Technology for efficient simulation of cancer cell transport

高效模拟癌细胞运输的技术

基本信息

批准号：
10460591
负责人：
Amanda E Randles
金额：
$ 35.82万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-15 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10460591
关键词：
Address Algorithms Automobile Driving Behavior Biomedical Research Biophysics Blood Vessels Blood flow Cancer Biology Cause of Death Cell Communication Cell model Cells Cellular biology Cessation of life Code Collaborations Communities Complement Complex Computer Models Computers Data Development Devices Diagnostic Disease Progression Disseminated Malignant Neoplasm Exhibits Extravasation Fostering Future Geometry Goals In Vitro Individual Infrastructure Intuition Knowledge Lead Link Liquid substance Location Malignant Neoplasms Methods Microfluidic Microchips Modeling Morphology Movement Neoplasm Circulating Cells Neoplasm Metastasis Outcomes Research Patients Pattern Penetration Plant Roots Process Property Research Research Personnel Resolution Role Scientist Site Software Framework Software Tools Structure Technology Testing Therapeutic Tumor Cell Migration United States Vascular System Work anticancer research base biomechanical model biophysical properties bioprinting cancer cell cell behavior cell motility cell type computer infrastructure computing resources experience experimental study hydrodynamic model in silico insight interest man mathematical model mechanical properties novel diagnostics novel therapeutics open source open source tool predictive modeling simulation tool tumor

项目摘要

Cancer is the attributed cause of death in one in four cases in the United States and metastasis, a complex multistep process leading to the spread of tumors, is responsible for more than 90% of these deaths. However, predicting the location of these secondary tumor sites is still an elusive goal. One of the fundamental hurdles is to understand the trajectory of cell movement through the vascular system and the likelihood of penetration of the vessel wall. Studies have demonstrated that more than 50% of cancer metastatic sites could be explained by the blood flow pattern between the primary and secondary; however, the development of predictive models is still needed. Insight into the underlying mechanisms of cancer metastasis will provide insight into disease progression and lead to the development of new diagnostic or therapeutic methods targeting regions of the vasculature likely to incur secondary tumor sites. Tools that can be easily tuned to allow not only patient-specific but cell-specific modeling would complement ongoing in vitro experiments and provide this critical insight. Such computational models would allow researchers to probe the influence of different biophysical properties on cancer-specific cell behavior without the need for either expensive experimental trials for each cell-type or extrapolate from findings for one cancer to apply to another. An expected outcome of this research to create a usable, scalable, and extensible software framework for use by the wider biomedical research community to study the role of biophysical properties on a cell's transport and potential arrest. On such a platform, users will be able to introduce models of their cells-of-interest and perform simulations on them with models we (or others in the community) have developed. The ability to seamlessly introduce new cell-types with minimal effort will foster entirely new collaborations between researchers and provide biologists who would not traditionally leverage computational resources to study cell-specific properties in the context of realistic vascular geometries. This work will set the stage for future studies expanding the capabilities of this open source model.

在美国，癌症是四分之一病例的死因，而且转移是癌症的主要原因导致肿瘤扩散的复杂多步骤过程，是 90% 以上的原因这些死亡。然而，预测这些继发性肿瘤部位的位置仍然是一个难题难以捉摸的目标。基本障碍之一是了解细胞运动的轨迹通过血管系统和穿透血管壁的可能性。研究有证明超过 50% 的癌症转移部位可以通过血液来解释初级和次级之间的流动模式；然而，预测技术的发展仍然需要模型。深入了解癌症转移的潜在机制将提供洞察疾病进展并导致新诊断或治疗方法的开发针对可能产生继发性肿瘤部位的脉管系统区域的方法。可以轻松调整的工具不仅可以进行患者特异性建模，还可以进行细胞特异性建模补充正在进行的体外实验并提供这一重要的见解。这样的计算模型将使研究人员能够探究不同生物物理特性对癌症特异性细胞行为，无需对每种细胞进行昂贵的实验试验细胞类型或从一种癌症的发现推断适用于另一种癌症。预期结果这项研究的目的是创建一个可用的、可扩展的、可扩展的软件框架，供更广泛的生物医学研究界研究生物物理特性对细胞的作用运输和可能的逮捕。在这样的平台上，用户将能够介绍模型他们感兴趣的细胞，并用我们（或业内其他人）的模型对它们进行模拟社区）已经发展起来。能够以最少的成本无缝引入新的细胞类型这一努力将促进研究人员之间全新的合作，并为生物学家提供传统上不会利用计算资源来研究细胞特定的特性现实血管几何形状的背景。这项工作将为未来的研究扩展奠定基础这个开源模型的功能。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts.

通过添加真实的红细胞计数来增强自适应物理细化模拟。

DOI：
发表时间：
2023-11
期刊：
影响因子：
0
作者：
Roychowdhury, Sayan;Balogh, Peter;Mahmud, Samreen T;Puleri, Daniel F;Martin, Aristotle;Gounley, John;Draeger, Erik W;Randles, Amanda
通讯作者：
Randles, Amanda

The role of adhesive receptor patterns on cell transport in complex microvessels.

粘附受体模式对复杂微血管中细胞运输的作用。

DOI：
发表时间：
2022-08
期刊：
影响因子：
0
作者：
Puleri, Daniel F;Randles, Amanda
通讯作者：
Randles, Amanda

Distributed Acceleration of Adhesive Dynamics Simulations.

粘合剂动力学模拟的分布式加速。

DOI：
发表时间：
2022-09
期刊：
影响因子：
0
作者：
Puleri, Daniel F;Martin, Aristotle X;Randles, Amanda
通讯作者：
Randles, Amanda

High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory.

高性能自适应物理细化可实现大规模追踪癌细胞轨迹。

DOI：
发表时间：
2022-09
期刊：
影响因子：
0
作者：
Puleri, Daniel F;Roychowdhury, Sayan;Balogh, Peter;Gounley, John;Draeger, Erik W;Ames, Jeff;Adebiyi, Adebayo;Chidyagwai, Simbarashe;Hernández, Benjamín;Lee, Seyong;Moore, Shirley V;Vetter, Jeffrey S;Randles, Amanda
通讯作者：
Randles, Amanda

Effect of constitutive law on the erythrocyte membrane response to large strains.

构成法对红细胞膜对大应变反应的影响。