Detection of microsatellite instability biomarkers for therapeutic clinical trial eligibility

检测治疗性临床试验资格的微卫星不稳定性生物标志物

基本信息

  • 批准号:
    9912125
  • 负责人:
  • 金额:
    $ 31.72万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-09-25 至 2022-03-31
  • 项目状态:
    已结题

项目摘要

When enrolling patients with advanced cancer in clinical trials, there is a need for clinical grade diagnostics to detect predictive biomarkers for novel immunotherapies. Microsatellite instability (MSI) has been identified as a novel predictive biomarker for cancer immunotherapy. Detecting MSI is currently accomplished with multiple redundant assays including immunohistochemistry for four proteins in the DNA repair pathway (MLH1, MSH2, MSH6, PMS2) and PCR for five selected microsatellite positions on finite tumor specimens (2). These diagnostic tests have been optimized for patients with colorectal cancer suspected of having germline Lynch Syndrome. Unfortunately, these assays oftentimes exhaust finite clinical specimens. The use of next generation sequencing (NGS)-based tests has expanded the profile of molecular diagnostics and raises the potential to integrate detection of MSI and eliminate the requirement for multiple parallel tests. While patients undergo genomic testing for other types of mutations such as point mutations, there is a critical need to augment current assays to include detection of microsatellite instability given its predictive value. Furthermore, current microsatellite detection algorithms have been specifically developed for a small number of cancer types and therefore are not accurate for MSI testing in most cancers. Our Clinical Laboratory Improvement Amendments (CLIA)--compliant Cancer Genomics Lab has extensive experience in developing clinical grade tumor sequencing, bioinformatics, and mutation-driven trials (3-6). We hypothesize that targeted DNA sequencing and analysis enables the detection of microsatellite instability in patient specimens from diverse cancer types. During the UH2 Phase of Analytic Validation, we will determine the sensitivity, specificity, reproducibility and reportable ranges of a targeted DNA microsatellite sequencing assay, MSI-Dx, utilizing clinical tumor specimens (Aim 1). We will demonstrate scalability, rapid turnaround, and use of MSI-Dx on a desktop sequencer. During the UH3 Phase of Clinical Validation, the MSI-Dx assay will be applied on a diverse collection of samples comprised of known MSI-H tumors including colorectal, endometrial, and other cancer types (Aim 2). Further, we will utilize the MSI-Dx assay for patients enrolled in a real time clinical tumor sequencing study (Aim 3). Importantly, MSI-Dx can be integrated with other NGS-based testing strategies. This assay will have a broad therapeutic impact by facilitating precision medicine clinical trials for patients with MSI-H tumors.
在临床试验中招募晚期癌症患者时,需要进行临床级诊断

项目成果

期刊论文数量(0)
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会议论文数量(0)
专利数量(0)

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Sameek Roychowdhury其他文献

Sameek Roychowdhury的其他文献

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{{ truncateString('Sameek Roychowdhury', 18)}}的其他基金

Liquid Biopsy for Rapid Detection and Real Time Monitoring of FGFR-altered Cancers
液体活检用于快速检测和实时监测 FGFR 改变的癌症
  • 批准号:
    10922903
  • 财政年份:
    2021
  • 资助金额:
    $ 31.72万
  • 项目类别:
Liquid Biopsy for Rapid Detection and Real Time Monitoring of FGFR-altered Cancers
液体活检用于快速检测和实时监测 FGFR 改变的癌症
  • 批准号:
    10282372
  • 财政年份:
    2021
  • 资助金额:
    $ 31.72万
  • 项目类别:
Detection of microsatellite instability biomarkers for therapeutic clinical trial eligibility
检测治疗性临床试验资格的微卫星不稳定性生物标志物
  • 批准号:
    9313523
  • 财政年份:
    2017
  • 资助金额:
    $ 31.72万
  • 项目类别:
Assay Validation of Targeted RNA sequencing to Detect Kinase Gene Fusions
用于检测激酶基因融合的靶向 RNA 测序的分析验证
  • 批准号:
    9762047
  • 财政年份:
    2016
  • 资助金额:
    $ 31.72万
  • 项目类别:
Assay Validation of Targeted RNA sequencing to Detect Kinase Gene Fusions
用于检测激酶基因融合的靶向 RNA 测序的分析验证
  • 批准号:
    9041381
  • 财政年份:
    2016
  • 资助金额:
    $ 31.72万
  • 项目类别:
Assay Validation of Targeted RNA sequencing to Detect Kinase Gene Fusions
用于检测激酶基因融合的靶向 RNA 测序的分析验证
  • 批准号:
    10005278
  • 财政年份:
    2016
  • 资助金额:
    $ 31.72万
  • 项目类别:

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