Glycoprotein Signatures as Biomarkers for Breast Cancer

糖蛋白特征作为乳腺癌的生物标志物

基本信息

批准号：
8232172
负责人：
Bruce A. Macher
金额：
$ 46.18万
依托单位：
SAN FRANCISCO STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-03-01 至 2016-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8232172
关键词：
Address Antibodies Biological Biological Markers Biological Process Blood Breast Breast Cancer Cell Breast Cancer Treatment Cancer cell line Cell Line Cell surface Cells Classification Cluster Analysis Coupled Data Data Set Databases Detection Diagnosis Diagnostic Disease Disease-Free Survival ERBB2 gene Early Diagnosis Epithelial Cells Epithelium Estrogen receptor negative Flow Cytometry Gene Expression Glycoproteins Goals Growth Hand Human Immunofluorescence Immunologic Knowledge Life Malignant - descriptor Mammary Neoplasms Mass Spectrum Analysis Mediating Messenger RNA Methods Mission Molecular Molecular Profiling Monitor Monitoring for Recurrence Neoplasm Metastasis Non-Malignant Outcome Patients Plasma Progesterone Receptors Protocols documentation Recurrence Research Research Project Grants Sampling Screening procedure Sensitivity and Specificity Source Students Subgroup Survival Rate Testing Training Translating Variant Work base cancer cell circulating cancer cell design improved malignant breast neoplasm migration new therapeutic target outcome forecast programs protein expression response therapeutic target tool tumor

项目摘要

DESCRIPTION (provided by applicant): Breast cancer is a heterogeneous disease. To improve our understanding of this disease and better treat its various forms, more information about the molecular variations that occur among its subtypes is needed. Better biomarkers are needed for its detection and for monitoring response to treatment. Additionally, improved methods for determining the chances of disease-free survival vs. disease recurrence are also needed. Although significant progress has been made in defining gene expression in breast cancer, our knowledge of protein expression profiles of various forms of this disease is limited. The long-term goals of the research are (1) to identify glycoprotein biomarker signatures that will be clinically useful for more effective detection and treatment of breast cancer; and (2) to develop a glycoproteomic breast cancer database that can be used to identify new therapeutic targets and improve our understanding of tumor-initiating cells and mechanisms that give rise to breast tumors. The objective of the current application is to identify glycoprotein signatures that can distinguish between luminal and basal breast cancer cell lines, and glycoprotein signatures that can distinguish between normal breast epithelial cells and malignant cell lines. The central hypothesis is that cell lines derived from malignant breast tumors and from normal breast epithelial cells have distinct glycoprotein profiles that can be used to classify them into various breast cancer subtypes and normal breast epithelial cells, respectively. We also hypothesize that a subset of these glycoproteins will serve as signatures that will distinguish among the three malignant breast cancer subtypes, and normal breast epithelial cells. Guided by strong preliminary data, these hypotheses will be tested through the following Specific Aims: 1a) Identify glycoprotein signatures for normal breast epithelial cells, and for luminal and basal breast cancer cell lines; 1b) Define the claudin-low type breast cancer cell glycoproteome; 2) Use immunofluorescence to validate glycoprotein signatures that classify breast cancer cell lines into basal and luminal subtypes. Aim 1 will be accomplished using a mass spectrometry-based protocol, coupled with hierarchical cluster analysis, previously demonstrated in the applicant's hands to result in a glycoprotein signature that distinguishes basal from luminal breast cancer cell lines. Aim 2 uses flow cytometry and antibodies to glycoprotein to validate the mass spectrometry-derived signature. Identifying differences in cell surface and secreted glycoprotein profiles from normal breast epithelia and those from various subtypes of breast cancer will advance diagnosis and treatment of this heterogeneous disease. Successful completion of the proposed studies will result in the identification of a set of antibodies that can be used to classify breast cancer cells into basal or luminal subtypes, and to discriminate malignant from non-malignant cells. The glycoprotein database produced through this work will provide information on potentially important biological differences between normal breast epithelia and breast cancer subtypes, as well as help identify potential therapeutic targets. PUBLIC HEALTH RELEVANCE: The proposed research addresses the need for improved diagnostic tools and treatments for breast cancer by providing new knowledge that can be translated into potentially new biomarkers and therapeutic targets. Thus, the proposed research is relevant to the part of NIH's mission that pertains to developing fundamental knowledge that will help to reduce the burdens of human illness and lengthen life.

描述（由申请人提供）：乳腺癌是一种异质疾病。为了提高我们对这种疾病的理解并更好地治疗其各种形式，需要更多有关其亚型之间发生的分子变异的信息。需要更好的生物标志物进行检测和监测对治疗的反应。此外，还需要改进的方法来确定无疾病生存的机会与疾病复发的机会。尽管在定义乳腺癌中的基因表达方面取得了重大进展，但我们对这种疾病各种形式的蛋白质表达谱的了解受到限制。研究的长期目标是（1）鉴定糖蛋白生物标志物特征，这些特征将在临床上可用于更有效的乳腺癌检测和治疗；（2）开发一种糖蛋白酶乳腺癌数据库，该数据库可用于鉴定新的治疗靶标，并提高我们对引起乳腺肿瘤的肿瘤发射细胞和机制的理解。当前应用的目的是鉴定可以区分腔内和基底乳腺癌细胞系的糖蛋白特征，以及可以区分正常乳腺上皮细胞和恶性细胞系的糖蛋白特征。中心假设是，源自恶性乳腺肿瘤和正常乳腺上皮细胞的细胞系具有不同的糖蛋白谱，可用于将其分为各种乳腺癌亚型和正常的乳腺上皮细胞。我们还假设，这些糖蛋白的一部分将用作特征，将区分三种恶性乳腺癌亚型和正常乳腺上皮细胞之间。在强大的初步数据的指导下，这些假设将通过以下特定目的进行检验：1A）确定正常乳腺上皮细胞的糖蛋白特征，以及用于腔内和基底乳腺癌细胞系的糖蛋白特征。 1b）定义claudin-low型乳腺癌细胞糖蛋白酶； 2）使用免疫荧光验证将乳腺癌细胞系分为基础和腔内亚型的糖蛋白特征。 AIM 1将使用基于质谱的方案，再加上分层群集分析来实现AIM 1，以前在申请人的手中证明了糖蛋白特征，从而导致糖蛋白特征区分开，该特征将基础与腔内乳腺癌细胞系区分开。 AIM 2使用流式细胞术和抗体来糖蛋白来验证质谱法衍生的特征。从正常乳腺癌和各种亚型的乳腺癌亚型的细胞表面和分泌的糖蛋白谱图中识别差异将提高这种异质性疾病的诊断和治疗。成功完成拟议的研究将导致鉴定一组可用于将乳腺癌细胞分类为基础或腔内亚型的抗体，并将恶性与非恶性细胞区分开。通过这项工作产生的糖蛋白数据库将提供有关正常乳腺癌和乳腺癌亚型之间潜在重要的生物学差异的信息，并有助于鉴定潜在的治疗靶标。公共卫生相关性：拟议的研究通过提供可以转化为潜在的新生物标志物和治疗靶标的新知识来解决改善乳腺癌诊断工具和治疗方法的需求。因此，拟议的研究与NIH使命的一部分有关，该任务与发展基本知识有关，这将有助于减轻人类疾病的负担并延长生命。