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    Predictive test for melanoma patient benefit from antibody drug blocking ligand activation of the T-cell programmed cell death 1 (PD-1) checkpoint protein and classifier development methods
    11.
    发明申请
    Predictive test for melanoma patient benefit from antibody drug blocking ligand activation of the T-cell programmed cell death 1 (PD-1) checkpoint protein and classifier development methods 有权
    黑素瘤患者的预测试验受益于抗体药物阻断配体激活T细胞程序性细胞死亡1（PD-1）检查点蛋白和分类器开发方法

    公开(公告)号：US20170039345A1

    公开(公告)日：2017-02-09

    申请号：US15207825

    申请日：2016-07-12

    Applicant: Biodesix, Inc.

    Inventor： Joanna Röder ,  Krista Meyer ,  Julia Grigorieva ,  Maxim Tsypin ,  Carlos Oliveira ,  Arni Steingrimsson ,  Heinrich Röder ,  Senait Asmellash ,  Kevin Sayers ,  Caroline Maher ,  Jeffrey Weber

    IPC: G06F19/00 ,  G01N33/68

    CPC classification number: G16H20/30 ,  G01N33/5743 ,  G01N33/6851 ,  G01N2333/70532 ,  G01N2800/52 ,  G06F19/00 ,  G06F19/24 ,  G06F19/3456 ,  G06F19/3481 ,  G16H20/10

    Abstract: A method is disclosed of predicting cancer patient response to immune checkpoint inhibitors, e.g., an antibody drug blocking ligand activation of programmed cell death 1 (PD-1) or CTLA4. The method includes obtaining mass spectrometry data from a blood-based sample of the patient, obtaining integrated intensity values in the mass spectrometry data of a multitude of pre-determined mass-spectral features; and operating on the mass spectral data with a programmed computer implementing a classifier. The classifier compares the integrated intensity values with feature values of a training set of class-labeled mass spectral data obtained from a multitude of melanoma patients with a classification algorithm and generates a class label for the sample. A class label “early” or the equivalent predicts the patient is likely to obtain relatively less benefit from the antibody drug and the class label “late” or the equivalent indicates the patient is likely to obtain relatively greater benefit from the antibody drug.

    Abstract translation: 公开了一种预测癌症患者对免疫检查点抑制剂的反应的方法，例如抗体药物阻断配体激活程序性细胞死亡1（PD-1）或CTLA4。 该方法包括从患者的血液样品获得质谱数据，获得众多预定质谱特征的质谱数据中的积分强度值; 并使用实现分类器的编程计算机对质谱数据进行操作。 分类器将积分强度值与通过分类算法从多个黑素瘤患者获得的类别标记质谱数据的训练集的特征值进行比较，并生成样本的类标签。 类别标签“早期”或等同物预测患者可能从抗体药物和类标签“晚期”获得相对较少的益处，或等同物表示患者可能从抗体药物获得相对较大的益处。

    Method for treating and identifying lung cancer patients likely to benefit from EGFR inhibitor and a monoclonal antibody HGF inhibitor combination therapy
    12.
    发明申请
    Method for treating and identifying lung cancer patients likely to benefit from EGFR inhibitor and a monoclonal antibody HGF inhibitor combination therapy 审中-公开
    用于治疗和鉴定可能受益于EGFR抑制剂和单克隆抗体HGF抑制剂联合疗法的肺癌患者的方法

    公开(公告)号：US20150285817A1

    公开(公告)日：2015-10-08

    申请号：US14678428

    申请日：2015-04-03

    Applicant: Biodesix, Inc. ,  AVEO Pharmaceuticals, Inc.

    Inventor： Heinrich Röder ,  Julia Grigorieva ,  May Han ,  Philip Komarnitsky ,  Jeno Gyuris

    IPC: G01N33/68 ,  G06F19/00 ,  A61K31/517 ,  A61K39/395 ,  A61K31/5377

    CPC classification number: G01N33/6848 ,  A61K31/517 ,  A61K31/5377 ,  A61K39/3955 ,  C07K16/22 ,  G01N33/57423 ,  G01N2800/52 ,  G16C99/00 ,  Y02A90/26 ,  Y10T436/24 ,  A61K2300/00

    Abstract: A test to identify whether a lung patient is likely to benefit from combination therapy in the form of an epidermal growth factor receptor inhibitor (EGFR-I) and a monoclonal antibody drug targeting hepatocyte growth factor (HGF) as compared to EGFR-I monotherapy. The test makes use of a mass spectrum obtained from a serum or plasma sample and a computer configured as a classifier operating on the mass spectrum and a training set in the form of class-labeled mass spectra from other cancer patients. The computer classifier executes a classification algorithm, such as K-nearest neighbor, and assigns a class label to the serum or plasma sample. Samples classified as “Poor” or the equivalent are associated with patients which are likely to benefit from the combination therapy more than from EGFR-I monotherapy. The invention also includes improved methods of treating patients predicted by the test.

    Abstract translation: 与EGFR-1单药治疗相比，用于鉴定肺部患者是否可能以表皮生长因子受体抑制剂（EGFR-I）和靶向肝细胞生长因子（HGF）的单克隆抗体药物的形式从组合疗法中受益的测试。 该测试使用从血清或血浆样品获得的质谱，以及配置为在质谱上操作的分类器的计算机和来自其他癌症患者的类别标记质谱图形式的训练集。 计算机分类器执行分类算法，如K最近邻，并为血清或血浆样本分配类别标签。 分类为“差”或等同物的样品与可能受益于组合疗法的患者比来自EGFR-I单一疗法的患者相关。 本发明还包括治疗通过测试预测的患者的改进方法。

    Classifier generation methods and predictive test for ovarian cancer patient prognosis under platinum chemotherapy
    13.
    发明授权
    Classifier generation methods and predictive test for ovarian cancer patient prognosis under platinum chemotherapy 有权

    公开(公告)号：US11621057B2

    公开(公告)日：2023-04-04

    申请号：US16092023

    申请日：2017-03-10

    Applicant: Biodesix, Inc.

