Detection of Emergent Mechanical Properties of Biologically Complex Cellular States

生物复杂细胞状态的紧急机械特性的检测

• 批准号: 10587097
• 负责人: Mark A LaBarge
• 金额: $ 65.37万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10587097
• 关键词: Acceleration; Age; Aging; BRCA1 gene; BRCA2 gene; Biological Clocks; Biology; Biomechanics; Breast; Breast Cancer Risk Factor; Breast Epithelial Cells; Cancer Detection; Cell Nucleus; Cell Surface Proteins; Cell membrane; Cells; Cellular biology; Characteristics; Chronology; Cities; Classification; Clinical; Complex; Cytoskeleton; Data; Detection; Devices; Diameter; Disease; Early Diagnosis; Educational process of instructing; Epigenetic Process; Epithelial Cells; Exhibits; Family; Family Cancer History; Family history of; Funding; Generations; Genetic; Genetic Screening; Germ-Line Mutation; High Risk Woman; High-Risk Cancer; Human; Immune; Intermediate Filaments; Knowledge; Machine Learning; Malignant Neoplasms; Measures; Mechanics; Microfluidics; Modeling; Molecular; Nature; PALB2 gene; Pathway interactions; Patients; Persons; Phenotype; Portraits; Predisposition; Property; Proteins; Publications; Publishing; Risk; Risk Estimate; Risk Factors; Surface; System; Time; Tissues; Validation; Variant; Woman; Work; cancer initiation; design; detection platform; experimental study; gene network; genetic testing; genetic variant; high risk; in silico; innovation; machine learning classification; malignant breast neoplasm; mammary epithelium; mechanical properties; molecular mechanics; molecular phenotype; new therapeutic target; non-genetic; older women; physical property; portability; response; screening; tool; trait; virulence gene; young woman

Project Summary Although aging, germline mutations, and family history of cancer are significant risks for breast cancer, it is still unclear why one person’s breast cells are more susceptible to this disease than another person’s. Aging changes cells and tissues such that they become more susceptible to cancer initiation. Our published data show that breast epithelial cells from young women who have high-risk germline mutations show accelerated aging with intermediate filament distribution, biological clock acceleration, and stromal immune cell milieu changes comparable to those of women who are 20–40 years older. In our currently funded R01EB024989, we discovered that the mechanical properties of normal breast epithelial cells, as measured by our mechano-Node Pore Sensing (mechano-NPS) platform, differ among younger and older women and that normal epithelial cells from genetically high-risk women who carry germline BRCA1, BRCA2, or PALB2 variants are mechanically “older” than their chronological age. We hypothesized that mechano-NPS can detect disease states based on the emergent mechanical properties that arise from the underlying molecular networks that define lineage and disease states. In this competitive renewal application, we extend this hypothesis to include detection of cancer susceptibility or risk, which is so far not detectable with genetic screening. We will innovate mechano-NPS and advance an in silico model of our device to increase the number of physical parameters it can measure, thereby providing a more complete portrait of single human mammary epithelial cells (HMECS) (Aim 1). We will build a machine learning cancer susceptibility detection system based on measuring mechanical properties of different primary HMEC (young, old, high-risk, family history of breast cancer, etc.) (Aim 2). Finally, we will dissect the molecular mechanisms of mechanical states measured by our advanced mechano-NPS platform (Aim 3). In the last funding period, we successfully designed, built, and validated the first-generation mechano-NPS platform at UC Berkeley and showed it to be portable and robust by building a second platform at City of Hope. The impact of our competitive renewal application will be far more reaching. Clinically useful genetic testing relies on a handful of known monogenic risk traits, but we hypothesize that emergent mechanical properties, measured from just a few hundred cells, are a characteristic of the biology that underlies cancer susceptible states, even those that are polygenic or epigenetic in nature and are passed within a family but that so far have defied definition.

项目摘要 尽管衰老、生殖细胞突变和癌症家族史是乳腺癌的重要风险，但它仍然是乳腺癌的重要因素。 目前还不清楚为什么一个人的乳腺细胞比另一个人的更容易患上这种疾病。增龄变化 细胞和组织，使得它们变得更容易发生癌症。我们公布的数据显示， 来自具有高风险生殖系突变的年轻女性的乳腺上皮细胞显示出加速老化， 中间丝分布、生物钟加速和基质免疫细胞环境变化 与年龄在20-40岁之间的妇女相比。在我们目前资助的R 01 EB 024989中，我们发现 正常乳腺上皮细胞的机械性能，如我们的机械节点孔测量， 感觉（机械性）平台，在年轻和老年妇女之间存在差异， 携带生殖系BRCA 1、BRCA 2或PALB 2变异的遗传高危女性在机械上是“老年人”， 比他们的实际年龄更大我们假设，mechano-bronchiatric可以检测疾病状态的基础上， 从定义谱系的底层分子网络中产生的新兴力学性质， 疾病状态。在这个竞争性的更新应用程序中，我们将这一假设扩展到包括癌症的检测 易感性或风险，这是迄今为止无法检测到的遗传筛查。我们将创新机械制造， 推进我们的设备的计算机模型，以增加它可以测量的物理参数的数量，从而 提供单个人乳腺上皮细胞（HMECS）的更完整的画像（目的1）。新的起点上建设更加富裕 机器学习癌症易感性检测系统的基础上测量不同的机械性能 原发性HMEC（年轻、老年、高危、乳腺癌家族史等）(Aim 2）。最后，我们将剖析 通过我们先进的机械状态测量平台（目标3）的分子机制。在 在上一个资助期内，我们成功地设计、建造并验证了第一代机械化平台， 加州大学伯克利分校，并通过在City of Hope建立第二个平台来展示它的便携性和强大性。的影响 我们的竞争性续约申请将更加深远。临床上有用的基因检测依赖于 少数已知的单基因风险特征，但我们假设，新兴的机械性能，测量 从几百个细胞中，是癌症易感状态的生物学特征， 那些是多基因或表观遗传的性质，并通过在一个家庭，但到目前为止，已违抗 定义.