Protein domains as molecular units to unravel functional pathways of cancer genes

蛋白质结构域作为分子单元来揭示癌症基因的功能途径

• 批准号: 7774972
• 负责人: MARICEL G. KANN
• 金额: $ 15.88万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE COUNTY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-29 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7774972
• 关键词: Accounting; Active Sites; Advanced Malignant Neoplasm; Antineoplastic Agents; Arts; Binding; Bioinformatics; Biological; Cancer Biology; Cancer Cluster; Cancerous; Cells; Characteristics; Classification; Computer Analysis; DNA Sequence; Data; Databases; Development; Disease; Disease Progression; Drug Delivery Systems; Eating; Evolution; Functional RNA; Genes; Genetic Variation; Goals; Human Genome; Individual; Inherited; Lead; Localized Malignant Neoplasm; Malignant Neoplasms; Methodology; Methods; Modeling; Molecular; Mutation; Oncogenes; Pathway interactions; Peptides; Pharmaceutical Preparations; Pharmacogenomics; Phenotype; Predisposition; Process; Protein Analysis; Protein Region; Proteins; Research; Resources; Role; Site; Structure; Technology; Tertiary Protein Structure; Work; base; cancer classification; fighting; functional genomics; functional/structural genomics; gene therapy; genome wide association study; high throughput technology; innovation; interest; new technology; novel strategies; novel therapeutic intervention; protein structure function; public health relevance; research and development; tumor molecular fingerprint

DESCRIPTION (provided by applicant): A major goal in cancer biology is to understand the protein interactions involved in the molecular pathways that lead to initiation and progression of the disease. Advances in sequencing technologies are generating an overwhelming amount of data towards that goal, however these data lack specific functional context for the molecules involved in cancer. This missing functional content could be provided by a bioinformatics approach that is based on domain analysis. Protein domains are evolutionary conserved regions of the proteins and are considered to be the functional and structural units of the protein. Functional and structural genomic studies have provided extensive information about protein domains and their functional roles. How- ever, current methods to analyze the molecular bases of cancer do not systematically integrate protein domain studies into their methodologies, and that are mostly based on the study of individual genes or proteins. Functional studies at the gene level are unreliable due to gene multi-functionality. Instead, studies at the domain level account for modularity of proteins and discriminate between protein regions with different functionality, which is more accurate and informative. Here, we propose the first genome-wide study of the molecular disruptions associated with cancer that relies on protein domains, rather than on proteins, as the molecular units of the study. Our hypothesis is that the disruptions within a domain that is shared by similar proteins will have related functional effects in cancer. Thus, relevant functional information can be transferred among proteins with similar functional characteristics. First, we will develop domain-based methodologies for the functional classification and of molecular disruptions related to cancer, as well as for the prediction of relevance to disease. Second, we will develop a novel approach to support pharmacogenomic studies of cancer drugs. Finally, we will integrate these domain-based analyses into a molecular database annotated with cancer phenotype information, which we will make publicly available. We expect this research to lead to new hypotheses for the biological mechanisms involved in the disease and to provide new molecular bases for the classification of cancer. This proposal will provide the foundational research for the development of new therapeutic approaches, new drug targets, and efficient gene therapies to fight cancer. PUBLIC HEALTH RELEVANCE: A major goal in cancer biology is to understand how the interaction between different proteins produced by the body can cause the disease. New technology is offering a very detailed look into the DNA sequences involved with cancer, but these advances also provide an overwhelming amount of data that does not necessarily give a clear picture as to how specific molecules function in the progression of the disease. One way to clarify this picture is to analyze protein domains. A protein domain is a certain region of a protein that has remained structurally identical over the course of evolution. These domains are considered to be what actually determines a protein's structure and function. Currently, research on the molecular bases of cancer focuses on individual genes or proteins. However, study on the gene level is unreliable, because each gene has many different functions, which confuses the data. Additionally, by analyzing domains, we can focus on the particular regions of the protein with functions we are interested in, providing more accurate and informative results. Here, we propose the first human genome-wide study of the molecular bases of cancer that relies on protein domains as the core of the study. Our hypothesis is that, by observing how the structure of protein domains changes in cancerous cells, we can predict the effect of cancer on other proteins with similar protein domains. First, we will develop domain-based methods for classifying the molecular indicators of cancer and examine how these relate to the disease. Second, we will develop a novel approach to support studies of cancer drugs. Finally, we will use our domain-based analyses as a basis for a molecular database containing information on the physical characteristics of cancer, which we will make publicly available. We expect this research to lead to new hypotheses for the biological effects of the disease and proved new molecular bases for classifying cancer. This proposal will provide the foundational research for the development of new therapeutic approaches, drug targets, and efficient gene therapies to fight cancer.

