Evaluation of Pre-Analytical Factors of Urine Samples for Urine Cancer Cell Cultures (UCCC) --A Non-Invasive Biomarker – in Monitoring Response and Recurrence of Bladder Cancer

尿癌细胞培养 (UCCC) 尿液样本分析前因素的评估——一种非侵入性生物标志物 — 用于监测膀胱癌的反​​应和复发

基本信息

  • 批准号:
    10640606
  • 负责人:
  • 金额:
    $ 36.03万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-06 至 2028-08-31
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY Bladder cancer is one of the top 10 most frequent cancers, yet the most underfunded cancer by NCI based on funding dollars and ratio of funding/mortality. There has been no significant improvement in overall survival and prognosis over the last thirty years except for the recent development of immunotherapy. After initial diagnosis and treatment, over 60% of the BC patients will relapse within two years and progression into advanced stages in up to 25% of patients. Therefore, almost all patients will need long-term expensive cystoscopy which makes bladder cancer the costliest cancer (per case) of all cancer types. If a sensitive but less expensive method to detect cancer were available, it would improve the treatment outcomes and decrease the cost. Dr. Xuefeng Liu (PI) and his team recently invented a robust method of conditional reprogramming (CR) technology to establish patient-derived cell models from cystoscopy or needle biopsies and urine samples of BC patients. The overall success rate was near 100%. These urine cancer cell cultures (UCCC) provide a simple, non-invasive, comfortable, reliable method to detect BC recurrence, and represent a living biomarker to predict patients’ response to chemotherapy and targeted therapy. Several cancer centers and laboratories including PI’s lab are actively involved in clinical trials to validate clinical utility of the UCCC in BC clinics. Since a variety of patient- context and collection, storage and transportation of urine samples to laboratories for cell cultures affect enrichment and viability of cancer cells in urine samples, it is urgent needed to evaluate pre-analytical factors of urine samples for UCCC and optimize these non-Invasive and living liquid biopsies as a routine approach in monitoring recurrence and prediction of response of BC patients. In this application, we propose to address the gaps by extending the work done by our team members on evaluating effects of sample processing protocols on UCCC analysis, to further investigate effect of patient-specific context. In this application, we will first further optimization of UCCC system to establish a culture kit for clinical applications, specifically we will optimize and simplify conditions with co-culture kits, conditioned medium (CM), hypoxic condition for maximal efficiency and robustness. Second, we will establish a Standard of Procedure - SOP- for urine collection and transportation in clinics: we will test pH, temperatures, minimal cell number, a cocktail with anti-biotics and Y-27632 affect UCCC cultures and success rate. Last, we will determine patient-context factors that affect UCCC cultures: we will evaluate how urine timing (days before surgery, and after surgery, early morning, noon, night, drinking water before urine collection, etc), urine volume affect cell viability and UCCC. Last, we will optimize a self- sampling procedures for BC patients. The overall goal is to expedite UCCC clinical assay development through evidence-based standardization of urine collection and handling practices, potentially approved by FDA as a standard method for bladder clinics.
项目摘要 膀胱癌是十大最常见的癌症之一,但根据NCI的数据, 资助金额和资助/死亡率。总体生存率没有显著改善, 在过去的30年中,除了免疫治疗的最新发展外,经初步诊断 超过60%的BC患者会在两年内复发并进入晚期 高达25%的患者。因此,几乎所有患者都需要长期昂贵的膀胱镜检查, 膀胱癌是所有癌症类型中最昂贵的癌症(每例)。如果一个敏感但不太昂贵的方法, 如果能够检测出癌症,它将改善治疗效果并降低成本。刘雪峰博士 (PI)和他的团队最近发明了一种强大的条件重编程(CR)技术方法, 来自膀胱镜检查或针穿刺活检和BC患者的尿液样品的患者来源的细胞模型。整体 成功率接近100%。这些尿癌细胞培养物(UCCC)提供了一种简单、非侵入性、 舒适,可靠的方法来检测BC复发,并代表一个活的生物标志物,以预测患者的 对化疗和靶向治疗的反应。几个癌症中心和实验室,包括PI的实验室, 积极参与临床试验,以验证UCCC在BC诊所的临床效用。由于各种各样的病人- 背景和收集,储存和运输尿液样本到实验室进行细胞培养影响 由于尿液样本中癌细胞的富集和活力,迫切需要评估分析前因素 尿液样本的UCCC和优化这些非侵入性和活的液体活检作为一种常规方法, 监测复发和预测BC患者的反应。在本申请中,我们提出解决 通过扩展我们的团队成员在评估样品处理方案效果方面所做的工作, 在UCCC分析中,进一步研究患者特定背景的影响。在本申请中,我们将首先进一步 优化UCCC系统,建立临床应用的培养试剂盒,具体来说,我们将优化和 用共培养试剂盒、条件培养基(CM)、低氧条件简化条件以获得最大效率, 鲁棒性第二,我们将建立一个标准的程序- SOP-尿液收集和运输, 诊所:我们将测试pH值,温度,最小细胞数,抗生素和Y-27632的鸡尾酒影响 UCCC文化和成功率。最后,我们将确定影响UCCC文化的患者背景因素:我们 将评估排尿时间(手术前、手术后、清晨、中午、晚上、饮酒) 尿液收集前的水等),尿量影响细胞活力和UCCC。最后,我们将优化一个自 BC患者的采样程序。总体目标是通过以下方式加快UCCC临床试验的开发: 尿液收集和处理实践的循证标准化,可能被FDA批准为 膀胱诊所的标准方法。

