Computational Analysis of Microtubule Dynamics for Personalized Cancer Therapy

个性化癌症治疗的微管动力学计算分析

• 批准号: 8656952
• 负责人: Alexandre Matov
• 金额: $ 0.99万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-05-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8656952
• 关键词: Affect; Algorithms; Androgen Receptor; Basic Science; Behavior; Binding; Biological Markers; Biology; Cancer Etiology; Cancer Patient; Cell Nucleus; Cell physiology; Cessation of life; Computer Analysis; Computer Assisted; Computer Vision Systems; Computers; Coupled; Cytoskeleton; Data; Data Set; Dependency; Diagnosis; Disease; Drug Targeting; Dynein ATPase; Event; Eye; FDA approved; Feedback; Gene Targeting; Genes; Genetic Transcription; Goals; Growth; Homeostasis; Image; Image Analysis; In Vitro; Individual; Label; Link; Malignant neoplasm of prostate; Measurable; Measures; Medical; Metastatic Prostate Cancer; Microscope; Microtubule Polymerization; Microtubule Stabilization; Microtubules; Modeling; Motor; Nuclear; Optics; Outcome; PC3 cell line; Paclitaxel; Pathway interactions; Patients; Pattern; Pharmaceutical Preparations; Phase; Physicians; Polymers; Process; Property; Protein Isoforms; Proteins; RNA Splicing; Renal Cell Carcinoma; Research; Research Project Grants; Resistance; Scheme; Second Primary Neoplasms; Taxane Compound; Testing; Therapeutic; Time; Transcriptional Regulation; Translational Research; Treatment Efficacy; Tubulin; Variant; Work; anticancer research; base; behavior test; cancer cell; cancer therapy; cellular targeting; chemotherapy; clinical decision-making; clinically relevant; design; disease phenotype; docetaxel; in vivo; inhibitor/antagonist; insight; male; mathematical model; novel; programs; prostate cancer cell; public health relevance; receptor binding; response; taxane; tool; trafficking; transcription factor; transcriptome sequencing; tumor

DESCRIPTION (provided by applicant): Optimized optics and feedback-controlled microscope hardware permit efficient acquisition of large, high- quality image datasets. Computer-based analyses deliver fast processing of high volume of image data which manually cannot be accomplished. The most exciting contribution that computer vision systems can make to translational cancer research, however, is to give access to image-based information that is inaccessible by eye. Computer vision programs can be directly coupled to mathematical models that describe the relation between hidden, invisible processes and measurable image events. Changes in the behavior of hidden processes are thus detectable as changes in the image. This study envisages the use of such algorithms to obtain statistically representative results for the differential effects of each of the three FDA-approved taxanes on the microtubule cytoskeleton in prostate cancer (PC) cell lines. My previous work in basic research has demonstrated the ability of computer-based analysis of the microtubule (MT) cytoskeleton to distinguish between weak disease phenotypes and establish links to MT dynamics in renal cell carcinoma. Therefore, the proposed translational research project can impact clinical decision-making by equipping physicians for the first time with a computer-aided tool allowing the design of an effective personalized MT-targeting chemotherapy of metastatic PC patients. Metastatic PC is treated primarily by means of taxane-based chemotherapy with one of the three FDA- approved taxanes (paclitaxel, docetaxel and cabazitaxel). However, currently there is no way of selecting the taxane for chemotherapy based on the particular pattern of dynamic behavior of the MT cytoskeleton in individual patients. In addition, recent data have indicated that AR binds MTs in order to traffic to the nucleus and that there are several clinically relevant AR splice variants i metastatic PC patients. To date, there is no information available on the potential effects of wild type or variant AR on MT dynamics and consequently no information on differential metastatic PC cell response to taxane treatment as a function of cellular AR content. Based on preliminary research, we hypothesize that there are inherent differences in tumor MT dynamics among individual PC patients, and that the presence of AR variants affects specific parameters of MT polymerization dynamics. If correct, this hypothesis has very significant implications for PC treatment. Because different microtubule-targeting drugs (even from within the same class like the taxanes) affect distinct parameters of MT dynamics, it is conceivable that we can match each drug with an individual tumor-specific "MT-dynamics signature" for maximum therapeutic efficacy.

描述（由申请人提供）：优化的光学器件和反馈控制的显微镜硬件允许高效采集大型高质量图像数据集。基于计算机的分析提供了手动无法完成的大量图像数据的快速处理。然而，计算机视觉系统对转化癌症研究的最令人兴奋的贡献是提供了肉眼无法获取的基于图像的信息。计算机视觉程序可以直接耦合到描述隐藏的、不可见的过程和可测量的图像事件之间关系的数学模型。因此，隐藏进程的行为变化可以作为图像的变化来检测。本研究设想使用这样的算法，以获得统计学上的代表性结果的差异影响的三个FDA批准的紫杉烷类的微管细胞骨架在前列腺癌（PC）细胞系。我以前在基础研究方面的工作已经证明了基于计算机的微管（MT）细胞骨架分析的能力，以区分弱疾病表型，并建立与肾细胞癌中MT动力学的联系。因此，拟议的转化研究项目可以通过首次为医生配备计算机辅助工具来影响临床决策，从而设计有效的转移性PC患者的个性化MT靶向化疗。转移性PC主要通过使用三种FDA批准的紫杉烷（紫杉醇、多西他赛和卡巴他赛）之一的基于紫杉烷的化疗来治疗。然而，目前还没有办法根据个体患者MT细胞骨架的特定动态行为模式来选择用于化疗的紫杉烷。此外，最近的数据表明，AR结合MT以运输到细胞核，并且在转移性PC患者中存在几种临床相关的AR剪接变体。到目前为止，还没有关于野生动物的潜在影响的信息。 类型或变体AR对MT动力学的影响，因此没有关于细胞AR含量对紫杉烷治疗的差异转移性PC细胞应答的信息。基于初步的研究，我们假设有固有的差异，在个别PC患者之间的肿瘤MT动力学，AR变体的存在影响MT聚合动力学的特定参数。如果正确，这一假设对PC治疗具有非常重要的意义。由于不同的微管靶向药物（甚至来自同一类别，如紫杉烷类）影响MT动力学的不同参数，因此可以想象，我们可以将每种药物与个体肿瘤特异性“MT动力学特征”相匹配，以获得最大的治疗效果。