statistics, clustering tracks, and simulating cell migration. CelltrackR supports the analysis of both 2D and 3D cell tracks. CelltrackR is an open-source package released under the GPL-2 license, and is freely available on both GitHub and CRAN. Although the package was designed specifically for immune cell migration data, many of its methods will also be of use in other research areas dealing with moving objects.

Cytotoxic T cells are able to efficiently eliminate cancer cells by additive cytotoxicity

Lethal hit delivery by cytotoxic T lymphocytes (CTL) towards B lymphoma cells occurs as a binary, "yes/no" process. In non-hematologic solid tumors, however, CTL often fail to kill target cells during 1:1 conjugation. Here we describe a mechanism of "additive cytotoxicity" by which time-dependent integration of sublethal damage events, delivered by multiple CTL transiting between individual tumor cells, mediates effective elimination. Reversible sublethal damage includes perforin-dependent membrane pore formation, nuclear envelope rupture and DNA damage. Statistical modeling reveals that 3 serial hits delivered with decay intervals below 50 min discriminate between tumor cell death or survival after recovery. In live melanoma lesions in vivo, sublethal multi-hit delivery is most effective in interstitial tissue where high CTL densities and swarming support frequent serial CTL-tumor cell encounters. This identifies CTL-mediated cytotoxicity by multi-hit delivery as an incremental and tunable process, whereby accelerating damage magnitude and frequency may improve immune efficacy.

Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations

Background

Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal effects. This review examined the use of DAGs in applied health research to inform recommendations for improving their transparency and utility in future research.

Methods

Original health research articles published during 1999–2017 mentioning ‘directed acyclic graphs’ (or similar) or citing DAGitty were identified from Scopus, Web of Science, Medline and Embase. Data were extracted on the reporting of: estimands, DAGs and adjustment sets, alongside the characteristics of each article’s largest DAG.

Results

A total of 234 articles were identified that reported using DAGs. A fifth (n = 48, 21%) reported their target estimand(s) and half (n = 115, 48%) reported the adjustment set(s) implied by their DAG(s). Two-thirds of the articles (n = 144, 62%) made at least one DAG available. DAGs varied in size but averaged 12 nodes [interquartile range (IQR): 9–16, range: 3–28] and 29 arcs (IQR: 19–42, range: 3–99). The median saturation (i.e. percentage of total possible arcs) was 46% (IQR: 31–67, range: 12–100). 37% (n = 53) of the DAGs included unobserved variables, 17% (n = 25) included ‘super-nodes’ (i.e. nodes containing more than one variable) and 34% (n = 49) were visually arranged so that the constituent arcs flowed in the same direction (e.g. top-to-bottom).

Conclusion

There is substantial variation in the use and reporting of DAGs in applied health research. Although this partly reflects their flexibility, it also highlights some potential areas for improvement. This review hence offers several recommendations to improve the reporting and use of DAGs in future research.

Local actin dynamics couple speed and persistence in a cellular Potts model of cell migration

Cell migration is astoundingly diverse. Molecular signatures, cell-cell interactions, and environmental structures each play their part in shaping cell motion, yielding numerous morphologies and migration modes. Nevertheless, in recent years, a simple unifying law was found to describe cell migration across many different cell types and contexts: faster cells turn less frequently. This universal coupling between speed and persistence (UCSP) was explained by retrograde actin flow from front to back, but it remains unclear how this mechanism generalizes to cells with complex shapes and cells migrating in structured environments, which may not have a well-defined front-to-back orientation. Here, we present an in-depth characterization of an existing cellular Potts model, in which cells polarize dynamically from a combination of local actin dynamics (stimulating protrusions) and global membrane tension along the perimeter (inhibiting protrusions). We first show that the UCSP emerges spontaneously in this model through a cross talk of intracellular mechanisms, cell shape, and environmental constraints, resembling the dynamic nature of cell migration in vivo. Importantly, we find that local protrusion dynamics suffice to reproduce the UCSP-even in cases in which no clear global, front-to-back polarity exists. We then harness the spatial nature of the cellular Potts model to show how cell shape dynamics limit both the speed and persistence a cell can reach and how a rigid environment such as the skin can restrict cell motility even further. Our results broaden the range of potential mechanisms underlying the speed-persistence coupling that has emerged as a fundamental property of migrating cells.

A tipping point in cancer-immune dynamics leads to divergent immunotherapy responses and hampers biomarker discovery

BACKGROUND

Predicting treatment response or survival of cancer patients remains challenging in immuno-oncology. Efforts to overcome these challenges focus, among others, on the discovery of new biomarkers. Despite advances in cellular and molecular approaches, only a limited number of candidate biomarkers eventually enter clinical practice.

METHODS

A computational modeling approach based on ordinary differential equations was used to simulate the fundamental mechanisms that dictate tumor-immune dynamics and to investigate its implications on responses to immune checkpoint inhibition (ICI) and patient survival. Using in silico biomarker discovery trials, we revealed fundamental principles that explain the diverging success rates of biomarker discovery programs.

