Highlights d A pan-tissue AHR signature identifies IL4I1 as a major AHRactivating enzyme d IL4I1-mediated Trp catabolism yields indoles and kynurenic acid that activate the AHR d IL4I1 promotes AHR-driven cancer cell motility and suppresses adaptive immunity d IL4I1 enhances CLL progression and is induced by immune checkpoint blockade

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Human plasmacytoid dendritic cells (pDC) are important modulators of adaptive T cell responses during viral infections. Recently, we found that human pDC produce the serine protease granzyme B (GrB), thereby regulating T cell proliferation in a GrB-dependent manner. In this study, we demonstrate that intrinsic GrB production by pDC is significantly inhibited in vitro and in vivo by clinically used vaccines against viral infections such as tick-borne encephalitis. We show that pDC GrB levels inversely correlate with the proliferative response of coincubated T cells and that GrB suppression by a specific Ab or a GrB substrate inhibitor results in enhanced T cell proliferation, suggesting a predominant role of GrB in pDC-dependent T cell licensing. Functionally, we demonstrate that GrBhigh but not GrBlow pDC transfer GrB to T cells and may degrade the ζ-chain of the TCR in a GrB-dependent fashion, thereby providing a possible explanation for the observed T cell suppression by GrB-expressing pDC. Modulation of pDC-derived GrB activity represents a previously unknown mechanism by which both antiviral and vaccine-induced T cell responses may be regulated in vivo. Our results provide novel insights into pDC biology during vaccinations and may contribute to an improvement of prophylactic and therapeutic vaccines.

Background and purpose Relative signal intensity of acute ischemic stroke lesions in fluid-attenuated inversion recovery (FLAIR-rSI) magnetic resonance imaging is associated with time elapsed since stroke onset with higher intensities signifying longer time intervals. In the randomized controlled WAKE-UP trial, intravenous alteplase was effective in patients with unknown onset stroke selected by visual assessment of DWI-FLAIR mismatch, i.e., in those with no marked FLAIR hyperintensity in the region of the acute DWI lesion. In this post-hoc analysis, we investigated if quantitatively measured FLAIR-rSI modifies treatment effect of intravenous alteplase. Methods FLAIR-rSI of stroke lesions was measured relative to signal intensity in a mirrored region in the contralesional hemisphere. The relationship between FLAIR-rSI and treatment effect on functional outcome assessed by the modified Rankin Scale (mRS) after 90 days was analysed by binary logistic regression using different endpoints, i.e., favourable outcome defined as mRS 0-1, independent outcome defined as mRS 0-2, ordinal analysis of mRS scores (shift analysis). All models were adjusted for NIHSS at symptom onset and stroke lesion volume. Results FLAIR-rSI was successfully quantified in stroke lesions in 433 patients (86% of 503 patients included in WAKE-UP). Mean FLAIR-rSI was 1.06 (SD 0.09). Interaction of FLAIR-rSI and treatment effect was not significant for mRS 0-1 (p=0.169) and shift analysis (p=0.086), but 2 reached significance for mRS 0-2 (p=0.004). We observed a smooth continuing trend of decreasing treatment effects in relation to clinical endpoints with increasing FLAIR-rSI. Conclusion In patients in whom no marked parenchymal FLAIR hyperintensity was detected by visual judgement in the WAKE-UP trial, higher FLAIR-rSI of DWI lesions was associated with decreased treatment effects of intravenous thrombolysis. This parallels the known association of treatment effect and elapsing time of stroke onset.

Tryptophan (Trp)-catabolic enzymes (TCEs) produce metabolites that activate the aryl hydrocarbon receptor (AHR) and promote tumor progression and immunosuppression in glioblastoma. As therapies targeting TCEs or AHR become available, a better understanding of Trp metabolism is required. Methods: The combination of LC-MS/MS with chemical isobaric labeling enabled the simultaneous quantitative comparison of Trp and its amino group-bearing metabolites in multiple samples. We applied this method to the sera of a cohort of 43 recurrent glioblastoma patients and 43 age- and sex-matched healthy controls. Tumor volumes were measured in MRI data using an artificial neural network-based approach. MALDI MSI visualized Trp and its direct metabolite N -formylkynurenine (FK) in glioblastoma tissue. Analysis of scRNA-seq data was used to detect the presence of Trp metabolism and AHR activity in different cell types in glioblastoma. Results: Compared to healthy controls, glioblastoma patients showed decreased serum Trp levels. Surprisingly, the levels of Trp metabolites were also reduced. The decrease became smaller with more enzymatic steps between Trp and its metabolites, suggesting that Trp availability controls the levels of its systemic metabolites. High tumor volume associated with low systemic metabolite levels and low systemic kynurenine levels associated with worse overall survival. MALDI MSI demonstrated heterogeneity of Trp catabolism across glioblastoma tissues. Analysis of scRNA-seq data revealed that genes involved in Trp metabolism were expressed in almost all the cell types in glioblastoma and that most cell types, in particular macrophages and T cells, exhibited AHR activation. Moreover, high AHR activity associated with reduced overall survival in the glioblastoma TCGA dataset. Conclusion: The novel techniques we developed could support the identification of patients that may benefit from therapies targeting TCEs or AHR activation.

Mass spectrometry imaging (MSI) vows to enable simultaneous spatially-resolved investigation of hundreds of metabolites in tissue sections, but it still relies on poorly defined ion images for data interpretation. Here, we outline moleculaR, a computational framework (https://github.com/CeMOS-Mannheim/moleculaR) that introduces probabilistic mapping and point-for-point statistical testing of metabolites in tissue. It enables collective molecular projections and consequently spatially-resolved investigation of ion milieus, lipid pathways or user-defined biomolecular ensembles within the same image.

Mass spectrometry imaging vows to enable simultaneous spatially resolved investigation of hundreds of metabolites in tissues, but it primarily relies on traditional ion images for non-data-driven metabolite visualization and analysis. The rendering and interpretation of ion images neither considers nonlinearities in the resolving power of mass spectrometers nor does it yet evaluate the statistical significance of differential spatial metabolite abundance. Here, we outline the computational framework moleculaR (https://github.com/CeMOS-Mannheim/moleculaR) that is expected to improve signal reliability by data-dependent Gaussian-weighting of ion intensities and that introduces probabilistic molecular mapping of statistically significant nonrandom patterns of relative spatial abundance of metabolites-of-interest in tissue. moleculaR also enables cross-tissue statistical comparisons and collective molecular projections of entire biomolecular ensembles followed by their spatial statistical significance evaluation on a single tissue plane. It thereby fosters the spatially resolved investigation of ion milieus, lipid remodeling pathways, or complex scores like the adenylate energy charge within the same image.