EFIRM Liquid Biopsy Research Laboratory: Early Lung Cancer Assessment
EFIRM 液体活检研究实验室:早期肺癌评估
基本信息
- 批准号:10763321
- 负责人:
- 金额:$ 93.21万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-09-13 至 2028-08-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAlgorithmsBenignBiological AssayBiological MarkersBloodBlood VolumeBlood specimenCancer BiologyCancer DetectionCancer PatientCharacteristicsClassificationClinicalCollaborationsDNA Sequence AlterationDataDetectionDevelopmentDiagnosisDiagnosticDiagnostic testsDiameterDiffusionDiseaseEarly DiagnosisEngineeringEnsureHeterogeneityHumanImageIndividualIndustryLaboratoriesLaboratory ResearchLesionLiquid substanceLungLung noduleMalignant - descriptorMalignant NeoplasmsMalignant neoplasm of lungMeasurementMethodsMethylationMicroRNAsModelingMolecularNoduleNon-MalignantNon-Small-Cell Lung CarcinomaPathologicPatientsPerformancePhasePlasmaPopulationPredictive Cancer ModelProceduresProspective cohortQualifyingRecommendationResearchResolutionScanningSecureSignal TransductionSomatic MutationSymptomsTechniquesTechnologyTestingThoracic RadiographyTissue SampleTumor MarkersValidationX-Ray Computed Tomographycancer biomarkerscancer diagnosiscandidate markercell free DNAchest computed tomographycirculating DNAcohortcomputed tomography screeningcurative treatmentsdeep learningelectric fieldformer smokerfrontierhistological specimensimprovedindustry partnerinterestliquid biopsylow dose computed tomographylung cancer screeningmalignant statemortalitymultiple omicsnever smokernovelpoint of carepre-clinicalprediction algorithmpredictive modelingprospectiveradiomicsreconstructionscreeningserial imagingsurveillance imagingtumor DNA
项目摘要
Project Summary/Abstract:
Computed tomography (CT) is currently the most sensitive test for detecting preclinical lung cancer. The
National Lung Screening Trial (NLST) demonstrated that routine low-dose CT screening reduces lung cancer
mortality by 20% relative to chest radiography. However, the increased use of CT has also resulted in the
discovery of an estimated 2 million screened and incidentally detected indeterminate pulmonary nodules (IPNs).
These nodules, less than 30 mm in diameter, are largely benign but a proportion possess malignancy potential.
Methods are urgently needed to better differentiate between individuals with benign disease and those should
undergo invasive diagnostic testing.
Liquid biopsy has found its way into the cancer lexicon as a reference to tumor biomarkers within blood or
other readily accessible biospecimens that reflect the presence and biology of cancer. To fully mature liquid
biopsy at the forefront of early cancer assessment, two frontiers must be addressed. The first is the development
(discovery and validation) of comprehensive personalized cancer-specific omics targets for early detection. The
second is the advancement and refinement of technologies that can detect the earliest shedding of these
circulating targets. This application is Phase 2 of the EFIRM-Liquid Biopsy Research Laboratory (E-LBRL) aims
to advance these two essential frontiers for early cancer assessment of indeterminate pulmonary nodules (IPNs):
early detection of lung cancer.
Our partnership interweaves the expertise of lung cancer biologists, clinicians, and biostatisticians with
industry engineers, converging on the novel liquid biopsy technology “EFIRM-Liquid biopsy (eLB)”.
Complementary to the performance of eLB, during the Phase 1 of E-LBRL, we have discovered a novel species
of cell-free DNA which are ultrashort and single-stranded (uscfDNA) and contribute to a population of a large
pool of Broad Range cfDNA (BRcfDNA). Unlike circulating tumor DNA which are rare or absent in early states,
the uscfDNA represent global/systemic changes in cancer and can be harnessed to detect the malignancy
status of the IPN. Additionally, due to their physical characteristics, these BRcfDNA biomarkers are optimal for
the eLB platform.
We hypothesize that signals from malignancy associated BRcfDNAs can be integrated with malignancy
associated somatic mutations, differentiated methylated regions, miRNA and radiomic imaging in an integrated
model termed IPN.CA to permit the earliest cancer assessment of IPN. Our industry partner together with a
Biomarker Reference Lab will convert individual eLB assays to multiplex arrays for CLIA-qualification. The eLB-
IPN.CA and its associated inputs will be a clinically deployable Laboratory Developed Test (LDT) for early cancer
assessment in IPN.
