Molecular Profiling of Premalignant Oral Lesions

口腔癌前病变的分子分析

• 批准号: 7095254
• 负责人: MARK W. LINGEN
• 金额: $ 32.8万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-18 至 2009-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7095254
• 关键词: biomarker; cell morphology; clinical research; gene expression profiling; head /neck neoplasm; human subject; keratinocyte; neoplastic transformation; oral mucosa; preneoplastic state; smoking; squamous cell carcinoma; tobacco abuse

DESCRIPTION (provided by applicant): Head and neck squamous cell carcinoma (HNSCC) is a major health problem affecting current and former tobacco users, with approximately 40,000 cases per year in the United States and 500,000 cases worldwide. The development of HNSCC is heralded by the development of dysplastic lesions within the mucosa and early diagnosis of pre-malignant lesions is known to directly correlate with increased survival. However, current diagnostic techniques for premalignant disease, based on recognition of nuclear and cellular atypia, are relatively poor predictors of ultimate clinical outcome. Since morphological or cytological changes may occur late in the process of transformation, histologically benign appearing lesions may have malignant potential. Conversely, even severely dysplastic oral lesions can undergo spontaneous regression. Thus, histological findings cannot clearly predict malignant change. A method for detecting molecularly premalignant lesions at an early stage and for predicting the likelihood of malignant progression is required. The goal of this proposal is to identify a panel of biomarkers that will allow for the identification of molecularly premalignant lesions. Accordingly, gene expression profiling of microdissected keratinocytes from biopsies containing normal mucosal tissue from nonsmokers and invasive HNSCC will be performed in order to identify potential oral mucosa progression markers (OPM). The interpretation and analysis of the array data will be performed within a newly established Bioinformatics Core. This web-accessible annotation, cataloging facility will use both unsupervised and supervised learning methodologies. The utility of these potential OPMs will then be validated using custom human tissue array samples having the different histologic diagnoses including: normal, reactive, hyperkeratosis, hyperplasia and various grades of dysplasia. These analyses may identify markers that correlate with the biologic severity of dysplasia and with the potential for malignant progression. This molecular analysis may also greatly improve diagnostic prediction compared to the cellular pattern recognition currently used by pathologists.

描述（由申请人提供）：头颈部鳞状细胞癌（HNSCC）是影响当前和既往烟草使用者的主要健康问题，美国每年约有40，000例，全球约有500，000例。HNSCC的发展是由粘膜内发育异常病变的发展预示的，并且已知癌前病变的早期诊断与生存率的增加直接相关。然而，目前的癌前病变的诊断技术，基于核和细胞凋亡的识别，是相对较差的最终临床结果的预测。由于形态学或细胞学变化可能发生在转化过程的后期，组织学上表现为良性的病变可能具有恶性潜能。相反，即使是严重的口腔发育异常病变也可以自发消退。因此，组织学检查结果不能明确预测恶变。需要一种用于在早期阶段检测分子上的癌前病变并用于预测恶性进展的可能性的方法。 该提案的目标是确定一组生物标志物，将允许识别的分子癌前病变。因此，将对来自含有来自非吸烟者和侵袭性HNSCC的正常粘膜组织的活检组织的微切割角质形成细胞进行基因表达谱分析，以鉴定潜在的口腔粘膜进展标志物（OPM）。阵列数据的解释和分析将在新建立的生物信息学核心中进行。这一可在网上查阅的注释和编目设施将使用无监督和监督学习方法。然后将使用具有不同组织学诊断的定制人体组织阵列样本验证这些潜在OPM的效用，所述组织学诊断包括：正常、反应性、角化过度、增生和各种等级的发育异常。这些分析可以识别与异型增生的生物学严重程度和恶性进展潜力相关的标志物。与病理学家目前使用的细胞模式识别相比，这种分子分析也可以大大提高诊断预测。