Modeling the Effect of Deregulated Proliferation and Apoptosis on the Growth Dynamics of Epithelial Cell Populations In Vitro

AbstractWe present a three-dimensional individual cell-based, biophysical model to study the effect of normal and malfunctioning growth regulation and control on the spatial-temporal organization of growing cell populations in vitro. The model includes explicit representations of typical epithelial cell growth regulation and control mechanisms, namely 1), a cell-cell contact-mediated form of growth inhibition; 2), a cell-substrate contact-dependent cell-cycle arrest; and 3), a cell-substrate contact-dependent programmed cell death (anoikis). The model cells are characterized by experimentally accessible biomechanical and cell-biological parameters. First, we study by variation of these cell-specific parameters which of them affect the macroscopic morphology and growth kinetics of a cell population within the initial expanding phase. Second, we apply selective knockouts of growth regulation and control mechanisms to investigate how the different mechanisms collectively act together. Thereby our simulation studies cover the growth behavior of epithelial cell populations ranging from undifferentiated stem cell populations via transformed variants up to tumor cell lines in vitro. We find that the cell-specific parameters, and in particular the strength of the cell-substrate anchorage, have a significant impact on the population morphology. Furthermore, they control the efficacy of the growth regulation and control mechanisms, and consequently tune the transition from controlled to uncontrolled growth that is induced by the failures of these mechanisms. Interestingly, however, we find the qualitative and quantitative growth kinetics to be remarkably robust against variations of cell-specific parameters. We compare our simulation results with experimental findings on a number of epithelial and tumor cell populations and suggest in vitro experiments to test our model predictions

A Comprehensive Model of the Spatio-Temporal Stem Cell and Tissue Organisation in the Intestinal Crypt

We introduce a novel dynamic model of stem cell and tissue organisation in murine intestinal crypts. Integrating the molecular, cellular and tissue level of description, this model links a broad spectrum of experimental observations encompassing spatially confined cell proliferation, directed cell migration, multiple cell lineage decisions and clonal competition

Susceptibility to collagen-induced arthritis is modulated by TGFβ responsiveness of T cells

The objective of our study was to determine the regulatory effects that endogenous transforming growth factor β (TGFβ) exerts on T cells in the pathogenesis of collagen-induced arthritis (CIA). CIA was induced in transgenic mice expressing a dominant negative TGFβ type II receptor in T cells under the control of the human CD2 promoter. Clinical and histological arthritis scores were determined and experiments on disease induction and the healing phase of disease were performed. The proliferation and cytokine production of draining lymph node cells in vitro were analyzed. Transgenic mice were more susceptible to induction of CIA. The overall incidence was higher in transgenic mice than in wild-type mice (57% vs 35%, P < 0.05). Affected transgenic animals displayed a significantly higher clinical (4.5 ± 0.6 vs 1.67 ± 0.19, P = 0.001) and histological arthritis score (8.01 ± 0.9 vs 4.06 ± 1.1, P < 0.05). Draining lymph node cells of transgenic mice secreted more tumor necrosis factor α and IFNγ and proliferated more vigorously in response to collagen type II and upon CD3/CD28 costimulation in vitro. Therefore, the regulation of T cells by endogenous TGFβ is important for the maintenance of joint integrity after arthritis induction. Defects in TGFβ-signalling as a susceptibility factor for rheumatoid arthritis may warrant further investigation

Strong Expression of Chemokine Receptor CXCR4 by Renal Cell Carcinoma Correlates with Advanced Disease

Diverse chemokines and their receptors have been associated with tumor growth, tumor dissemination, and local immune escape. In different tumor entities, the level of chemokine receptor CXCR4 expression has been linked with tumor progression and decreased survival. The aim of this study was to evaluate the influence of CXCR4 expression on the progression of human renal cell carcinoma. CXCR4 expression of renal cell carcinoma was assessed by immunohistochemistry in 113 patients. Intensity of CXCR4 expression was correlated with both tumor and patient characteristics. Human renal cell carcinoma revealed variable intensities of CXCR4 expression. Strong CXCR4 expression of renal cell carcinoma was significantly associated with advanced T-status (P = .039), tumor dedifferentiation (P = .0005), and low hemoglobin (P = .039). In summary, strong CXCR4 expression was significantly associated with advanced dedifferentiated renal cell carcinoma

Assessing the impact of COVID-19 on liver cancer management (CERO-19).

