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A High Throughput, Human, In Vitro Model of Neuronal Stretch Injury

A High Throughput, Human, In Vitro Model of Neuronal Stretch Injury
神经元牵张损伤的高通量人体体外模型
批准号:
9316304
负责人:
John D Finan
金额:
$23.4万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-02-01 至 2019-01-31

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中文摘要
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英文摘要
More than 100 clinical trials have been conducted in traumatic brain injury (TBI). Nevertheless, this condition, which is the most common killer of young people in the United States, remains without a proven therapy. TBI is hard to treat because it is heterogeneous: every patient has a different combination of pathologies and a different combination of genetic strengths and weaknesses. There may not be a single drug that treats all TBI pathologies in all patients. However, it may be possible to develop a suite of treatments for important pathologies of TBI by studying each in isolation. In the same spirit, treatment may be more effective if it is tailored to common, influential genotypes. Targeting subsets of TBI pathology in subsets of patients may enable piece-wise solution of a problem that seems impossible to solve at a single stroke. However, it requires a new type of pre-clinical model. In this proposal, neuronal stretch injury (NSI) is isolated from other TBI pathologies and applied to human induced pluripotent stem cell-derived neurons (hiPSCNs) for the first time. hiPSCNs can be engineered to contain the genomes of specific patients, or to differ from controls by a single genetic variant (these are known as isogenic cell lines). Homogeneous human neurons can be generated in large numbers, making these cells ideal for high throughput drug discovery. The model applies a biofidelic stretch insult in a 96 well format for the first time. However, a screen cannot be conducted until a very high level of consistency has been achieved and the capacity to detect therapeutic benefit has been verified. High throughput screens make many comparisons with few replicates so they require an extremely rigorous assay. Standard deviations should be 6 times smaller than the difference between positive and negative controls (corresponds to z>0 where z is the standard validation parameter in the field). The long term goal is to discover new treatments for NSI and understand patient-specific, cell autonomous factors driving pathology. The overall objective of this application, which is a vital step towards this goal, is to develop our existing NSI model into a rigorous high throughput drug screening assay. Our central hypothesis is that z will be >0 in the optimized model. hiPSCNs will be cultured on silicone membranes and stretched with a custom-built device to induce NSI. NSI pathology will be measured by quantitative analysis of cell viability and morphology in fluorescent microscopic images. The model will be optimized in 3 steps: optimization of the mechanical insult, optimization of the injury phenotype and optimization of the therapeutic effect of positive control compounds. The rationale for this work is to build a platform for future experiments that discover novel NSI therapies, measure the influence of genetic variants and address other aspects of the in situ condition (e.g. oxygen glucose deprivation, astrocyte activation, inflammatory cytokines etc.). This work will enable the first high throughput screen for an NSI therapy. It will also enable the first isogenic experiment in neurotrauma. These tools hold the promise of incremental clinical success in place of the status quo of total clinical failure.
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  • 批准号:
    31760279
  • 项目类别:
    地区科学基金项目
  • 资助金额:
    35.0万元
  • 批准年份:
    2017
  • 负责人:
    丁银秀
  • 依托单位: