Personalized assessment of bladder cancer treatment response using urinary molecular biomarkers
使用尿液分子生物标志物对膀胱癌治疗反应进行个性化评估
基本信息
- 批准号:10514572
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:AdultAfghanistanAromatic AminesAwarenessBCG LiveBacillus Calmette-Guerin TherapyBenignBiologicalBiological MarkersBladderBloodCancer DetectionCancer PatientCessation of lifeChemical ExposureClinicalClinical TrialsClinical Trials DesignClinics and HospitalsCollaborationsCystoscopyCytologyDataDecision MakingDevelopmentDiagnosisDiagnosticDiagnostic SensitivityDiseaseDoctor of PhilosophyEmotionalEnvironmental ExposureEpidemiologistExposure toFoundationsGeneral PopulationGoalsHealthHealth Services AccessibilityHematuriaHigh-Throughput RNA SequencingIraqLesionLiquid substanceMalignant NeoplasmsMalignant neoplasm of urinary bladderMeasurementMeasuresMedicalMessenger RNAMicrofluidicsMicroscopicModelingMolecularMonitorMorbidity - disease rateNucleic AcidsOperative Surgical ProceduresParticulatePatientsPerformancePopulationPrediction of Response to TherapyProceduresRecording of previous eventsRecurrenceResearchResearch DesignResearch PersonnelResidual CancersRiskRisk AssessmentRisk FactorsSamplingScientistScreening for cancerServicesSmokeSmokingSolidStagingSymptomsTechnologyTestingTherapeutic InterventionTobacco useTranslationsTransurethral ResectionTumor-DerivedUrineUrologic DiseasesUrologic OncologyUrologic SurgeonValidationVeteransVietnamagent orangebiomarker discoverybiomarker panelburden of illnessburn pitcancer riskcancer typeclinical translationdiagnostic strategydiagnostic toolexperiencefallshigh riskimprovedimproved outcomeintravesicalmolecular diagnosticsmolecular markernon-muscle invasive bladder cancerpatient stratificationpersonalized approachpersonalized medicinepersonalized therapeuticprospectiveresponserisk stratificationscreeningtooltreatment responsetreatment strategytumorurinaryvalidation studies
项目摘要
Bladder cancer is the sixth most common cancer in the U.S., has one of the highest recurrence rates of all solid
cancers, and is the most expensive cancer to treat from diagnosis to death. Veterans are at increased risk for
bladder cancer due higher rates of tobacco use and environmental exposure. There are significant unmet needs
for biomarkers and molecular diagnostic tools to better inform decision making across all stages of bladder
cancer. For patients with early stage disease, current diagnostic approaches are either invasive (e.g. cystoscopy)
or lack sensitivity (e.g. urine cytology). We propose to develop molecular diagnostics that will lead to more
effective and personalized therapeutic strategies for patients with localized bladder cancer. Tumor-derived
nucleic acids in biological fluids such as urine represent promising biomarkers for non-invasive measurement of
disease burden and response to therapy. Previously, we developed a pipeline for bladder cancer biomarker
discovery, validation, and technology integration for clinical translation. We applied high throughput RNA
sequencing of urinary sediments as a biomarker discovery tool and identified a urinary mRNA (u-mRNA) panel
with promising diagnostic performance. In parallel, we validated an integrated microfluidics cartridge capable
of “sample-in, answer-out” within 90 minutes using a separate u-mRNA panel. Our recent preliminary data
indicate further improvement of diagnostic performance by combining the two panels within the integrated
cartridge. Based on these promising preliminary data, we propose three specific aims: 1) to validate the
optimized mRNA panel for bladder cancer surveillance and risk stratification; 2) to validate the optimized u-
mRNA panel to improve bladder cancer screening and assess risk stratification; and 3) to validate the optimized
u-mRNA panel for response assessment and monitoring in patients with high risk NMIBC treated with BCG
immunotherapy. Our team is led by experienced academic VA investigators with complimentary expertise in
molecular diagnostics (Liao), urologic oncology (Liao, Leppert), and clinical validation study design (Liao, Yu).
Successful completion of the studies proposed here will serve as a foundation for incorporating urine-based
biomarkers in bladder cancer surveillance and into prospective clinical trials to assess therapeutic interventions.
