Advanced Methods to Evaluate Extracellular Matrix and Crosslinking in the Tumor M

描述(申请人提供)：细胞外基质(ECM)的组成和结构定义了肿瘤细胞的转移结果，特别是肿瘤细胞是否会从非侵袭性表型转变为侵袭性表型。然而，负责的细胞外生物分子在很大程度上是未知的。识别和了解特定的ECM蛋白和修饰在肿瘤进展中的作用需要对肿瘤微环境中的ECM进行更全面和准确的表征。ECM蛋白通常是共价交联的，使它们不能溶解和蛋白水解性切割。因此，传统蛋白质组学技术对组织样本的分析不能反映实际的蛋白质组成。缺乏合适的样品制备和定量方法来准确地表征ECM的分子特征，仍然是该领域取得进展的主要障碍。这项R33应用的重点是开发和验证识别和量化ECM蛋白质和交联肽的方法，这些蛋白质和交联肽在支持或抑制肿瘤发生事件的基质之间存在差异。我们已经取得了相当大的进展，在我们的“肿瘤相关细胞外基质的详细特征的样品制备方法”R21授权概述的目标。这项工作的亮点包括1)开发用于评估ECM驱动的表型的细胞培养模型，2)定义一个健壮的ECM提取方案，该方案将细胞污染降至最低，并允许对强共轭可溶和不可溶ECM组分进行蛋白质组学分析，以及3)应用无标记相对定量方法来估计蛋白质丰度的变化。最终，这项工作产生了一种蛋白质组学方法，与所有其他测试的方法相比，该方法可以更准确地表示组织蛋白质组成。这项R33延期拨款中建议的工作建立在这些进展的基础上，通过提供必要的方法来深入描述肿瘤进展期间的ECM，以提供以前无法获得的细胞微环境重塑事件的分子细节。为了便于绝对定量，我们开发了一个稳定同位素标记报告肽的文库，为ECM蛋白提供了一个敏感的代理。我们将为含有羟脯氨酸残基的纤维胶原蛋白生成额外的多肽，以便将这些重标记的文库添加到感兴趣的ECM样本中进行蛋白质定量。这种方法将允许更高的吞吐量分析，改进的灵敏度、准确性，以及蛋白质水平的样品内和样品间比较。我们将产生一种交联肽鉴定策略来表征赖氨酰氧化酶(LOX)介导的与肿瘤进展相关的交联链的类型和位置。该方法包括蛋白质水解肽的混合亲和标记，然后串联亲和纯化用于选择性交联肽的浓缩。该方法最初将使用对照蛋白质和组织进行开发，然后应用于我们癌症模型的组织和接受/-LOX抑制剂治疗的对照小鼠。最后，我们将通过结合或内部标准肽库应用稳定的同位素脉冲标记方法来检查ECM组成的变化和肿瘤前病变、早期和晚期肿瘤之间的交联性。由含有食物的稳定同位素赖氨酸提供的30天脉冲标记将允许测量结合到小鼠组织和肿瘤的ECM中的新蛋白质。蛋白质丰度和时间点之间的降解差异将使用包含我们的报告肽的子集的Arg来解释。这些实验应该使我们能够获得以前无法达到的分子分辨率，了解肿瘤进展过程中发生的ECM沉积、加工和降解之间的动态和相互作用关系。这些ECM特异性技术的绝对量化和验证方法的发展将提高我们探索和表征ECM在癌症进展中的作用的能力。这些方法将帮助研究人员了解一个知之甚少的基础生物学、癌症进展和纤维化疾病的一般领域。在这一历史上被忽视的领域的发现可能会为我们对这些疾病的理解提供范式转变，以及被认为是治疗靶点的蛋白质类型，以及作为诊断标记的来源。这些研究将提供重要的试剂(报告多肽文库质粒和sIL-PTM多肽)和必要的资源(方案和数据集)，以推动该领域朝着其最终目标--使发现改善患者生活--迈进。

DESCRIPTION (provided by applicant): The composition and architecture of the extracellular matrix (ECM) defines the metastatic outcome of tumor cells, specifically whether a tumor cell will transition from a non-invasive to an invasive phenotype. However, the extracellular biomolecules responsible are largely unknown. Identifying and understanding the role of specific ECM proteins and modifications involved in tumor progression requires a more comprehensive and precise characterization of ECM within tumor microenvironments. ECM proteins are often covalently cross-linked rendering them resistant to solubilization and proteolytic cleavage. As a result, analyses of tissue samples by traditional proteomic techniques fail to reflect actual protein composition. Lack of suitable sample preparation and quantification methods for accurate molecular characterization of ECM remains a major barrier to progress in the field. The focus of this R33 application is on development and validation of methods to identify and quantify ECM proteins and crosslinked peptides that differ between matrices that support or suppress tumorigenic events. We have made considerable progress towards the goals outlined in our "Sample Preparation Methods for the Detailed Characterization of Tumor Associated Extracellular Matrix" R21 grant. The highlights of this work involves 1) development of cell culture models for evaluating ECM driven phenotypes, 2) defining a robust ECM extraction protocol that minimizes cellular contamination and permits proteomic analysis of both the strong chaotrope soluble and insoluble ECM fractions, and 3) application of a label- free relative-quantification approach for estimation of protein abundance changes. Ultimately, this work has yielded a proteomic method that results in a more accurate representation of tissue protein composition compared to all others tested. The work proposed in this R33 extension grant builds on these advancements by providing the methods necessary for in-depth characterization of ECM during tumor progression to deliver previously unobtainable molecular detail of cellular microenvironment remodeling events. To facilitate absolute quantification we have developed a library of stable isotope labeled reporter peptides that provide a sensitive proxy for ECM proteins. We will generate additional peptides for fibrillar collagens that contain hydroxyproline residues so that these heavy-labeled libraries can be added to ECM samples of interest for protein quantification. This approach will allow for higher- throughput analysis, improved sensitivity, accuracy, and intra- and inter- sample comparison of protein levels. We will generate a crosslinked-peptide identification strategy to characterize the types and sites of lysyl oxidase (LOX) mediated crosslinks that correlate with tumor progression. The method involves mixed affinity labeling of proteolytic peptides followed by tandem affinity purification for selective crosslinked peptide enrichment. The method will initially be developed using control proteins and tissues, and then applied to tissues from our cancer model and control mice treated +/- LOX inhibitor. Finally, we will examine alterations in ECM composition and crosslinking between pre-neoplastic lesions, early stage, and late stage tumors by applying a stable isotope pulse labeling approach in conjunction with or internal standard peptide library. A 30 day pulse labeling provided by stable isotope Lys containing chow will allow for measurements of new protein incorporated into the ECM of mouse tissue and tumors. Protein abundance and degradation differences between time points will be accounted for using the Arg containing subset of our reporter peptides. These experiments should allow us to obtain molecular resolution, previously unattainable, of the dynamic and reciprocal relationship between ECM deposition, processing and degradation that occur during tumor progression. The development of the proposed methods for absolute quantification and validation of these ECM specific techniques will advance our ability to explore and characterize the role of the ECM in cancer progression. The methods will help investigators understand a poorly understood area of basic biology, cancer progression, and fibrotic diseases in general. Findings in this historically overlooked area are likely to provide paradigm shifts in our understanding of these diseases and the types of proteins considered for therapeutic targeting, and as sources of diagnostic markers. These studies will provide important reagents (reporter peptide library plasmids and SIL-PTM peptides) and resources (protocols and datasets) necessary to move this field toward its ultimate goal of enabling discoveries that improve patients' lives.