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Current Opinion in Systems Biology最新文献

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Leveraging mathematical models to improve the statistical robustness of cancer immunotherapy trials
IF 3.4
Current Opinion in Systems Biology Pub Date : 2025-01-11 DOI: 10.1016/j.coisb.2024.100540
Jeroen H.A. Creemers , Johannes Textor
{"title":"Leveraging mathematical models to improve the statistical robustness of cancer immunotherapy trials","authors":"Jeroen H.A. Creemers ,&nbsp;Johannes Textor","doi":"10.1016/j.coisb.2024.100540","DOIUrl":"10.1016/j.coisb.2024.100540","url":null,"abstract":"<div><div>Cancer immunotherapy is an important application area for mathematical modeling. Current modeling studies have a range of ambitious goals from dose optimization to creating “digital twins” of individual cancer patients for treatment response prediction. Here we focus on a humbler, but nonetheless important, goal: aiding with the planning and design of clinical trials. Cancer immunotherapy trials can be hard to design due to heterogeneous and time-varying treatment effects. While clinical statisticians already use computer simulations, these rarely integrate explicit pathophysiological mechanisms, such as cancer-immune interactions, to specifically adapt the design to the treatment. Encouraged by rapid progress in mathematical modeling, we here propose an “in-silico-first” approach–already common in industry–where doctors, statisticians, and modelers build knowledge-based mathematical models to examine and refine the statistical design of clinical trials. Ultimately, we hope that this collaborative effort will lead to more robust designs of future clinical trials, resulting in improved success rates.</div></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"40 ","pages":"Article 100540"},"PeriodicalIF":3.4,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Calcium-mediated mitochondrial energy deficiency in Parkinson's and Alzheimer's diseases: Insights from computational modelling
IF 3.4
Current Opinion in Systems Biology Pub Date : 2025-01-10 DOI: 10.1016/j.coisb.2024.100539
Valérie Voorsluijs , Alexander Skupin
{"title":"Calcium-mediated mitochondrial energy deficiency in Parkinson's and Alzheimer's diseases: Insights from computational modelling","authors":"Valérie Voorsluijs ,&nbsp;Alexander Skupin","doi":"10.1016/j.coisb.2024.100539","DOIUrl":"10.1016/j.coisb.2024.100539","url":null,"abstract":"<div><div>Alzheimer's and Parkinson's diseases are the most prevalent neurodegenerative disorders worldwide and are characterised by progressive cognitive and functional impairments caused by neuronal loss. Energy deficiency is a predominant hallmark of their pathophysiology and plays a central role in the development of the disease, notably by mitochondrial dysfunction enhancing protein aggregation and oxidative stress which trigger subsequently immune responses and neuronal loss. Quantifying this energetic deficiency and identifying specific causative mechanisms from the complex network of interacting metabolic and regulatory pathways at play is rather challenging, where integrative mathematical modelling represents a powerful tool to support these investigations. Here, we review the latest developments in integrative modelling in brain bioenergetics in relation to Alzheimer's and Parkinson's diseases where we focus on the regulatory role of Ca<sup>2+</sup> signalling. Finally, we discuss recent challenges and future directions to improve the current understanding of the energy-deficiency theory of neurodegeneration.</div></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"40 ","pages":"Article 100539"},"PeriodicalIF":3.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Editorial Board Page 编委会页面
IF 3.4
Current Opinion in Systems Biology Pub Date : 2024-12-01 DOI: 10.1016/S2452-3100(24)00031-3
{"title":"Editorial Board Page","authors":"","doi":"10.1016/S2452-3100(24)00031-3","DOIUrl":"10.1016/S2452-3100(24)00031-3","url":null,"abstract":"","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"39 ","pages":"Article 100535"},"PeriodicalIF":3.4,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Untangling cell–cell communication networks and on-treatment response in immunotherapy
