Monitoring Immunotherapy Response via Gene Silencing Landscapes in Cell-Free DNA
通过游离 DNA 中的基因沉默景观监测免疫治疗反应
基本信息
- 批准号:10760450
- 负责人:
- 金额:$ 39.8万
- 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:2023-09-01 至 2025-02-28
- 项目状态:未结题
- 来源:
- 关键词:AddressBenchmarkingBiological AssayBiological MarkersBiological Specimen BanksBloodBlood TestsBudgetsCancer PatientCharacteristicsCirculationClinicalClinical SensitivityClinical TrialsComplexDNA ProbesDataDetectionDevelopmentEpigenetic ProcessGene SilencingGenomeGenomic SegmentGenomicsGoalsHypermethylationImmuneImmune checkpoint inhibitorImmunotherapeutic agentImmunotherapyKineticsMalignant NeoplasmsMalignant neoplasm of lungMeasurementMeasuresMethodsMethylationMonitorMutationNon-Small-Cell Lung CarcinomaOutcomePaperPatientsPatternPerformancePhasePlasmaPrediction of Response to TherapyPublishingReproducibilityScanningScreening for cancerSensitivity and SpecificitySignal TransductionSmall Business Innovation Research GrantSomatic MutationSpecific qualifier valueSpecificitySurveysTechnologyTherapeuticTherapeutic EquivalencyTreatment EfficacyTumor TissueUniversitiesValidationWorkcancer genomecancer immunotherapycancer typecell free DNAcheckpoint therapychemotherapyclinical practiceclinical predictorscommercializationdensitydisorder controleffective therapyexome sequencingimmune cell infiltrateimprovedineffective therapiesliquid biopsymutantpatient subsetspromoterradiological imagingresponders and non-respondersresponseserial imagingside effectsurvival outcometumortumor DNAvalidation studiesvirtual
项目摘要
ABSTRACT:
Immunotherapies produce remarkable, long-term responses in subsets of patients with non-small cell lung
cancer, but unfortunately, most patients do not respond to such treatment. Current biomarkers to predict which
patients will benefit have limited accuracy, and decisions to continue or suspend treatment are mainly guided by
monitoring of radiographic changes in tumor size. However, unusual immune-related response patterns such
as pseudo-progression, mixed response, and delayed response can make scans difficult to interpret. Circulating
tumor DNA (ctDNA) has emerged as a highly promising biomarker for monitoring immunotherapy efficacy.
Several studies involving various immunotherapy agents and multiple types of cancer have demonstrated that
early reduction in ctDNA levels during treatment are predictive of tumor response and improved survival
outcomes. However, existing technologies that measure ctDNA by probing for common somatic mutations will
fail patients whose tumors lack these mutations. This limitation is being addressed by creating customized
assays based on patient-specific tumor mutation profiles; but this approach is complex, expensive, and slow.
We have developed a ctDNA assay technology based on detection of epigenetic features that are found in
virtually all cancer cell genomes. Preliminary data indicate that our approach has broad patient coverage and
can be applied to multiple types of cancer without requiring tumor profiling and assay customization. As proof
of concept, we aim to establish the utility of our assay technology for monitoring of lung cancer immunotherapy
response. In this Phase I SBIR application, we will evaluate the analytical and baseline clinical performance
characteristics of the assay technology, with a plan for a larger follow-on clinical utility study in Phase II. The
analytical validation and baseline clinical performance metrics will be benchmarked against existing commercial
mutation-based ctDNA assays to justify further development and commercialization of our technology.
