CAREER: Virtual physiology of human tumor tissue for malignancy quantification

职业：用于恶性肿瘤定量的人体肿瘤组织虚拟生理学

• 批准号: 2340149
• 负责人: Mahsa Dabaghmeshin
• 金额: $ 54.19万
• 依托单位: University of Wisconsin-Milwaukee
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-09-01 至 2029-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2340149&HistoricalAwards=false
• 关键词: CAREER; Virtual; physiology; human; tumor

This project is developing virtual tumor tissues to address the shortcomings of in-vitro models and reduce the reliance on animal models by replicating human tissue. These virtual tissues are applied to enhance the understanding of tumor malignancy and mechanisms involved that increase the accuracy of early diagnosis and treatment decision-making for the most prevalent type of pancreatic tumor, pancreatic ductal adenocarcinoma (PDAC). The method to develop a virtual PDAC is personalize-able to represent a specific human tissue and generalizable to generate other tissues that can be used to elucidate mechanisms involved in the progression of other diseases such as atherosclerotic cardiovascular diseases, healing of chronic wounds and bones, and spreading of viruses and immune cells. This project provides early exposure to STEM for undergraduate students, to learn about and apply advanced computing in biomedical engineering. Furthermore, this project supports early research opportunities from sophomore year onward to prepare them for graduate study. This project will enhance a diverse workforce by mentoring undergraduate and graduate students and incorporating advanced computing into the undergraduate curriculum. In this CAREER project, a patient-specific image-based in-silico modeling is developed and applied to replicate the virtual physiology of human tumor tissue. The developed virtual tumor tissues generate a fundamental understanding of cellular and molecular mechanisms underlying the tumor’s malignancy, composition, and characteristics that alter the tumor’s malignancy. Furthermore, the model development of this proposal yields a state-of-the-art platform to replicate the complexity and heterogeneity of tumor tissue as observed in humans. Massively parallel codes accomplish the in-silico modeling to overcome memory capacity limitations and reduce time-to-solution. The in-silico models of human tissue are vital for envisioned disease progression screening, mechanistic studies, pre-clinical trials, and a safe environment for new treatment evaluations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目正在开发虚拟肿瘤组织，以解决体外模型的缺点，并通过复制人体组织来减少动物模型的缓解。这些虚拟肿瘤用于增强对肿瘤恶性肿瘤和涉及的机制的理解，以提高早期诊断和治疗决策的准确性，以最普遍的胰腺肿瘤，胰腺导管腺癌（PDAC）。开发虚拟PDAC的方法是个性化的，可以代表特定的人体组织，并且可以概括地产生其他时间来阐明参与其他疾病进展的机制，例如动脉粥样硬化心血管疾病，例如动脉粥样硬化的心血管疾病，慢性伤口和骨骼的愈合以及病毒和免疫细胞的传播。该项目为本科生提供了早期接触STEM的暴露，以了解和应用生物医学工程中的高级计算。此外，该项目支持大二一年的早期研究机会，以便他们为研究生学习做好准备。该项目将通过心理本科生和研究生来增强不同的劳动力，并将高级计算纳入本科课程中。在这个职业项目中，开发了一种基于患者的基于患者的基于图像的内部建模，并应用于复制人类肿瘤组织的虚拟生理学。发达的虚拟肿瘤组织产生了对肿瘤的恶性肿瘤，组成和特征的细胞和分子机制的基本了解，从而改变了肿瘤的恶性肿瘤。此外，该提案的模型开发产生了一个最先进的平台，以复制人类观察到的肿瘤组织的复杂性和异质性。大规模并行代码完成了内部建模，以克服内存能力限制并减少时间到期。人类组织的核内模型对于设想的疾病进展筛查，机械研究，临床前试验以及用于新的治疗评估的安全环境至关重要。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来支持的。