生物技术进展 ›› 2020, Vol. 10 ›› Issue (4): 417-425.DOI: 10.19586/j.2095-2341.2020.0019

• 研究论文 • 上一篇    下一篇

基于生物信息学分析SCHIP1在急性髓系白血病中的表达及其临床意义

许杰,王可飞,魏晓晶,龚莉欣,焦阳,邱录贵,郝牧*   

  1. 北京协和医学院, 中国医学科学院血液病医院(中国医学科学院血液学研究所), 实验血液学国家重点实验室, 国家血液病临床医学研究中心, 天津 300020
  • 收稿日期:2020-02-26 出版日期:2020-07-25 发布日期:2020-05-11
  • 通讯作者: 郝牧 E-mail: haomu@ihcams.ac.cn
  • 作者简介:许杰 E-mail:xujie@ihcams.ac.cn
  • 基金资助:
    国家自然科学基金项目(81570181;81630007);天津市自然科学基金项目(17JCYBJC27900);中国医学科学院医学与健康科技创新工程项目(CAMS-2017-I2M-1-005;CAMS-2016-I2M-3-013);中国医学科学院中央公益性科研院所基本科研业务费2018年青年医学人才奖励项目(2018RC320012)。

Expression and Prognostic Significance of SCHIP1 in Acute Myeloid Leukemia: Analysis Based on  Bioinformatics

XU Jie, WANG Kefei, WEI Xiaojing, GONG Lixin, JIAO Yang, QIU Lugui, HAO Mu   

  1. State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Tianjin 300020, China
  • Received:2020-02-26 Online:2020-07-25 Published:2020-05-11

摘要: 通过数据挖掘和生物信息学分析手段,探讨施旺膜蛋白相互作用因子1(schwannomin interacting protein 1,SCHIP1)基因在急性髓系白血病患者中的表达情况及其临床意义。首先,对Oncomine数据库中收录的所有急性髓系白血病(acute myloid leukaemia,AML)数据集进行荟萃分析,筛选出目标基因SCHIP1并进一步分析其在AML病人中的表达变化。随后,从GEO数据库中下载含生存信息的AML数据集源文件,分析SCHIP1表达对疾病的预后作用。另外,利用TCGA数据库对SCHIP1的表达情况进行亚组分析及与FLT3基因突变、PML/RARα融合基因和RAS活化等高危因素进行相关性分析。最后,利用GEPIA2工具验证SCHIP1的表达情况、预后意义及与FLT3、PML基因表达的相关性。结果发现Oncomine数据库中收录了44个AML数据集,总计共3 534个样本数据。其中5个数据集共1 188个样本包含“Cancer vs. Normal”的mRNA表达数据,对其进行荟萃分析显示SCHIP1位于显著高表达分子的第17位。生存分析显示,SCHIP1表达量与AML患者总体生存率呈负相关。亚组分析显示SCHIP1在M0/M1/M2中较M3/M6中表达更高,但与年龄、性别和种族无关。另外,相关性研究分析显示SCHIP1与FLT3基因突变弱相关,但与PML/RARα融合基因和RAS活化等高危因素无显著相关性。这些结果表明SCHIP1在急性髓系白血病中高表达,且其高表达与患者的生存预后呈显著负相关。因此,SCHIP1可作为疾病的预后生物标志物,并有望成为AML的精准治疗靶点。

关键词: 急性髓系白血病, SCHIP1, 生物信息学分析

Abstract: The study was aimed to  investigate the expression and clinical significance of schwannomin interacting protein 1 (SCHIP1) in patients with acute myeloid leukemia through data mining and bioinformatics analysis. First of all, a meta-analysis was performed on all AML data sets including  the Oncomine database,  which aimed to screen the target gene SCHIP1 and further analyze its expression changes in AML patients. Then, AML dataset source files containing survival information were downloaded from GEO database to analyze the prognostic effect of SCHIP1 on disease. And the expression of SCHIP1 among subgroup and the correlation with FLT3 gene mutation, PML/RARα fusion and RAS activation were analyzed using TCGA database. Ultimately, GEPIA2 was used to verify the expression and prognostic significance of SCHIP1 and its correlation with FLT3 and PML gene expression. Results showed that 44 AML datasets were included in Oncomine database, with a total of 3 534 sample data. And a total of 1 188 samples from 5 datasets contained mRNA expression data of "Cancer vs. Normal", and a meta-analysis of these samples showed that SCHIP1 was the 17th most highly expressed molecule. Then, survival analysis showed a negative correlation between SCHIP1 expression and overall survival in AML patients. And subgroup analysis showed that the expression of SCHIP1 in M0/M1/M2 was higher than that in M3/M6, regardless of age, gender or race. In addition, correlation analysis showed a weak correlation between SCHIP1 and FLT3 gene mutation, but no significant correlation with PML/RARα fusion, RAS activation and other risk factors. These results showed that SCHIP1 is highly expressed in acute myeloid leukemia (AML), and its high expression is significantly negatively correlated with overall survival of patients.Therefore, it can be used as a prognostic biomarker for the disease, and it is expected to become a precise therapeutic target for AML.

Key words: acute myeloid leukemia, SCHIP1, bioinformatics analysis