{"title":"From regulation of cell fate decisions towards patient-specific treatments, insights from mechanistic models of signalling pathways","authors":"Mareike Simon , Fabian Konrath , Jana Wolf","doi":"10.1016/j.coisb.2024.100533","DOIUrl":null,"url":null,"abstract":"<div><p>Cell fate decisions are tightly regulated by complex signalling networks. Disturbed signalling through these networks is prominent in disease development. To elucidate pathway contributions and effects of alterations to the regulation of proliferation, quiescence, senescence, and apoptosis, computational modelling has been essential. Modelling heterogeneity on different scales was shown to be important for cell fate prediction. In recent years, personalised models capturing signalling and cell fate decisions have been developed. Of special interest is the application of these models to predict the response to drugs. In this review, we highlight examples of mathematical models of signalling pathways that regulate disease-relevant cell fate decisions on the path to develop individualised patient models for optimal treatment prediction.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310024000295/pdfft?md5=a7902f0bcf991e2a2e087d02b9cf0b9d&pid=1-s2.0-S2452310024000295-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Systems Biology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452310024000295","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Cell fate decisions are tightly regulated by complex signalling networks. Disturbed signalling through these networks is prominent in disease development. To elucidate pathway contributions and effects of alterations to the regulation of proliferation, quiescence, senescence, and apoptosis, computational modelling has been essential. Modelling heterogeneity on different scales was shown to be important for cell fate prediction. In recent years, personalised models capturing signalling and cell fate decisions have been developed. Of special interest is the application of these models to predict the response to drugs. In this review, we highlight examples of mathematical models of signalling pathways that regulate disease-relevant cell fate decisions on the path to develop individualised patient models for optimal treatment prediction.
期刊介绍：
Current Opinion in Systems Biology is a new systematic review journal that aims to provide specialists with a unique and educational platform to keep up-to-date with the expanding volume of information published in the field of Systems Biology. It publishes polished, concise and timely systematic reviews and opinion articles. In addition to describing recent trends, the authors are encouraged to give their subjective opinion on the topics discussed. As this is such a broad discipline, we have determined themed sections each of which is reviewed once a year. The following areas will be covered by Current Opinion in Systems Biology: -Genomics and Epigenomics -Gene Regulation -Metabolic Networks -Cancer and Systemic Diseases -Mathematical Modelling -Big Data Acquisition and Analysis -Systems Pharmacology and Physiology -Synthetic Biology -Stem Cells, Development, and Differentiation -Systems Biology of Mold Organisms -Systems Immunology and Host-Pathogen Interaction -Systems Ecology and Evolution
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