Highly Integrated Nucleic-Acid Analysis Using Graphene Bioelectronics
使用石墨烯生物电子学进行高度集成的核酸分析
基本信息
- 批准号:10584520
- 负责人:
- 金额:$ 18.99万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-04-01 至 2024-12-31
- 项目状态:已结题
- 来源:
- 关键词:AffinityAnimal ModelBiological AssayBiological MarkersBiopsyBiopsy SpecimenBlindedBuffersClinicalClinical TrialsComplexConsumptionCore FacilityDNADNA ProbesDevelopmentDevicesDiagnosisDiagnosticDiseaseDisease ProgressionElectrodesElectronicsGenerationsGenomicsGoalsHospitalsHourImmunoassayInterventionInvestigationMeasurableMeasuresMicroRNAsMonitorMusNoninfiltrating Intraductal CarcinomaNucleic AcidsOligonucleotidesOperative Surgical ProceduresOutcomePathway interactionsPatientsPerformancePlasmaPopulationPrognosisProgressive DiseasePropertyPublic HealthReactionRecurrenceResearchRisk AssessmentSamplingSignal PathwaySignal TransductionTechnologyTestingTherapeuticTimeTransducersTransistorsTranslatingTranslational ResearchValidationVisitXenograft Modelbioelectronicsbreast cancer progressioncirculating microRNAclinical careclinical translationcohortcostdetection limitdiagnostic technologiesdisease diagnosisearly screeninggenomic predictorsgraphenehuman subjectimprovedindividualized medicineliquid biopsymalignant breast neoplasmmicro-total analysis systemmouse modelnew therapeutic targetnext generationoutcome predictionovertreatmentpH gradientpoint of carepoint-of-care diagnosispre-clinicalpreventprognosticprogramsresponsescreeningsensortargeted treatmenttechnology platformtechnology validationtreatment responsetreatment strategyuser-friendlyvoltage
项目摘要
PROJECT SUMMARY
The circulating population of microRNAs in biofluids are ideal biomarkers for various diseases. Point-of-care
profiling of circulating microRNAs is in insatiable demand, but typical approaches, e.g., immunoassays and
microRNA assays are lab-based/centralized, expensive ($400–1,000/test), and time-consuming (>6 hours). We
will develop a highly integrated, all-nanobioelectronic platform technology for multiplex, high-accuracy
circulating-microRNA analysis that is capable of profiling circulating microRNAs in a 50-μL plasma with ultra-
high sensitivity (sub-fM) and efficiencies in time (<40 minutes) and cost (<$10/test), thereby enabling high-
performance circulating-microRNA analysis at the point of test. The novelty of the program is to harness
graphene-based bioelectronics to integrate circulating microRNA isolation, concentration, amplification, and
quantification into a self-contained device. In order to proof the concept of this technology, the program will
include the development and validation of two generations of graphene-based analytical platforms, GAP1 and
GAP2. Three specific aims with measurable milestones will be pursued. (1) We will demonstrate that multiple
microRNA analytes can be amplified via hybridization chain reaction on a probe-functionalized graphene sensor
array and the analyte concentrations can be readily interrogated by the graphene sensor array and translated
into electrical signals. We will develop GAP1 to selectively quantify eight pre-selected target microRNAs
(MDCIS8) spiked in 5-μL buffer. The detection limit of the specific microRNAs is expected to be at fM level. (2)
We will demonstrate that target circulating microRNAs can be isolated from plasma by immobilizing them on a
DNA-functionalized graphene electrode and releasing them into a small-volume simple cargo solution upon the
generation of pH gradient by applying voltage bias between the graphene-DNA electrode with a bare graphene
electrode. We will develop a graphene-based circulating-microRNA isolation module, combine the module with
GAP1 to form GAP2, and use GAP2 to profile circulating MDCIS8 in lysed samples of 50-μL plasma from NSG
mice. The GAP2 is expected to concentrate the microRNAs by >5× and deliver sub-fM level sensitivity. (3) We
will demonstrate the feasibility of using this platform technology for diagnostic applications. We will use GAP2 to
quantify circulating MDCIS8, whose expression levels are indicative to pre-invasive breast cancer, in 50-μL
plasma samples from a user blinded cohort of the MIND murine model. The profiling result will be analyzed to
predict the progression of pre-invasive breast cancer whose rapid, inexpensive diagnosis remains a challenge.
