Exploiting collagen organization to predict and prevent tumor metastasis

利用胶原组织来预测和预防肿瘤转移

• 批准号: 7852224
• 负责人: Edward Bernard Brown
• 金额: $ 231.18万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7852224
• 关键词: Biopsy; Blood Vessels; Cancer Patient; Clinical; Collagen; Collagen Fiber; Data; Detection; Disseminated Malignant Neoplasm; Drug Delivery Systems; Evaluation; Fiber; Generations; Goals; Invaded; Lead; Learning; Mammary Neoplasms; Measures; Modeling; Molecular; Mus; Nature; Neoplasm Metastasis; Optical Methods; Optics; Outcome; Pathway interactions; Patients; Process; Public Health; Quality of life; Relaxin; Signal Transduction; Therapeutic Intervention; Tissues; abstracting; cell motility; clinically relevant; lymph nodes; malignant breast neoplasm; neoplastic cell; prevent; public health relevance; second harmonic; therapeutic target; tumor

DESCRIPTION (Provided by the applicant) Abstract: The extent and nature of the ordering of collagen fibers within a tumor has significant influence on metastasis: in murine breast tumor models, tumor cells move towards blood vessels along fibers that are visible via second harmonic generation (SHG), and SHG is exquisitely sensitive to molecular ordering. Tumor cells that move along SHG fibers are significantly faster than those moving independently, and SHGassociated motility is correlated with metastatic ability. Furthermore, the tumor-host interface contains radially oriented SHG fibers associated with tumor cells invading the surrounding tissue. Lastly, we have shown that treatment of tumors with relaxin, known to alter metastatic ability, alters collagen ordering as detectable by SHG. Consequently, we believe that the process of establishing ordered fibers offers an exciting, and currently unexploited, therapeutic target. To take advantage of this, we must first learn the cellular players and molecular signals by which collagen ordering is induced. Therefore, in this application we propose to determine the key cells and signals which influence the ordering of collagen in breast tumors. The tumor draining lymph node is the first bridgehead for many metastasizing tumor cells and we have exciting preliminary data suggesting that changes in collagen ordering within the node are evident (via SHG) before clinical detection of metastatic cancer, therefore we will also determine the key cells and signals which influence the ordering of collagen in the draining lymph node. Additionally, we will determine if SHG measures of collagen ordering in breast tumors and draining nodes are clinically useful predictors of metastatic outcome in breast cancer patient biopsies. This project has a high impact because it has two independent pathways to clinical relevance, by developing promising antimetastatic drug targets, and by developing an optical method to predict metastatic ability. Public Health Relevance: This project can positively impact public health in several ways. One part of the project is a determination of the cells and signals responsible for ordering collagen in breast tumors, and the resultant effects on metastasis. This will lead to target molecules for therapeutic intervention with the goal of inhibiting breast tumor metastasis. A second part of the project is an evaluation of the ability of optical measures of collagen ordering to predict metastatic ability. This will lead to an improvement in quality of life for breast cancer patients as therapy is customized to patient need.

描述（由申请人提供） 摘要：肿瘤内胶原纤维排序的程度和性质对转移有显着影响：在小鼠乳腺肿瘤模型中，肿瘤细胞沿着通过二次谐波发生（SHG）可见的纤维向血管移动，而 SHG 对分子排序非常敏感。沿着SHG纤维移动的肿瘤细胞明显比独立移动的肿瘤细胞快，并且SHG相关的运动与转移能力相关。此外，肿瘤-宿主界面包含与侵入周围组织的肿瘤细胞相关的径向定向SHG纤维。最后，我们已经证明，用松弛素（已知可以改变转移能力）治疗肿瘤，可以改变 SHG 检测到的胶原蛋白排序。因此，我们相信建立有序纤维的过程提供了一个令人兴奋且目前尚未开发的治疗靶点。为了利用这一点，我们必须首先了解诱导胶原蛋白排序的细胞参与者和分子信号。因此，在本申请中，我们建议确定影响乳腺肿瘤中胶原蛋白排序的关键细胞和信号。肿瘤引流淋巴结是许多转移性肿瘤细胞的第一个桥头堡，我们有令人兴奋的初步数据表明，在临床检测转移性癌症之前，节点内胶原蛋白排序的变化是明显的（通过SHG），因此我们还将确定影响引流淋巴结中胶原蛋白排序的关键细胞和信号。此外，我们将确定乳腺肿瘤和引流节点中胶原蛋白排序的 SHG 测量是否是乳腺癌患者活检中转移结果的临床有用预测因子。该项目具有很高的影响力，因为它有两条独立的临床相关途径：开发有前景的抗转移药物靶点，以及开发预测转移能力的光学方法。 公共卫生相关性：该项目可以通过多种方式对公共卫生产生积极影响。该项目的一部分是确定乳腺肿瘤中负责排列胶原蛋白的细胞和信号，以及由此产生的对转移的影响。这将产生用于治疗干预的靶分子，其目标是抑制乳腺肿瘤转移。该项目的第二部分是评估胶原蛋白排序的光学测量预测转移能力的能力。这将改善乳腺癌患者的生活质量，因为治疗是根据患者的需求定制的。