Automated plasma EV-PDL1 analysis for cancer immunotherapy

用于癌症免疫治疗的自动血浆 EV-PDL1 分析

基本信息

  • 批准号:
    10545706
  • 负责人:
  • 金额:
    $ 39.99万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-09-19 至 2024-08-31
  • 项目状态:
    已结题

项目摘要

ABSTRACT Challenges. There are over 4000 clinical trials testing anti-PD1/PD-L1 immune checkpoint inhibitors (ICI), either alone or in combination with other therapies. While many patients benefit, the vast amount do not, all at a considerable cost. The most validated and FDA-approved biomarker to guide patient selection is through immunohistochemical (IHC) staining and scoring of tissue biopsies for PD-L1 (e.g. Tumor Proportion Score, TPS). Unfortunately, TPS is an imperfect biomarker: i) it requires surgical or image guided tissue biopsy which is sometimes difficult to perform; ii) the site and timing of tissue acquisition and staining protocols can influence the accuracy of TPS; iii) IHC takes days to process, delaying treatment; iv) many TPS-positive patients do not respond to ICI treatment; and v) TPS can change during chemo, targeted and ICI therapies. Phase I goals. Accure Health proposes to explore an alternative approach: circulating PD-L1 biomarker assay based on Technology-integrated magneto-electronic sensing (TiMES) of extracellular vesicles (EVs). Supported by promising clinical data, we hypothesize that circulating EV analysis integrating PD-L1 expression from primary and metastatic lesions can be a more comprehensive marker. We propose two specific aims. Aim 1. Develop an automated TiMES assay to analyze pan EV-PDL1 and cell type-specific EV-PDL1. Aim 2. Establish TiMES EV-PDL1 scores and correlate with TPS. We envision the automated TiMES EV-PDL1 assay and integrated scores can be utilized in clinical trials testing anti-PD1/PD-L1 mono- or combination therapies. It can provide a faster and more reliable solution for evaluating treatment response, and help accelerate regulatory decision-making.
摘要 挑战有超过4000项临床试验测试抗PD 1/PD-L1免疫检查点抑制剂(ICI), 单独或与其它疗法联合使用。虽然许多患者受益,但大量患者并没有受益, 相当大的代价。最有效和FDA批准的指导患者选择的生物标志物是通过 组织活检的免疫组织化学(IHC)染色和PD-L1评分(例如肿瘤比例评分, TPS)。不幸的是,TPS是一种不完美的生物标志物:i)它需要手术或图像引导的组织活检, 有时难以执行; ii)组织采集和染色方案的部位和时间可能影响 TPS的准确性; iii)IHC需要几天的时间来处理,延迟治疗; iv)许多TPS阳性患者不需要 对ICI治疗有反应;和v)TPS可以在化疗、靶向和ICI治疗期间改变。 第一阶段的目标。Accure Health建议探索一种替代方法:循环PD-L1生物标志物检测 基于细胞外囊泡(EV)的技术集成磁电传感(TiMES)。 在有希望的临床数据的支持下,我们假设循环EV分析整合PD-L1表达 可以作为一个更全面的标志物。我们提出两个具体目标。目的 1.开发自动化TiMES检测试剂盒,以分析泛EV-PDL 1和细胞类型特异性EV-PDL 1。目标二。 建立TiMES EV-PDL 1评分并与TPS相关。我们设想自动化的TiMES EV-PDL 1测定 并且综合评分可用于测试抗PD 1/PD-L1单一或组合疗法的临床试验。它 可以为评估治疗反应提供更快、更可靠的解决方案, 监管决策。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Liyun Jessica Sang其他文献

Liyun Jessica Sang的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 39.99万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了