文摘:
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 }}
Michael T Barrett其他文献
Michael T Barrett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 }}
{{ truncateString('Michael T Barrett', 18)}}的其他基金
HRD-IA signatures in pancreatic ductal adenocarcinoma
胰腺导管腺癌中的 HRD-IA 特征
- 批准号:
10551899 - 财政年份:2022
- 资助金额:
$ 39.8万 - 项目类别:
HRD-IA signatures in pancreatic ductal adenocarcinoma
胰腺导管腺癌中的 HRD-IA 特征
- 批准号:
10515859 - 财政年份:2022
- 资助金额:
$ 39.8万 - 项目类别:
High Definition Clonal Analyses of Archival Pancreatic Adenocarcinoma Samples
存档胰腺腺癌样本的高清克隆分析
- 批准号:
8220862 - 财政年份:2010
- 资助金额:
$ 39.8万 - 项目类别:
High Definition Clonal Analyses of Archival Pancreatic Adenocarcinoma Samples
存档胰腺腺癌样本的高清克隆分析
- 批准号:
8035406 - 财政年份:2010
- 资助金额:
$ 39.8万 - 项目类别:
High Definition Clonal Analyses of Archival Pancreatic Adenocarcinoma Samples
存档胰腺腺癌样本的高清克隆分析
- 批准号:
7778986 - 财政年份:2010
- 资助金额:
$ 39.8万 - 项目类别:
相似国自然基金
企业绩效评价的DEA-Benchmarking方法及动态博弈研究
- 批准号:70571028
- 批准年份:2005
- 资助金额:16.5 万元
- 项目类别:面上项目
相似海外基金
An innovative EDI data, insights & peer benchmarking platform enabling global business leaders to build data-led EDI strategies, plans and budgets.
创新的 EDI 数据、见解
- 批准号:
10100319 - 财政年份:2024
- 资助金额:
$ 39.8万 - 项目类别:
Collaborative R&D
BioSynth Trust: Developing understanding and confidence in flow cytometry benchmarking synthetic datasets to improve clinical and cell therapy diagnos
BioSynth Trust:发展对流式细胞仪基准合成数据集的理解和信心,以改善临床和细胞治疗诊断
- 批准号:
2796588 - 财政年份:2023
- 资助金额:
$ 39.8万 - 项目类别:
Studentship
Collaborative Research: SHF: Medium: A Comprehensive Modeling Framework for Cross-Layer Benchmarking of In-Memory Computing Fabrics: From Devices to Applications
协作研究:SHF:Medium:内存计算结构跨层基准测试的综合建模框架:从设备到应用程序
- 批准号:
2347024 - 财政年份:2023
- 资助金额:
$ 39.8万 - 项目类别:
Standard Grant
Elements: CausalBench: A Cyberinfrastructure for Causal-Learning Benchmarking for Efficacy, Reproducibility, and Scientific Collaboration
要素:CausalBench:用于因果学习基准测试的网络基础设施,以实现有效性、可重复性和科学协作
- 批准号:
2311716 - 财政年份:2023
- 资助金额:
$ 39.8万 - 项目类别:
Standard Grant
Benchmarking collisional rates and hot electron transport in high-intensity laser-matter interaction
高强度激光-物质相互作用中碰撞率和热电子传输的基准测试
- 批准号:
2892813 - 财政年份:2023
- 资助金额:
$ 39.8万 - 项目类别:
Studentship
FET: Medium: Quantum Algorithms, Complexity, Testing and Benchmarking
FET:中:量子算法、复杂性、测试和基准测试
- 批准号:
2311733 - 财政年份:2023
- 资助金额:
$ 39.8万 - 项目类别:
Continuing Grant
Collaborative Research: BeeHive: A Cross-Problem Benchmarking Framework for Network Biology
合作研究:BeeHive:网络生物学的跨问题基准框架
- 批准号:
2233969 - 财政年份:2023
- 资助金额:
$ 39.8万 - 项目类别:
Continuing Grant
Establishing and benchmarking advanced methods to comprehensively characterize somatic genome variation in single human cells
建立先进方法并对其进行基准测试,以全面表征单个人类细胞的体细胞基因组变异
- 批准号:
10662975 - 财政年份:2023
- 资助金额:
$ 39.8万 - 项目类别:
Collaborative Research: BeeHive: A Cross-Problem Benchmarking Framework for Network Biology
合作研究:BeeHive:网络生物学的跨问题基准框架
- 批准号:
2233968 - 财政年份:2023
- 资助金额:
$ 39.8万 - 项目类别:
Continuing Grant