描述（由申请人提供）：癌症生物学的一个主要目标是了解导致疾病发生和进展的分子途径中涉及的蛋白质相互作用。测序技术的进步正在为实现这一目标产生大量数据，但是这些数据缺乏与癌症相关的分子的特定功能背景。这种缺失的功能内容可以通过基于领域分析的生物信息学方法来提供。蛋白质结构域是蛋白质的进化保守区域，被认为是蛋白质的功能和结构单元。功能和结构基因组研究提供了有关蛋白质结构域及其功能作用的广泛信息。然而，目前分析癌症分子基础的方法并没有系统地将蛋白质结构域研究整合到其方法中，而且大多基于对单个基因或蛋白质的研究。由于基因的多功能性，基因水平的功能研究是不可靠的。相反，域水平的研究考虑了蛋白质的模块化并区分具有不同功能的蛋白质区域，这更加准确和信息丰富。在这里，我们提出了第一个与癌症相关的分子破坏的全基因组研究，该研究依赖于蛋白质结构域，而不是蛋白质，作为研究的分子单位。我们的假设是，相似蛋白质共享的结构域内的破坏将对癌症产生相关的功能影响。因此，相关的功能信息可以在具有相似功能特征的蛋白质之间转移。首先，我们将开发基于领域的方法，用于功能分类和与癌症相关的分子破坏，以及预测与疾病的相关性。其次，我们将开发一种新方法来支持癌症药物的药物基因组学研究。最后，我们将把这些基于领域的分析整合到一个带有癌症表型信息注释的分子数据库中，我们将公开该数据库。我们期望这项研究能够对疾病的生物学机制提出新的假设，并为癌症的分类提供新的分子基础。该提案将为开发新的治疗方法、新的药物靶点和有效的基因疗法来对抗癌症提供基础研究。 公共健康相关性：癌症生物学的一个主要目标是了解人体产生的不同蛋白质之间的相互作用如何导致疾病。新技术正在对与癌症有关的 DNA 序列进行非常详细的研究，但这些进步也提供了大量的数据，但这些数据不一定能清楚地说明特定分子在疾病进展中如何发挥作用。澄清这一情况的一种方法是分析蛋白质结构域。蛋白质结构域是蛋白质的某个区域，在进化过程中结构保持不变。这些结构域被认为真正决定了蛋白质的结构和功能。目前，癌症分子基础的研究主要集中在单个基因或蛋白质上。然而，基因层面的研究并不可靠，因为每个基因都有许多不同的功能，导致数据混乱。此外，通过分析结构域，我们可以专注于具有我们感兴趣的功能的蛋白质的特定区域，从而提供更准确和信息丰富的结果。在这里，我们提出了第一个针对癌症分子基础的人类全基因组研究，该研究依赖于蛋白质结构域作为研究的核心。我们的假设是，通过观察癌细胞中蛋白质结构域的结构如何变化，我们可以预测癌症对具有相似蛋白质结构域的其他蛋白质的影响。首先，我们将开发基于领域的方法来对癌症的分子指标进行分类，并检查它们与疾病的关系。其次，我们将开发一种新方法来支持癌症药物的研究。最后，我们将使用基于领域的分析作为包含癌症物理特征信息的分子数据库的基础，我们将公开该数据库。我们预计这项研究将为该疾病的生物学效应带来新的假设，并证明癌症分类的新分子基础。该提案将为开发新的治疗方法、药物靶点和有效的基因疗法来对抗癌症提供基础研究。