Multiscale systems biology modeling to exploit tumor-stromal metabolic crosstalk in colorectal cancer

多尺度系统生物学模型利用结直肠癌中的肿瘤间质代谢串扰

基本信息

批准号：
10251884
负责人：
Stacey Deleria Finley
金额：
$ 64.56万
依托单位：
UNIVERSITY OF SOUTHERN CALIFORNIA
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-13 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10251884
关键词：
3-Dimensional Address Apoptosis Automobile Driving Behavior Binding Biochemical Biological Assay Cancer Cell Growth Cancer Model Cell Culture Techniques Cell Proliferation Cells Cellular Metabolic Process Cessation of life Coculture Techniques Colon Carcinoma Colorectal Cancer Complement Computer Models Data Dependence Diagnosis Disease Drug resistance Ecosystem Environment Feedback Fibroblasts Glucose Glutamine Growth Image Imaging Techniques Immunotherapy Individual KRAS2 gene Lead Malignant Neoplasms Mass Spectrum Analysis Mathematics Measures Mediating Metabolic Metabolic Pathway Metabolism Modeling Molecular Monitor Morbidity - disease rate Nutrient Organoids Outcome PIK3CA gene Pathway interactions Patients Pharmaceutical Preparations Physiological Play Population Pre-Clinical Model Principal Investigator Production Reaction Relapse Research Resistance Role Signal Transduction Source Stromal Cells Stromal Neoplasm Survival Rate Systems Biology Testing Therapeutic Therapeutic Effect Tissues Tumor-Derived United States Validation Work acquired drug resistance base cancer cell cancer therapy cell behavior cell growth cell motility clinically relevant cohort colon cancer patients colon cancer treatment computer framework computer studies experimental study innovation insight metabolomics metastatic colorectal molecular modeling mortality multi-scale modeling mutant neoplastic cell novel novel strategies novel therapeutic intervention predictive modeling quantitative imaging simulation spatiotemporal standard of care targeted treatment therapy resistant treatment response treatment strategy tumor tumor growth tumor metabolism tumor microenvironment

项目摘要

Project Summary: Colorectal cancer (CRC) remains one of the deadliest cancers in the United States, with a 5-year survival rate of 10% for patients with metastatic disease. Over 120,000 people are diagnosed with CRC each year, leading to approximately 50,000 deaths. Even with the current standard of care, CRC patients have a high rate of relapse, and resistance to therapy is a key contributor to their high morbidity and mortality. Interactions between tumor and stromal cells are a source of acquired drug resistance. Cancer-associated fibroblasts (CAFs) are a dominant cellular component of the tumor stroma and play a significant role in drug resistance by contributing to the altered metabolism that is a hallmark of CRC. Recent studies suggest reciprocal metabolic reprogramming among CRC cells and CAFs. However, questions still remain regarding the metabolic dependencies of these two cell populations in the context of treatment response. Thus, quantifying the collective cell dynamics (i.e. cooperation or competition) of tumor and CAF cells in their metabolic ecosystem may provide insight needed to develop optimal cancer therapies. Despite many computational models of colorectal cancer growth and progression, there is currently no quantitative spatiotemporal description of the interactions between colon cancer cells and stromal cells, or the metabolic dependencies of these two cell populations. The proposed research addresses this limitation by developing an experiment-based, multiscale computational model of tumor-stromal metabolic interactions in colon cancer. We hypothesize that exploiting tumor-stromal metabolic dependencies will enhance the effects of therapeutic strategies to inhibit tumor growth. We will test this hypothesis by using a systems biology approach and pursuing three aims that combine computational and experimental studies: (1) Develop computational models of intracellular metabolic pathways in CRC cells and CAFs that promote colon cancer proliferation; (2) Develop a spatial multiscale model of colon cancer cell growth, integrating the pathway models of tumor-CAF metabolic crosstalk; and (3) Identify and validate treatment strategies that exploit tumor and CAF metabolism. This work applies a systems biology approach comprised of novel mathematical frameworks across scales, quantitative imaging techniques, and physiologically-relevant preclinical models. We have assembled a dynamic team of Principal Investigators to successfully complete this project, integrating expertise in computational systems biology (lead by Finley) and modeling multicellular interactions in biochemical signaling environments (lead by Macklin), driven by cutting-edge high-throughput experimental data in realistic conditions (lead by Mumenthaler). As a result, this work will generate the first multiscale model that explicitly accounts for molecular interactions between tumor and stromal cells in the context of colorectal cancer. We will apply the model to identify novel strategies that inhibit tumor growth by exploiting the tumor-stromal cell metabolic interactions, and the model predictions will be validated experimentally.

项目摘要：结直肠癌（CRC）仍然是美国最致命的癌症之一，转移性疾病患者的5年生存率为10％。超过12万人被诊断出患有CRC 每年，导致大约50,000人死亡。即使有当前的护理标准，CRC患者也有高复发率和对治疗的抵抗力是其高发病率和死亡率的关键因素。肿瘤和基质细胞之间的相互作用是获得耐药性的来源。癌症相关成纤维细胞（CAF）是肿瘤基质的主要细胞成分，在药物中起重要作用抗药性通过促进改变的新陈代谢而成为CRC的标志。最近的研究表明 CRC细胞和CAF之间的相互代谢重编程。但是，关于在治疗反应的背景下，这两个细胞群的代谢依赖性。因此，量化其肿瘤和CAF细胞中的集体细胞动力学（即合作或竞争）代谢生态系统可能会提供开发最佳癌症疗法所需的见解。尽管有许多结直肠癌的生长和进展的计算模型，但目前尚无定量时空描述结肠癌细胞与基质细胞之间的相互作用，或这两个细胞群的代谢依赖性。拟议的研究通过开发基于实验的肿瘤代谢相互作用的基于实验的多尺度计算模型结肠癌。我们假设利用肿瘤 - 层代谢依赖性将增强抑制肿瘤生长的治疗策略。我们将使用系统生物学方法检验该假设并追求结合计算和实验研究的三个目标：（1）开发计算 CRC细胞和促进结肠癌增殖的CAF中细胞内代谢途径的模型；（2）开发结肠癌细胞生长的空间多尺度模型，整合肿瘤-CAF的途径模型代谢串扰；（3）确定并验证利用肿瘤和CAF代谢的治疗策略。这项工作采用了一种系统生物学方法，该方法由跨尺度的新数学框架组成，定量成像技术和与生理相关的临床前模型。我们已经组装了动态的主要研究人员团队成功完成该项目，将专业知识整合到计算系统生物学（Finley领导）和生化信号中的多细胞相互作用建模环境（由麦克林（Macklin）领导），由前时候高通量实验数据驱动条件（由Mumenthaler领导）。结果，这项工作将生成第一个明确的多尺度模型在结直肠癌的背景下，肿瘤与基质细胞之间的分子相互作用。我们将应用模型来确定通过利用肿瘤细胞抑制肿瘤生长的新型策略代谢相互作用和模型预测将通过实验验证。