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用于多发性骨髓瘤精准医学发展的多组学肿瘤分析技术。

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma.

作者信息

Ovejero Sara, Moreaux Jerome

机构信息

Department of Biological Hematology, CHU Montpellier, 34295 Montpellier, France.

Institute of Human Genetics, UMR 9002 CNRS-UM, 34000 Montpellier, France.

出版信息

Explor Target Antitumor Ther. 2021;2(1):65-106. doi: 10.37349/etat.2021.00034. Epub 2021 Feb 28.

Abstract

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

摘要

多发性骨髓瘤(MM)是第二常见的血液系统癌症,由骨髓中异常浆细胞的积累引起。其分子病因尚未完全明确,且患者之间存在很大的异质性,这使得治疗决策变得复杂。在过去几十年中,新疗法和药物的发展显著提高了MM患者的生存率。然而,耐药性和复发仍然是最常见的死亡原因,也是需要克服的主要挑战。能够分析大量临床和生物学数据的高通量组学技术的出现,改变了MM的诊断和治疗方式。将组学数据(基因突变、基因表达、表观遗传信息以及蛋白质和代谢物水平)与数千名患者的临床病史相结合,可以构建评分系统,以在诊断时对风险进行分层,并预测对治疗的反应,帮助临床医生针对每个具体病例做出更明智的决策。毫无疑问,MM治疗的未来依赖于基于组学研究建立的预测模型的个性化治疗。本综述总结了MM的当前治疗方法、组学技术在MM中的应用及其在个性化医疗实施中的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6582/9400753/b9c9cc83a41c/etat-02-100234-g001.jpg

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