{"title":"Shaping the future of precision oncology: Integrating circadian medicine and mathematical models for personalized cancer treatment","authors":"Janina Hesse , Nina Nelson , Angela Relógio","doi":"10.1016/j.coisb.2024.100506","DOIUrl":null,"url":null,"abstract":"<div><p>The growing numbers of cancer cases represent a medical and societal burden worldwide. More than half of all cancer patients are treated with chemotherapy. Yet, chemotherapeutic drugs kill not only cancer cells, but also healthy tissue, causing massive adverse side effects. Recent research on circadian medicine suggests that side-effects can be reduced, and treatment efficacy increased, by considering the biological clock of patients. Integrating circadian profiles of molecular clock markers in personalized mathematical models can simulate individual circadian dynamics of drug uptake, drug action and cellular response to chemotherapy. This requires advanced computational tools that balance prediction quality with overfitting. Personalized mathematical models will eventually lead to an optimal alignment of treatment timing with the inner circadian clock of the patient, reducing side effects, increasing efficacy and enhancing patient well-being.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"37 ","pages":"Article 100506"},"PeriodicalIF":3.4000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310024000027/pdfft?md5=ca1548e10b73e11752c874903a1363a1&pid=1-s2.0-S2452310024000027-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/S2452310024000027","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
The growing numbers of cancer cases represent a medical and societal burden worldwide. More than half of all cancer patients are treated with chemotherapy. Yet, chemotherapeutic drugs kill not only cancer cells, but also healthy tissue, causing massive adverse side effects. Recent research on circadian medicine suggests that side-effects can be reduced, and treatment efficacy increased, by considering the biological clock of patients. Integrating circadian profiles of molecular clock markers in personalized mathematical models can simulate individual circadian dynamics of drug uptake, drug action and cellular response to chemotherapy. This requires advanced computational tools that balance prediction quality with overfitting. Personalized mathematical models will eventually lead to an optimal alignment of treatment timing with the inner circadian clock of the patient, reducing side effects, increasing efficacy and enhancing patient well-being.
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