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结节病:蛋白质组学和改善个体化医学的新视角。

Sarcoidosis: proteomics and new perspectives for improving personalized medicine.

机构信息

a Laboratory of Functional Proteomics, Department of Life Sciences , University of Siena . Siena , Italy.

b UOC Respiratory Diseases and Lung Transplantation, Department Internal and Specialist Medicine , University of Siena , Siena , Italy.

出版信息

Expert Rev Proteomics. 2018 Oct;15(10):829-835. doi: 10.1080/14789450.2018.1528148. Epub 2018 Sep 28.

Abstract

Through synergistic approaches integrating biomedical data from omics sciences to the clinical practice, precision medicine aims at more accurate identification of risk factors, characterization of endotypes, patient stratification, establishment of individualized therapy, and prediction of outcomes. Areas covered: This review evaluates the potential role of different omics approaches for the development and application of precision medicine to sarcoidosis patients. This systemic and heterogeneous inflammatory disease is of unknown etiology, affects people of any age, and requires genotypic and phenotypic characterization. The latter can be achieved through the integration of genomic (i.e. information about genes and their mutations potentially involved in sarcoidosis), transcriptomic (reflecting the dynamic state of a cell and measuring the transcribed genes over time), and proteomic data (i.e. proteins in bronchoalveolar lavage, lung tissues, lung cells, serum and immunity system). Expert commentary: Genomic studies have revealed numerous aspects of sarcoidosis; however, for precision medicine, it is necessary to implement genomics with other omic approaches. The improving reliability of omics data, their storage, and their bioinformatics processing represents the next step to recapitulate in silico biological systems, with the final aim to simulate potential molecular pathways involved in the pathology and useful for clinical purposes.

摘要

通过整合组学科学的生物医学数据与临床实践的协同方法,精准医学旨在更准确地识别风险因素、描述表型、对患者进行分层、制定个体化治疗方案以及预测预后。

涵盖领域

本文评价了不同组学方法在发展和应用于类肉瘤病患者的精准医学中的潜在作用。这种系统性和异质性炎症性疾病病因不明,可影响任何年龄段的人群,需要对基因型和表型进行特征描述。后者可通过整合基因组学(即可能与类肉瘤病相关的基因及其突变的信息)、转录组学(反映细胞的动态状态,随时间测量转录基因)和蛋白质组学数据(即支气管肺泡灌洗液、肺组织、肺细胞、血清和免疫系统中的蛋白质)来实现。

专家评论

基因组研究揭示了类肉瘤病的许多方面;然而,对于精准医学,有必要将基因组学与其他组学方法结合起来。提高组学数据的可靠性、存储和生物信息学处理,代表着下一步是在计算机中重现生物系统,最终目的是模拟涉及病理学的潜在分子途径,以便于临床应用。

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