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中文摘要
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描述(由申请人提供):浅表性膀胱肿瘤的复发现象使膀胱癌成为世界范围内最常见的癌症之一,因此是医疗保健系统的巨大负担。浅表性肿瘤患者应继续接受常规膀胱镜检查,以早期发现新的肿瘤发展。这是由于缺乏临床有用的标志物,可以检测膀胱癌的存在而无需侵入性手术。因此,使用可靠的诊断标记物的尿液分析测定的发展将对患者和医疗保健系统都有巨大的好处。本提案旨在基于蛋白质组学表达谱来定义膀胱癌的分子特征。尿液样本的蛋白质补体将使用二维、液相分离和下游质量制图技术的新组合进行分析。包括定量和结构信息的数据将与临床和病理参数相关联。因此,拟议的研究将确定膀胱癌存在的分子谱。
英文摘要
DESCRIPTION (provided by applicant): The recurrence phenomenon of superficial bladder tumors makes bladder cancer one of the most prevalent cancers world-wide and is therefore a great burden to healthcare systems. Patients with superficial tumors are under continued surveillance by routine cystoscopy examinations of the bladder for early detection of new tumor developments. This is due to the lack of clinically useful markers which can detect the presence of bladder cancer without invasive procedures. Consequently, the development of urinalysis assays using reliable diagnostic markers would be of tremendous benefit to both patients and healthcare systems. This proposal aims to define molecular signature(s) of bladder cancer based on proteomic expression profiles. The protein complement of urine samples will be profiled using a novel combination of two-dimensional, liquid-phase separation and downstream mass mapping techniques. Data comprised of both quantitative and structural information will be correlated with clinical and pathological parameters. Thus, the proposed investigation will identify molecular profiles which are indicative of the presence of bladder cancer. Public health impact: The project seeks insights that will enable improvements in the non-invasive diagnosis of bladder cancer, through analysis of naturally voided urine. This will avoid unnecessary cystoscopy and therefore reduce patient discomfort and reduce health costs. Furthermore, the establishment of an accurate urine-based assay could lead to the development of routine screening of the population.
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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
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