We foresee that our approach will allow personalization of treatment strategies to improve outcomes for BC
patients in both veterans and the general population.
膀胱癌是美国第六大常见癌症,是所有实体癌症中复发率最高的癌症之一
癌症,并且是从诊断到死亡的治疗费用最高的癌症,退伍军人面临更高的风险。
膀胱癌由于烟草使用率和环境暴露率较高而存在显着的未满足的需求。
用于生物标志物和分子诊断工具,以更好地为膀胱各个阶段的决策提供信息
对于早期疾病患者,目前的诊断方法是侵入性的(例如膀胱镜检查)。
或缺乏敏感性(例如尿液细胞学),我们建议开发分子诊断技术,以产生更多结果。
针对局限性膀胱癌患者的有效且个性化的治疗策略。
尿液等生物体液中的核酸代表了用于非侵入性测量的有前途的生物标志物
此前,我们开发了膀胱癌生物标志物的管道。
我们应用高通量 RNA 进行临床转化。
将尿沉渣测序作为生物标志物发现工具并鉴定尿 mRNA (u-mRNA) 组
同时,我们验证了具有良好诊断性能的集成微流体盒。
使用我们最近的初步数据,可以在 90 分钟内实现“样本输入、结果输出”。
表明通过将集成的两个面板结合起来可以进一步提高诊断性能
基于这些有希望的初步数据,我们提出了三个具体目标:1)验证
用于膀胱癌监测和风险分层的优化 mRNA 组合;2) 验证优化的 u-
mRNA panel 可改善膀胱癌筛查并评估风险分层;3) 验证优化结果;
u-mRNA panel 用于评估和监测接受 BCG 治疗的高危 NMIBC 患者的反应
我们的团队由经验丰富的 VA 学术研究人员领导,他们在免疫治疗方面拥有丰富的专业知识。
分子诊断(Liao)、泌尿肿瘤学(Liao、Leppert)和临床验证研究设计(Liao、Yu)。
成功完成此处提出的研究将为纳入基于尿液的研究奠定基础
膀胱癌监测和前瞻性临床试验中的生物标志物以评估治疗干预措施。
我们预计,我们的方法将允许个性化治疗策略,以改善 BC 的结果
患者包括退伍军人和普通人群。
项目成果
期刊论文数量(0)
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JOSEPH C LIAO其他文献
JOSEPH C LIAO的其他文献
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{{ truncateString('JOSEPH C LIAO', 18)}}的其他基金
Intraoperative integration of artificial intelligence during cystoscopic surgery
膀胱镜手术中人工智能的术中整合
- 批准号:
10544344 - 财政年份:2022
- 资助金额:
-- - 项目类别:
Intraoperative integration of artificial intelligence during cystoscopic surgery
膀胱镜手术中人工智能的术中整合
- 批准号:
10365872 - 财政年份:2022
- 资助金额:
-- - 项目类别:
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MagSToNE - 用于消除肾结石碎片的磁性系统
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10491338 - 财政年份:2021
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BCCMA: Basic and Translational Mechanisms of Cancer Initiation of the Urothelium in Veterans Exposed to Carcinogens: Leveraging Artificial Neural Networks to Enhance Detection of Carcinoma in situ
BCCMA:暴露于致癌物的退伍军人尿路上皮癌症发生的基本和转化机制:利用人工神经网络增强原位癌的检测
- 批准号:
10260145 - 财政年份:2021
- 资助金额:
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MagSToNE - a magnetic system for kidney stone fragment elimination
MagSToNE - 用于消除肾结石碎片的磁性系统
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10354258 - 财政年份:2021
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BCCMA: Basic and Translational Mechanisms of Cancer Initiation of the Urothelium in Veterans Exposed to Carcinogens: Leveraging Artificial Neural Networks to Enhance Detection of Carcinoma in situ
BCCMA:暴露于致癌物的退伍军人尿路上皮癌症发生的基本和转化机制:利用人工神经网络增强原位癌的检测
- 批准号:
10513315 - 财政年份:2021
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Personalized assessment of bladder cancer treatment response using urinary molecular biomarkers
使用尿液分子生物标志物对膀胱癌治疗反应进行个性化评估
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Personalized assessment of bladder cancer treatment response using urinary molecular biomarkers
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