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High-Resolution Dynamic Imaging of Ovarian Cancer Metastasis Post Chemotherapy

High-Resolution Dynamic Imaging of Ovarian Cancer Metastasis Post Chemotherapy
卵巢癌化疗后转移的高分辨率动态成像
批准号:
10314067
负责人:
Marcin Iwanicki
金额:
$18.21万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-12-08 至 2023-11-30

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中文摘要
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Project Summary/Abstract Women undergoing chemotherapy treatment for ovarian cancer (OC) can develop new peritoneal metastases during recovery time, indicating a possibility that therapy promotes the evolution of metastatic cell populations. Therefore, it is of the highest clinical interest to study the effects of chemotherapy on peritoneal dissemination. A hallmark of OC peritoneal dissemination is a disruption of tumor tissue that leads to the formation of carcinoma outgrowths that subsequently detach, transit into the peritoneal cavity, and intercalate into mesothelium that covers vital organs. In this application, we hypothesize that chemotherapy disrupts tumor tissue, promotes outgrowths, cell detachment, and tumor mesothelial intercalation. To test our hypothesis, we propose two Aims that center on the development of in vitro and in vivo imaging approaches that will enable visualization and quantification of OC dissemination post-chemotherapy. In Aim 1 of this project, we will establish an organoid-based imaging assay to determine the effects of chemotherapy on OC organoid structure, outgrowth formation, cell detachment, and mesothelial intercalation. Aim 2 of this proposal focuses on developing an in vivo imaging assay in a mouse model to study the dynamic activities of OC in response to chemotherapy. To complete these aims, we have assembled an interinstitutional team with members that bring unique expertise in tissue engineering of OC dissemination, 3D in vivo imaging of the mouse reproductive system, and genetically modified models of ovarian cancer. This multi-PI combined efforts will provide much-needed information about the effects of chemotherapy on the dynamics of OC peritoneal dissemination.
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DOI: 10.1002/adbi.202200197
发表时间: 2022-12
期刊: Advanced biology
影响因子: 3.7
作者: []
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