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公开(公告)号：US10181009B2
公开(公告)日：2019-01-15
申请号：US11134688
申请日：2005-05-19
IPC分类号： G06F19/20 , C12Q1/6886 , G06F19/24
摘要： The invention provides a molecular marker set that can be used for prognosis of colorectal cancer in a colorectal cancer patient. The invention also provides methods and computer systems for evaluating prognosis of colorectal cancer in a colorectal cancer patient based on the molecular marker set. The invention also provides methods and computer systems for determining chemotherapy for a colorectal cancer patient and for enrolling patients in clinical trials.
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公开(公告)号：US08655598B2
公开(公告)日：2014-02-18
申请号：US13037156
申请日：2011-02-28
摘要： This invention is a model that simulates the complexity of biological signaling in a cell in response to radiation therapy. Using gene expression profiles and radiation survival assays in an algorithm, a systems model was generated of the radiosensitivity network. The network consists of ten highly interconnected genetic hubs with significant signal redundancy. The model was validated with in vitro tests perturbing network components, correctly predicting radiation sensitivity ⅔ times. The model's clinical relevance was shown by linking clinical radiosensitivity targets to the model network. Clinical applications were confirmed by testing model predictions against clinical response to preoperative radiochemotherapy in patients with rectal or esophageal cancer.
摘要翻译： 本发明是模拟响应于放射治疗的细胞中生物信号传导的复杂性的模型。 在算法中使用基因表达谱和放射线存活测定法，产生了放射敏感性网络的系统模型。 该网络由十个高度互联的遗传中心组成，具有显着的信号冗余。 该模型通过体外测试扰动网络组件进行验证，正确预测辐射灵敏度为2/3倍。 通过将临床放射敏感性目标与模型网络相关联，显示了模型的临床相关性。 临床应用通过对直肠或食管癌患者术前放射化学疗法临床反应的模型预测进行验证。
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公开(公告)号：US20090076734A1
公开(公告)日：2009-03-19
申请号：US12210135
申请日：2008-09-12
CPC分类号： G16B5/00 , C12Q1/6883 , G16B25/00 , G16B40/00 , G16H50/50
摘要： Described are mathematical models and method, e.g., computer-implemented methods, for predicting tumor sensitivity to radiation therapy, which can be used, e.g., for selecting a treatment for a subject who has a tumor.
摘要翻译： 描述了用于预测对放射治疗的肿瘤敏感性的数学模型和方法，例如计算机实现的方法，其可以用于例如用于选择具有肿瘤的受试者的治疗。
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公开(公告)号：US20060195269A1
公开(公告)日：2006-08-31
申请号：US11134688
申请日：2005-05-19
申请人： Timothy Yeatman , Steven Eschrich , Gregory Bloom
发明人： Timothy Yeatman , Steven Eschrich , Gregory Bloom
IPC分类号： G06F19/00
CPC分类号： G06F19/20 , C12Q1/6886 , C12Q2600/106 , C12Q2600/118 , G06F19/24
摘要： The invention provides a molecular marker set that can be used for prognosis of colorectal cancer in a colorectal cancer patient. The invention also provides methods and computer systems for evaluating prognosis of colorectal cancer in a colorectal cancer patient based on the molecular marker set. The invention also provides methods and computer systems for determining chemotherapy for a colorectal cancer patient and for enrolling patients in clinical trials.
摘要翻译： 本发明提供可用于结肠直肠癌患者结肠直肠癌预后的分子标记物。 本发明还提供了基于分子标记物组来评估结直肠癌患者的结肠直肠癌预后的方法和计算机系统。 本发明还提供了用于确定结肠直肠癌患者的化学疗法的方法和计算机系统，并且用于在临床试验中招募患者。
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公开(公告)号：US08660801B2
公开(公告)日：2014-02-25
申请号：US13037153
申请日：2011-02-28
摘要： Described are mathematical models and method, e.g., computer-implemented methods, for predicting tumor sensitivity to radiation therapy, which can be used, e.g., for selecting a treatment for a subject who has a tumor.
摘要翻译： 描述了用于预测对放射治疗的肿瘤敏感性的数学模型和方法，例如计算机实现的方法，其可以用于例如用于选择具有肿瘤的受试者的治疗。
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公开(公告)号：US20120053911A1
公开(公告)日：2012-03-01
申请号：US13037153
申请日：2011-02-28
摘要： Described are mathematical models and method, e.g., computer-implemented methods, for predicting tumor sensitivity to radiation therapy, which can be used, e.g., for selecting a treatment for a subject who has a tumor.
摘要翻译： 描述了用于预测对放射治疗的肿瘤敏感性的数学模型和方法，例如计算机实现的方法，其可以用于例如用于选择具有肿瘤的受试者的治疗。
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公开(公告)号：US20100240540A1
公开(公告)日：2010-09-23
申请号：US12728840
申请日：2010-03-22
IPC分类号： C40B30/00
CPC分类号： C12Q1/6886 , C12Q2600/118 , C12Q2600/158
摘要： Actively dividing tumors appear to progress to a life threatening condition more rapidly than slowly dividing tumors. Assessing actively dividing tumors currently involves a manual assessment of the number of mitotic cells in a histological slide prepared from the tumor and assessed by a trained pathologist. Disclosed is a method for using cumulative information from a series of expressed genes to determine tumor prognosis. This cumulative information can be used to categorize tumor samples into high mitotic states or low mitotic states using a mathematical algorithm and gene expression data derived from microarrays or quantitative-Polymerase Chain Reaction (Q-PCR) data. The specific mathematical description outlines how the algorithm assesses the most informative subset of genes from the full list of genes during the assessment of each sample.
