Suppr超能文献

精准医学的艺术与挑战:将基因组数据解读并整合到临床实践中。

Art and Challenges of Precision Medicine: Interpreting and Integrating Genomic Data Into Clinical Practice.

作者信息

Madhavan Subha, Subramaniam Somasundaram, Brown Thomas D, Chen James L

机构信息

From the Innovation Center for Biomedical Informatics, Georgetown University, Washington, DC; Swedish Cancer Institute, Seattle, WA; The Ohio State University, Columbus, OH.

出版信息

Am Soc Clin Oncol Educ Book. 2018 May 23;38:546-553. doi: 10.1200/EDBK_200759.

Abstract

Precision medicine is at the forefront of innovation in cancer care. With the development of technologies to rapidly sequence DNA from tumors, cell-free DNA, proteins, and even metabolites coupled with the rapid decline in the cost of genomic sequencing, there has been an exponential increase in the amount of data generated for each patient diagnosed with cancer. The ability to harness this explosion of data will be critical to improving treatments for patients. Precision medicine lends itself to big data or "informatics" approaches and is focused on storing, accessing, sharing, and studying these data while taking necessary precautions to protect patients' privacy. Major cancer care stakeholders have developed a variety of systems to incorporate precision medicine technologies into patient care as soon as possible and also to provide the ability to store and analyze the omics and clinical data aggregately in the future. Scaling these precision medicine programs within the confines of health care system silos is challenging, and research consortiums are being formed to overcome these limitations. Incorporating and interpreting the results of precision medicine sequencing is complex and rapidly changing, necessitating reliance on a group of experts. This is often performed at molecular tumor boards at large academic and research institutions with available in-house expertise, but alternative models clinical decision support software or of virtual tumor boards potentially expand these advances to almost any patient, regardless of site of care. The promises of precision medicine will be more quickly realized by expanding collaborations to rapidly process and interpret the growing volumes of omics data.

摘要

精准医学处于癌症治疗创新的前沿。随着从肿瘤、游离DNA、蛋白质甚至代谢物中快速测序DNA的技术发展,以及基因组测序成本的迅速下降,每个癌症确诊患者产生的数据量呈指数级增长。利用这些数据爆炸的能力对于改善患者治疗至关重要。精准医学适用于大数据或“信息学”方法,专注于存储、访问、共享和研究这些数据,同时采取必要措施保护患者隐私。主要的癌症治疗利益相关者已经开发了各种系统,以便尽快将精准医学技术纳入患者护理,并在未来提供汇总存储和分析组学及临床数据的能力。在医疗系统孤岛的范围内扩展这些精准医学项目具有挑战性,正在形成研究联盟以克服这些限制。纳入和解释精准医学测序结果既复杂又迅速变化,需要依赖一组专家。这通常在拥有内部专业知识的大型学术和研究机构的分子肿瘤委员会进行,但临床决策支持软件或虚拟肿瘤委员会等替代模式有可能将这些进展扩展到几乎任何患者,无论其护理地点如何。通过扩大合作以快速处理和解释不断增长的组学数据量,将更快实现精准医学的前景。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验