公开(公告)号：US20170023575A1

公开(公告)日：2017-01-26

申请号：US15177813

申请日：2016-06-09

Applicant: Purdue Research Foundation

Inventor： M. Daniel Raftery ,  Vincent Asiago ,  Kwadwo Owusu-sarfo ,  Bowei Xi

IPC: G01N33/574 ,  G01R33/465 ,  G01N30/72 ,  G06F19/00 ,  G01N24/08

CPC classification number: G01N33/57438 ,  G01N24/08 ,  G01N30/72 ,  G01N30/7233 ,  G01N33/6806 ,  G01N33/6848 ,  G01N2030/8818 ,  G01N2560/00 ,  G01R33/465 ,  G16H50/20

Abstract: The present disclosure relates to a panel of a plurality of metabolite species that is useful for the identification or detection of subjects having pancreatic cancer, including methods for identifying such metabolic biomarkers within biological samples. The disclosure also includes a statistical model for predicting the presence of pancreatic cancer in a subject's biofluid by quantifying and comparing positive and negative fold changes in metabolite species' concentration; comparing the subject's metabolite species' concentrations to a predetermined value.

Abstract translation: 本公开涉及可用于鉴定或检测具有胰腺癌的受试者的多种代谢物种的一组，包括鉴定生物样品内的这些代谢生物标志物的方法。 本公开还包括通过定量和比较代谢物种浓度的正负折叠变化来预测受试者生物流体中胰腺癌存在的统计模型; 将受试者的代谢物种类浓度与预定值进行比较。

公开(公告)号：US20150056605A1

公开(公告)日：2015-02-26

申请号：US14465535

申请日：2014-08-21

Applicant: PURDUE RESEARCH FOUNDATION

Inventor： M. Daniel Raftery ,  Vincent M. Asiago ,  Kwadwo Owusu-sarfo ,  Bowei Xi

IPC: G01N33/574 ,  G01N33/68 ,  G01N24/08 ,  H01J49/40 ,  H01J49/00 ,  C12Q1/00 ,  G01N30/72

CPC classification number: G01N33/57438 ,  G01N24/08 ,  G01N30/72 ,  G01N30/7233 ,  G01N33/6806 ,  G01N33/6848 ,  G01N2030/8818 ,  G01N2560/00 ,  G01R33/465 ,  G16H50/20

Abstract: The present disclosure relates to a panel of a plurality of metabolite species that is useful for the identification or detection of subjects having pancreatic cancer, including methods for identifying such metabolic biomarkers within biological samples. The disclosure also includes a statistical model for predicting the presence of pancreatic cancer in a subject's biofluid by quantifying and comparing positive and negative fold changes in metabolite species' concentration; comparing the subject's metabolite species' concentrations to a predetermined value.

Abstract translation: 本公开涉及可用于鉴定或检测具有胰腺癌的受试者的多种代谢物种的一组，包括鉴定生物样品内的这些代谢生物标志物的方法。 本公开还包括通过定量和比较代谢物种浓度的正负折叠变化来预测受试者生物流体中胰腺癌存在的统计模型; 将受试者的代谢物种类浓度与预定值进行比较。

公开(公告)号：US20140162903A1

公开(公告)日：2014-06-12

申请号：US14068923

申请日：2013-10-31

Applicant: Purdue Research Foundation

Inventor： M. Daniel Raftery ,  Siwei Wei ,  Susan E. Clare

IPC: G01N33/49

CPC classification number: G01N33/57415 ,  G01N2405/00 ,  G01N2405/04 ,  G01N2560/00

Abstract: The present disclosure relates to a panel of metabolite species that is useful for forecasting the outcome of preoperative chemotherapy for the treatment of breast cancer, including methods for identifying and using such metabolite species that can be measured in biological samples taken before treatment. In preferred embodiments, a method of forecasting a treatment outcome before subjecting a breast cancer patient to preoperative chemotherapy is disclosed that includes measuring the concentration of at least one metabolite species in a sample of a biofluid taken from the breast cancer patient before preoperative chemotherapy treatment.

Abstract translation: 本公开涉及可用于预测用于治疗乳腺癌的术前化学疗法的结果的代谢物种类的一组，包括用于鉴定和使用可在治疗前采集的生物样品中测量的此类代谢物种的方法。 在优选实施方案中，公开了一种在对乳腺癌患者进行术前化学疗法之前预测治疗结果的方法，其包括测量在术前化学治疗之前从乳腺癌患者获取的生物流体样品中至少一种代谢物种的浓度。

公开(公告)号：US20130023056A1

公开(公告)日：2013-01-24

申请号：US13624042

申请日：2012-09-21

Applicant: PURDUE RESEARCH FOUNDATION

Inventor： M. Daniel Raftery ,  Vincent Moseti Asiago ,  G.A. Nagana Gowda ,  Leiddy Alvarado

IPC: G01N27/62 ,  C07C215/40 ,  C07C53/02 ,  C07D233/56 ,  G06F17/18 ,  C07C229/08 ,  C07C59/235 ,  C07D207/16 ,  C07C229/22 ,  C07C229/36 ,  C07C59/01 ,  C07C229/24

CPC classification number: G01N33/57415 ,  G01N30/463 ,  G01N30/7206 ,  G01N33/6803 ,  G01N33/6848 ,  G01N2800/60 ,  Y10T436/201666

Abstract: A monitoring test for recurrent breast cancer with a high degree of sensitivity and specificity is provided that detects the presence of a panel of multiplicity of biomarkers that were identified using metabolite profiling methods. The test is capable of detecting breast cancer recurrence about a years earlier than current available monitoring diagnostic tests. The panel of biomarkers is identified using a combination of nuclear magnetic resonance (NMR) and two dimensional gas chromatography-mass spectrometry (GC×GC-MS) to produce the metabolite profiles of serum samples. The NMR and GC×GC-MS data are analyzed by multivariate statistical methods to compare identified metabolite signals between samples from patients with recurrence of breast cancer and those from patients having no evidence of disease.