RESULTS

Our model shows that a tipping point-a sharp state transition between immune control and immune evasion-induces a strongly non-linear relationship between patient survival and both immunological and tumor-related parameters. In patients close to the tipping point, ICI therapy may lead to long-lasting survival benefits, whereas patients far from the tipping point may fail to benefit from these potent treatments.

CONCLUSION

These findings have two important implications for clinical oncology. First, the apparent conundrum that ICI induces substantial benefits in some patients yet completely fails in others could be, to a large extent, explained by the presence of a tipping point. Second, predictive biomarkers for immunotherapy should ideally combine both immunological and tumor-related markers, as a patient's distance from the tipping point can typically not be reliably determined from solely one of these. The notion of a tipping point in cancer-immune dynamics helps to devise more accurate strategies to select appropriate treatments for patients with cancer.

Immunophenotyping Reveals Longitudinal Changes in Circulating Immune Cells During Radium-223 Therapy in Patients With Metastatic Castration-Resistant Prostate Cancer

Background

Radium-223 improves overall survival (OS) in men with bone metastatic castration-resistant prostate cancer (mCRPC). While the exact mechanism behind this survival benefit remains unclear, radium-induced immunological mechanisms might contribute to the OS advantage. We performed a comprehensive evaluation of the immunological changes in mCRPC patients by phenotyping the peripheral blood mononuclear cells (PBMCs) during radium-223 therapy.

Materials and Methods

In this prospective, single-arm, exploratory study, PBMCs of 30 mCRPC patients were collected before, during, and after treatment with radium-223. Lymphocyte and monocyte counts were analyzed to get insight into general immune cell trends. Next, we analyzed changes in T cell subsets, myeloid-derived suppressor cells (MDSCs), and immune checkpoint expression using linear regression models. Per subset, the 6-month change (% of baseline) was determined. Bootstrapped 95% confidence intervals were used to measure the degree of uncertainty of our findings.

Results

We observed a substantial decrease in absolute lymphocyte counts (-0.12 * 10^9 cells/L per injection, 95% CI: -0.143 - -0.102). Simultaneously, an increase was observed in the proportion of T cells that expressed costimulatory (ICOS) or inhibitory (TIM-3, PD-L1, and PD-1) checkpoint molecules. Moreover, the fraction of two immunosuppressive subsets – the regulatory T cells and the monocytic MDSCs – increased throughout treatment. These findings were not more pronounced in patients with an alkaline phosphatase response during therapy.

Conclusion

Immune cell subsets in patients with mCRPC changed during radium-223 therapy, which warrants further research into the possible immunological consequences of these changes.

Artistoo, a library to build, share, and explore simulations of cells and tissues in the web browser

The cellular Potts model (CPM) is a powerful in silico method for simulating biological processes at tissue scale. Their inherently graphical nature makes CPMs very accessible in theory, but in practice, they are mostly implemented in specialised frameworks users need to master before they can run simulations. We here present Artistoo (Artificial Tissue Toolbox), a JavaScript library for building ‘explorable’ CPM simulations where viewers can change parameters interactively, exploring their effects in real time. Simulations run directly in the web browser and do not require third-party software, plugins, or back-end servers. The JavaScript implementation imposes no major performance loss compared to frameworks written in C++; Artistoo remains sufficiently fast for interactive, real-time simulations. Artistoo provides an opportunity to unlock CPM models for a broader audience: interactive simulations can be shared via a URL in a zero-install setting. We discuss applications in CPM research, science dissemination, open science, and education.

Human type 1 and type 2 conventional dendritic cells express indoleamine 2,3-dioxygenase 1 with functional effects on T cell priming

Dendritic cells (DCs) are key regulators of the immune system that shape T cell responses. Regulation of T cell induction by DCs may occur via the intracellular enzyme indoleamine 2,3‐dioxygenase 1 (IDO), which catalyzes conversion of the essential amino acid tryptophan into kynurenine. Here, we examined the role of IDO in human peripheral blood plasmacytoid DCs (pDCs), and type 1 and type 2 conventional DCs (cDC1s and cDC2s). Our data demonstrate that under homeostatic conditions, IDO is selectively expressed by cDC1s. IFN‐γ or TLR ligation further increases IDO expression in cDC1s and induces modest expression of the enzyme in cDC2s, but not pDCs. IDO expressed by conventional DCs is functionally active as measured by kynurenine production. Furthermore, IDO activity in TLR‐stimulated cDC1s and cDC2s inhibits T cell proliferation in settings were DC‐T cell cell‐cell contact does not play a role. Selective inhibition of IDO1 with epacadostat, an inhibitor currently tested in clinical trials, rescued T cell proliferation without affecting DC maturation status or their ability to cross‐present soluble antigen. Our findings provide new insights into the functional specialization of human blood DC subsets and suggest a possible synergistic enhancement of therapeutic efficacy by combining DC‐based cancer vaccines with IDO inhibition.

