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中文摘要
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 描述(申请人提供):膀胱癌(BCA)是世界上最常见的五种恶性肿瘤之一。仅在美国,2012年新发的BCA病例估计为73,500例,死亡人数估计为14,880人。在临床表现上,大多数膀胱肿瘤是非肌肉侵袭性的,可以通过经尿道肿瘤电切术进行治疗,然而,超过70%的BCA患者在确诊后的头两年内会复发。这种复发现象使BCA成为世界上最常见的癌症之一。此外,一旦接受治疗,患者将继续接受常规膀胱镜检查,以检测新的肿瘤发展,因此BCA的医疗成本是主要负担。该项目的总体目标是开发能够通过尿检实现准确、非侵入性的BCA检测的检测方法。利用高通量基因组图谱技术,我们已经获得了一系列分子特征,其表现优于目前用于检测BCA的任何尿液分析方法。第一个具体目标是使用替代技术来验证这些特征的组成部分的诊断准确性。目标是确定该方法的技术和科学价值。将设计进一步的具体目标,以确定将选定的基于核酸的分子特征发展成具有临床实用价值的可靠分析的可行性。在拟议的研究结束时,分析方法将准备好开发用于临床。用于膀胱癌检测和疾病状态评估的非侵入性尿液检测方法的发展将对患者和医疗保健系统都有极大的好处。
英文摘要
 DESCRIPTION (provided by applicant): Bladder cancer (BCa) is among the five most common malignancies worldwide. In the US alone, new BCa cases for 2012 are estimated at 73,500 with estimated deaths at 14,880. At presentation, the majority of bladder tumors are non‐muscle invasive, and can be treated by transurethral resection of the tumor, however, more than 70% of patients with BCa will have a recurrence during the first two years after diagnosis. This recurrence phenomenon makes BCa one of the most prevalent cancers worldwide. Furthermore, once treated, patients are under continued surveillance with routine cystoscopy for detection of new tumor development, so the healthcare costs of BCa are a major burden. The overall goal of this project is to develop assays that can achieve the accurate, non‐invasive detection of BCa via urinalysis. Using high‐throughput genomic profiling technologies, we have derived a series of molecular signatures that outperform any currently used urinalysis assay for BCa detection. The first specific aims are designed to validate the diagnostic accuracy of components of these signatures using alternative techniques. The goal is to establish the technical and scientific merit of the approach. Further specific aims will be designed to determine the feasibility of developing selected nucleic acid‐based molecular signatures into robust assays with clinical utility. At the end of the proposed study, assays will be ready for development for use in the clinic. The development of non‐invasive, urine based assays for bladder cancer detection and disease status evaluation will be of tremendous benefit to both patients and the healthcare system.
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Prognostic analysis and progression modeling of basal-like breast cancer using multi-region sequencing
Disease Progression Modeling of Bladder Cancer
  • 批准号:
    10518025
  • 项目类别:
  • 资助金额:
    $50.75万
  • 财政年份:
    2022
  • 负责人:
    Steve Goodison
  • 依托单位:
Disease Progression Modeling of Bladder Cancer
  • 批准号:
    10674950
  • 项目类别:
  • 资助金额:
    $48.57万
  • 财政年份:
    2022
  • 负责人:
    Steve Goodison
  • 依托单位:
Advanced Computational Approaches to Delineating Dynamic Cancer Progression Processes by Using Massive Static Sample Data
海外基金