上海交通大学学报（医学版）

上海交通大学学报（医学版） ›› 2018, Vol. 38 ›› Issue (9): 1027-.doi: 10.3969/j.issn.1674-8115.2018.09.005

• 论著·基础研究 • 上一篇    下一篇

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   

  1. 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
  • 出版日期:2018-09-28 发布日期:2018-10-15
  • 作者简介:严天奇（1993—），男，硕士生，电子信箱：tianqi_yan@sjtu.edu.cn。
  • 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   

  1. 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:2018-09-28 Published:2018-10-15
  • Supported by:
    National Natural Science Foundation of China, 81570122, 81770205; Shanghai Municipal Education Commission—Gaofeng Clinical Medicine Support, 20161303

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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。

关键词: 急性淋巴细胞白血病, 基因融合, 基因突变, 知识库

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.

Key words: acute lymphoblastic leukemia, gene fusion, gene mutation, knowledge database

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