论著·基础研究

急性淋巴细胞白血病基因融合与突变知识库的构建

  • 严天奇 1 ,
  • 陈立伟 2 ,
  • 朱勇梅 2 ,
  • 李剑峰 2 ,
  • 代雨婷 2 ,
  • 3 ,
  • 崔舒雅 2 ,
  • 姜璐 2 ,
  • 陈冰 2 ,
  • 黄金艳 2
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  • 1. 上海交通大学系统生物医学研究院,系统生物医学教育部重点实验室,上海 200240;2.上海交通大学医学院附属瑞金医院,上海血液学研究所,医学基因组学国家重点实验室,上海 200025;3.上海交通大学生命科学技术学院,上海 200240
严天奇(1993—),男,硕士生,电子信箱:tianqi_yan@sjtu.edu.cn。

网络出版日期: 2018-10-15

基金资助

国家自然科学基金( 81570122,81770205);上海市教育委员会高峰高原学科建设计划( 20161303)

Construction of a knowledge database of gene fusion and mutation in acute lymphoblastic leukemia

  • YAN Tian-qi1 ,
  • CHEN Li-wei2 ,
  • ZHU Yong-mei2 ,
  • LI Jian-feng2 ,
  • DAI Yu-ting2 ,
  • 3 ,
  • CUI Shu-Ya2 ,
  • JIANG Lu2 ,
  • CHEN Bing2 ,
  • HUANG Jin-yan2
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  • 1. Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China; 2. State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; 3. School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China

Online published: 2018-10-15

Supported by

National Natural Science Foundation of China, 81570122, 81770205; Shanghai Municipal Education Commission—Gaofeng Clinical Medicine Support, 20161303

摘要

目的 ·建立急性淋巴细胞白血病( acute lymphoblastic leukemia,ALL)基因融合与突变知识库,以辅助临床基因检测。方法 ·通过对文献进行文本挖掘,收集 ALL相关的基因融合与突变注释信息。基于 NodeJS平台的 Express框架和 MySQL数据库系统的服务端开发环境,构建知识库服务网站。结果 ·通过对文献进行文本挖掘和人工手动矫正,共收集了 246条 ALL相关融合和突变基因词条,每项词条包含生物学性状、临床相关性解释、临床指导意见、靶向药物和化疗药物等多个生物学和临床相关条目,建立起一个便于管理的 ALL相关知识库。结论 ·该知识库除了包含 ALL相关或潜在相关癌症基因基本信息外,还着重整理了临床相关的注释信息,为 ALL的临床基因检测及后续的精准医疗提供参考。

本文引用格式

严天奇 1 , 陈立伟 2 , 朱勇梅 2 , 李剑峰 2 , 代雨婷 2 , 3 , 崔舒雅 2 , 姜璐 2 , 陈冰 2 , 黄金艳 2 . 急性淋巴细胞白血病基因融合与突变知识库的构建[J]. 上海交通大学学报(医学版), 2018 , 38(9) : 1027 . DOI: 10.3969/j.issn.1674-8115.2018.09.005

Abstract

Objective · To construct a database of fusion and mutation gene annotations for acute lymphoblastic leukemia (ALL) to assist genetic testing. Methods · ALL related gene annotations were collectedmining medical literature. The web server of the database was constructed based on Express framework, a NodeJS web application framework, and MySQL as the server-side development environment. Results · A total of 246 ALL-associated fusion and mutation gene entries were collected through programmed and manual text mining, including biological characteristics, clinical characteristics, clinical directions, target drugs and chemotherapeutic drugs. A web server of the ALL related gene knowledge database was established for convenient data management. Conclusion · In addition to the basic information about ALL related or potentially related genes, the database also involves clinical information which can be a reference tool for precision medicine of ALL.
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