Molecular Analysis of OSCC Tumor Invasion

淋巴结阳性口腔鳞状细胞癌（OSee）患者的5年生存率仅为20-30% 即使是多模式治疗。不幸的是，目前的分期系统不能预测osee肿瘤 淋巴结疾病或患者结果，并且没有单个基因被证明具有足够的预后效用。 此外，最先进的临床成像技术可能会错过亚临床转移。发现更多 一种预测淋巴结阳性原发性肿瘤和患者预后的准确而有力的方法， 需要鉴定和表征肿瘤微环境中表达的基因。使用 包括骨赘和间质成分的Affyellow微阵列和肿瘤样本， 我们已经发现了一个基因标记，它可以预测哪些原发性肿瘤会转移到 淋巴结在这个建议中，使用这个osee初步节点正签名进行比较，我们将 检验一个假设，即一个更准确和可靠的标志，用于预测osee淋巴结疾病 可以通过分别从OSEE肿瘤和间质中获得基因标记来鉴定 淋巴结阴性和阳性的Osee原发性肿瘤的组分。在Aim-1中，我们将使用微阵列， 激光捕获显微切割（LeM），并统计以识别Osee肿瘤细胞成分节点 使用Osee淋巴结阳性和阴性原发性肿瘤的阳性标记。在Aim-2中，我们将使用 微阵列、LeM和统计学来定义osee基质区室的节点阳性特征 使用OSEE淋巴结阳性和阴性原发肿瘤。两种分子特征都将得到验证 在RNA和蛋白质水平上。此外，将测试每个签名预测淋巴结疾病的能力 使用盲。osee肿瘤的队列。最后，将使用统计平台比较所有签名， 并且将使用相同的OSEE群组选择能够预测淋巴结阳性的最佳基因组 肿瘤的这项研究将涉及一个多学科的合作者团队，他们具有DNA和组织方面的专业知识。 微阵列、激光捕获显微切割、肿瘤和分子生物学、统计学、医学、头颈部 外科学和病理学以及多机构合作。除了找出最好的签名， 预测osee结疾病，这项研究的结果将确定基因，生物标志物和信号 肿瘤微环境中可作为诊断、预后和治疗靶点的通路 问题研究在该提议中鉴定的准确和可靠的淋巴结转移基因标签将具有 对降低OSEE患者死亡率和发病率具有深远的临床效用。

Patients with node positive oral squamous cell carcinomas (OSee) have a 5-year survival of only 20-30% even with multi-modality treatment. Unfortunately, the current staging system does not predict osee tumor nodal disease or patient outcome, and no single gene has been shown to have sufficient prognostic utility. Moreover, state-of-the-art clinical imaging techniques can miss sub-clinical metastases. Discovering a more accurate and powerful way of predicting lymph node positive primary tumors and patient outcomes will require identification and characterization of the genes expressed within the tumor microenvironment. Using Affymetrix microarrays and tumor specimens comprised of both osee neoplastic and stromal components, we have discovered a gene signature that predicts which osee primary tumors will metastasize to the lymph nodes. In this proposal, using this osee preliminary node positive signature for comparison, we will test the hypothesis that a more accurate and reliable signature for prediction of osee lymph node disease can be identified by separately acquiring gene signatures from the osee neoplastic and the stromal components of lymph node negative and positive osee primary tumors. In Aim-1 we will use microarrays, laser capture microdissection (LeM), and statistics to identify the osee Neoplastic cell component node positive signature using osee lymph node positive and negative primary tumors. In Aim-2 we will use microarrays, LeM and statistics to define a node positive signature for the osee Stromal compartment using osee lymph node positive and negative primary tumors. Both molecular signatures will be validated at the RNA and protein level. Additionally, each signature will be tested for its ability to predict nodal disease using a blinded. cohort of osee tumors. Finally, all signatures will be compared using statistical platforms, and the best set of genes will be selected that can predict node positivity using the same cohort of osee tumors. This study will involve a multi-disciplinary team of collaborators with expertise in DNA and tissue microarrays, laser capture microdissection, tumor and molecular biology, statistics, medicine, head and neck surgery, and pathology as well as multi-institutional collaborations. Besides identifying the best signature for prediction of osee nodal disease, the results from this study will identify genes, biomarkers and signaling pathways in the tumor microenvironment that can be targeted for diagnostic, prognostic and therapeutic studies. The accurate and reliable lymph node metastasis gene signature identified in this proposal will have a profound clinical utility for reducing osee patient mortality and morbidity.