Characterizing Oral Cancer Progression via Saliva Proteomics

描述(申请人提供)：口腔癌在美国每年造成超过30,000例癌症，是全球第六大常见癌症。这些癌症的五年存活率(约50%)是癌症主要发展部位中最差的之一，在过去30年中没有显著改善。可靠的分子标记可以在过程的早期预测这种转变，并在容易获得的临床样本中进行筛选，将使患者能够进行更知情的治疗和监测，并有助于显著改善口腔癌患者的预后。这项拟议工作的总体目标是通过识别整个人类唾液中可预测口腔癌发展的蛋白质生物标志物来满足这一关键需求。这一目标将通过三个具体目标来实现：1)表征与口腔癌进展相关的分泌性唾液蛋白质组的变化；2)表征与口腔癌进展相关的口腔脱落上皮细胞蛋白质组和组织活检的变化；3)通过靶向质谱分析验证候选的预测口腔癌蛋白质生物标记物。将使用由组装的研究团队开发的战略，包括新的多肽分级方法、基于靶向质谱学的生物标记物验证方法以及使计算和生物信息学工具成为可能的方法。将分析一个信息量很大的口腔癌进展模型，该模型由从口腔癌发展中期阶段的个人收集的独特临床样本组成，控制吸烟的风险因素，并能够识别癌症发展早期的诊断蛋白质变化。总而言之，先进技术、独特临床样本的可用性以及集合的研究团队的集体专业知识将为成功发现和验证口腔癌的有前景的临床生物标记物提供条件。 与公众健康相关：拟议的研究将确定临床唾液样本中预测口腔癌发展的蛋白质，提供有希望的诊断标记物，这些标记物可以开发成常规的临床患者测试。因此，拟议研究的结果将对改进临床上口腔癌的诊断和治疗产生直接影响，从而减少这种癌症造成的重大痛苦和死亡。

DESCRIPTION (provided by applicant): Oral cancer accounts for over 30,000 cases of cancer per year in the United States and is the sixth most common cancer worldwide. The five-year survival rate (approximately 50%) from these carcinomas is one of the worst for the major sites of cancer development, and has not significantly improved in the past 30 years. Reliable molecular markers that can predict this transition early in the process and be screened for in readily obtained clinical samples would enable more informed treatment and monitoring of patients, and help to significantly improve the prognosis of oral cancer patients. The overall objective of the proposed work is to address this critical need by identifying protein biomarkers in whole human saliva that are predictive of oral cancer development. This objective will be achieved through three Specific Aims: 1) Characterize changes in the secreted saliva proteome associated with oral cancer progression; 2) Characterize changes in the exfoliated oral epithelial cellular proteome and tissue biopsies associated with oral cancer progression; 3) Validate candidate predictive oral cancer protein biomarkers via targeted mass spectrometric analysis. Strategies developed by the assembled research team, including novel peptide fractionation methods, targeted mass spectrometry-based biomarker validation methods, and enabling computational and bioinformatic tools will be employed. A highly informative oral cancer progression model will be analyzed, composed of unique clinical samples collected from individuals at intermediate stages of oral cancer development, controlling for the risk factor of smoking, and enabling the identification of diagnostic protein changes at the earliest stages of cancer development. Taken together, the combination of advanced technologies, availability of unique clinical samples, and the collective expertise of the assembled research team will provide for the successful discovery and validation of promising clinical biomarkers of oral cancer. RELEVANCE TO PUBLIC HEALTH: The proposed studies will identify proteins in clinical saliva samples that are predictive of oral cancer development, providing promising diagnostic markers which can be developed into routine clinical patient tests. As such the findings from the proposed studies will have a direct impact on improving the diagnosis and treatment of oral cancer in the clinic, thereby leading to a decrease in the significant suffering and death caused by this cancer.