Towards Integrative Glycoinformatics for Glycan Based Biomarker Cancer Research and Discovery

Sandra V. Bennun, Deniz Bayçın Hızal, R. Ranzinger, M. Betenbaugh
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引用次数: 2

Abstract

Despite some recent successes in deciphering new cancer molecular makers, there is still a clear and continual need to develop new technologies that help characterizing existing biomarkers or facilitate discovery of new biomarkers. An important systems biology opportunity on this respect is provided by understanding the glycosylation changes associated with cancer. Indeed, interest in cancer glycosylation has expanded over the past decade and large amount of data relevant to cancer glycosylation has been accumulating rapidly. Furthermore, new and improved sophisticated glycoinformatics tools, methods and databases for glycan analysis now offer the opportunity to investigate this data for understanding the role that glycans play in cancer glycosylation. Here we summarize developments of glycoinformatics tools to support analysis of cancer glycosylation and experimental glycoproteomics approaches. In addition, we discuss challenges faced by glycoinformatics for the integration and interrogation of disparate high-throughput glycan data sets in order to assimilate technologies and better address cancer glycosylation. We also provide examples of integrative glycoinformatics approaches that lead to a better understanding of cancer glycosylation as a complex cellular process.
基于糖聚糖的生物标志物癌症研究与发现的整合糖信息学研究
尽管最近在破译新的癌症分子制造者方面取得了一些成功,但显然仍然需要开发新的技术来帮助表征现有的生物标志物或促进新的生物标志物的发现。了解与癌症相关的糖基化变化提供了这方面一个重要的系统生物学机会。事实上,在过去的十年中,人们对癌症糖基化的兴趣不断扩大,与癌症糖基化相关的大量数据也在迅速积累。此外,新的和改进的复杂糖信息学工具、方法和数据库为糖基化分析提供了研究这些数据的机会,以了解糖基化在癌症中所起的作用。在这里,我们总结糖信息学工具的发展,以支持分析癌症糖基化和实验糖蛋白组学方法。此外,我们还讨论了糖信息学在整合和查询不同的高通量聚糖数据集方面所面临的挑战,以便吸收技术并更好地解决癌症糖基化问题。我们还提供了综合糖信息学方法的例子,这些方法可以更好地理解癌症糖基化是一个复杂的细胞过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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