    Inventor： Arni Steingrimsson ,  Joanna Röder ,  Julia Grigorieva ,  Heinrich Röder ,  Krista Meyer

    IPC: G16B40/00 ,  G16B40/20 ,  G16H20/40

    Abstract: A method of generating a classifier includes a step of classifying each member of a development set of samples with a class label in a binary classification scheme with a first classifier; and generating a second classifier using a classifier development process with an input classifier development set being the members of the development set assigned one of the two class labels in the binary classification scheme by the first classifier. The second classifier stratifies the members of the set with an early label into two further sub-groups. We also describe identifying a plurality of different clinical sub-groups within the development set based on the clinical data and for each of the different clinical sub-groups, conducting a classifier generation process for each of the clinical sub-groups thereby generating clinical subgroup classifiers. We further describe an example of a hierarchical arrangement of such classifiers and their use in predicting, in advance of treatment, ovarian cancer patient outcomes on platinum-based chemotherapy.

    Cancer patient selection for administration of therapeutic agents using mass spectral analysis of blood-based samples
    17.
    发明申请
    Cancer patient selection for administration of therapeutic agents using mass spectral analysis of blood-based samples 审中-公开
    使用血液样品的质谱分析来治疗药物的癌症患者选择

    公开(公告)号：US20140284468A1

    公开(公告)日：2014-09-25

    申请号：US14295783

    申请日：2014-06-04

    Applicant: Biodesix, Inc.

    Inventor： Julia Grigorieva ,  Heinrich Röder ,  Maxim Tsypin

    IPC: G01N33/68 ,  H01J49/40

    CPC classification number: G01N33/6848 ,  G01N33/57415 ,  G01N2800/52 ,  G16C20/20 ,  G16C20/70 ,  G16H10/40 ,  H01J49/00 ,  H01J49/40 ,  Y02A90/22

    Abstract: Methods using mass spectral data analysis and a classification algorithm provide an ability to determine whether a solid epithelial tumor cancer patient is likely to benefit from a therapeutic agent or a combination of therapeutic agents targeting agonists of the receptors, receptors or proteins involved in MAPK (mitogen-activated protein kinase) pathways or the PKC (protein kinase C) pathway upstream from or at Akt or ERK/JNK/p38 or PKC, such as therapeutic agents targeting EGFR and/or HER2. The methods also provide the ability to determine whether the cancer patient is likely to benefit from the combination of a therapeutic agent targeting EFGR and a therapeutic agent targeting COX2; or whether the cancer patient is likely to benefit from the treatment with an NF-κB inhibitor.

    Abstract translation: 使用质谱数据分析和分类算法的方法提供了确定固体上皮肿瘤癌症患者是否可能受益于治疗剂或靶向受体，受体或参与MAPK的蛋白质（促分裂原）的治疗剂的组合的能力 激活的蛋白激酶）途径或在Akt或ERK / JNK / p38或PKC上游的PKC（蛋白激酶C）途径，例如靶向EGFR和/或HER2的治疗剂。 所述方法还提供了确定癌症患者是否可能受益于靶向EFGR2的治疗剂与靶向COX2的治疗剂的组合的能力的能力; 或者癌症患者是否可能受益于用NF-κB抑制剂治疗。

    Method for predicting whether a cancer patient will not benefit from platinum-based chemotherapy agents
    18.
    发明申请
    Method for predicting whether a cancer patient will not benefit from platinum-based chemotherapy agents 审中-公开
    预测癌症患者是否不会受益于铂类化疗药物的方法

    公开(公告)号：US20140200825A1

    公开(公告)日：2014-07-17

    申请号：US14212567

    申请日：2014-03-14

    Applicant: Biodesix, Inc.

    Inventor： Joanna Röder ,  Heinrich Röder ,  Julia Grigorieva

    IPC: G06F19/00 ,  H01J49/26

    CPC classification number: H01J49/26 ,  G01N33/57488 ,  G01N33/6848 ,  G01N2800/52 ,  G06F19/34 ,  G16C20/70 ,  G16H50/20 ,  G16H50/50 ,  H01J49/0027 ,  Y02A90/26

    Abstract: A testing method for identification whether a cancer patient is a member of a group or class of cancer patients that are not likely to benefit from administration of a platinum-based chemotherapy agent, e.g., cisplatin, carboplatin or analogs thereof, either alone or in combination with other non-platinum chemotherapy agents, e.g., gemcitabine and paclitaxel. This identification can be made in advance of treatment. The method uses a mass spectrometer obtaining a mass spectrum of a blood-based sample from the patient, and a computer operating as a classifier and using a stored training set comprising class-labeled spectra from other cancer patients.

    Abstract translation: 用于鉴定癌症患者是否是不可能单独或组合地施用铂类化疗药物（例如顺铂，卡铂或其类似物）而不可能受益的癌症患者的成员的测试方法 与其他非铂化疗药物，例如吉西他滨和紫杉醇。 该鉴定可以在治疗之前进行。 该方法使用质谱仪获得来自患者的基于血液的样品的质谱，以及作为分类器操作的计算机，并使用包含来自其他癌症患者的类别标记光谱的存储的训练组。

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