Testing Graphical Causal Models Using the R Package "dagitty"

Causal diagrams such as directed acyclic graphs (DAGs) are used in several scientific fields to help design and analyze studies that aim to infer causal effects from observational data; for example, DAGs can help identify suitable strategies to reduce confounding bias. However, DAGs can be difficult to design, and the validity of any DAG-derived strategy hinges on the validity of the postulated DAG itself. Researchers should therefore check whether the assumptions encoded in the DAG are consistent with the data before proceeding with the analysis. Here, we explain how the R package 'dagitty', based on the web tool dagitty.net, can be used to test the statistical implications of the assumptions encoded in a given DAG. We hope that this will help researchers discover model specification errors, avoid erroneous conclusions, and build better models. © 2021 The Authors. Basic Protocol 1: Constructing and importing DAG models from the dagitty web interface Support Protocol 1: Installing R, RStudio, and the dagitty package Basic Protocol 2: Testing DAGs against categorical data Basic Protocol 3: Testing DAGs against continuous data Support Protocol 2: Testing DAGs against continuous data with non-linearities Basic Protocol 4: Testing DAGs against a combination of categorical and continuous data.

Activated adaptive immune system in dissected bicuspid aortic valve aortas: trigger for dissection?

Background/Introduction

Bicuspid aortic valve (BAV) is associated with ascending aorta aneurysms and dissections. Presently, genetic factors and pathological flow patterns are considered responsible for aneurysm formation in BAV. Despite, indication for preventive surgery is presently only defined by vessel diameter which is poor marker for dissection, as it does not take other processes responsible for the vulnerability of the aorta into account.

Purpose

Inflammation is not considered a player in BAV aortopathy. We introduce a quantitative immunohistochemistry (IHC) approach to sensitively look at the potential role of both the innate and adaptive immune system in BAV aortopathy.

Methods

Dilated (n=8), non-dilated (n=14) and dissected (n=4) BAV ascending aortas were collected during surgery or from post-mortem donors. Median time from symptoms to surgery for dissections was just over 4 hours. Tissue was stained with a novel 8-colour IHC technique allowing for simultaneous visualization of 6 markers per slide, completed with DAPI nuclear counter-stain and elastin fiber autofluorescence. One panel focused on the adaptive immune system (identifying B cells and classic dendritic cells type 2 (cDC2s) and phenotyping T cells), and the other on the innate immune system (assessing macrophage polarization and neutrophil extravasation). All cells were identified and comprehensively phenotyped using automated quantitative analysis.

Results

Aneurysm formation was associated with an organized and consistent increase of lymphocytes in the adventitia. B cell follicles and helper T cell expansion were identified, suggestive of a targeted adaptive immune response (Fig. 1a). Only dissected aortas showed a statistically significant increase of helper T (p=0.3) and cDC2s (p=0.3) in the media, when compared to non-dilated and dilated samples (Fig. 1b). The short time between dissection symptoms and surgery suggests these cells were present before the dissection occurred. Furthermore, aneurysms and dissections are associated with a shift in macrophage phenotype to the more aggressive M1-like subset. In summary, we found that a progression of aggressive immune cells in the adventitia and media was correlated to a progression in disease state; from normal to dilated to dissected.

Conclusions

Aorta dilatation in patients with BAV is associated with an expansion of B and helper T cells in the adventitial compartment without changes in the media. This result might indicate an antigen-driven adaptive immune response. Only dissections show an increase in helper T cells and cDC2s in the media, together with polarization of macrophages to a more M1-like phenotype. We hypothesize that antigen-specific helper T cells expand in the adventitia, migrate to the media, and then potentiate macrophages which can eventually lead to tissue degeneration. These associations could shine light on the final step in the deterioration of the aorta towards a dissection.

Figure 1. Microscopy results

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): TTW-NWO open technology grant (STW-14716), ERC-2014-StG-336454-CoNQUeST

Human pDCs Are Superior to cDC2s in Attracting Cytolytic Lymphocytes in Melanoma Patients Receiving DC Vaccination

Plasmacytoid dendritic cells (pDCs) and type 2 conventional dendritic cells (cDC2s) are currently under evaluation for use in cancer vaccines. Although both DC subsets can activate adaptive and innate lymphocytes, their capacity to recruit such cells is rarely considered. Here, we show that pDCs and cDC2s display a striking difference in chemokine secretion, which correlates with the recruitment of distinct types of immune effector cells. Activated pDCs express high levels of CXCR3 ligands and attract more CD8⁺ T cells, CD56⁺ T cells, and γδ T cells in vitro, compared to cDC2s. Skin from melanoma patients shows an influx of immune effector cells following intradermal vaccination with pDCs or cDC2s, with pDCs inducing the strongest influx of lymphocytes known to possess cytolytic activity. These findings suggest that combining both DC subsets could unite the preferred chemoattractive properties of pDCs with the superior T cell priming properties of cDC2s to ultimately enhance vaccine efficacy.