IF 3.4
Current Opinion in Systems Biology Pub Date : 2024-11-19 DOI: 10.1016/j.coisb.2024.100534
Lisa Maria Steinheuer , Niklas Klümper , Tobias Bald , Kevin Thurley
{"title":"Untangling cell–cell communication networks and on-treatment response in immunotherapy","authors":"Lisa Maria Steinheuer ,&nbsp;Niklas Klümper ,&nbsp;Tobias Bald ,&nbsp;Kevin Thurley","doi":"10.1016/j.coisb.2024.100534","DOIUrl":"10.1016/j.coisb.2024.100534","url":null,"abstract":"<div><div>Immunotherapies have shown efficacy in improving autoimmune conditions such as rheumatoid arthritis and are now widely established for various cancer entities. Nevertheless, predicting patient outcomes prior to therapy remains very challenging, likely attributable to the diversity and complex, interactive dynamics of immune cells. Recent advancements in statistical analysis as well as machine learning and mathematical modeling techniques have provided insights into immune-cell regulation and tumor-immune dynamics. Here, we discuss recent developments in this field, with the aim of deriving a path to improvements in treatment biomarker identification and adverse effect prediction. Deriving a quantitative understanding of the complex interactions among immune cell subpopulations holds promise for optimizing treatment strategies in numerous health conditions from chronic inflammation to cancer.</div></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"40 ","pages":"Article 100534"},"PeriodicalIF":3.4,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
From regulation of cell fate decisions towards patient-specific treatments, insights from mechanistic models of signalling pathways 从细胞命运决定的调控到针对患者的治疗，信号通路机理模型的启示
IF 3.4
Current Opinion in Systems Biology Pub Date : 2024-08-28 DOI: 10.1016/j.coisb.2024.100533
Mareike Simon , Fabian Konrath , Jana Wolf
{"title":"From regulation of cell fate decisions towards patient-specific treatments, insights from mechanistic models of signalling pathways","authors":"Mareike Simon ,&nbsp;Fabian Konrath ,&nbsp;Jana Wolf","doi":"10.1016/j.coisb.2024.100533","DOIUrl":"10.1016/j.coisb.2024.100533","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":"39 ","pages":"Article 100533"},"PeriodicalIF":3.4,"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":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142089337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Editorial overview: Systems biology of ecological interactions across scales 编辑综述：跨尺度生态相互作用的系统生物学
IF 3.4
Current Opinion in Systems Biology Pub Date : 2024-08-02 DOI: 10.1016/j.coisb.2024.100532
Edo Kussell, Nobuto Takeuchi
{"title":"Editorial overview: Systems biology of ecological interactions across scales","authors":"Edo Kussell,&nbsp;Nobuto Takeuchi","doi":"10.1016/j.coisb.2024.100532","DOIUrl":"10.1016/j.coisb.2024.100532","url":null,"abstract":"","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"39 ","pages":"Article 100532"},"PeriodicalIF":3.4,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A critical review of multiscale modeling for predictive understanding of cancer cell metabolism 多尺度建模用于预测性了解癌细胞代谢的重要综述
IF 3.4
Current Opinion in Systems Biology Pub Date : 2024-07-20 DOI: 10.1016/j.coisb.2024.100531
Marco Vanoni , Pasquale Palumbo , Stefano Busti , Lilia Alberghina
{"title":"A critical review of multiscale modeling for predictive understanding of cancer cell metabolism","authors":"Marco Vanoni ,&nbsp;Pasquale Palumbo ,&nbsp;Stefano Busti ,&nbsp;Lilia Alberghina","doi":"10.1016/j.coisb.2024.100531","DOIUrl":"10.1016/j.coisb.2024.100531","url":null,"abstract":"<div><p>Metabolism, whose reprogramming is an established cancer hallmark, promotes growth and proliferation in cancer cells. Genome-wide metabolic models are becoming increasingly capable of describing cancer growth. Multiscale models may allow the capture of other relevant features of cancer cells and their relationship with the tumor microenvironment. The merging of multiscale metabolic modeling and artificial intelligence can lead to a paradigm shift in oncology, possibly leading to patient-specific personalized digital twins.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"39 ","pages":"Article 100531"},"PeriodicalIF":3.4,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141840042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Network modeling approaches for metabolic diseases and diabetes 代谢性疾病和糖尿病的网络建模方法
