Quantitative profiling of glycosaminoglycans from breast tumor tissue arrays

乳腺肿瘤组织阵列中糖胺聚糖的定量分析

• 批准号: 8889224
• 负责人: JOSEPH ZAIA
• 金额: $ 24.92万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8889224
• 关键词: Address; Advanced Development; Age; American; Archives; Basic Cancer Research; Biological Markers; Biopsy; Biopsy Specimen; Breast Cancer Cell; Cancer Etiology; Cancer Prognosis; Cell Count; Cell surface; Cells; Chondroitin Sulfates; Data; Development; Diagnosis; Diagnostic Neoplasm Staging; Digestion; Enzymes; Extracellular Matrix; Funding; Glycosaminoglycans; Glycoside Hydrolases; Goals; Grant; Growth; Growth Factor; Health; Heparitin Sulfate; Heterogeneity; Human; Hyaluronan; In Situ; Knowledge; Lead; Malignant Neoplasms; Mammalian Cell; Mammary Gland Parenchyma; Mammary Neoplasms; Metastatic Carcinoma; Methods; Mission; Molecular; Molecular Structure; Nature; Neoplasm Metastasis; Normal Cell; Normal tissue morphology; Paraffin Embedding; Phase; Phenotype; Pilot Projects; Play; Polysaccharides; Process; Proteins; Proteoglycan; Relative (related person); Reproducibility; Research; Research Personnel; Role; Series; Signal Pathway; Slide; Specimen; Speed; Staging; Stimulus; Structure; Surface; Technology; Therapeutic; Tissue Microarray; Tissues; Tumor Tissue; Tumor stage; Woman; Work; analytical method; angiogenesis; anticancer research; base; cancer cell; cell growth; extracellular; improved; infiltrating duct carcinoma; liquid chromatography mass spectrometry; lymph nodes; malignant breast neoplasm; meetings; neoplastic cell; new technology; outcome forecast; programs; protein expression; receptor; technology development; therapeutic development; tumor; tumor progression

DESCRIPTION (provided by applicant): Breast cancer is the second leading cause of cancer lethality, and the most common cancer among women; 12% of American women will be diagnosed with breast cancer. Unfortunately, breast cancer is notorious for its poor prognosis and lack of effective therapeutics due to its highly metastatic nature. Proteoglycans play a critical role in cell-cell, cell-matrix interaction and regulate important signaling pathways. Inded, proteoglycans and their extracellular processing enzymes are deregulated in human breast cancers relative to normal tissues. Despite this, there is a serious lack of information concerning the mechanisms whereby cancer cells become dysregulated through altering the structures of glycosaminoglycans (GAGs) on their surfaces and in extracellular matrices. While there is a wealth of archived breast tumor tissue microarrays (TMAs) available, no methods are available for determining GAG structures and abundances from these arrays. This application aims to develop new technology to catalyze progress in cancer research for better understanding of the changes to expression of GAGs that occur as a function of breast cancer grade and stage. The challenge of cancer heterogeneity is best addressed through the analysis of the minimum number of cells possible from graded and staged biopsy samples such as those available in breast tumor TMAs. We will develop new technology with the sensitivity and speed necessary for query of the molecular structures of GAGs expressed in these tissue arrays. The ability to analyze such arrays for GAG expression is beyond any technology available at present. This proposed technology development will give cancer researchers the means to determine the mechanisms whereby cancer cells alter the structures of cell surface and extracellular matrix GAGs in order to escape normal regulatory controls and progress towards metastasis. The goal of the requested R21 activity is to develop methods and demonstrate the feasibility of quantitative structural analysis of GAGs from breast tumor tissue arrays. This will be the basis of a subsequent request for phase II (R33) activity for advanced development of the technology. We will (1) develop technology with the speed and sensitivity required for analysis of GAGs from breast cancer tissue arrays; (2) conduct a set of pilot studies on GAG expression using graded human breast cancer tissue arrays. This activity will facilitate broader use of GAG glycomics in cancer research towards a better understanding of the remodeling of cancer cell surfaces and extracellular matrices necessary for dysregulated growth and metastasis. Such technology meets the mission of the NCI's goals of funding research with high potential for positive impact on understanding of GAG expression on cancer prognosis. The proposed glycomics technology development will meet the IMAT program's goal of supporting the development of transformative technologies for cancer research.

描述（由申请人提供）：乳腺癌是癌症致死率的第二大原因，也是女性中最常见的癌症； 12%的美国女性将被诊断出患有乳腺癌。不幸的是，乳腺癌因其高度转移性而因其预后不良且缺乏有效的治疗方法而臭名昭著。蛋白多糖在细胞与细胞、细胞与基质的相互作用中发挥着关键作用，并调节重要的信号传导途径。事实上，相对于正常组织，在人类乳腺癌中蛋白聚糖及其细胞外加工酶的调节失调。尽管如此，有关方面的信息却严重缺乏。 癌细胞通过改变其表面和细胞外基质中的糖胺聚糖 (GAG) 结构而变得失调的机制。虽然有大量已存档的乳腺肿瘤组织微阵列 (TMA)，但没有方法可用于确定这些阵列中的 GAG 结构和丰度。该应用旨在开发新技术来促进癌症研究的进展，以便更好地了解随着乳腺癌分级和分期而发生的 GAG 表达变化。癌症异质性的挑战最好通过分析分级和分期活检样本（例如乳腺肿瘤 TMA 中可用的样本）中可能的最小数量的细胞来解决。我们将开发具有查询这些组织阵列中表达的 GAG 分子结构所需的灵敏度和速度的新技术。分析此类阵列的 GAG 表达的能力超出了目前任何可用的技术。这项拟议的技术开发将为癌症研究人员提供确定癌细胞改变细胞表面和细胞外基质 GAG 结构以逃避正常监管控制并进展到转移的机制的方法。所请求的 R21 活动的目标是开发方法并证明对乳腺肿瘤组织阵列中的 GAG 进行定量结构分析的可行性。这将是基础 随后请求进行第二阶段（R33）活动以推进该技术的开发。我们将 (1) 开发具有分析乳腺癌组织阵列中的 GAG 所需的速度和灵敏度的技术； (2) 使用分级的人乳腺癌组织芯片进行一系列关于 GAG 表达的初步研究。这项活动将促进 GAG 糖组学在癌症研究中的更广泛应用，从而更好地了解癌细胞表面和细胞外基质的重塑，这是生长和转移失调所必需的。这种技术符合 NCI 的目标，即资助对了解 GAG 表达对癌症预后产生积极影响的研究。拟议的糖组学技术开发将实现 IMAT 计划支持癌症研究变革技术开发的目标。