Expression Based Markers for Breast Cancer Detection

用于乳腺癌检测的基于表达的标记

• 批准号: 6952363
• 负责人: Jeffrey R. Marks
• 金额: $ 55.12万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-30 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6952363
• 关键词: antibody formation; biomarker; breast neoplasm /cancer diagnosis; cancer information system; circulating neoplastic cell; clinical research; cooperative study; diagnosis design /evaluation; early diagnosis; female; gene expression; human subject; mammary epithelium; mass spectrometry; mathematical model; molecular biology information system; molecular genetics; molecular oncology; neoplastic process; nucleic acid sequence; patient oriented research; tissue resource /registry; women' s health

DESCRIPTION (provided by applicant): In this renewal application for a Biomarker Development Laboratory, the investigators propose to use a carefully collected, curated and annotated bank of specimens to critically evaluate and compare a series of assays and lead markers to determine whether a clinically useful tool can be developed to augment mammography and ultrasound for the detection of breast cancer. The investigators believe early detection of breast cancer can only be improved by considering the problems inherent in the current best practice and supplying novel algorithms for solving these problems. Given the heterogeneity of the disease, its uncertain biologic progression, its high prevalence, and the variety of ways in which it is currently detected, our group considers it unlikely that any single approach will prove to be reliably effective in either improving upon or replacing current screening and diagnostic practices. Therefore, this proposal seeks to critically compare a series of molecular approaches that when applied in some combination will yield significant enhancement in the early detection of clinically relevant breast disease. The study will build upon and incorporate data from a separately funded NIH study that seeks to improve radiologic screening for breast cancer. Molecular markers will be incorporated with clinical and demographic data to build a comprehensive model for breast cancer prediction. This proposal combines the expertise and resources of Duke, Abbott Laboratories, Eastern Virginia Medical School, and University of Pittsburgh Medical Center.

描述（由申请人提供）：在生物标志物开发实验室的更新申请中，研究人员建议使用精心收集、整理和注释的样本库来批判性地评估和比较一系列测定和先导标志物，以确定是否可以开发出临床上有用的工具来增强乳房 X 光检查和超声检查以检测乳腺癌。研究人员认为，只有考虑当前最佳实践中固有的问题并提供解决这些问题的新算法，才能改善乳腺癌的早期检测。考虑到该疾病的异质性、其不确定的生物学进展、其高患病率以及目前检测方法的多样性，我们的小组认为任何单一方法不太可能被证明能够可靠有效地改进或取代当前的筛查和诊断实践。因此，该提案旨在批判性地比较一系列分子方法，当这些方法以某种组合应用时，将显着增强临床相关乳腺疾病的早期检测。该研究将基于并整合来自美国国立卫生研究院单独资助的一项研究的数据，该研究旨在改善乳腺癌的放射学筛查。分子标记将与临床和人口统计数据相结合，建立乳腺癌预测的综合模型。该提案结合了杜克大学、雅培实验室、东弗吉尼亚医学院和匹兹堡大学医学中心的专业知识和资源。