BACKGROUND & AIMS: The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems and it may have heavily impacted patients with liver cancer (LC). Herein, we evaluated whether the schedule of LC screening or procedures has been interrupted or delayed because of the COVID-19 pandemic. METHODS: An international survey evaluated the impact of the COVID-19 pandemic on clinical practice and clinical trials from March 2020 to June 2020, as the first phase of a multicentre, international, and observational project. The focus was on patients with hepatocellular carcinoma or intrahepatic cholangiocarcinoma, cared for around the world during the first COVID-19 pandemic wave. RESULTS: Ninety-one centres expressed interest to participate and 76 were included in the analysis, from Europe, South America, North America, Asia, and Africa (73.7%, 17.1%, 5.3%, 2.6%, and 1.3% per continent, respectively). Eighty-seven percent of the centres modified their clinical practice: 40.8% the diagnostic procedures, 80.9% the screening programme, 50% cancelled curative and/or palliative treatments for LC, and 41.7% modified the liver transplantation programme. Forty-five out of 69 (65.2%) centres in which clinical trials were running modified their treatments in that setting, but 58.1% were able to recruit new patients. The phone call service was modified in 51.4% of centres which had this service before the COVID-19 pandemic (n = 19/37). CONCLUSIONS: The first wave of the COVID-19 pandemic had a tremendous impact on the routine care of patients with liver cancer. Modifications in screening, diagnostic, and treatment algorithms may have significantly impaired the outcome of patients. Ongoing data collection and future analyses will report the benefits and disadvantages of the strategies implemented, aiding future decision-making. LAY SUMMARY: The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems globally. Herein, we assessed the impact of the first wave pandemic on patients with liver cancer and found that routine care for these patients has been majorly disrupted, which could have a significant impact on outcomes

Stochastic system identification without an a priori chosen kinetic model—exploring feasible cell regulation with piecewise linear functions

Computational Bioscience: Cell-regulation appears more diverse than originally thought Classical cell-regulation models are often imperfectly fitting or even inconsistent with experimental data suggesting inappropriate model assumptions. Martin Hoffmann from Fraunhofer ITEM Regensburg and Jörg Galle from IZBI Leipzig analysed different protein and gene expression data using general purpose piecewise linear functions for system identification. They assessed data corresponding to various experimental techniques for their potential to determine the parameters of their models. Single-cell recordings of expression values over time were most effective for parameter identification. Generally, different and often non-classical cell-regulation models were consistent with the experimental data, even for restrictive error bounds. The authors used virtual treatment experiments to demonstrate that precise knowledge of cell regulation is important for assessing therapy effects. Their findings clearly argue in favour of system identification being performed without an a priori chosen kinetic model

Systemic therapy of advanced hepatocellular carcinoma.

For a decade, sorafenib remained the only approved first-line treatment and standard of care for advanced hepatocellular carcinoma. The treatment landscape has been evolving rapidly over the past 2 years with the approval of additional first-and second-line systemic treatments, most of which are targeted therapies. The expected approval of immunotherapies constitutes a paradigm shift: for the first time in years, a checkpoint inhibitor in combination with a VEGF antibody recently outperformed sorafenib with regards to efficacy. The wider availability of systemic therapies increases the chance for longer overall survival but raises new questions concerning the role of local options, treatment choice and sequential treatment. Following an expert discussion at the German Cancer Congress 2020 in Berlin, this article aims to summarize the current evidence on and experience of treatment choice and sequence in first- and second-line therapy