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Ciphergen积极参与寻找判断肝脏疾病进程的生物学指标

【 2005-12-02 发布 】 美迪医讯
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一个联合小组已经开发了一项血液诊断检测方法,用以检测肝脏疾病的进程,从而减少为了制定治疗方案而在丙型肝炎患者中进行痛苦而昂贵的肝脏活检的需要。

Ciphergen生物系统公司(Fremont, CA, USA)将与大学Galveston医学分校(UTMB, USA)合作研究该项目。Ciphergen将提供配套蛋白质组学解决方案,进行寻找生物指标和开发新型检测方法,用以分析检测UTMB收集的标本。这包括Ciphergen公司的Deep Proteome、Pattern跟踪和处理、蛋白质芯片系统。Ciphergen将在制定协议过程中,拥有首先选择和谈判排他性许可证,并参与UTMB正在进行的肝脏疾病的研究之中。

UTMB病理学教授John R. Petersen和内科学教授Ned Snyder教授研究了HCV感染如何损伤肝脏。他们一直对如何确定HCV导致肝脏损伤的血液标记物十分感兴趣。医生们一致认为这种生物指标十分有利于鉴别需要治疗和需要监测的患者。为了鉴别生物学指标,Ciphergen将使用该公司以蛋白质芯片检测为基础的表面增强激光解析/电离--时间--飞行--质谱分析(SELDI-TOF-MS)系统。

Search for Liver Disease Markers
 
An alliance has been formed to develop a diagnostic blood test that can measure the progress of liver disease and thereby reduce the need for painful and costly biopsies in patients with the hepatitis C virus (HCV) to identify the need for treatment.

Ciphergen Biosystems, Inc. (Fremont, CA, USA) will collaborate with the University of Texas Medical Branch at Galveston (UTMB, USA) on the project. Ciphergen will provide its suite of proteomic solutions, designed for biomarker discovery and development of assays, to analyze clinical samples collected at UTMB. This suite includes Ciphergen’s Deep Proteome, Pattern Track, and Process and ProteinChip systems. Ciphergen will have a first option to negotiate an exclusive license to discoveries made during the agreement and will take part in UTMB’s ongoing research in liver disease.

John R. Petersen, Ph.D., professor of pathology at UTMB, and Ned Snyder, M.D., professor of internal medicine at UTMB, have been studying how HCV infection can damage or destroy the liver. They have been interested in using blood markers that can help determine the amount of liver damage that has been caused by HCV. Doctors agree that such biomarkers would be extremely useful in identifying which patients require treatment and for monitoring patients. To identify biomarkers, Ciphergen will use its ProteinChip array-based surface enhanced laser desorption/ionization--time-of-flight--mass spectrometry (SELDI-TOF-MS) system.

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本文关键字: Ciphergen,生物学指标 
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