IF 3.4
Current Opinion in Systems Biology Pub Date : 2024-06-21 DOI: 10.1016/j.coisb.2024.100530
Apurva Badkas , Maria Pires Pacheco , Thomas Sauter
{"title":"Network modeling approaches for metabolic diseases and diabetes","authors":"Apurva Badkas ,&nbsp;Maria Pires Pacheco ,&nbsp;Thomas Sauter","doi":"10.1016/j.coisb.2024.100530","DOIUrl":"https://doi.org/10.1016/j.coisb.2024.100530","url":null,"abstract":"<div><p>Metabolic diseases (MD) are amenable to network-based modeling frameworks, given the systemic perturbations induced by disrupted molecular mechanisms. We present here a brief overview of network modeling methods applied to inborn errors of metabolism (IEM), systemic metabolic conditions (mainly diabetes), and metabolism-related inflammation and autoimmune disorders. Clinical diagnosis and identification of causal agents in IEMs and uncovering the multifactorial mechanisms underlying the development of diabetes and other systemic metabolic diseases are the main challenges being addressed. The review also highlights some of the studies undertaken to investigate the role of the gut microbiome in MD, especially in diabetes. While the network frameworks employed in different modeling approaches have provided novel insights, some technique-specific limitations and overall gaps in general research trends need further attention.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"39 ","pages":"Article 100530"},"PeriodicalIF":3.4,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S245231002400026X/pdfft?md5=3af7589f4c37de8917481422dc190763&pid=1-s2.0-S245231002400026X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141594008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Editorial Board Page 编辑委员会页面
IF 3.7
Current Opinion in Systems Biology Pub Date : 2024-06-01 DOI: 10.1016/S2452-3100(24)00022-2
{"title":"Editorial Board Page","authors":"","doi":"10.1016/S2452-3100(24)00022-2","DOIUrl":"https://doi.org/10.1016/S2452-3100(24)00022-2","url":null,"abstract":"","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"38 ","pages":"Article 100526"},"PeriodicalIF":3.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310024000222/pdfft?md5=716e77e36be5ebe62ada61f5a261ff2e&pid=1-s2.0-S2452310024000222-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141264011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Computational systems biology of cellular processes in the human lymph node 人体淋巴结细胞过程的计算系统生物学
IF 3.7
Current Opinion in Systems Biology Pub Date : 2024-06-01 DOI: 10.1016/j.coisb.2024.100518
Sonja Scharf , Jörg Ackermann , Patrick Wurzel , Martin-Leo Hansmann , Ina Koch
{"title":"Computational systems biology of cellular processes in the human lymph node","authors":"Sonja Scharf ,&nbsp;Jörg Ackermann ,&nbsp;Patrick Wurzel ,&nbsp;Martin-Leo Hansmann ,&nbsp;Ina Koch","doi":"10.1016/j.coisb.2024.100518","DOIUrl":"10.1016/j.coisb.2024.100518","url":null,"abstract":"<div><p>The human immune system is determined by the functionality of the human lymph node. With the use of high-throughput techniques in clinical diagnostics, a large number of data is currently collected. The new data on the spatiotemporal organization of cells offer new possibilities to build a mathematical model of the human lymph node - a <em>virtual lymph node</em>. The virtual lymph node can be applied to simulate drug responses and may be used in clinical diagnosis. Here, we review mathematical models of the human lymph node from the viewpoint of cellular processes. Starting with classical methods, such as systems of differential equations, we discuss the values of different levels of abstraction and methods in the range of artificial intelligence techniques formalism.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"38 ","pages":"Article 100518"},"PeriodicalIF":3.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310024000143/pdfft?md5=66c9fec4f5325a388d754ce533b52cf6&pid=1-s2.0-S2452310024000143-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141031573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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