Quantitative profiling of glycosaminoglycans from breast tumor tissue arrays

描述（由申请人提供）：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患有乳腺癌。不幸的是，乳腺癌因其高转移性而预后差和缺乏有效的治疗方法而臭名昭著。蛋白聚糖在细胞-细胞、细胞-基质相互作用中起着关键作用，并调节重要的信号传导途径。与正常组织相比，乳腺癌中的蛋白聚糖及其胞外加工酶失调。尽管如此，仍然严重缺乏关于 癌细胞通过改变其表面和细胞外基质中糖胺聚糖（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，但没有方法可用于从这些阵列确定GAG结构和丰度。该申请旨在开发新技术，以促进癌症研究的进展，以便更好地了解作为乳腺癌级别和阶段的函数发生的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（如乳腺肿瘤TMA中可用的样本）中可能的最小细胞数来解决。我们将开发新的技术，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。分析此类阵列的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确定癌细胞改变细胞表面和细胞外基质GAG结构的机制的手段，以逃避正常的监管控制并向转移发展。所要求的R21活动的目标是开发方法并证明乳腺肿瘤组织阵列中GAG定量结构分析的可行性。这将是基础， 随后申请第二阶段（R33）活动，以进一步开发该技术。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）使用分级的人类乳腺癌组织阵列对GAG表达进行一系列试点研究。这一活动将促进GAG糖组学在癌症研究中的更广泛应用，以更好地理解生长和转移失调所必需的癌细胞表面和细胞外基质的重塑。这种技术符合NCI资助研究的目标的使命，对理解GAG表达对癌症预后的积极影响具有很高的潜力。拟议的糖组学技术开发将满足IMAT计划的目标，即支持癌症研究变革性技术的开发。

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.