Quantitative profiling of glycosaminoglycans from breast tumor tissue arrays

描述(申请人提供)：乳腺癌是癌症致死的第二大原因，也是女性中最常见的癌症；12%的美国女性将被诊断为乳腺癌。不幸的是，乳腺癌因其高度转移的性质而臭名昭著，其预后很差，缺乏有效的治疗方法。蛋白多糖在细胞-细胞、细胞-基质相互作用中发挥重要作用，并调节重要的信号通路。与正常组织相比，蛋白多糖及其细胞外加工酶在人类乳腺癌中被解除调控。尽管如此，仍然严重缺乏关于以下方面的信息 癌细胞通过改变其表面和细胞外基质中的糖胺多聚糖(GAG)的结构而变得失调的机制。虽然有大量存档的乳腺肿瘤组织微阵列(TMA)可用，但没有方法可以从这些阵列中确定GAG结构和丰度。这项应用旨在开发新的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表达的变化。癌症异质性的挑战最好通过分析分级和分期活检样本中可能的最小细胞数量来解决，例如那些在乳腺肿瘤TMA中可用的细胞。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。分析这种阵列以获得GAG表达的能力超出了目前可用的任何技术。这项拟议的技术开发将为癌症研究人员提供手段，以确定癌细胞为逃避正常调控和转移而改变细胞表面和细胞外基质GAG结构的机制。所要求的R21活动的目标是开发方法并证明对来自乳腺肿瘤组织阵列的GAG进行定量结构分析的可行性。这将是 随后要求开展第二阶段(R33)活动，以促进技术的高级开发。我们将(1)开发具有分析乳腺癌组织阵列中GAG所需的速度和灵敏度的技术；(2)利用分级的人类乳腺癌组织阵列进行一系列关于GAG表达的初步研究。这一活动将促进GAG糖组分在癌症研究中的更广泛应用，以更好地了解癌细胞表面和细胞外基质的重塑，这是失调生长和转移所必需的。这种技术符合国家癌症研究所的目标，即资助对了解GAG表达对癌症预后有积极影响的高潜力研究。拟议的糖组分技术开发将满足IMAT计划支持癌症研究变革性技术开发的目标。

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.