Adrenal insufficiency is a contraindication for omalizumab therapy in mast cell activation disease: risk for serum sickness

Omalizumab is an effective therapeutic humanized murine IgE antibody in many cases of primary systemic mast cell activation disease (MCAD). The present study should enable the clinician to recognize when treatment of MCAD with omalizumab is contraindicated because of the potential risk of severe serum sickness and to report our successful therapeutic strategy for such adverse event (AE). Our clinical observations, a review of the literature including the event reports in the FDA AE Reporting System, the European Medicines Agency Eudra-Vigilance databases (preferred search terms: omalizumab, Xolair®, and serum sickness) and information from the manufacturer’s Novartis database were used. Omalizumab therapy may be more likely to cause serum sickness than previously thought. In patients with regular adrenal function, serum sickness can occur after 3 to 10 days which resolves after the antigen and circulating immune complexes are cleared. If the symptoms do not resolve within a week, injection of 20 to 40 mg of prednisolone on two consecutive days could be given. However, in MCAD patients whose adrenal cortical function is completely suppressed by exogenous glucocorticoid therapy, there is a high risk that serum sickness will be masked by the MCAD and evolve in a severe form with pronounced damage of organs and tissues, potentially leading to death. Therefore, before the application of the first omalizumab dose, it is important to ensure that the function of the adrenal cortex is not significantly limited so that any occurring type III allergy can be self-limiting.

Inverse Square Lévy Walks are not Optimal Search Strategies for d≥2

The Lévy hypothesis states that inverse square Lévy walks are optimal search strategies because they maximize the encounter rate with sparse, randomly distributed, replenishable targets. It has served as a theoretical basis to interpret a wealth of experimental data at various scales, from molecular motors to animals looking for resources, putting forward the conclusion that many living organisms perform Lévy walks to explore space because of their optimal efficiency. Here we provide analytically the dependence on target density of the encounter rate of Lévy walks for any space dimension d; in particular, this scaling is shown to be independent of the Lévy exponent α for the biologically relevant case d≥2, which proves that the founding result of the Lévy hypothesis is incorrect. As a consequence, we show that optimizing the encounter rate with respect to α is irrelevant: it does not change the scaling with density and can lead virtually to any optimal value of α depending on system dependent modeling choices. The conclusion that observed inverse square Lévy patterns are the result of a common selection process based purely on the kinetics of the search behavior is therefore unfounded.

Local Attachment Explains Small World-like Properties of Fibroblastic Reticular Cell Networks in Lymph Nodes

Fibroblastic reticular cells (FRCs) form a cellular network that serves as the structural backbone of lymph nodes and facilitates lymphocyte migration. In mice, this FRC network has been found to have small-world properties. Using a model based on geographical preferential attachment, we simulated the formation of a variety of cellular networks and show that similar small-world properties robustly emerge under such natural conditions. By estimating the parameters of this model, we generated FRC network representations with realistic topological properties. We found that the topological properties change markedly when the network is expanded from a thin slice to a three-dimensional cube. Typical small-world properties were found to persist as network size was increased. The simulated networks were very similar to two-dimensional and three-dimensional lattice networks. According to the used metrics, these lattice networks also have small-world properties, indicating that lattice likeness is sufficient to become classified as a small-world network. Our results explain why FRC networks have small-world properties and provide a framework for simulating realistic FRC networks.

Immature Neutrophils Released in Acute Inflammation Exhibit Efficient Migration despite Incomplete Segmentation of the Nucleus

Acute inflammation recruits neutrophils with a band-shaped nucleus to the circulation. This neutrophil population was recently shown to have superior antibacterial capacity. Early recruitment of banded neutrophils to an infection site will likely improve the outcome of the immune response, yet it critically depends on efficient migration. However, the current dogma states that the segmentation of the mature neutrophil nucleus has evolved to favor migration through narrow pores as found between endothelial cells and in the interstitium. Therefore, we hypothesized that banded neutrophils migrate less efficiently than neutrophils with segmented nuclei, whereas recently described neutrophils with hypersegmented nuclei would in turn migrate more efficiently. Acute inflammation was evoked in a human model of experimental endotoxemia to recruit neutrophil subsets with different nuclear segmentation to the circulation. To simulate migration toward an infection site, migration of the subsets was studied in in vitro models of transendothelial migration or interstitial chemokinesis and chemotaxis. In both models, nuclear segmentation did not increase migration speed. In dense collagen matrices, the speed of the hypersegmented neutrophils was even reduced compared with the banded neutrophils. Fluorescence microscopy suggested that the hypersegmented neutrophils displayed reduced rear release and deposited more membrane vesicles. Vice versa, migration through narrow pores did not induce nuclear segmentation in the neutrophils. In conclusion, like neutrophils with a segmented nucleus, the banded subset exhibited efficient migration through narrow pores. These findings suggest that the nucleus does not preclude the banded subset from reaching an infection site.

