权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Cancer patient on a chip

芯片上的癌症患者

基本信息

批准号：
10646186
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
项目类别：
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/10646186
关键词：
3-Dimensional Advanced Malignant Neoplasm Algorithms Architecture Biological Biomedical Engineering Biopsy Bioreactors Blood Blood Vessels Bone Tissue Breast Adenocarcinoma Breast Carcinoma CLIA certified Cancer Biology Cancer Patient Cells Circulation 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 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 Therapeutic Thick Tissue Model Tissues Validation Vascular Endothelium Vascularization Woman Work anticancer research 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 therapeutic target transcriptome sequencing triple-negative invasive breast carcinoma tumor tumor progression

项目摘要

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