摘要翻译： 与慢慢分裂的肿瘤相比，积极分裂的肿瘤似乎进展到危及生命的疾病。 目前，对积极分割肿瘤的评估包括手动评估从肿瘤制备的组织学载玻片中有丝分裂细胞的数量，并由训练有素的病理学家进行评估。 公开了一种使用来自一系列表达基因的累积信息来确定肿瘤预后的方法。 该累积信息可用于使用来自微阵列或定量聚合酶链反应（Q-PCR）数据的数学算法和基因表达数据将肿瘤样品分类为高有丝分裂状态或低有丝分裂状态。 具体的数学描述概述了在评估每个样本时，算法如何从基因的完整列表中评估基因的最有信息的子集。
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8.发明申请Identification of Novel Targets for Radio Sensitization Using a Genomic-Based Radiation Sensitivity Classifier 有权使用基于基因组的辐射灵敏度分类器识别无线电敏化的新目标公开(公告)号：US20050123945A1
公开(公告)日：2005-06-09
申请号：US10904326
申请日：2004-11-04
CPC分类号： G01N33/5005 , C12Q1/025 , G01N2500/00 , G01N2800/52
摘要： A classifier to predict cellular radiation sensitivity based on gene expression profiles in thirty-five cell lines from the NCI panel of 60 cancer cell lines (NCI-60), using a novel approach to predictive gene analysis. Three novel genes are provided, retinoblastoma binding protein 4 (RbAp48), G-protein signaling regulator 19 (RGS19) and ribose-5-phosphate isomerase A (R5PIA) whose expression values were correlated with radiation sensitivity.
摘要翻译： 一种基于60个癌细胞系（NCI-60）NCI组的三十五个细胞系中基因表达谱的细胞辐射敏感性分类器，采用新的预测基因分析方法。 提供三个新基因，其表达值与辐射敏感性相关，视网膜母细胞瘤结合蛋白4（RbAp48），G蛋白信号调节因子19（RGS19）和核糖-5-磷酸异构酶A（R5PIA）。
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公开(公告)号：US09037416B2
公开(公告)日：2015-05-19
申请号：US12728840
申请日：2010-03-22
CPC分类号： C12Q1/6886 , C12Q2600/118 , C12Q2600/158
摘要： Actively dividing tumors appear to progress to a life threatening condition more rapidly than slowly dividing tumors. Assessing actively dividing tumors currently involves a manual assessment of the number of mitotic cells in a histological slide prepared from the tumor and assessed by a trained pathologist. Disclosed is a method for using cumulative information from a series of expressed genes to determine tumor prognosis. This cumulative information can be used to categorize tumor samples into high mitotic states or low mitotic states using a mathematical algorithm and gene expression data derived from microarrays or quantitative-Polymerase Chain Reaction (Q-PCR) data. The specific mathematical description outlines how the algorithm assesses the most informative subset of genes from the full list of genes during the assessment of each sample.
摘要翻译： 与慢慢分裂的肿瘤相比，积极分裂的肿瘤似乎进展到危及生命的疾病。 目前，对积极分割肿瘤的评估包括手动评估从肿瘤制备的组织学载玻片中有丝分裂细胞的数量，并由训练有素的病理学家进行评估。 公开了一种使用来自一系列表达基因的累积信息来确定肿瘤预后的方法。 该累积信息可用于使用来自微阵列或定量聚合酶链反应（Q-PCR）数据的数学算法和基因表达数据将肿瘤样品分类为高有丝分裂状态或低有丝分裂状态。 具体的数学描述概述了在评估每个样本时，算法如何从基因的完整列表中评估基因的最有信息的子集。
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公开(公告)号：US20120041908A1
公开(公告)日：2012-02-16
申请号：US13037156
申请日：2011-02-28
摘要： This invention is a model that simulates the complexity of biological signaling in a cell in response to radiation therapy. Using gene expression profiles and radiation survival assays in an algorithm, a systems model was generated of the radiosensitivity network. The network consists of ten highly interconnected genetic hubs with significant signal redundancy. The model was validated with in vitro tests perturbing network components, correctly predicting radiation sensitivity 2/3 times. The model's clinical relevance was shown by linking clinical radiosensitivity targets to the model network. Clinical applications were confirmed by testing model predictions against clinical response to preoperative radiochemotherapy in patients with rectal or esophageal cancer.
摘要翻译： 本发明是模拟响应于放射治疗的细胞中生物信号传导的复杂性的模型。 在算法中使用基因表达谱和放射线存活测定法，产生了放射敏感性网络的系统模型。 该网络由十个高度互联的遗传中心组成，具有显着的信号冗余。 该模型通过体外测试扰动网络组件进行验证，正确预测辐射灵敏度为2/3倍。 通过将临床放射敏感性目标与模型网络相关联，显示了模型的临床相关性。 临床应用通过对直肠或食管癌患者术前放射化学疗法临床反应的模型预测进行验证。
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