Ading color to cancer, adenovirus and flow cytometry to identify and capture CTCs
为癌症、腺病毒和流式细胞术着色以识别和捕获 CTC
基本信息
- 批准号:8336845
- 负责人:
- 金额:$ 15.22万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-09-21 至 2013-08-31
- 项目状态:已结题
- 来源:
- 关键词:Adenovirus VectorAdenovirusesAerosolsAffinity ChromatographyAntibodiesAntigensBiological AssayBiological MarkersBiologyBiomedical EngineeringBiopsyBloodBlood CellsBlood CirculationBlood specimenCancer PatientCardiovascular systemCell NucleusCell SeparationCellsCessation of lifeCharacteristicsChimeric ProteinsClinicClinicalColorCytosolDataDetectionDevicesDiagnosisDiagnosticDisseminated Malignant NeoplasmDoctor of PhilosophyEarly identificationEngineeringEpithelialEvaluationFlow CytometryFluorescent in Situ HybridizationFrequenciesGene Expression ProfileGeneticGenomeGoalsGrowthHourIndividualInvadedLabelLeftLegal patentLesionLibrariesMalignant - descriptorMalignant NeoplasmsMalignant neoplasm of lungMeasuresMediatingMicrofluidicsMicroscopyMolecularMutationNeoplasm MetastasisNon-Small-Cell Lung CarcinomaNucleic AcidsOncologistOrganPathway interactionsPatientsPhenotypePrimary NeoplasmProcessProliferatingProteinsReporterReportingResearch PersonnelReverse Transcriptase Polymerase Chain ReactionRiskSamplingScienceSeriesSerotypingSignal PathwaySiteSolid NeoplasmSolutionsSorting - Cell MovementStagingSystemTechniquesTechnologyTestingTissuesTranslatingViralViral VectorVirusbasecancer cellcancer therapycostdefective adenoviral vectordesigndetectormalignant phenotypemicro-total analysis systemmicrochipneoplastic cellnovelnovel diagnosticsperipheral bloodpoint-of-care diagnosticsprognosticresponseselective expressiontherapeutic targettooltumorviral detectionvoltage
项目摘要
"Ad'ing color to cancer: adenovirus & flow cytometry to identify & capture CTCs "
NanoSort
RESEARCH & RELATED Other Project Information
7. PROJECT SUMMARY
We propose a novel technique to identify and capture circulating tumor cels (CTCs) using enginered
adenoviruses and sophisticated flow cytometry. Current techniques for detection of CTCs include reverse
transcriptase-polymerase chain reaction (RT-PCR), flow cytometry, fluorescence in situ hybridization, and,
more recently, microfluidics. Unfortunately, RT-PCR does not distinguish between viable metastatic CTC
versus nucleic acids or celular fragments originating from the primary tumor. ! Antibody-based techniques
cannot be used for detection of all cancers, but only those cancers that express the most common and well-
characterized markers. As such, there is a desperate need to develop new diagnostic agents and tools that not
only detect and capture CTCs but also quantify their malignant potential and identify 'up-front' the therapies
that are most effective in ablating an individual patient's tumor. Despite the complexity and variability of
cancers at a genome scale, a unifying theme is their growth deregulation phenotypes, the so-called hallmarks
of cancer, which are conferred by mutations in a relatively small number of key pathways. Rather than focus on
detecting individual genetic lesions that are numerous and highly variable between tumors, we propose to
create diagnostic viruses that incorporate multiple transcriptional and molecular modules in their genomes to
infect and detect a patient's tumor, report its molecular 'hallmarks' and its response to different therapies 'up-
front'. Using these agents, the molecular lesions and malignant characteristics of any given tumor wil be
rapidly discerned (within 24 hours) and scored via a standardized automated platform. Furthermore, these
agents could also be used as reporters to determine rapidly and directly if a patient's tumor is likely to respond
to a particular therapy. Our goal is to develop a standardized automated platform that provides point-of-care
diagnostics to inform clinical decisions at a level of molecular sophistication and prognostic power that is not
possible with any other detection system, biomarkers or correlative gene expression signatures. To achieve
this, we will combine transformative new technological platforms developed at the Salk, UCSD, and NanoSort
that label tumor cells in different colors based on their acquisition of molecular lesions that dictate malignant
progression and response to therapy, facilitating their detection, quantification and isolation using an integrated
'lab-on a chip' flow cytometer. !
“为癌症添加颜色:腺病毒和流式细胞术识别和捕获 CTC”
纳米排序
研究及相关其他项目信息
7. 项目概要
我们提出了一种利用工程化方法识别和捕获循环肿瘤细胞(CTC)的新技术
腺病毒和复杂的流式细胞术。目前检测 CTC 的技术包括反向检测
转录酶聚合酶链式反应 (RT-PCR)、流式细胞术、荧光原位杂交,以及
最近,微流体技术。不幸的是,RT-PCR 无法区分存活的转移性 CTC
与源自原发肿瘤的核酸或细胞片段相比。 !基于抗体的技术
不能用于检测所有癌症,而只能用于检测那些表达最常见和最良好的癌症。
特征标记。因此,迫切需要开发新的诊断剂和工具,而不是
不仅可以检测和捕获 CTC,还可以量化其恶性潜力并确定“预先”疗法
对消融个别患者的肿瘤最有效。尽管存在复杂性和可变性
在基因组规模的癌症中,一个统一的主题是它们的生长失调表型,即所谓的标志
癌症的发生是由相对少数关键途径的突变造成的。而不是专注于
检测肿瘤之间数量众多且高度可变的个体遗传病变,我们建议
创建在其基因组中整合多个转录和分子模块的诊断病毒
感染并检测患者的肿瘤,报告其分子“标志”及其对不同疗法的反应“向上”
正面'。使用这些药物,任何给定肿瘤的分子病变和恶性特征将被
通过标准化自动化平台快速识别(24 小时内)并评分。此外,这些
试剂还可以用作报告者来快速直接地确定患者的肿瘤是否可能产生反应
到特定的治疗。我们的目标是开发一个标准化的自动化平台,提供现场护理
诊断在分子复杂性和预后能力水平上为临床决策提供信息
可能与任何其他检测系统、生物标志物或相关基因表达特征一起使用。达到
为此,我们将结合索尔克、加州大学圣地亚哥分校和 NanoSort 开发的变革性新技术平台
根据肿瘤细胞获得的指示恶性的分子病变,用不同的颜色标记肿瘤细胞
进展和对治疗的反应,利用集成的方法促进其检测、量化和分离
“芯片实验室”流式细胞仪。 !
项目成果
期刊论文数量(0)
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Lyudmila Bazhenova其他文献
Lyudmila Bazhenova的其他文献
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{{ truncateString('Lyudmila Bazhenova', 18)}}的其他基金
Ading color to cancer, adenovirus and flow cytometry to identify and capture CTCs
为癌症、腺病毒和流式细胞术着色以识别和捕获 CTC
- 批准号:
8223340 - 财政年份:2011
- 资助金额:
$ 15.22万 - 项目类别:
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