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A unique approach combining avatar mice and targeted mass spectrometry to identify blood biomarkers for early detection of breast cancer

A unique approach combining avatar mice and targeted mass spectrometry to identify blood biomarkers for early detection of breast cancer
一种独特的方法,结合阿凡达小鼠和靶向质谱分析来识别血液生物标志物,以早期检测乳腺癌
批准号:
9354414
负责人:
Michael T. Lewis
金额:
$56.54万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-19 至 2021-08-31

项目摘要

项目成果

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中文摘要
翻译
项目摘要/摘要 数以千万计的妇女通过乳房X光检查进行基于人群的乳腺癌筛查。去- 尽管早期发现具有挽救生命的潜力,但乳房X光检查的筛查指南存在争议, 继续发展。争论的焦点是乳房X光摄影鉴别良性肿瘤和癌性乳腺瘤的特异性。 在某些患者群体(例如,乳房致密的妇女)中乳房X光检查的敏感性,以及 关于过度诊断的证据(例如某些导管原位癌)。我们的最终临床目标是开发一种 血液检测用于乳腺癌的早期检测,可与乳房X光检查结合使用,以改善 在筛查过程中的敏感性和特异性,因此通过检测可治疗的CAN-1具有巨大的临床影响。 乳房X光检查漏掉CER(降低死亡率),避免不必要的侵入性手术 黑色或非危及生命的疾病。 尽管做出了相当大的努力,但试图确定基于血液的筛查生物标记物以早期检测 由于技术和方法的限制,乳腺癌已经失败了。显然,新的方法正在 这是正当的。我们正在提出一种全新的策略,基于对候选双链的初步发现 “阿凡达小鼠”(携带早期传代人乳腺癌异种移植瘤)血浆中的前兆标志物,以及 通过使用基于靶向形式的质量的新型生物标记管道的生物标记分类和验证来降低 光谱分析(MS)、多反应监测(MRM)。如果成功,这项研究将为 将这一通用方法应用于乳腺癌以外的其他癌症部位。 简而言之,在化身小鼠血浆中确定的候选循环生物标记物将在血浆中得到验证 并根据综合蛋白质基因组分析确定进一步测试的优先顺序 由NCI基因组和蛋白质组联盟(TCGA和CPTAC)生成的大型乳腺癌数据集。A 11月- 将开发基于多重MRM的EL分析并进行分析验证(根据已建立的适合于 目的指南)对多达50-100个优先的生物标志物候选进行量化。候选生物标志物将是 在现有的、强烈无偏见的血浆样本收集中进行评估,其中血浆是事先收集的 符合探头研究设计标准的活检,根据SOP从患有未诊断的乳房的妇女- 图形损伤。候选生物标记物的表现将首先在训练集中进行评估(100个CA- ES,100名对照),以验证哪些候选人在病例和对照组之间显示了血浆水平的平均差异。 巨魔,并测试建立多标记预测模型的可能性。随后,个别糖果- 日期生物标记物(以及潜在的多标记物预测模型)将以独立的 验证集(150例病例,150例对照),以评估标记物/面板的敏感性和特异性。
英文摘要
Project Summary/Abstract Tens of millions of women undergo population-based screening for breast cancer by mammography. De- spite the life-saving potential of early detection, screening guidelines for mammography are controversial and continue to evolve. At issue are the specificity of mammography for distinguishing benign vs cancerous le- sions, the sensitivity of mammography in some patient populations (e.g. women with dense breasts), and con- cerns regarding over-diagnosis (e.g. some ductal carcinoma in situ). Our ultimate clinical aim is to develop a blood test for early detection of breast cancer that can be used in conjunction with mammography to improve sensitivity and specificity during screening, and thus have enormous clinical impact by detecting treatable can- cers missed by mammography (reducing mortality) and by avoiding unnecessary invasive procedures for be- nign or non-life-threatening disease. Despite considerable effort, attempts to identify blood-based screening biomarkers for early detection of breast cancer have failed, due to technological and methodological limitations. Clearly new approaches are warranted. We are proposing a completely novel strategy, based on the initial discovery of candidate bi- omarkers in the plasma of “avatar mice” (harboring early passage human breast cancer xenografts), and fol- lowed by biomarker triage and validation using a novel biomarker pipeline based on a targeted form of mass spectrometry (MS), multiple reaction monitoring (MRM). If successful, this study could provide a road map for applying this general approach to other cancer sites, beyond breast cancer. Briefly, candidate circulating biomarkers identified in the avatar mouse plasma will be verified in the plasma from the human patients and prioritized for further testing based on integrative proteo-genomic analyses using large breast cancer datasets generated by NCI genomic and proteomic consortia (TCGA and CPTAC). A nov- el, multiplex MRM-based assay will be developed and analytically validated (according to established fit-for- purpose guidelines) to quantify up to 50-100 prioritized biomarker candidates. Candidate biomarkers will be evaluated in an existing, strongly unbiased collection of plasma samples in which plasmas were collected prior to biopsy, compliant with PRoBE study design criteria, under an SOP from women with undiagnosed mammo- graphic lesions. Performance of the candidate biomarkers will initially be assessed in a training set (100 cas- es, 100 controls) to verify which candidates show a mean difference in plasma levels between cases vs con- trols, and to test the possibility of building a multiple marker prediction model. Subsequently, individual candi- date biomarkers (as well as a potential multiple marker prediction model) will be assessed in an independent validation set (150 cases, 150 controls) to estimate the sensitivity and specificity of the markers/panel.
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Core-001
  • 批准号:
    10710331
  • 项目类别:
  • 资助金额:
    $20.0万
  • 财政年份:
    2022
  • 负责人:
    Michael T. Lewis
  • 依托单位:
Core-001
  • 批准号:
    10710333
  • 项目类别:
  • 资助金额:
    $20.0万
  • 财政年份:
    2022
  • 负责人:
    Michael T. Lewis
  • 依托单位:
INTEGRATING OMICS AND QUANTITATIVE IMAGING DATA IN CO-CLINICAL TRIALS TO PREDICT TREATMENT RESPONSE IN TRIPLE NEGATIVE BREAST CANCER
  • 批准号:
    10688170
  • 项目类别:
  • 资助金额:
    $62.02万
  • 财政年份:
    2019
  • 负责人:
    Michael T. Lewis
  • 依托单位:
INTEGRATING OMICS AND QUANTITATIVE IMAGING DATA IN CO-CLINICAL TRIALS TO PREDICT TREATMENT RESPONSE IN TRIPLE NEGATIVE BREAST CANCER
  • 批准号:
    10241425
  • 项目类别:
  • 资助金额:
    $63.29万
  • 财政年份:
    2019
  • 负责人:
    Michael T. Lewis
  • 依托单位:
海外基金