Deep Sequencing Reveals Transient Segregation of T Cell Repertoires in Splenic T Cell Zones during an Immune Response

Immunological differences between hosts, such as diverse TCR repertoires, are widely credited for reducing the risk of pathogen spread and adaptation in a population. Within-host immunological diversity might likewise be important for robust pathogen control, but to what extent naive TCR repertoires differ across different locations in the same host is unclear. T cell zones (TCZs) in secondary lymphoid organs provide secluded microenvironmental niches. By harboring distinct TCRs, such niches could enhance within-host immunological diversity. In contrast, rapid T cell migration is expected to dilute such diversity. In this study, we combined tissue microdissection and deep sequencing of the TCR β-chain to examine the extent to which TCR repertoires differ between TCZs in murine spleens. In the absence of Ag, we found little evidence for differences between TCZs of the same spleen. Yet, 3 d after immunization with sheep RBCs, we observed a >10-fold rise in the number of clones that appeared to localize to individual zones. Remarkably, these differences largely disappeared at 4 d after immunization, when hallmarks of an ongoing immune response were still observed. These data suggest that in the absence of Ag, any repertoire differences observed between TCZs of the same host can largely be attributed to random clone distribution. Upon Ag challenge, TCR repertoires in TCZs first segregate and then homogenize within days. Such "transient mosaic" dynamics could be an important barrier for pathogen adaptation and spread during an immune response.

Adjustment for time-invariant and time-varying confounders in 'unexplained residuals' models for longitudinal data within a causal framework and associated challenges

‘Unexplained residuals’ models have been used within lifecourse epidemiology to model an exposure measured longitudinally at several time points in relation to a distal outcome. It has been claimed that these models have several advantages, including: the ability to estimate multiple total causal effects in a single model, and additional insight into the effect on the outcome of greater-than-expected increases in the exposure compared to traditional regression methods. We evaluate these properties and prove mathematically how adjustment for confounding variables must be made within this modelling framework. Importantly, we explicitly place unexplained residual models in a causal framework using directed acyclic graphs. This allows for theoretical justification of appropriate confounder adjustment and provides a framework for extending our results to more complex scenarios than those examined in this paper. We also discuss several interpretational issues relating to unexplained residual models within a causal framework. We argue that unexplained residual models offer no additional insights compared to traditional regression methods, and, in fact, are more challenging to implement; moreover, they artificially reduce estimated standard errors. Consequently, we conclude that unexplained residual models, if used, must be implemented with great care.

Robust causal inference using directed acyclic graphs: the R package 'dagitty'

Directed acyclic graphs (DAGs), which offer systematic representations of causal relationships, have become an established framework for the analysis of causal inference in epidemiology, often being used to determine covariate adjustment sets for minimizing confounding bias. DAGitty is a popular web application for drawing and analysing DAGs. Here we introduce the R package 'dagitty', which provides access to all of the capabilities of the DAGitty web application within the R platform for statistical computing, and also offers several new functions. We describe how the R package 'dagitty' can be used to: evaluate whether a DAG is consistent with the dataset it is intended to represent; enumerate 'statistically equivalent' but causally different DAGs; and identify exposure-outcome adjustment sets that are valid for causally different but statistically equivalent DAGs. This functionality enables epidemiologists to detect causal misspecifications in DAGs and make robust inferences that remain valid for a range of different DAGs. The R package 'dagitty' is available through the comprehensive R archive network (CRAN) at [https://cran.r-project.org/web/packages/dagitty/]. The source code is available on github at [https://github.com/jtextor/dagitty]. The web application 'DAGitty' is free software, licensed under the GNU general public licence (GPL) version 2 and is available at [http://dagitty.net/].

Transmembrane Helices Are an Overlooked Source of Major Histocompatibility Complex Class I Epitopes

About a fourth of the human proteome is anchored by transmembrane helices (TMHs) to lipid membranes. TMHs require multiple hydrophobic residues for spanning membranes, and this shows a striking resemblance with the requirements for peptide binding to major histocompatibility complex (MHC) class I. It, therefore, comes as no surprise that bioinformatics analysis predicts an over-representation of TMHs among strong MHC class I (MHC-I) binders. Published peptide elution studies confirm that TMHs are indeed presented by MHC-I. This raises the question how membrane proteins are processed for MHC-I (cross-)presentation, with current research focusing on soluble antigens. The presentation of membrane-buried peptides is likely important in health and disease, as TMHs are considerably conserved and their presentation might prevent escape mutations by pathogens. Therefore, it could contribute to the disease correlations described for many human leukocyte antigen haplotypes.

