Project 2: Profiling Gene Expression and Mechanophenotype in Circulating Tumor Cells Ex Vivo

项目 2：离体循环肿瘤细胞的基因表达和机械表型分析

• 批准号: 10681243
• 负责人: Ian Y Wong
• 金额: $ 22.58万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10681243
• 关键词: 3-Dimensional; Affect; Biochemistry; Biocompatible Materials; Bioinformatics; Biological Assay; Biomedical Engineering; Blood Circulation; Bone Marrow Stem Cell; Breast Cancer Cell; Cell Communication; Cells; Cellular Spheroids; Centers of Research Excellence; Coculture Techniques; Computational Biology; Confocal Microscopy; Cultured Tumor Cells; Data; Disease Progression; Distant; Drug Screening; Drug resistance; Engineering; Epithelium; Estrogen receptor positive; Exhibits; Extracellular Matrix; Family suidae; Fibroblasts; Fibroins; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genetic Transcription; Genomics; Goals; Heterogeneity; Homing; Human; Individual; Invaded; Liver; Lung; Malignant Neoplasms; Maps; Mechanics; Mentors; Mesenchymal; Metastatic Neoplasm to the Bone; Microfluidics; Micrometastasis; Modeling; Morphology; National Institute of Biomedical Imaging and Bioengineering; Neoplasm Circulating Cells; Neoplasm Metastasis; Organ; Outcome; Patients; Pattern; Pharmaceutical Preparations; Phenotype; Primary Neoplasm; Proliferating; Research; Research Personnel; Research Project Grants; Sampling; Silk; Site; Sorting; Stimulus; Stromal Cells; Technology; Therapeutic; Tissue constructs; Tissues; Traction; Validation; Xenograft procedure; bone; cancer cell; cell motility; cell type; colonization resistance; high throughput screening; human disease; inhibitor; malignant breast neoplasm; mechanical stimulus; mimetics; neoplastic cell; pre-clinical; programs; response; self assembly; single cell analysis; spatiotemporal; therapy resistant; transcriptome sequencing; transcriptomic profiling; tumor microenvironment

PROJECT SUMMARY Primary tumors shed circulating tumor cells (CTCs) into the bloodstream that metastasize preferentially to distant organs, resulting in 90% of cancer related fatalities. For example, estrogen receptor positive (ER+) breast cancers exhibit high rates of metastasis to bone, with decreased rates to liver and lung. CTCs exhibit heterogeneous gene expression programs and functional phenotypes, which are selected by soluble and mechanical interactions within each metastatic “niche.” A critical challenge is to predict how patient-specific CTCs disseminate throughout the body and respond to therapeutic treatments. An exciting strategy is to culture CTCs ex vivo for drug screening informed by genomic and transcriptional profiling. We seek to elucidate how CTCs respond to different features of the metastatic niche by engineering controlled interactions with tissue-specific extracellular matrix (ECM) and with human primary stromal cells, which may recapitulate disease progression and therapeutic resistance in these microenvironmental contexts. Our long-term goal is to establish preclinical assays for patient CTCs to predict metastatic disease progression and screen targeted inhibitors. Realization of this goal involves several technical challenges, including: 1) Tissue-mimetic matrix with tunable biochemistry and mechanics, 2) Multicellular tissue constructs with controlled size and cellular composition, 3) Gene expression profiling of CTCs in response to soluble and mechanical stimuli, 4) Spatiotemporal analysis of phenotypic heterogeneity, including the epithelial- mesenchymal transition (EMT), and 5) Validation with human patient samples. Thus, our overall objective is to understand how CTC gene expression and mechanophenotype is regulated by matrix or stromal interactions in tissue-mimetic microenvironments. This discovery-based approach can deconstruct patterns of gene expression driven by decellularized extracellular matrix or the secretome of human stromal cells. Such bioinformatics analyses can identify possible therapeutic strategies based on existing patient, xenograft, and high-throughput screens. PI: Wong is a New Investigator with expertise in cancer cell migration, biomaterials, and microfluidics. Mentor: Reichner is an expert on directed cell migration and mechanobiology and Mentor: Bertone is an expert on single cell analyses in cancer. We investigate the relative contributions of microenvironmental stimuli using three aims: AIM 1 will elucidate how individual breast cancer cells interact with tissue-mimetic matrix and AIM 2 will engineer co-cultured multicellular spheroids with stromal cells.

项目总结 原发肿瘤将循环中的肿瘤细胞(CTCs)送入血液中进行转移 更倾向于转移到远处的器官，导致90%的癌症相关死亡。例如，雌激素 受体阳性(ER+)乳腺癌骨转移率高，肝脏转移率低 还有肺。CTC表现出不同的基因表达程序和功能表型，这是 通过每个转移的“利基”中的可溶的和机械的相互作用来选择。一个关键的挑战是 预测针对患者的CTCs如何在全身扩散并对治疗作出反应。一个 令人兴奋的策略是体外培养CTCs，通过基因组和转录图谱进行药物筛选。 我们试图阐明CTC如何通过工程控制对转移的生态位的不同特征做出反应 与组织特异性细胞外基质(ECM)和人类原代基质细胞的相互作用，这可能 概述在这些微环境背景下的疾病进展和治疗耐药性。 我们的长期目标是为患者CTCs建立临床前检测以预测转移性疾病 进展和筛选靶向抑制剂。实现这一目标涉及几个技术挑战， 包括：1)具有可调节生物化学和力学的组织模拟基质；2)多细胞组织结构 在控制大小和细胞组成的情况下，3)CTCs对可溶性和 机械刺激，4)表型异质性的时空分析，包括上皮细胞- 间充质转化(EMT)，以及5)人类患者样本的验证。因此，我们的总体目标是 了解CTC基因表达和机制表型如何受基质或基质相互作用的调节 在模拟组织的微环境中。这种基于发现的方法可以解构基因的模式。 由脱细胞的细胞外基质或人基质细胞分泌组驱动的表达。是这样的 生物信息学分析可以根据现有的患者、异种移植和 高吞吐量屏幕。 Pi：Wong是一名新的研究人员，在癌细胞迁移、生物材料和微流体方面拥有专业知识。导师： Reichner是定向细胞迁移和机械生物学方面的专家，也是他的导师：Bertone是 癌症中的单细胞分析。我们研究了微环境刺激的相对贡献 三个目标：目标1将阐明单个乳腺癌细胞如何与组织模拟基质和目标2相互作用 将设计出与基质细胞共同培养的多细胞球体。