Abstract translation: 提供了具有高度灵敏度和特异性的复发性乳腺癌的监测测试，其检测使用代谢物分析方法鉴定的多组生物标志物的存在。 该测试能够比当前可用的监测诊断测试早一年检测乳腺癌复发。 使用核磁共振（NMR）和二维气相色谱 - 质谱（GC×GC-MS）的组合鉴定生物标志物组，以产生血清样品的代谢物谱。 通过多变量统计学方法分析NMR和GC×GC-MS数据，以比较乳腺癌复发患者和无疾病证据患者的样本之间的鉴定代谢信号。

公开(公告)号：US20160363560A9

公开(公告)日：2016-12-15

申请号：US14167270

申请日：2014-01-29

Applicant: Purdue Research Foundation

Inventor： M. Daniel Raftery ,  Jian Zhang ,  Zane Hammoud

IPC: G01N27/74

CPC classification number: G01N27/74 ,  G01N33/57488 ,  G01N2570/00

Abstract: Methods for the detection and screening of esophageal adenocarcinoma (EAC) patients and for the monitoring of EAC treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. In other aspects, methods for detection and screening for the progression of high-risk conditions (BE and HGD) to EAC and to monitoring treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. The biomarkers are sensitive and specific for the detection of EAC, and can also be used to classify Barrett's esophagus (BE) and high-grade dysplasia (HGD), which are widely regarded as precursors of EAC.

Abstract translation: 公开了使用小分子代谢物生物标志物的小组或小组检测和筛选食管腺癌（EAC）患者和用于监测EAC治疗的方法。 在其他方面，公开了用于检测和筛选高危条件（BE和HGD）进展到EAC以及使用小分子代谢物生物标志物的小组或小组进行监测的方法。 生物标志物对EAC的检测敏感且特异，也可用于对Barrett食管（BE）和高度发育异常（HGD）进行分类，被广泛认为是EAC的前体。

公开(公告)号：US20140148349A1

公开(公告)日：2014-05-29

申请号：US14167270

申请日：2014-01-29

Applicant: Purdue Research Foundation

Inventor： M. Daniel Raftery ,  Jian Zhang ,  Zane Hammoud

IPC: G01N27/74

CPC classification number: G01N27/74 ,  G01N33/57488 ,  G01N2570/00

Abstract: Methods for the detection and screening of esophageal adenocarcinoma (EAC) patients and for the monitoring of EAC treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. In other aspects, methods for detection and screening for the progression of high-risk conditions (BE and HGD) to EAC and to monitoring treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. The biomarkers are sensitive and specific for the detection of EAC, and can also be used to classify Barrett's esophagus (BE) and high-grade dysplasia (HGD), which are widely regarded as precursors of EAC.

Abstract translation: 公开了使用小分子代谢物生物标志物的小组或小组检测和筛选食管腺癌（EAC）患者和用于监测EAC治疗的方法。 在其他方面，公开了用于检测和筛选高危条件（BE和HGD）进展到EAC以及使用小分子代谢物生物标志物的小组或小组进行监测的方法。 生物标志物对EAC的检测敏感且特异，也可用于对Barrett食管（BE）和高度发育异常（HGD）进行分类，被广泛认为是EAC的前体。

公开(公告)号：US20130282300A1

公开(公告)日：2013-10-24

申请号：US13918796

申请日：2013-06-14

Applicant: Purdue Research Foundation

Inventor： M. Daniel Raftery ,  Huanwen Chen ,  Zhengzheng Pan

IPC: H01J49/00 ,  G01R33/465

CPC classification number: H01J49/0036 ,  G01R33/465 ,  H01J49/145 ,  H01J49/165

Abstract: A method for differentiating complex biological samples, each sample having one or more metabolite species. The method comprises producing a mass spectrum by subjecting the sample to a mass spectrometry analysis, the mass spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; subjecting the individual spectral peaks of the mass spectrum to a statistical pattern recognition analysis; identifying the one or more metabolite species contained within the sample by analyzing the individual spectral peaks of the mass spectrum; and assigning the sample into a defined sample class.

Abstract translation: 用于区分复杂生物样品的方法，每个样品具有一种或多种代谢物种。 该方法包括通过对样品进行质谱分析来产生质谱，所述质谱包含代表样品中所含的一种或多种代谢物种类的各个光谱峰; 对质谱的各个光谱峰进行统计模式识别分析; 通过分析质谱的各个光谱峰来识别样品中所含的一种或多种代谢物; 并将样本分配到定义的样本类中。