MICRORNA BIOMARKERS FOR CERVICAL CANCER

项目简介（由申请人提供）：项目概述据估计，今年美国将有大约12,340例子宫颈癌新病例，其中4,030名妇女将死于这种疾病（美国癌症协会）。在世界范围内，侵袭性宫颈癌是一个更大的问题，是女性中第二大常见的癌症。在标准治疗之前准确预测宫颈癌预后的方法对于早期识别治疗失败高风险患者至关重要。对于这些高危患者，改良疗法可能用于提高患者生存率。然而，传统的临床病理特征，如肿瘤分级和分期，对宫颈癌的预后价值有限。因此，需要开发新的方法来改善预后。在本研究中，我们将验证多个选择的microrna的表达特征可以可靠地预测宫颈癌预后的假设。MicroRNAs （miRNAs）是一个新发现的非编码小RNA分子家族，它们共同控制着数千种蛋白质编码基因的表达。最近的研究表明，mirna是预测癌症治疗结果的有希望的生物标志物。然而，mirna在宫颈癌中的预后价值尚未得到研究。本研究的主要目标是建立一个基于mirna的模型来可靠地预测宫颈癌的预后。我们的初步分析已经确定了两种可预测宫颈癌预后的mirna。在这里，我们建议通过分析大量宫颈肿瘤中所有与宫颈相关的miRNA来显著扩展我们的初步研究，以鉴定新的miRNA生物标志物。然后将这些miRNA生物标志物结合起来，建立一个显著改善宫颈癌预后的稳健模型。

DESCRIPTION (provided by applicant): Project Summary It is estimated that there will be about 12,340 new cases of cervical cancer and those 4,030 women will die of this disease this year in the United States (American Cancer Society). Worldwide, invasive cervical cancer is an even greater problem and is the second most commonly diagnosed cancer in women. A method to accurately predict cervical cancer outcome prior to standard therapy would be critical for the early identification of patients with high risk of treatment failures. For these high-risk patients modified therapy could potentially be applied for improved patient survival. However, traditional clinic pathologic features, such as tumor grade and stage, have limited prognostic values in cervical cancer. Thus, new methods need to be developed for improved prognostic performance. In this proposed research, we will test the hypothesis that the expression signature of multiple selected microRNAs can reliably predict the outcome of cervical cancer. MicroRNAs (miRNAs) are a newly discovered family of small non- coding RNA molecules that collectively control the expression of thousands of protein-coding genes. Recent studies indicate that miRNAs are promising biomarkers to predict cancer therapy outcomes. However, the prognostic value of miRNAs in cervical cancer has not been investigated. The major goal of this research is to build a miRNA-based model to robustly predict cervical cancer outcome. Our preliminary analysis has identified two miRNAs that are predictive of cervical cancer outcome. Here, we propose to significantly expand our preliminary study to identify new miRNA biomarkers by analyzing all cervix-related miRNAs in a large number of cervical tumors. These miRNA biomarkers will then be combined to build a robust model for significantly improved prognosis of cervical cancer.