项目成果

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Xuefeng Liu其他文献

Xuefeng Liu的其他文献

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{{ truncateString('Xuefeng Liu', 18)}}的其他基金

Developing Functional Human Cell Models to Study Initiation and Progression of Prostate Cancer between AA and EA men
开发功能性人体细胞模型来研究 AA 和 EA 男性前列腺癌的发生和进展
  • 批准号:
    10566633
  • 财政年份:
    2023
  • 资助金额:
    $ 36.03万
  • 项目类别:
Validating Urine Derived Cancer Cells (UDCC) -- Non-Invasive and Living Liquid Biopsies -- in Bladder Cancer Clinics
在膀胱癌诊所中验证尿液衍生癌细胞 (UDCC)——非侵入性活体液体活检
  • 批准号:
    10395552
  • 财政年份:
    2021
  • 资助金额:
    $ 36.03万
  • 项目类别:
Validating Urine Derived Cancer Cells (UDCC) -- Non-Invasive and Living Liquid Biopsies -- in Bladder Cancer Clinics
在膀胱癌诊所中验证尿液衍生癌细胞 (UDCC)——非侵入性活体液体活检
  • 批准号:
    10605346
  • 财政年份:
    2021
  • 资助金额:
    $ 36.03万
  • 项目类别:
Conditionally Reprogrammed Cell Model for Castration-Resistant Prostate Cancer (CRPC)
去势抵抗性前列腺癌 (CRPC) 的条件重编程细胞模型
  • 批准号:
    10336637
  • 财政年份:
    2019
  • 资助金额:
    $ 36.03万
  • 项目类别:
Conditionally Reprogrammed Cell Model for Castration-Resistant Prostate Cancer (CRPC)
去势抵抗性前列腺癌 (CRPC) 的条件重编程细胞模型
  • 批准号:
    10223223
  • 财政年份:
    2019
  • 资助金额:
    $ 36.03万
  • 项目类别:
Conditionally Reprogrammed Cell Model for Castration-Resistant Prostate Cancer (CRPC)
去势抵抗性前列腺癌 (CRPC) 的条件重编程细胞模型
  • 批准号:
    10478023
  • 财政年份:
    2019
  • 资助金额:
    $ 36.03万
  • 项目类别:
NON-CANONICAL FUNCTIONS OF HTERT IN CELL IMMORTALIZATION BY HPV
HTERT 在 HPV 细胞永生化中的非典型功能
  • 批准号:
    8685210
  • 财政年份:
    2013
  • 资助金额:
    $ 36.03万
  • 项目类别:
NON-CANONICAL FUNCTIONS OF HTERT IN CELL IMMORTALIZATION BY HPV
HTERT 在 HPV 细胞永生化中的非典型功能
  • 批准号:
    8568104
  • 财政年份:
    2013
  • 资助金额:
    $ 36.03万
  • 项目类别:

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