共查询到18条相似文献,搜索用时 46 毫秒
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蛋白质组学及其在肿瘤研究中的应用 总被引:2,自引:0,他引:2
简要介绍了蛋白质组学的概念、研究方法及其在肿瘤研究中的应用.蛋白质组学研究直接定位于蛋白质水平,从整体、动态、定量的角度去研究基因的功能,是后基因组计划的一个重要组成部分.恶性肿瘤是一种多基因参与的复杂疾病,从蛋白质整体水平上研究恶性肿瘤将有助于进一步揭示恶性肿瘤的发病机制,发现恶肿瘤特异性的标志物及其药物治疗的靶标. 相似文献
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蛋白质组学在贝类研究中的应用 总被引:2,自引:0,他引:2
随着人类基因组计划的完成,功能基因组学的研究日益蓬勃发展。作为功能基因组学的重要支柱,蛋白质组学的研究旨在阐明基因组所表达的真正执行生命活动的全部蛋白质的表达规律和生物功能。伴随着研究的不断深入,蛋白质组学技术已涉及水产经济动物如鱼、虾、贝的研究。尽管在水产动物的研究中运用蛋白质组学技术较晚,但进展迅速。目前对于贝类相关蛋白质组学的研究尚未有一系统总结。因此,基于贝类蛋白质组学中双向电泳体系的构建和优化、生物矿化、发育与免疫和环境毒理学的相关研究做一综述。 相似文献
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差异蛋白质组学在筛选肿瘤标记中的应用 总被引:1,自引:0,他引:1
目前,利用差异蛋白质组技术对肿瘤早期标记蛋白的筛选已在世界范围内形成热潮。介绍了蛋白组学、差异蛋白质组学、肿瘤标记、常用的差异蛋白质组学技术及其在筛选肿瘤标记中的应用.最后指出了研究中存在的问题,并对前景进行了展望。 相似文献
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蛋白质组学在信号转导研究中的应用 总被引:2,自引:0,他引:2
新近发展起来的蛋白质组学高通量技术引入到信号转导通路研究中,产生了一个新的研究领域:信号转导蛋白质组学。其作为功能蛋白质组学的一个重要组成部分,以研究信号转导通路以及其中的信号分子改变的蛋白质组学。克服了传统地针对单条信号转导通路以及其中的单个信号分子研究策略的局限性,能够在一次实验中系统地研究多条信号转导通路中的蛋白质一蛋白质间的相互作用、蛋白质磷酸化等翻译后修饰和下游靶蛋白的改变,有助于全面阐述信号转导通路,已成为一个新的研究热点。 相似文献
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临床蛋白质组学是将蛋白质组学技术应用于临床医学研究,它主要围绕疾病的预防、早期诊断和治疗等方面开展研究,其中,恶性肿瘤是临床蛋白质组学研究的一个重点研究对象.由于肿瘤生物标志物对早期诊断具有重要价值,所以临床蛋白质组学的主要目标之一是寻找合适的肿瘤生物标志物,多分子生物标志物已成为寻找肿瘤生物标志物的一个研究趋势.简要介绍了临床蛋白质组学的基本概念,实验设计,临床样本收集与预处理以及蛋白质组学技术在临床研究中的应用与进展. 相似文献
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Yong Jin Heo Chanwoong Hwa Gang-Hee Lee Jae-Min Park Joon-Yong An 《Molecules and cells》2021,44(7):433
Multi-omics approaches are novel frameworks that integrate multiple omics datasets generated from the same patients to better understand the molecular and clinical features of cancers. A wide range of emerging omics and multi-view clustering algorithms now provide unprecedented opportunities to further classify cancers into subtypes, improve the survival prediction and therapeutic outcome of these subtypes, and understand key pathophysiological processes through different molecular layers. In this review, we overview the concept and rationale of multi-omics approaches in cancer research. We also introduce recent advances in the development of multi-omics algorithms and integration methods for multiple-layered datasets from cancer patients. Finally, we summarize the latest findings from large-scale multi-omics studies of various cancers and their implications for patient subtyping and drug development. 相似文献
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《Expert review of proteomics》2013,10(3):259-267
Constitutive activity of kinases is known to be crucial for a tumor to maintain its malignant phenotype, a phenomenon which is often referred to as oncogene addiction. The in-depth analysis of aberrant signaling pathways by the analysis of protein phosphorylation has become feasible through recent advances in proteomics technology. In this article we will review developments in the field of phosphoproteomics and its application in cancer research. The most widely used technologies for the generic enrichment of phosphopeptides are discussed as well as targeted approaches for the analysis of a specific subset of phosphopeptides. Validation experiments of phosphorylation sites using targeted mass spectrometry are also explained. Finally, we will highlight applications of phosphoproteomic technology in cancer research using cell lines and tissue. 相似文献
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《Expert review of proteomics》2013,10(1):9-10
