Ex Vivo Drug Response Profiling and Outcome Prediction in Lung Adenocarcinoma
研究概览
详细说明
Non-small cell lung cancer (NSCLC) treatment decisions often rely on DNA sequencing, which only partially captures the tumor's mutational landscape and may miss other complex resistance mechanisms. Consequently, an unbiased functional drug screen is essential to rapidly identify optimal next-line therapies. Current drug sensitivity testing (DST) is limited by inefficient live tumor cells isolation. To address this, a rapid, unbiased DST platform utilizing FDA-approved targeted therapies was developed. Our approach uses malignant pleural effusions (MPEs) as a rich source of viable tumor cells. Because MPEs are highly heterogeneous, tumor cells are first identified via EpCAM flow cytometry, and the sample is enriched for tumor cells by depleting CD45+ immune cells using antibody-coated magnetic beads. These enriched tumor cells are then seeded into drug-containing plates. Following 72-hour incubation, cell viability is assessed using the CellTiter-Glo assay. Treatment efficacy is determined by the degree of reduction in cell viability at a range of drug concentrations, where the most effective treatment is the drug that reduces cell viability at the lowest concentration range.
To link clinical outcome and ex-vivo drug response assays, the investigators systematically measure drug sensitivity and resistance of primary tumor cells ex-vivo using a diverse compound library for individual patients in need of treatment. By systematically analyzing ex-vivo drug response patterns, tumors should be functionally grouped, by response phenotype. While for the purpose of this study selection of a specific treatment will not be based on ex-vivo drug response assays, clinical response- and follow-up data of patients will be prospectively collected in parallel.
研究类型
注册 (估计的)
联系人和位置
学习地点
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Israel
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Ramat Gan、Israel、以色列、5262100
- 招聘中
- Sheba medical center
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接触:
- Michael Peled, MD PhD
- 电话号码:972-3-5308420
- 邮箱:michael.peled@sheba.health.gov.il
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参与标准
资格标准
适合学习的年龄
- 成人
- 年长者
接受健康志愿者
取样方法
研究人群
描述
Inclusion Criteria:
- Presence of pleural effusion in patient with a diagnosis of a lung cancer or suspected to be diagnosed with lung cancer according to their CT imaging, who are in need for pleural effusion drainage due to shortness of breath, and are willing to donate effusion for ex-vivo drug sensitivity testing.
- Patient's written informed consent present.
- Ability to understand the nature of the trial and the trial related procedures and to comply with them.
Exclusion Criteria:
- negative cytology for malignancy in the last 6 months
学习计划
研究是如何设计的?
设计细节
队列和干预
团体/队列 |
干预/治疗 |
|---|---|
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Patients with diagnosis of a Lung adenocarcinoma with the need of pleural drainage due to MPE
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Non-Interventional Study, patients go through pleural drainage due to shortness of breath
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研究衡量的是什么?
主要结果指标
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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Statistically significant correlation between patients' drug response by ex-vivo drug profiling and expected drug sensitivity according to genetic sequencing
大体时间:From enrollment until results of clinical genetic sequencing and drug sensitivity testing are obtained (within 3 weeks).
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Ex-vivo drug sensitivity categorizes drugs as sensitive/not sensitive.
Results will be compared with the expected sensitivity of drugs according to the driver mutation found be genetic sequencing.
For example, in EGFR-driven lung cancer, the tumor cells are expected to be more sensitive to EGFR-targeting drugs than to ALK-targeting drugs.
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From enrollment until results of clinical genetic sequencing and drug sensitivity testing are obtained (within 3 weeks).
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次要结果测量
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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Accuracy of patients' drug response prediction by ex-vivo drug profiling
大体时间:from date of enrollment until progression (latest 24 months)
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Ex-vivo drug sensitivity categorizes drugs as sensitive/not sensitive.
Results will be compared with clinical outcome of patient (response vs. progressive disease as defined by RECISET score)
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from date of enrollment until progression (latest 24 months)
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合作者和调查者
研究记录日期
研究主要日期
学习开始 (实际的)
初级完成 (估计的)
研究完成 (估计的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
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