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Investigation of an LMO4- and BRCA1 -containing complex involved in breast cancer

Investigation of an LMO4- and BRCA1 -containing complex involved in breast cancer
涉及乳腺癌的含 LMO4 和 BRCA1 复合物的研究
批准号:
nhmrc : 253662
负责人:
Prof Jacqueline Matthews
金额:
$29.36万
依托单位:
依托单位国家:
澳大利亚
项目类别:
NHMRC Project Grants
财政年份:
2003
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2003-01-01 至 2005-12-31

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中文摘要
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英文摘要
Breast cancer will affect one in twelve Australian women and a quarter of those will die from breast cancer. At present we still know little about what causes the disease, and there is currently a lot of activity in the field of breast cancer research that will ultimately increase our ability to both detect its development at early stages and to provide effective treatments for the disease. We do know that losing the function of a few genes (breast cancer susceptibility genes) leads to a very high likelihood of developing cancer, and we know that the normal roles of the proteins that are produced from these genes are to prevent cancers from occurring in a spontaneous fashion. However, the inheritance of mutations in breast cancer susceptibility genes accounts for only a few percent of breast cancer cases. A recently discovered protein, known as LMO4, has been found at abnormal levels in over 50% of non-inherited breast tumors. This protein has been found to both interact with the protein from the most commonly occurring breast cancer susceptibility gene, known as BRCA1, and to prevent the normal activity of BRCA1. Thus, if we could develop reagents that prevent LMO4 from interacting with BRCA1, we could use those reagents as lead compounds for the development of anti-breast cancer drugs. Before we can develop such reagents we need to fully understand both what these proteins look like and how they interact. We already know that two other proteins, known as ldb1 and CtIP are involved in the LMO4:BRCA1 interaction. We will investigate the ways in which all of these proteins interact, from determining how strong each interaction is, to getting atomic level information about which surfaces of the proteins make the most contribution to each interaction. This should let us identify good targets for the design and development of anti-breast cancer drugs.
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