Project 1: Patterned Heterogeneity in Colon Cancer

项目 1：结肠癌的模式异质性

• 批准号: 10392897
• 负责人: Marian L Waterman
• 金额: $ 38.57万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10392897
• 关键词: 3-Dimensional; Address; Affect; Angiogenesis Inhibitors; Behavior; Bioinformatics; Biological Markers; Biological Models; Blood Vessels; CRISPR/Cas technology; Cell Adhesion Molecules; Cell Lineage; Cells; Colon Carcinoma; Colonic Neoplasms; Colorectal Cancer; Communities; Complex; Data; Defect; Diffusion; Drug resistance; Environment; Epigenetic Process; Feedback; Gene Expression; Genetic; Genetic Engineering; Glycolysis; Goals; Growth; Heterogeneity; Human; Immune; Individual; Lead; Ligands; Link; Malignant Neoplasms; Metabolic; Metabolism; Modeling; Molecular; Morphology; Mus; Nutrient; Oncogenic; Outcome; Pathway interactions; Patients; Pattern; Pattern Formation; Pharmacotherapy; Phenotype; Population; Process; Prognosis; Reaction; Regulation; Research; Resistance; Resistance development; Resolution; Role; Signal Transduction; Signaling Molecule; Solid; Solid Neoplasm; Spottings; Starvation; Stress; Symbiosis; System; Systems Biology; Testing; Therapeutic Intervention; WNT Signaling Pathway; Work; Xenograft Model; Xenograft procedure; beta catenin; bevacizumab; cancer cell; cancer imaging; cancer stem cell; cancer therapy; colon cancer cell line; colon growth; design; differential expression; drug development; drug sensitivity; effective therapy; experimental study; genetic variant; in vivo; mathematical model; metabolic phenotype; mortality; multi-scale modeling; neoplastic cell; non-genetic; novel; organizational structure; predictive modeling; resistance mechanism; single-cell RNA sequencing; small molecule; stem-like cell; subcutaneous; therapy resistant; transcriptome; tumor; tumor growth; tumor heterogeneity; tumor microenvironment; tumor xenograft; tumorigenesis; wound

In many solid malignancies, molecular and cellular heterogeneity within a single tumor confounds our ability to understand tumorigenesis and to design effective therapies. Much effort has focused on genetic variants, the forces that lead to clonal outgrowth, and the relevance these clones have to the development of drug resistance. However it is the highly dynamic forms of non-genetic heterogeneity that are thought to enable adaptation to the rapidly changing stresses that confront the tumor as it grows and wounds the surrounding environment. Little is understood about non-genetic heterogeneity, whether it reflects a random epiphenomenon or mutualistic cooperation among cancer cells to benefit the tumor as a whole. Here we address these questions using a systems biology approach to mathematically model a pattern of non-genetic heterogeneity in xenografted colon tumors. Our studies of Wnt-β-signaling and its regulation of glycolysis have led us to discover a striking quasi-regular array of cell clusters (spots). Cells clusters are identified by high levels of Wnt (β-catenin and its target LEF1) and we identify a similar spotted pattern using markers of glycolysis. Manipulation of the levels of Wnt signaling in these xenografts changes the spotted pattern and reduces tumor growth. Whether the growth defect is functionally linked to the changes in pattern and heterogeneity is a fundamental unknown we wish to address. The overarching goal of this project therefore is to identify molecules and strategies that create pattern in this system, to ask how these strategies influence tumor growth, and to determine whether these mechanisms are involved in drug resistance. Aim 1 will use high-resolution single cell RNA-seq (scRNA-seq) and tumor imaging to build on our existing mathematical model and to explain the relationships between tumor heterogeneity, growth and invasion. Data from experiments wherein expression of candidate regulators and cell populations have been manipulated will be used to validate and refine the predictive power of our model. Work in Aim 2 will build a general model(s) that can explain how overt differences in tumor growth, heterogeneity, and metabolism arise as emergent behaviors of non-linearly interacting networks that qualitatively and quantitatively affect the Wnt pathway. In Aim 3 we use xenograft models that develop resistance to the anti-angiogenic drug bevacizumab and single cell RNA-seq approaches to examine the changes in cellular heterogeneity and patterning that accompany acquisition of resistance. Mathematical modeling will identify the most likely resistance mechanisms: mutualistic metabolic symbiosis, metabolic/population rewiring, mutualistic non-metabolic symbiosis, or none of the above. Modeling predictions of strategies that re-establish drug sensitivity will be tested via genetic engineering (CRISPR/Cas9) or small molecule drug therapies.

在许多实体恶性肿瘤中，单个肿瘤内的分子和细胞异质性使我们无法确定肿瘤的发生和发展。 了解肿瘤发生并设计有效的治疗方法。许多努力都集中在遗传变异上， 导致克隆生长的力量，以及这些克隆与药物开发的相关性 阻力然而，人们认为，正是非遗传异质性的高度动态形式， 适应快速变化的压力，面对肿瘤，因为它的增长和伤口周围 环境人们对非遗传异质性知之甚少，无论它是否反映了一种随机性， 癌细胞之间的副现象或互利合作使整个肿瘤受益。这里我们 使用系统生物学方法来解决这些问题， 异种移植结肠肿瘤的异质性。我们对Wnt-β信号及其对糖酵解的调节的研究， 使我们发现了一个惊人的准规则排列的细胞簇（点）。细胞簇通过高分辨率 水平的Wnt（β-连环蛋白及其靶LEF 1），我们使用以下标记物鉴定了类似的斑点模式： 糖酵解操纵这些异种移植物中Wnt信号传导的水平改变了斑点图案， 减少肿瘤生长。生长缺陷是否在功能上与模式的变化有关， 异质性是我们希望解决的一个基本的未知数。因此，本项目的总体目标是 来识别在这个系统中创造模式的分子和策略， 肿瘤生长，并确定这些机制是否涉及耐药性。目标1将使用 高分辨率单细胞RNA-seq（scRNA-seq）和肿瘤成像，以建立在我们现有的数学 模型，并解释肿瘤异质性，生长和侵袭之间的关系。数据从 其中已经操纵了候选调节物和细胞群体的表达的实验将被 用于验证和改进我们模型的预测能力。目标2中的工作将建立一个通用模型， 可以解释肿瘤生长，异质性和代谢的明显差异如何出现， 非线性相互作用网络的行为定性和定量地影响Wnt途径。在 目的3：我们使用对抗血管生成药物贝伐单抗和单抗产生耐药性的异种移植模型， 细胞RNA-seq方法来检查细胞异质性和伴随的模式的变化， 获得抵抗力。数学建模将确定最可能的耐药机制： 互惠的代谢共生，代谢/人口重新布线，互惠的非代谢共生，或没有 上面的。重建药物敏感性的策略的建模预测将通过遗传学方法进行测试。 基因工程（CRISPR/Cas9）或小分子药物疗法。