The GAP2 prediction outcome will be combined with that based on surgical biopsy to establish the accuracy of
the technology for progression prediction. The expected prediction accuracy is >96%. If successful, the
technology will offer a new pathway to next-generation point-of-care genomic diagnostic/prognostic micro total
analysis systems that would be cheap enough and user friendly enough to be used in various clinical settings.
项目摘要
生物流体中的microRNA循环群体是各种疾病的理想生物标志物。Point-of-care
循环微RNA的谱分析是永不满足的需求,但典型的方法,例如,免疫测定和
microRNA检测是基于实验室/集中式的,昂贵(400 - 1000美元/次),耗时(>6小时)。我们
将开发高度集成的全纳米生物电子平台技术,
循环microRNA分析,该分析能够在50 μL血浆中用超声波分析循环microRNA。
高灵敏度(亚fM)和时间效率(<40分钟)和成本(<10美元/测试),从而实现高
在测试点进行循环microRNA分析。该计划的新奇在于利用
基于石墨烯的生物电子学集成循环microRNA分离,浓缩,扩增,
量化到一个独立的设备。为了证明这项技术的概念,该计划将
包括开发和验证两代基于石墨烯的分析平台,GAP 1和
差距2.将努力实现三个具体目标和可衡量的里程碑。(1)我们将证明,
微RNA分析物可以通过探针功能化的石墨烯传感器上的杂交链反应来扩增
并且分析物浓度可以容易地被石墨烯传感器阵列询问并且被转换
转换成电信号我们将开发GAP 1来选择性地定量八种预先选择的靶microRNA。
(MDCIS 8)加标于5 μL缓冲液中。特异性microRNA的检测限预计在fM水平。(二)
我们将证明,通过将靶循环microRNA固定在一个微载体上,可以从血浆中分离出靶循环microRNA。
DNA官能化的石墨烯电极,并将它们释放到小体积的简单货物溶液中,
通过在石墨烯-DNA电极与裸石墨烯之间施加偏压产生pH梯度
电极上我们将开发一种基于石墨烯的循环microRNA分离模块,联合收割机该模块与
GAP 1形成GAP 2,并使用GAP 2分析NSG 50 μL血浆裂解样本中的循环MDCIS 8
小鼠预计GAP 2将microRNA浓缩>5倍,并提供亚fM水平的灵敏度。(3)我们
将展示使用该平台技术进行诊断应用的可行性。我们将使用GAP 2
定量50 μL中的循环MDCIS 8,其表达水平指示浸润前乳腺癌
来自MIND鼠模型的用户盲组的血浆样品。分析结果将被分析,
预测浸润前乳腺癌的进展,其快速,廉价的诊断仍然是一个挑战。
GAP 2预测结果将与基于手术活检的结果相结合,以确定以下指标的准确性:
进展预测技术。预测准确率> 96%。如果成功,
技术将为下一代即时基因诊断/预后微全
分析系统将足够便宜且足够用户友好,可用于各种临床环境。
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)
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{{ truncateString('Jinglei Ping', 18)}}的其他基金
Cell Control via Spatiotemporal Microenvironmental pH Modulation
通过时空微环境 pH 调节进行细胞控制
- 批准号:
10713388 - 财政年份:2023
- 资助金额:
$ 18.99万 - 项目类别:
Highly Integrated Nucleic-Acid Analysis Using Graphene Bioelectronics
使用石墨烯生物电子学进行高度集成的核酸分析
- 批准号:
10372664 - 财政年份:2022
- 资助金额:
$ 18.99万 - 项目类别:
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