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The Odd-Even Effect of Polymorphic CA repeats in the 5' Regulatory Region of the

The Odd-Even Effect of Polymorphic CA repeats in the 5' Regulatory Region of the
多态性 CA 重复序列在 5 调控区的奇偶效应
批准号:
7500858
负责人:
IVAN P GORLOV
金额:
$7.7万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-09-24 至 2010-08-31

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Mutations in highly penetrant genes (such as BRCA1/2) are responsible for less than half of all strongly familial breast cancers and account for only about 5% of all breast cancers; no clear role for these genes in sporadic breast cancers has emerged. Therefore, identifying novel polymorphic germline mutations that affect the risk of breast cancer is important. Epidermal growth factor receptor (EGFR) plays an important role in several processes directly involved in the incidence and progression of breast cancer. The level of expression of EGFR is one of the major predictors of prognosis for breast cancer patients. The results of several studies have suggested that germline mutations in the EGFR gene can also modulate breast cancer risk. One of the most interesting polymorphisms in the EGFR gene is the polymorphic CA repeat (rs11568315) located in the gene's regulatory region. Both our preliminary data and previously published data indicate a massive deficit of odd-numbered CA repeats in four ethnic groups studied: whites, Asians , Hispanics (Mexican Americans), and African Americans. We hypothesized that odd-numbered alleles (e.g., 15, 17, 19) are detrimental and confer increased risk of breast cancer. We named this hypothesis the "odd-even" hypothesis. This project is designed to test the odd-even hypothesis. We will genotype the polymorphic CA repeat plus 15 additional potentially functional single-nucleotide polymorphisms in the EGFR gene in DNA samples already collected from 1,500 patients with breast cancer and 1,500 matched control subjects. The risk associated with the genetic polymorphisms will be estimated in the context of known epidemiologic risk factors such as age, family history of breast cancer, age at menarche, age at menopause, and age at first childbirth. Information on these risk factors is also already collected and available for the analysis. We will also analyze EGFR expression in 50 breast cancer cell lines and correlate it with the odd-even status of the CA repeat. The results of this study will elucidate the role of genetic polymorphisms in the EGFR gene in modulating the risk of breast cancer. EGFR expression in breast tumors is an important predictor of prognosis for breast cancer patients. A polymorphic CA repeat (rs11568315) located in the regulatory region of the gene is one of the most promising polymorphisms modulating the risk of breast cancer. We noticed that there is a massive deficit of odd-numbered alleles in all four ethnic groups studied: Caucasians, Asians, Hispanics (Mexican Americans), and African Americans. We hypothesized that odd-numbered alleles occur less frequently than expected because they are detrimental and confer an increased risk of cancer, including breast cancer. The goal of this research project is to test this hypothesis by determining whether odd-numbered repeats in the EGFR gene are associated with an increased risk of breast cancer. To achieve this goal, we will compare the frequencies of odd-numbered alleles in cases and controls and frequencies of 15 additional potentially functional single-nucleotide polymorphisms from the EGFR gene. We will also analyze EGFR expression in 50 breast cancer cell lines and correlate it with the odd-even status of the CA repeat. The results obtained in this study will improve our understanding of how genetic polymorphisms in this key gene modulate breast cancer risk.
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会议论文
Modified logistic regression models using gene coexpression and clinical features to predict prostate cancer progression.
使用基因共表达和临床特征来预测前列腺癌进展的修改逻辑回归模型。
DOI: 10.1155/2013/917502
发表时间: 2013
期刊: Computational and mathematical methods in medicine
影响因子: --
作者: [Zhao,Hongya, Logothetis,ChristopherJ, Gorlov,IvanP, Zeng,Jia, Dai,Jianguo]
通讯作者: Dai,Jianguo
Analytics Core
  • 批准号:
    10434071
  • 项目类别:
  • 资助金额:
    $29.4万
  • 财政年份:
    2019
  • 负责人:
    IVAN P GORLOV
  • 依托单位:
Analytics Core
  • 批准号:
    10212413
  • 项目类别:
  • 资助金额:
    $33.73万
  • 财政年份:
    2019
  • 负责人:
    IVAN P GORLOV
  • 依托单位:
CORE 3: Bioinformatics
CORE 3: Bioinformatics
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