项目概要/摘要:
计算机断层扫描(CT)是目前检测临床前肺癌最敏感的测试。的
国家肺筛查试验(NLST)表明,常规低剂量CT筛查可减少肺癌
死亡率相对于胸部X线摄影降低了20%。然而,CT使用的增加也导致了
发现了估计200万个筛查和偶然发现的不确定的肺结节(IPN)。
这些直径小于30 mm的结节大部分是良性的,但也有一部分具有恶性潜能。
迫切需要更好地区分患有良性疾病的个体和那些应该
进行侵入性诊断测试。
液体活检已经进入癌症词典,作为血液或血液中肿瘤生物标志物的参考。
其他容易获得的反映癌症存在和生物学的生物标本。到完全成熟的液体
活组织检查处于早期癌症评估的最前沿,必须解决两个前沿问题。一是发展
(发现和验证)用于早期检测的全面个性化癌症特异性组学靶标。的
第二是技术的进步和完善,可以检测到这些最早的脱落
循环目标该应用程序是EFIRM-液体活检研究实验室(E-LBRL)目标的第2阶段
推进不确定性肺结节(IPN)早期癌症评估的两个基本前沿:
肺癌的早期诊断
我们的合作伙伴关系将肺癌生物学家,临床医生和生物统计学家的专业知识与
行业工程师,聚集在新的液体活检技术“EFIRM-Liquid biopsy(eLB)"。
作为eLB性能的补充,在E-LBRL的第一阶段,我们发现了一种新物种
超短和单链的无细胞DNA(uscfDNA),并有助于大量的
宽范围cfDNA(BRcfDNA)池。与循环肿瘤DNA不同,循环肿瘤DNA在早期状态下是罕见或不存在的,
uscfDNA代表癌症的整体/系统变化,
IPN的现状。此外,由于它们的物理特性,这些BRcfDNA生物标志物是最佳的,
eLB平台。
我们假设来自恶性肿瘤相关BRcfDNA的信号可以与恶性肿瘤整合,
相关的体细胞突变,分化的甲基化区域,miRNA和放射组学成像在一个整合的
模型称为IPN.CA,以允许IPN的最早癌症评估。我们的行业合作伙伴与
生物标志物参考实验室将单个eLB检测转换为多重阵列,以进行CLIA确认。eLB-
IPN.CA及其相关输入将是用于早期癌症的临床可部署的实验室开发测试(LDT)
评估IPN。
项目成果
期刊论文数量(1)
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 }}
DENISE R. ABERLE其他文献
DENISE R. ABERLE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('DENISE R. ABERLE', 18)}}的其他基金
Integrated Molecular, Cellular, and Imaging Characterization of NLST detected lung cancer
NLST 检测肺癌的综合分子、细胞和成像特征
- 批准号:
10415430 - 财政年份:2021
- 资助金额:
$ 93.21万 - 项目类别:
Individually-tailored clinical decision support for management of indeterminate pulmonary nodules
针对不确定肺结节管理的个性化临床决策支持
- 批准号:
10307996 - 财政年份:2018
- 资助金额:
$ 93.21万 - 项目类别:
EFIRM-Liquid Biopsy (eLB): Ultrasensitive ctDNA and miRNA Detection for Early Assessment of Lung Cancer
EFIRM-液体活检 (eLB):用于肺癌早期评估的超灵敏 ctDNA 和 miRNA 检测
- 批准号:
10225427 - 财政年份:2018
- 资助金额:
$ 93.21万 - 项目类别:
EFIRM-Liquid Biopsy (eLB): Ultrasensitive ctDNA and miRNA Detection for Early Assessment of Lung Cancer
EFIRM-液体活检 (eLB):用于肺癌早期评估的超灵敏 ctDNA 和 miRNA 检测
- 批准号:
9982813 - 财政年份:2018
- 资助金额:
$ 93.21万 - 项目类别:
EFIRM-Liquid Biopsy (eLB): Ultrasensitive ctDNA and miRNA Detection for Early Assessment of Lung Cancer
EFIRM-液体活检 (eLB):用于肺癌早期评估的超灵敏 ctDNA 和 miRNA 检测
- 批准号:
10456340 - 财政年份:2018
- 资助金额:
$ 93.21万 - 项目类别:
Individually-tailored clinical decision support for management of indeterminate pulmonary nodules
针对不确定肺结节管理的个性化临床决策支持
- 批准号:
10055957 - 财政年份:2018
- 资助金额:
$ 93.21万 - 项目类别:
Individually-tailored clinical decision support for management of indeterminate pulmonary nodules
针对不确定肺结节管理的个性化临床决策支持
- 批准号:
10539247 - 财政年份:2018
- 资助金额:
$ 93.21万 - 项目类别:
Molecular and Imaging Biomarkers for Early Lung Cancer Detection in the Setting of Indeterminate Pulmonary Nodules
不确定肺结节中早期肺癌检测的分子和影像生物标志物
- 批准号:
10231155 - 财政年份:2016
- 资助金额:
$ 93.21万 - 项目类别:
Molecular and Imaging Biomarkers for Early Lung Cancer Detection in the Setting of Indeterminate Pulmonary Nodules
不确定肺结节中早期肺癌检测的分子和影像生物标志物
- 批准号:
10018815 - 财政年份:2016
- 资助金额:
$ 93.21万 - 项目类别:
The Boston University-UCLA Lung Cancer Biomarker Development Lab
波士顿大学-加州大学洛杉矶分校肺癌生物标志物开发实验室
- 批准号:
9277841 - 财政年份:2016
- 资助金额:
$ 93.21万 - 项目类别:
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:
$ 93.21万 - 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:
$ 93.21万 - 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:
$ 93.21万 - 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:
$ 93.21万 - 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:
$ 93.21万 - 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:
$ 93.21万 - 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:
$ 93.21万 - 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:
$ 93.21万 - 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:
$ 93.21万 - 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:
$ 93.21万 - 项目类别:
Continuing Grant