{"title":"A hybrid multiscale model for investigating tumor angiogenesis and its response to cell-based therapy.","authors":"Melisa Hendrata, Janti Sudiono","doi":"10.3233/ISB-170469","DOIUrl":null,"url":null,"abstract":"<p><p>Angiogenesis, a formation of blood vessels from an existing vasculature, plays a key role in tumor growth and its progression into cancer. The lining of blood vessels consists of endothelial cells (ECs) which proliferate and migrate, allowing the capillaries to sprout towards the tumor to deliver the needed oxygen. Various treatments aiming to suppress or even inhibit angiogenesis have been explored. Mesenchymal stem cells (MSCs) have recently been undergoing development in cell-based therapy for cancer due to their ability to migrate towards the capillaries and induce the apoptosis of the ECs, causing capillary degeneration. However, further investigations in this direction are needed as it is usually difficult to preclinically assess the efficacy of such therapy. We develop a hybrid multiscale model that integrates molecular, cellular, tissue and extracellular components of tumor system to investigate angiogenesis and tumor growth under MSC-mediated therapy. Our simulations produce angiogenesis and vascular tumor growth profiles as observed in the experiments. Furthermore, the simulations show that the effectiveness of MSCs in inducing EC apoptosis is density dependent and its full effect is reached within several days after MSCs application. Quantitative agreements with experimental data indicate the predictive potential of our model for evaluating the efficacy of cell-based therapies targeting angiogenesis.</p>","PeriodicalId":39379,"journal":{"name":"In Silico Biology","volume":"13 1-2","pages":"1-20"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/ISB-170469","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"In Silico Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/ISB-170469","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 6
Abstract
Angiogenesis, a formation of blood vessels from an existing vasculature, plays a key role in tumor growth and its progression into cancer. The lining of blood vessels consists of endothelial cells (ECs) which proliferate and migrate, allowing the capillaries to sprout towards the tumor to deliver the needed oxygen. Various treatments aiming to suppress or even inhibit angiogenesis have been explored. Mesenchymal stem cells (MSCs) have recently been undergoing development in cell-based therapy for cancer due to their ability to migrate towards the capillaries and induce the apoptosis of the ECs, causing capillary degeneration. However, further investigations in this direction are needed as it is usually difficult to preclinically assess the efficacy of such therapy. We develop a hybrid multiscale model that integrates molecular, cellular, tissue and extracellular components of tumor system to investigate angiogenesis and tumor growth under MSC-mediated therapy. Our simulations produce angiogenesis and vascular tumor growth profiles as observed in the experiments. Furthermore, the simulations show that the effectiveness of MSCs in inducing EC apoptosis is density dependent and its full effect is reached within several days after MSCs application. Quantitative agreements with experimental data indicate the predictive potential of our model for evaluating the efficacy of cell-based therapies targeting angiogenesis.
In Silico BiologyComputer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍:
The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.