MicroRNA determinants of oral cancer detection

描述（由申请人提供）：口腔癌是最常见的癌症之一。在美国，每年有超过39，000例新的口腔癌病例。它每年造成大约8，000人死亡，大约每小时1人死亡。口腔癌的主要临床问题之一是疾病的晚期发现。提高患者生存率需要更好的 我们的目标是了解口腔癌的发生和发展，以便在疾病过程的早期检测到侵袭性肿瘤，并可以部署有针对性的治疗干预措施。虽然许多研究致力于研究口腔癌发生的分子事件，但大多数努力都集中在蛋白质编码基因上。关于非编码基因作用的知识（例如，microRNA）在口腔癌中的作用相对有限。我们最近的研究已经证明了microRNA失调在口腔癌中的关键作用。然而，与早期口腔癌相关的全面microRNA改变模式仍然缺乏，这阻碍了microRNA作为诊断生物标志物的潜在利用。 口腔刷检细胞学是一种微创的方法，可用于从可疑的口腔病变中收集细胞进行组织学和生化分析。我们最近的研究结果表明，我们可以一致地测量刷口腔细胞学样本中的RNA标记。在这项研究中，我们将从刷口腔细胞学样本中识别与早期口腔癌相关的独特microRNA特征（具体目标1）。然后，我们将在一个独立的样本集中测试这些microRNA标记物的诊断价值（特定目标2）。将开发统计分类模型来评估这些microRNA的诊断价值。 该提案将微创方法与新兴的基因组技术相结合，以利用口腔癌中的microRNA决定簇。这项研究的结果将为更广泛的基于患者的研究提供强有力的理论基础和科学基础，以识别和验证用于早期检测口腔癌的microRNA生物标志物。

DESCRIPTION (provided by applicant): Oral cancer is one of the most common cancers. In the US there are over 39,000 new cases of oral cancer each year. It causes approximately 8,000 deaths per year, killing roughly 1 person per hour. One of the major clinical problems of oral cancer is the late detection of the disease. Improvement in patient survival requires a better understanding of oral cancer initiation and progression, so that aggressive tumors can be detected early in the disease process and targeted therapeutic interventions can be deployed. While many studies have been devoted to investigate molecular events in tumorigenesis of oral cancer, most efforts are focused on protein coding genes. The knowledge on the role of non-coding genes (e.g., microRNA) in oral cancer is relatively limited. Our recent studies have demonstrated critical contributions of microRNA deregulation in oral cancer. However, the comprehensive microRNA alteration pattern associated with early stage oral cancer is still lacking, which hindered the potential utilization of microRNA as diagnostic biomarkers. Brush oral cytology is a minimally-invasive method that can be used to collect cells from suspect oral lesions for histological and biochemical analyze. Our recent results demonstrated that we can consistently measure RNA markers in the brush oral cytology samples. In this study, we will identify unique microRNA signatures that associated with early stage oral cancer from the brush oral cytology samples (Specific Aim 1). We will then test the diagnostic values of these microRNA markers in an independent sample set (Specific Aim 2). Statistical classification models will be developed to assess the diagnostic values of these microRNAs. This proposal combines minimally-invasive methods with the emerging genomic technologies to harness microRNA determinants in oral cancer. The outcomes from this study will provide strong rationale and scientific foundation for more extensive patient- based studies to identify and validate microRNA biomarkers for early detection of oral cancer.