Harnessing RNA sequencing for global, unbiased evaluation of two new adjuvants for dendritic-cell immunotherapy

Effective stimulation of immune cells is crucial for the success of cancer immunotherapies. Current approaches to evaluate the efficiency of stimuli are mainly defined by known flow cytometry-based cell activation or cell maturation markers. This method however does not give a complete overview of the achieved activation state and may leave important side effects unnoticed. Here, we used an unbiased RNA sequencing (RNA-seq)-based approach to compare the capacity of four clinical-grade dendritic cell (DC) activation stimuli used to prepare DC-vaccines composed of various types of DC subsets; the already clinically applied GM-CSF and Frühsommer meningoencephalitis (FSME) prophylactic vaccine and the novel clinical grade adjuvants protamine-RNA complexes (pRNA) and CpG-P. We found that GM-CSF and pRNA had similar effects on their target cells, whereas pRNA and CpG-P induced stronger type I interferon (IFN) expression than FSME. In general, the pathways most affected by all stimuli were related to immune activity and cell migration. GM-CSF stimulation, however, also induced a significant increase of genes related to nonsense-mediated decay, indicating a possible deleterious effect of this stimulus. Taken together, the two novel stimuli appear to be promising alternatives. Our study demonstrates how RNA-seq based investigation of changes in a large number of genes and gene groups can be exploited for fast and unbiased, global evaluation of clinical-grade stimuli, as opposed to the general limited evaluation of a pre-specified set of genes, by which one might miss important biological effects that are detrimental for vaccine efficacy.

Local fit evaluation of structural equation models using graphical criteria

Evaluation of model fit is critically important for every structural equation model (SEM), and sophisticated methods have been developed for this task. Among them are the χ² goodness-of-fit test, decomposition of the χ², derived measures like the popular root mean square error of approximation (RMSEA) or comparative fit index (CFI), or inspection of residuals or modification indices. Many of these methods provide a global approach to model fit evaluation: A single index is computed that quantifies the fit of the entire SEM to the data. In contrast, graphical criteria like d-separation or trek-separation allow derivation of implications that can be used for local fit evaluation, an approach that is hardly ever applied. We provide an overview of local fit evaluation from the viewpoint of SEM practitioners. In the presence of model misfit, local fit evaluation can potentially help in pinpointing where the problem with the model lies. For models that do fit the data, local tests can identify the parts of the model that are corroborated by the data. Local tests can also be conducted before a model is fitted at all, and they can be used even for models that are globally underidentified. We discuss appropriate statistical local tests, and provide applied examples. We also present novel software in R that automates this type of local fit evaluation. (PsycINFO Database Record

The Reticular Cell Network: A Robust Backbone for Immune Responses

Lymph nodes are meeting points for circulating immune cells. A network of reticular cells that ensheathe a mesh of collagen fibers crisscrosses the tissue in each lymph node. This reticular cell network distributes key molecules and provides a structure for immune cells to move around on. During infections, the network can suffer damage. A new study has now investigated the network's structure in detail, using methods from graph theory. The study showed that the network is remarkably robust to damage: it can still support immune responses even when half of the reticular cells are destroyed. This is a further important example of how network connectivity achieves tolerance to failure, a property shared with other important biological and nonbiological networks.

T-cell Landscape in a Primary Melanoma Predicts the Survival of Patients with Metastatic Disease after Their Treatment with Dendritic Cell Vaccines

Tumor-infiltrating lymphocytes appear to be a predictor of survival in many cancers, including cutaneous melanoma. We applied automated multispectral imaging to determine whether density and distribution of T cells within primary cutaneous melanoma tissue correlate with survival of metastatic melanoma patients after dendritic cell (DC) vaccination. CD3(+) T cell infiltration in primary tumors from 77 metastatic melanoma patients was quantified using the ratio of intratumoral versus peritumoral T-cell densities (I/P ratio). Patients with longer survival after DC vaccination had stronger T-cell infiltration than patients with shorter survival in a discovery cohort of 19 patients (P = 0.000026) and a validation cohort of 39 patients (P = 0.000016). I/P ratio was the strongest predictor of survival in a multivariate analysis including M substage and serum lactate dehydrogenase level. To evaluate I/P ratio as a predictive biomarker, we analyzed 19 chemotherapy-treated patients. Longer survival times of DC-vaccinated compared with chemotherapy-treated patients was observed for high (P = 0.000566), but not low (P = 0.154) I/P ratios. In conclusion, T-cell infiltration into primary melanoma is a strong predictor of survival after DC vaccination in metastatic melanoma patients who, on average, started this therapy several years after primary tumor resection. The infiltration remains predictive even after adjustment for late-stage prognostic markers. Our findings suggest that the I/P ratio is a potential predictive biomarker for treatment selection. Cancer Res; 76(12); 3496-506. ©2016 AACR.