Towards revolutionary biomarkers, a considerable amount of research funds and time have been dedicated to proteomics. Although the discovery of novel biomarkers at the dawn of proteomics was a promising development, only a few identified biomarkers seemed to be beneficial for cancer patients. We may need to approach this issue differently, instead of only extending the conventional approaches that have been used historically. The study of biomarkers is essentially a study of diseases and the biochemistry relating to peptide, protein and post-translational modifications is only a tool. A problem-oriented approach should be needed in biomarker development. Clinician participation in the study of biomarkers will lead to realistic, practical and interesting biomarker candidates, which justify the time and expense involved in validation studies. Although discussion in this article is focused on cancer biomarkers, it can generally be applied to biomarker studies for other diseases. 相似文献
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Marcello Manfredi Jessica Brandi Claudia Di Carlo Virginia Vita Vanella Elettra Barberis Emilio Marengo 《Expert review of proteomics》2013,10(9):733-747
ABSTRACTIntroduction: Discovery proteomics for cancer research generates complex datasets of diagnostic, prognostic, and therapeutic significance in human cancer. With the advent of high-resolution mass spectrometers, able to identify thousands of proteins in complex biological samples, only the application of bioinformatics can lead to the interpretation of data which can be relevant for cancer research.Areas covered: Here, we give an overview of the current bioinformatic tools used in cancer proteomics. Moreover, we describe their applications in cancer proteomics studies of cell lines, serum, and tissues, highlighting recent results and critically evaluating their outcomes.Expert opinion: The use of bioinformatic tools is a fundamental step in order to manage the large amount of proteins (from hundreds to thousands) that can be identified and quantified in a cancer biological samples by proteomics. To handle this challenge and obtain useful data for translational medicine, it is important the combined use of different bioinformatic tools. Moreover, a particular attention to the global experimental design, and the integration of multidisciplinary skills are essential for best setting of tool parameters and best interpretation of bioinformatics output. 相似文献
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Marilyne Labrie Nicholas D Kendsersky Hongli Ma Lydia Campbell Jennifer Eng Koei Chin 《Expert review of proteomics》2013,10(10):841-850
ABSTRACTIntroduction: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a challenging task. Furthermore, emerging studies show that genetic alterations are frequently poorly represented at the protein level adding a layer of complexity. With improvements in large-scale proteomic technologies, proteomics studies have the potential to provide robust analysis of the pathways driving high HGSC behavior.Areas covered: This review summarizes recent large-scale proteomics findings across adequately sized ovarian cancer sample sets. Key words combined with ‘ovarian cancer’ including ‘proteomics’, ‘proteogenomic’, ‘reverse-phase protein array’, ‘mass spectrometry’, and ‘adaptive response’, were used to search PubMed.Expert opinion: Proteomics analysis of HGSC as well as their adaptive responses to therapy can uncover new therapeutic liabilities, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is a pressing need to better understand how the genomic and epigenomic heterogeneity intrinsic to ovarian cancer is reflected at the protein level and how this information could be used to improve patient outcomes. 相似文献
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