CAREER: Virtual physiology of human tumor tissue for malignancy quantification

该项目正在开发虚拟肿瘤组织，以解决体外模型的缺点，并通过复制人类组织来减少对动物模型的依赖。这些虚拟组织被应用于增强对肿瘤恶性度的了解和所涉及的机制，从而提高对胰腺最常见的肿瘤类型-胰腺导管腺癌(PDAC)的早期诊断和治疗决策的准确性。开发虚拟PDAC的方法是个性化的--能够表示特定的人体组织，并可一般化地生成其他组织，这些组织可用于阐明其他疾病的进展机制，如动脉粥样硬化性心血管疾病、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的机会，以学习和应用生物医学工程中的先进计算。此外，这个项目支持从大二开始的早期研究机会，为他们的研究生学习做准备。该项目将通过指导本科生和研究生并将先进计算纳入本科课程来增强多样化的劳动力队伍。在这个职业项目中，开发了一种基于患者特定图像的硅内建模，并将其应用于复制人类肿瘤组织的虚拟生理。开发的虚拟肿瘤组织使人们对肿瘤恶性的细胞和分子机制、组成和改变肿瘤恶性的特征有了基本的了解。此外，该方案的模型开发产生了一个最先进的平台，以复制在人类中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硅内建模，以克服内存容量的限制，减少求解时间。人体组织的硅胶模型对于可预见的疾病进展筛查、机制研究、临床前试验和新治疗评估的安全环境至关重要。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.