HLA Preferences for Conserved Epitopes: A Potential Mechanism for Hepatitis C Clearance

Hepatitis C virus (HCV) infections affect more than 170 million people worldwide. Most of these individuals are chronically infected, but some clear the infection rapidly. Host factors seem to play a key role in HCV clearance, among them are the human leukocyte antigen (HLA) class I molecules. Certain HLA molecules, e.g., B*27 and B*57, are associated with viral clearance. To identify potential mechanisms for these associations, we assess epitope distribution differences between HLA molecules using experimentally verified and in silico predicted HCV epitopes. Specifically, we show that the NS5B protein harbors the largest fraction of conserved regions among all HCV proteins. Such conserved regions could be good targets for cytotoxic T-cell (CTL) responses. We find that the protective HLA-B*27 molecule preferentially presents cytotoxic T-cell (CTL) epitopes from NS5B and, in general, presents the most strongly conserved epitopes among the 23 HLA molecules analyzed. In contrast, HLA molecules known to be associated with HCV persistence do not have similar preferences and appear to target the variable P7 protein. Overall, our analysis suggests that by targeting highly constrained - and thereby conserved - regions of HCV, the protective HLA molecule HLA-B*27 reduces the ability of HCV to escape the cytotoxic T-cell response of the host. For visualizing the distribution of both experimentally verified and predicted epitopes across the HCV genome, we created the HCV epitope browser, which is available at theory.bio.uu.nl/ucqi/hcv.

Crawling and Gliding: A Computational Model for Shape-Driven Cell Migration

Cell migration is a complex process involving many intracellular and extracellular factors, with different cell types adopting sometimes strikingly different morphologies. Modeling realistically behaving cells in tissues is computationally challenging because it implies dealing with multiple levels of complexity. We extend the Cellular Potts Model with an actin-inspired feedback mechanism that allows small stochastic cell rufflings to expand to cell protrusions. This simple phenomenological model produces realistically crawling and deforming amoeboid cells, and gliding half-moon shaped keratocyte-like cells. Both cell types can migrate randomly or follow directional cues. They can squeeze in between other cells in densely populated environments or migrate collectively. The model is computationally light, which allows the study of large, dense and heterogeneous tissues containing cells with realistic shapes and migratory properties.

Cell migration is involved in vital processes like morphogenesis, regeneration and immune system responses, but can also play a central role in pathological processes like metastasization. Computational models have been successfully employed to explain how single cells migrate, and to study how diverse cell-cell interactions contribute to tissue level behavior. However, there are few models that implement realistic cell shapes in multicellular simulations. The method we present here is able to reproduce two different types of motile cells—amoeboid and keratocyte-like cells. Amoeboid cells are highly motile and deform frequently; many cells can act amoeboid in certain circumstances e.g., immune system cells, epithelial cells, individually migrating cancer cells. Keratocytes are (fish) epithelial cells which are famous for their ability to preserve their shape and direction when migrating individually; during wound healing, keratocytes migrate collectively, in sheets, to the site needing reepithelialization. Our method is computationally simple, improves the realism of multicellular simulations and can help assess the tissue level impact of specific cell shapes. For example, it can be employed to study the tissue scanning strategies of leukocytes, the circumstances in which cancer cells adopt amoeboid migration strategies, or the collective migration of keratocytes.

Blood and Cerebrospinal Fluid α-Tocopherol and Selenium Concentrations in Neonatal Foals with Neuroaxonal Dystrophy

Background

Equine neuroaxonal dystrophy/equine degenerative myeloencephalopathy (NAD/EDM) is a neurodegenerative disorder affecting genetically predisposed foals maintained on α‐tocopherol (α‐TP)‐deficient diet.

Objective

Intramuscular α‐TP and selenium (Se) administration at 4 days of age would have no significant effect on serum or cerebrospinal fluid (CSF) α‐TP in healthy foals. Serum and CSF α‐TP, but not Se, would be significantly decreased in NAD/EDM‐affected foals during first year of life.

Animals

Fourteen Quarter horse foals; 10 healthy foals supplemented with 0.02 mL/kg injectable α‐TP and Se (n = 5) or saline (n = 5) at 4 days of age and 4 unsupplemented NAD/EDM‐affected foals.

Methods

Complete neurologic examinations were performed, blood and CSF were collected before (4 days of age) and after supplementation at 10, 30, 60, 120, 180, 240, and 360 days of age. Additional blood collections occurred at 90, 150, 210, and 300 days. At 540 days, NAD/EDM‐affected foals and 1 unsupplemented healthy foal were euthanized and necropsies performed.

Results

Significant decreases in blood, CSF α‐TP and Se found in the first year of life in all foals, with most significant changes in serum α‐TP from 4–150 days. Dam α‐TP and Se significantly influenced blood concentrations in foals. Injection of α‐TP and Se did not significantly increase CSF Se, blood or CSF α‐TP in healthy foals. NAD/EDM‐affected foals had significantly lower CSF α‐TP through 120 days.

Conclusions and Clinical Importance

Injection of α‐TP and Se at 4 days of age does not significantly increase blood or CSF α‐TP. Despite all 14 foals remaining deficient in α‐TP, only the 4 genetically predisposed foals developed NAD/EDM.

