Cancer patient on a chip

芯片上的癌症患者

• 批准号: 10417097
• 负责人: Gordana Vunjak-Novakovic
• 金额: $ 51.16万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10417097
• 关键词: 3-Dimensional; Advanced Malignant Neoplasm; Algorithms; Architecture; Biological; Biomedical Engineering; Biopsy; Bioreactors; Blood; Blood Circulation; Blood Vessels; Bone Tissue; Breast Adenocarcinoma; Breast Carcinoma; CLIA certified; Cancer Biology; Cancer Patient; Cells; Clinical; Data; Data Engineering; Dependence; Development; Drug Targeting; Drug resistance; Endothelial Cells; Engineering; Extravasation; Functional disorder; Genetic Transcription; Goals; Heart; Heterogeneity; Homing; Hormones; Human; Human Pathology; Image; Immune; Individual; Institutional Review Boards; Label; Link; Liver; Lung; Malignant Bone Neoplasm; Malignant Neoplasms; Mammary Gland Parenchyma; Mammary Neoplasms; Metastatic Neoplasm to the Lung; Metastatic breast cancer; Methodology; Methods; Modality; Modeling; Neoplasm Circulating Cells; Neoplasm Metastasis; Normal tissue morphology; Oncology; Operative Surgical Procedures; Organoids; Pathology; Patients; Perfusion; Pharmaceutical Preparations; Physiological; Primary Neoplasm; Property; Proteins; Protocols documentation; Publishing; Resistance; Role; Site; Slice; Specificity; Specimen; System; Systems Biology; Testing; Thick; Tissue Model; Tissues; Validation; Vascular Endothelium; Woman; Work; anticancer research; base; bone; cancer cell; cohort; design; drug sensitivity; drug testing; exome; human model; in vitro Model; induced pluripotent stem cell; insight; malignant breast neoplasm; migration; neoplastic cell; novel; novel therapeutics; pre-clinical; preclinical study; predictive modeling; predictive panel; recruit; response; scaffold; single cell analysis; single-cell RNA sequencing; targeted treatment; therapeutic target; transcriptome sequencing; triple-negative invasive breast carcinoma; tumor; tumor progression

SUMMARY The availability of predictive in vitro models of human tumors designed to accurately recapitulate key aspects of human pathophysiology would be transformative to cancer research and pre-clinical validation of new therapeutic modalities. We assembled an interdisciplinary team of leading experts in bioengineering, cancer biology, systems biology, pathology and oncology to establish such model. Based on extensive prior work, we propose to develop a state-of-the art “cancer patient on a chip” of invasive human breast carcinoma. The tumor will be physiologically integrated with their cognate metastatic sites (lung, liver, bone) via vascular perfusion containing circulating cells. The tumor compartment will be established directly from surgical specimens grown in 3D, organotypic conditions while target metastatic sites and vasculature will be established from blood-derived, patient-matched iPS cells, under an active institutional review board protocol. The system is imaging compatible and supports long-term culture (up to 12 weeks). Biological fidelity and heterogeneity of primary and metastatic sites, as implemented in the context of such vascularized multi-tissue platform, will be validated by single-cell analyses vs. the corresponding native tumor. For these studies, we will recruit a cohort of patients with metastatic tumors. Our ultimate goal is to demonstrate utility of the platform in elucidating mechanisms of tumor progression and drug resistance, by testing drug panels predicted by a novel RNA-seq-based, NY CLIA certified methodology (OncoTreat). Our hypothesis is that our system will recapitulate key properties of the metastatic breast adenocarcinoma and enable identification of target proteins that mechanistically drive tumor progression and drug sensitivity/resistance. Three specific aims will be pursued in a highly integrated fashion: Aim 1: Bioengineer a 3D human breast carcinoma model and metastasis host tissues; Establish a model of metastasis in an integrated patient-on-a-chip platform; Aim 3: Elucidate master regulators and predict drug sensitivity in metastatic cells using the “cancer patient on a chip” model. We anticipate that this platform would have broad utility in cancer research and in patient-specific testing of new therapeutic modalities.

总结 预测性体外人类肿瘤模型的可用性旨在准确概括关键 人类病理生理学的各个方面将改变癌症研究和临床前验证， 新的治疗方式。我们组建了一个跨学科的团队，由生物工程领域的顶尖专家组成， 癌症生物学、系统生物学、病理学和肿瘤学建立这种模型。基于广泛 在先前的工作中，我们建议开发一种最先进的侵入性人类乳腺癌的“芯片上的癌症患者”。 carcinoma.肿瘤将在生理上与它们的同源转移部位（肺，肝， 骨）通过含有循环细胞的血管灌注。将直接建立肿瘤区室 从在3D、器官型条件下生长的手术标本中， 将在一个积极的机构审查委员会的领导下， 议定书该系统与成像兼容，并支持长期培养（长达12周）。生物 原发性和转移性位点的保真度和异质性，如在这样的背景下实施的， 血管化多组织平台，将通过单细胞分析与相应的天然 肿瘤对于这些研究，我们将招募一组转移性肿瘤患者。我们的最终目标是 证明该平台在阐明肿瘤进展和耐药性机制方面的实用性， 通过基于RNA-seq的新型NYCLIA认证方法（OncoTreat）预测的药物组进行测试。我们 假设我们的系统将概括转移性乳腺癌的关键特性， 能够鉴定在机制上驱动肿瘤进展的靶蛋白， 灵敏度/电阻。将以高度综合的方式追求三个具体目标：目标1：生物工程 三维人乳腺癌模型和转移宿主组织; 集成患者芯片平台;目标3：阐明主调节因子并预测药物敏感性， 使用“癌症患者芯片”模型来检测转移细胞。我们预计，这个平台将有 在癌症研究和新治疗方式的患者特异性测试中的广泛用途。