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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.

Motivation: Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. Results: To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. Availability and Implementation: The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF. Contact: j.heringa@vu.nl

Motivation: Understanding the processes involved in multi-cellular pattern formation is a central problem of developmental biology, hopefully leading to many new insights, e.g. in the treatment of various diseases. Defining suitable computational techniques for development modelling, able to perform in silico simulation experiments, is an open and challenging problem. Results: Previously, we proposed a coarse-grained, quantitative approach based on the basic Petri net formalism, to mimic the behaviour of the biological processes during multicellular differentiation. Here, we apply our modelling approach to the well-studied process of Caenorhabditis elegans vulval development. We show that our model correctly reproduces a large set of in vivo experiments with statistical accuracy. It also generates gene expression time series in accordance with recent biological evidence. Finally, we modelled the role of microRNA mir-61 during vulval development and predict its contribution in stabilizing cell pattern formation. Contact: feenstra@few.vu.nl Supplementary information: Supplementary data are available at Bioinformatics online.

This position paper argues that the operational modelling approaches from the formal methods community can be applied fruitfully within the systems biology domain. The results can be complementary to the traditional mathematical descriptive modelling approaches used in systems biology. We discuss one example: a recent Petri net analysis of C. elegans vulval development.