Age-Dependent Cell Trafficking Defects in Draining Lymph Nodes Impair Adaptive Immunity and Control of West Nile Virus Infection

Impaired immune responses in the elderly lead to reduced vaccine efficacy and increased susceptibility to viral infections. Although several groups have documented age-dependent defects in adaptive immune priming, the deficits that occur prior to antigen encounter remain largely unexplored. Herein, we identify novel mechanisms for compromised adaptive immunity that occurs with aging in the context of infection with West Nile virus (WNV), an encephalitic flavivirus that preferentially causes disease in the elderly. An impaired IgM and IgG response and enhanced vulnerability to WNV infection during aging was linked to delayed germinal center formation in the draining lymph node (DLN). Adoptive transfer studies and two-photon intravital microscopy revealed a decreased trafficking capacity of donor naïve CD4+ T cells from old mice, which manifested as impaired T cell diapedesis at high endothelial venules and reduced cell motility within DLN prior to antigen encounter. Furthermore, leukocyte accumulation in the DLN within the first few days of WNV infection or antigen-adjuvant administration was diminished more generally in old mice and associated with a second aging-related defect in local cytokine and chemokine production. Thus, age-dependent cell-intrinsic and environmental defects in the DLN result in delayed immune cell recruitment and antigen recognition. These deficits compromise priming of early adaptive immune responses and likely contribute to the susceptibility of old animals to acute WNV infection.

Lymphatic Interventions for Treatment of Chylothorax

PURPOSE

To determine effectiveness of lymphatic interventional procedures for treatment of chylothorax.

MATERIAL AND METHODS

Analysis of interventions performed from 2001 to 2014.

RESULTS

In 21 patients with therapy resistant chylothorax a lymphatic radiological intervention was attempted, which could be performed in 19 cases: 17 thoracic duct embolizations (15 transabdominal, one transzervical and one retrograde transvenous procedure), 2 percutaneous destructions of lymphatic vessels, one CT-guided injection of ethanol next to a duplicated thoracic duct. Fourteen of seventeen (82.3 %) of the technically successful embolizations lead to clinical cure. This encluded three patients with prior unsuccessful surgical thoracic duct ligation. Also the injection of ethanol was clinically effective. Complications were a bile peritonitis requiring operation, and one clinical deterioration of unknown cause.

CONCLUSION

Interventional lymphatic procedures allow for effective treatment in many cases of chylothorax, and should be considered early during treatment.

KEY POINTS

• Thoracic duct embolization is an effective treatment method for chylothorax. • If embolization is impossible, percutaneous lymphatic destruction or injection of sclerosants/tissue adhesive next to the thoracic duct may be tried.

An open data ecosystem for cell migration research

Cell migration research has recently become both a high content and a high throughput field thanks to technological, computational, and methodological advances. Simultaneously, however, urgent bioinformatics needs regarding data management, standardization, and dissemination have emerged. To address these concerns, we propose to establish an open data ecosystem for cell migration research.

Random migration and signal integration promote rapid and robust T cell recruitment

To fight infections, rare T cells must quickly home to appropriate lymph nodes (LNs), and reliably localize the antigen (Ag) within them. The first challenge calls for rapid trafficking between LNs, whereas the second may require extensive search within each LN. Here we combine simulations and experimental data to investigate which features of random T cell migration within and between LNs allow meeting these two conflicting demands. Our model indicates that integrating signals from multiple random encounters with Ag-presenting cells permits reliable detection of even low-dose Ag, and predicts a kinetic feature of cognate T cell arrest in LNs that we confirm using intravital two-photon data. Furthermore, we obtain the most reliable retention if T cells transit through LNs stochastically, which may explain the long and widely distributed LN dwell times observed in vivo. Finally, we demonstrate that random migration, both between and within LNs, allows recruiting the majority of cognate precursors within a few days for various realistic infection scenarios. Thus, the combination of two-scale stochastic migration and signal integration is an efficient and robust strategy for T cell immune surveillance.

Activated CD4+ T cells enter the splenic T-cell zone and induce autoantibody-producing germinal centers through bystander activation

CD4(+) T (helper) cells migrate in huge numbers through lymphoid organs. However, little is known about traffic routes and kinetics of CD4(+) T-cell subsets within different organ compartments. Such information is important because there are indications that CD4(+) T cells may influence the function of microenvironments depending on their developmental stage. Therefore, we investigated the migration of resting (naïve), activated, and recently activated (memory) CD4(+) T cells through the different compartments of the spleen. Resting and recently activated CD4(+) T cells were separated from thoracic duct lymph and activated CD4(+) T cells were generated in vitro by cross-linking the T-cell receptor and CD28. The present study shows that all three CD4(+) T-cell subsets selectively accumulate in the T-cell zone of the spleen. However, only activated T cells induce the formation of germinal centers (GCs) and autoantibodies in rats and mice. Our results suggest that in a two-step process they first activate B cells independent of the T-cell receptor repertoire and CD40 ligand (CD154) expression. The activated B cells then form GCs whereby CD154-dependent T-cell help is needed. Thus, activated T cells may contribute to the development of autoimmune diseases by activating autoreactive B cells in an Ag-independent manner.