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Developing Adhesome Technology as a Physical Marker of Highly Metastatic Cells

开发粘附体技术作为高度转移细胞的物理标记

基本信息

批准号：
9922219
负责人：
Adam J Engler
金额：
$ 23.63万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
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：
2018-05-01 至 2021-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9922219
关键词：
Address Adhesions Adhesives Biological Assay Biological Markers Biophysics Biopsy Blood Cations Cell Count Cell Line Cells Clinic Clinical Data Detection Devices Disease Disease Progression Engineering Ensure Environment Epithelial Cells Estrogen Receptors Extravasation Fatty acid glycerol esters Fibroblasts Flow Cytometry Focal Adhesions Heterogeneity Hour Impairment In Vitro Invaded Label Lead Lung Lung Neoplasms Malignant neoplasm of lung Mammary Neoplasms Mammary gland Measures Metastatic breast cancer Methods Molecular NOD/SCID mouse Needle biopsy procedure Neoplasm Metastasis Nonmetastatic Pancreas Patient Monitoring Patients Phenotype Population Prevalence Primary Neoplasm Process Prognostic Marker Prostate Prostatic Neoplasms Relapse Research Risk Solid Neoplasm Sorting - Cell Movement Speed TACSTD1 gene Technology Testing Time Tissues Tumor Markers Tumor-Derived Woman base cancer cell cancer therapy clinical predictors diagnostic biomarker improved in vivo innovation malignant breast neoplasm metastatic process migration neoplastic cell physical property physical state prognostic prostate cancer cell line screening stem-like cell technology validation trait tumor tumor xenograft

项目摘要

Project Summary Diagnostic markers have improved our ability to identify tumors at earlier stages, but secondary metastases are still exceedingly common and aggressive. Metastases result from primary tumors shedding a small subpopulation of stem-like cells that can migrate through adjacent stroma and disseminate throughout the body unlike those cells remaining in the primary tumor. Progress towards identifying molecular prognostic markers of these stem-like cells that could assess metastatic risk has been limited; very recently however, evidence has suggested that a tumor's physical state may act as an alternative prognostic marker . We have observed that one such physical marker–adhesion strength–varies in metastatic epithelial cell lines from mammary, prostate, and lung tumors due to differences in focal adhesion assembly in stromal-like conditions, e.g. low Mg+2 and Ca+2. Thus strongly adherent sub-populations are slower and less processive than their unselected counterparts. Our hypothesis is that the converse population, i.e. weakly adherent tumor cells in the stroma, represents the most metastatic sub-population, which can be purified based on their adhesion strength and counted to determine metastatic risk. To isolate this converse population of weakly adherent cells, we have developed an “adhesome” flow chamber assay that will subject cells to low shear (<10 dynes/cm2) in stromal-like environments and rapidly (<10 min) sort 107 cells. Using this technology for proof-of-concept in Aim 1, we will validate its sorting efficiency and fidelity and observe the potential of weakly adherent cells to detach, migrate, and invade engineered microenvironments that resemble adjacent tumor stroma. In Aim 2, we will test the adhesome flow chamber's ability to predict breast cancer metastatic risk in vivo by injecting selected cells into mammary fat pads. We will then assess the propensity of weakly or strongly adherent cells to form or not form metastases, respectively. Cells from primary tumor stroma will be directly assessed to identify cells with a weakly adhesive signature and correlate that with secondary metastasis formation as would occur in the clinic. By validating across tumor types, this Innovative Molecular and Cellular Analysis Technologies R21 proposal will establish an adhesome flow chamber technology and validate our hypothesis that weakly adherent tumor cells are capable of migrating and forming secondary metastases, i.e. establish metastatic risk. Thus this technology should provide clinicians with addition prognostic assessment of a tumor's metastatic risk.

项目总结