Simulation studies of social systems: telling the story based on provenance patterns.

Social simulation studies are complex. They typically combine various data sources and hypotheses about the system's mechanisms that are integrated by intertwined processes of model building, simulation experiment execution and analysis. Various documentation approaches exist to increase the transparency and traceability of complex social simulation studies. Provenance standards enable the formalization of information on sources and activities, which contribute to the generation of an entity, in a queryable and computationally accessible manner. Provenance patterns can be defined as constraints on the relationships between specific types of activities and entities of a simulation study. In this paper, we refine the provenance pattern-based approach to address specific challenges of social agent-based simulation studies. Specifically, we focus on the activities and entities involved in collecting and analysing primary data about human decisions, and the collection and quality assessment of secondary data. We illustrate the potential of this approach by applying it to central activities and results of an agent-based simulation project and by presenting its implementation in a web-based tool.

Normalization of Snai1-mediated vessel dysfunction increases drug response in cancer.

Blood vessels in tumors are often dysfunctional. This impairs the delivery of therapeutic agents to and distribution among the cancer cells. Subsequently, treatment efficacy is reduced, and dose escalation can increase adverse effects on non-malignant tissues. The dysfunctional vessel phenotypes are attributed to aberrant pro-angiogenic signaling, and anti-angiogenic agents can ameliorate traits of vessel dysfunctionality. However, they simultaneously reduce vessel density and thereby impede drug delivery and distribution. Exploring possibilities to improve vessel functionality without compromising vessel density in the tumor microenvironment, we evaluated transcription factors (TFs) involved in epithelial-mesenchymal transition (EMT) as potential targets. Based on similarities between EMT and angiogenic activation of endothelial cells, we hypothesized that these TFs, Snai1 in particular, might serve as key regulators of vessel dysfunctionality. In vitro, experiments demonstrated that Snai1 (similarly Slug and Twist1) regulates endothelial permeability, permissiveness for tumor cell transmigration, and tip/stalk cell formation. Endothelial-specific, heterozygous knock-down of Snai1 in mice improved vascular quality in implanted tumors. This resulted in better oxygenation and reduced metastasis. Notably, the tumors in Snai1KD mice responded significantly better to chemotherapeutics as drugs were transported into the tumors at strongly increased rates and more homogeneously distributed. Thus, we demonstrate that restoring vessel homeostasis without affecting vessel density is feasible in malignant tumors. Combining such vessel re-engineering with anti-cancer drugs allows for strategic treatment approaches that reduce treatment toxicity on non-malignant tissues.

Basal-like mammary carcinomas stimulate cancer stem cell properties through AXL-signaling to induce chemotherapy resistance.

Basal-like breast cancer (BLBC) is the most aggressive and heterogeneous breast cancer (BC) subtype. Conventional chemotherapies represent next to surgery the most frequently employed treatment options. Unfortunately, resistant tumor phenotypes often develop, resulting in therapeutic failure. To identify the early events occurring upon the first drug application and initiating chemotherapy resistance in BLBC, we leveraged the WAP-T syngeneic mammary carcinoma mouse model and we developed a strategy combining magnetic-activated cell sorting (MACS)-based tumor cell enrichment with high-throughput transcriptome analyses. We discovered that chemotherapy induced a massive gene expression reprogramming toward stemness acquisition to tolerate and survive the cytotoxic treatment in vitro and in vivo. Retransplantation experiments revealed that one single cycle of cytotoxic drug combination therapy (Cyclophosphamide, Adriamycin and 5-Fluorouracil) suffices to induce resistant tumor cell phenotypes in vivo. We identified Axl and its ligand Pros1 as highly induced genes driving cancer stem cell (CSC) properties upon chemotherapy in vivo and in vitro. Furthermore, from our analysis of BLBC patient datasets, we found that AXL expression is also strongly correlated with CSC-gene signatures, a poor response to conventional therapies and worse survival outcomes in those patients. Finally, we demonstrate that AXL inhibition sensitized BLBC-cells to cytotoxic treatment in vitro. Together, our data support AXL as a promising therapeutic target to optimize the efficiency of conventional cytotoxic therapies in BLBC.

A basic macroeconomic agent-based model for analyzing monetary regime shifts.

In macroeconomics, an emerging discussion of alternative monetary systems addresses the dimensions of systemic risk in advanced financial systems. Monetary regime changes with the aim of achieving a more sustainable financial system have already been discussed in several European parliaments and were the subject of a referendum in Switzerland. However, their effectiveness and efficacy concerning macro-financial stability are not well-known. This paper defines the economic requirements for modeling the current monetary system and introduces the corresponding macroeconomic agent-based model (MABM) in a continuous-time stochastic agent-based simulation environment with a provenance model. This MABM aims to present a starting point for exploring and analyzing monetary reforms. In this context, the monetary system affects the lending potential of banks and might impact the dynamics of financial crises. MABMs are predestined to replicate emergent financial crisis dynamics, analyze institutional changes within a financial system, and thus measure macro-financial stability. The used simulation environment makes the model more accessible and facilitates exploring the impact of different hypotheses and mechanisms in a less complex way. Moreover, the model replicates a wide range of stylized economic facts, which validates it as an analysis tool to implement and compare monetary regime shifts.

ROBO3s: a novel ROBO3 short isoform promoting breast cancer aggressiveness.

Basal-like breast cancer (BLBC) is a highly aggressive breast cancer subtype frequently associated with poor prognosis. Due to the scarcity of targeted treatment options, conventional cytotoxic chemotherapies frequently remain the standard of care. Unfortunately, their efficacy is limited as BLBC malignancies rapidly develop resistant phenotypes. Using transcriptomic and proteomic approaches in human and murine BLBC cells, we aimed to elucidate the molecular mechanisms underlying the acquisition of aggressive and chemotherapy-resistant phenotypes in these mammary tumors. Specifically, we identified and characterized a novel short isoform of Roundabout Guidance Receptor 3 (ROBO3s), upregulated in BLBC in response to chemotherapy and encoding for a protein variant lacking the transmembrane domain. We established an important role for the ROBO3s isoform, mediating cancer stem cell properties by stimulating the Hippo-YAP signaling pathway, and thus driving resistance of BLBC cells to cytotoxic drugs. By uncovering the conservation of ROBO3s expression across multiple cancer types, as well as its association with reduced BLBC-patient survival, we emphasize its potential as a prognostic marker and identify a novel attractive target for anti-cancer drug development.

Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race.

Individuals' decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for Linked Lives (ML3) to describe the diverse decision processes of linked lives succinctly in continuous time. The context of individuals is modelled by networks the individual is part of, such as family ties and other social networks. Central concepts, such as behaviour conditional on agent attributes, age-dependent behaviour, and stochastic waiting times, are tightly integrated in the language. Thereby, alternative decisions are modelled by concurrent processes that compete by stochastic race. Using a migration model, we demonstrate how this allows for compact description of complex decisions, here based on the Theory of Planned Behaviour. We describe the challenges for the simulation algorithm posed by stochastic race between multiple concurrent complex decisions.