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Background and aims Autoimmune hepatitis (AIH) is a chronic liver disease that regularly relapses when immunosuppression is tapered. It is thought to be driven by T-cells, whereas the etiologic impact of an apparently deregulated B lineage system, as evidenced by hypergammaglobulinemia and autoantibodies, remains elusive. We set out to investigate T and B cell repertoires supporting chronic inflammation in AIH. Approach and results T and B cell receptor (TCR/BCR) and human leukocyte antigen (HLA) next-generation immunosequencing were used to record immune signatures from a cohort of 60 patients with AIH and disease controls. Blood and liver B lineage immune metrics were not indicative of a dominant directional antigen selection apart from a slight skewing of IGHV-J genes. More importantly, we found strong AIH-specific TRBV-J skewing not attributable to the HLA-DRB1 specificities of the cohort. This TCR repertoire bias was generated as a result of peripheral T cell (de)selection and persisted in disease remission. Using a clustering algorithm according to antigenic specificity, we identified liver TCR clusters that were shared between patients with AIH but were absent or deselected in patients with other liver pathologies. Conclusions Patients with AIH show profound and persisting T-cell architectural changes that may explain high relapse rates after tapering immunosuppression. Liver T-cell clusters shared between patients may mediate liver damage and warrant further study.

Effective treatment of invasive lobular carcinoma (ILC) of the breast is hampered by late detection, invasive growth, distant metastasis, and poor response to chemotherapy. Phosphoinositide 3-kinase (PI3K) signaling, one of the major druggable oncogenic signaling networks, is frequently activated in ILC. We investigated treatment response and resistance to AZD8055, an inhibitor of mammalian target of rapamycin (mTOR), in the K14-cre;Cdh1Flox/Flox;Trp53Flox/Flox (KEP) mouse model of metastatic ILC. Inhibition of mTOR signaling blocked the growth of primary KEP tumors as well as the progression of metastatic disease. However, primary tumors and distant metastases eventually acquired resistance after long-term AZD8055 treatment, despite continued effective suppression of mTOR signaling in cancer cells. Interestingly, therapeutic responses were associated with increased expression of genes related to antigen presentation. Consistent with this observation, increased numbers of tumor-infiltrating major histocompatibility complex class II-positive (MHCII+) immune cells were observed in treatment-responsive KEP tumors. Acquisition of treatment resistance was associated with loss of MHCII+ cells and reduced expression of genes related to the adaptive immune system. The therapeutic efficacy of mTOR inhibition was reduced in Rag1−/- mice lacking mature T and B lymphocytes, compared to immunocompetent mice. Furthermore, therapy responsiveness could be partially rescued by transplanting AZD8055-resistant KEP tumors into treatment-naïve immunocompetent hosts. Collectively, these data indicate that the PI3K signaling pathway is an attractive therapeutic target in invasive lobular carcinoma, and that part of the therapeutic effect of mTOR inhibition is mediated by the adaptive immune system.

In myelodysplastic syndromes with a partial deletion of the long arm of chromosome 5, del(5q), lenalidomide is believed to reverse anergic T-cell immunity in the bone marrow resulting in suppression of the del(5q) clone. In this study we used next-generation sequencing of immunoglobulin heavy chain (IGH) and T-cell receptor beta (TRB) rearrangements in bone marrow-residing and peripheral blood-circulating lymphocytes of patients with del(5q) myelodysplastic syndromes to assess the immune architecture and track adaptive immune responses during treatment with lenalidomide. The baseline bone marrow B-cell space in patients was comparable to that of age-matched healthy controls in terms of gene usage and IGH clonality, but showed a higher percentage of hypermutated IGH sequences, indicating an expanded number of antigen-experienced B lineage cells. Bone marrow B lineage clonality decreased significantly and hypermutated IGH clones normalized upon lenalidomide treatment, well in line with the proliferative effect on healthy antigen-inexperienced B-cell precursors previously described for this drug. The T-cell space in bone marrow of patients with del(5q) myelodysplastic syndromes showed higher TRB clonality compared to that of healthy controls. Upon lenalidomide treatment, myelodysplastic syndrome-specific T-cell clusters with low to medium spontaneous generation probabilities emerged; these clusters were shared across patients, indicating a common antigen-driven T-cell response pattern. Hence, we observed B lineage diversification and generation of new, antigen-dependent T-cell clusters, compatible with a model of adaptive immunity induced against the del(5q) clone by lenalidomide. Overall, this supports the concept that lenalidomide not only alters the functional T-cell state, but also the composition of the T- and B-cell repertoires in del(5q) myelodysplastic syndromes.

OA gold Eukaryotic gene expression is regulated by transcription factors (TFs) binding to promoter as well as distal enhancers. TFs recognize short, but specific binding sites (TFBSs) that are located within the promoter and enhancer regions. Functionally relevant TFBSs are often highly conserved during evolution leaving a strong phylogenetic signal. While multiple sequence alignment (MSA) is a potent tool to detect the phylogenetic signal, the current MSA implementations are optimized to align the maximum number of identical nucleotides. This approach might result in the omission of conserved motifs that contain interchangeable nucleotides such as the ETS motif (IUPAC code: GGAW). Here, we introduce ConBind, a novel method to enhance alignment of short motifs, even if their mutual sequence similarity is only partial. ConBind improves the identification of conserved TFBSs by improving the alignment accuracy of TFBS families within orthologous DNA sequences. Functional validation of the Gfi1b + 13 enhancer reveals that ConBind identifies additional functionally important ETS binding sites that were missed by all other tested alignment tools. In addition to the analysis of known regulatory regions, our web tool is useful for the analysis of TFBSs on so far unknown DNA regions identified through ChIP-sequencing.

Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes. DOI: http://dx.doi.org/10.7554/eLife.11469.001, eLife digest Blood stem cells and blood progenitor cells replenish a person’s entire blood system throughout their life and are crucial for survival. The stem cells have the potential to become any type of blood cell – including white blood cells and red blood cells – while the progenitor cells are slightly more restricted in the types of blood cell they can become. It is important to understand how the balance of cell types is maintained because, in cancers of the blood (also known as leukaemias), this organisation is lost and some cells proliferate abnormally. Almost all of a person’s cells will contain the same genetic information, but different cell types arise when different genes are switched on or off. The genes encoding proteins called transcription factors are particularly important because the proteins can control – either by activating or repressing – many other genes. Importantly, some of these genes will encode other transcription factors, meaning that these proteins essentially work together in networks. Schütte et al. have now combined extensive biochemical experiments with computational modelling to study some of the transcription factors that define blood stem cells and blood progenitor cells in mice. Firstly, nine transcription factors, which were already known to be important in blood stem cells, were thoroughly studied in mouse cells that could be grown in the laboratory. These experiments provided an overall view of which other genes these transcription factors control. Additional targeted investigations of the nine transcription factors then revealed how these proteins act in combination to activate or repress their respective activities. With this information, Schütte et al. built a computational model, which accurately reproduced how real mouse blood stem and progenitor cells behave when, for example, a transcription factor is deleted. Furthermore, the model could also predict what happens in single cells if the amounts of the transcription factors change. Lastly, Schütte et al. studied a common type of leukaemia. The model showed that the mutations that occur in this cancer change the finely tuned balance of the nine transcription factors; this may explain why leukaemia cells behave abnormally. In future these models could be extended to more transcription factors and other cell types and cancers. DOI: http://dx.doi.org/10.7554/eLife.11469.002