Woehrle, S. | bioRxiv Science

bioRxiv2024

Dynamic modelling of signalling pathways when ODEsare not feasible

MotivationMathematical modelling plays a crucial role in understanding inter- and intracellular signalling processes. Currently, ordinary differential equations (ODEs) are the predominant approach in systems biology for modelling such pathways. While ODE models offer mechanistic interpretability, they also suffer from limitations, including the need to consider all relevant compounds, resulting in large models difficult to handle numerically and requiring extensive data. ResultsIn previous work, we introduced the retarded transient function (RTF) as an alternative method for modelling temporal responses of signalling pathways. Here, we extend the RTF approach to integrate concentration or dose-dependencies into the modelling of dynamics. With this advancement, RTF modelling now fully encompasses the application range of ordinary differential equation (ODE) models, which comprises predictions in both time and concentration domains. Moreover, characterizing dose-dependencies provides an intuitive way to investigate and characterize signalling differences between biological conditions or cell-types based on their response to stimulating inputs. To demonstrate the applicability of our extended approach, we employ data from time- and dose-dependent inflammasome activation in bone-marrow derived macrophages (BMDMs) treated with nigericin sodium salt. Our results show the effectiveness of the extended RTF approach as a generic framework for modelling dose-dependent kinetics in cellular signalling. The approach results in intuitively interpretable parameters that describe signal dynamics and enables predictive modelling of time- and dose-dependencies even if only individual cellular components are quantified. AvailabilityThe presented approach is available within the MATLAB-based Data2Dynamics modelling toolbox at https://github.com/Data2Dynamics and https://zenodo.org/records/14008247 and as R code at https://github.com/kreutz-lab/RTF. Contactclemens.kreutz@uniklinik-freiburg.de

systems biology↗

bioRxiv2019

Werner syndrome helicase is a selective vulnerability of microsatellite instability high tumor cells

Targeted cancer therapy is based on exploiting selective dependencies of tumor cells. By leveraging recent large-scale genomic profiling and functional screening of cancer cell lines we identified Werner syndrome helicase (WRN) as a novel specific vulnerability of microsatellite instability-high (MSI-H) cancer cells. MSI, caused by defective mismatch repair is frequently detected in human malignancies, in particular in colorectal, endometrial and gastric cancers. We demonstrate that WRN inactivation selectively impairs the viability of MSI-H but not microsatellite stable (MSS) colorectal and endometrial cancer cell lines. In MSI-H cells, WRN loss results in the emergence of chromosome breaks, chromatin bridges and micronuclei highlighting defective genome integrity. WRN variants harboring mutations abrogating the ATPase function of WRN helicase fail to rescue the viability phenotype of WRN-depleted MSI-H colorectal cells. Our study suggests that pharmacological inhibition of WRN helicase function might represent a novel opportunity to develop a targeted therapy for MSI-H cancers.

cancer biology↗