The proteogenomic path towards biomarker discovery.
The proteogenomic path towards biomarker discovery.
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DOI：
10.1111/j.1399-3046.2008.01018.x
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发表时间：
2008-11
影响因子：
1.3
通讯作者：
Sarwal MM
中科院分区：
文献类型：
--
作者：
Sigdel TK;Sarwal MM
对用于疾病诊断和预后的生物标志物的需求从未如此强烈。随着基因组数据的可用性和蛋白质组数据的可用性增加，生物标志物的发现变得越来越可行。然而，这项任务是艰巨的，需要在移植，免疫学，遗传学，分子生物学，生物统计学和生物信息学领域工作的研究人员之间的合作。随着高通量组学技术如基因组学和蛋白质组学（统称为蛋白质基因组学）的进步，已经努力从新的和待发现的生物标志物开发诊断工具。然而，生物标志物验证，特别是在器官移植中，仍然具有挑战性，因为缺乏真正的诊断类别的金标准和面临高通量数据去卷积的分析瓶颈。尽管微阵列技术相对成熟，但蛋白质组学在数据标准化和分析方法方面仍处于发展阶段。研究设计、样本选择和严格的数据分析是使用高通量蛋白质组学技术发现生物标志物的关键问题，该技术联合收割机了基因组学和蛋白质组学的使用和优势。本文综述了利用基因组学和蛋白质组学发现器官移植相关生物标志物的研究现状和最新进展，重点介绍了蛋白质组学技术的发展。
The desire for biomarkers for diagnosis and prognosis of diseases has never been greater. With the availability of genome data and an increased availability of proteome data, the discovery of biomarkers has become increasingly feasible. However, the task is daunting and requires collaborations among researchers working in the fields of transplantation, immunology, genetics, molecular biology, biostatistics, and bioinformatics. With the advancement of high throughput omic techniques such as genomics and proteomics (collectively known as proteogenomics), efforts have been made to develop diagnostic tools from new and to-be discovered biomarkers. Yet biomarker validation, particularly in organ transplantation, remains challenging because of the lack of a true gold standard for diagnostic categories and analytical bottlenecks that face high-throughput data deconvolution. Even though microarray technique is relatively mature, proteomics is still growing with regards to data normalization and analysis methods. Study design, sample selection, and rigorous data analysis are the critical issues for biomarker discovery using high-throughout proteogenomic technologies that combine the use and strengths of both genomics and proteomics. In this review, we look into the current status and latest developments in the field of biomarker discovery using genomics and proteomics related to organ transplantation, with an emphasis on the evolution of proteomic technologies.
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