Combining Machine Learning and Nanofluidic Technology for The Multiplexed Diagnosis of Pancreatic Adenocarcinoma
结合机器学习和纳流体技术进行胰腺癌的多重诊断
基本信息
- 批准号:10613226
- 负责人:
- 金额:$ 38.83万
- 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:2023-06-01 至 2026-05-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAlgorithmsBenchmarkingBenignBiological AssayBiological MarkersBlindedBloodBlood specimenCA-19-9 AntigenCancer EtiologyCell LineCessation of lifeClassificationClinicalDataData SetDetectionDevelopmentDiagnosisDiagnosticDiseaseDisease ProgressionDistant MetastasisEarly DiagnosisElementsEndoscopic BiopsyEndoscopyEnvironmentEvaluationGoalsHourImageIndividualKRAS2 geneLesionLocalized DiseaseMachine LearningMagnetic Resonance ImagingMagnetismMalignant - descriptorMalignant NeoplasmsMalignant neoplasm of pancreasMembrane ProteinsMessenger RNAMethodsMicroRNAsModelingMolecular ProfilingMonitorMutation DetectionNeoplasm MetastasisNucleic AcidsOperative Surgical ProceduresPancreasPancreatic AdenocarcinomaPancreatic DiseasesPancreatic Ductal AdenocarcinomaPancreatitisPatient-Focused OutcomesPatientsPerformancePhysiciansPlasmaPositron-Emission TomographyProteinsRNARNA ProbesResectableRoleSamplingSortingStagingStreamSurfaceTechnologyTestingTrainingTumor-DerivedTumor-associated macrophagesUnited StatesValidationVesicleWorkX-Ray Computed Tomographycell free DNAcell typeclinical diagnosticscohortdesigndetection limitdetection sensitivitydiagnostic signaturediagnostic valuedisorder controldrug efficacyefficacious treatmentextracellular vesiclesimprovedinnovationinstrumentationliquid biopsymachine learning classificationmachine learning classifiermanufacturabilitymicrofluidic technologymultimodalitynanofluidicnanoparticlenanoporenanoscaleneoplastic cellnext generationnoninvasive diagnosisnovel strategiesoperationphysical propertypredictive panelprognostic signatureprotein expressionscreeningstandard of caretreatment responsetumortumor DNA
项目摘要
Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death in
the United States with an overall 5-year survival of 9%. Diagnosis and staging continue to rely
on endoscopic biopsy and imaging, and as such most patients are diagnosed at an advanced
stage. Sufficiently sensitive and specific screening tests for early disease remain elusive.
Moreover, while curative-intent surgery is an option for patients whose disease is confined to
the pancreas, distinguishing patients with metastases who are unlikely to benefit from surgery,
remains challenging due to occult metastases not detectable by imaging. To address these
challenges, several blood-based liquid biopsy biomarkers have been developed but show low
sensitivity for detection of early-stage disease. We have recently shown that circulating tumor
derived extracellular vesicles(EVs) can be isolated from blood and their RNA cargo used to
diagnose early pancreatic cancer and stage disease. These findings suggest an opportunity to
improve patient outcomes through development of a non-invasive diagnostic for pancreatic
cancer. However, as has been well documented, EVs are highly heterogeneous in their
expression of protein surface markers and their nucleic acid and protein cargo, and originate
from multiple cell types in the tumor micro environment (TME) (e.g. tumor cells, tumor
associated macrophages). The ultimate goal of this proposal is to address a fundamental
technological unmet need in EV diagnostics, by further developing our new approach to EV
subpopulation isolation using magnetic nanopores, which combines the benefits of nano-scale
sorting with sufficiently fast flow rates (106x faster than typical nanofluidic approaches) to be
practical for clinical diagnostics. In this R33, we develop this approach into a multiplexed EV
assay that will allow multiple unique EV sub-populations - based on surface marker expression-
to be isolated and their RNA cargo profiled. Building on our prior work that demonstrated the
value of analyzing single EV-subpopulations, and improved sensitivity of a multi-analyte vs
single analyte test, we will develop a multi-analyte EV-based assay that algorithmically
combines tumor associated EV RNA from multiple circulating EV isolates from the TME, as well
as Circulating cell-free DNA (ccfDNA) concentration, circulating tumor DNA-based KRAS
mutation detection, and CA19-9 using machine learning.
胰腺导管腺癌(PDAC)是美国癌症相关死亡的第三大原因
项目成果
期刊论文数量(0)
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Erica Carpenter其他文献
Erica Carpenter的其他文献
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{{ truncateString('Erica Carpenter', 18)}}的其他基金
Real-time monitoring of circulating pancreatic tumor cells and clusters
实时监测循环胰腺肿瘤细胞和簇
- 批准号:
9512562 - 财政年份:2016
- 资助金额:
$ 38.83万 - 项目类别:
Real-time monitoring of circulating pancreatic tumor cells and clusters
实时监测循环胰腺肿瘤细胞和簇
- 批准号:
10219169 - 财政年份:2016
- 资助金额:
$ 38.83万 - 项目类别:
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