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作者:

Liu, Bo (Liu, Bo.) (学者:刘博) | Li, Xingrui (Li, Xingrui.) | Wang, Huina (Wang, Huina.) | Zhao, Shuangtao (Zhao, Shuangtao.) | Li, Jianqiang (Li, Jianqiang.) (学者:李建强) | Qu, Guangzhi (Qu, Guangzhi.) | Wang, Fei (Wang, Fei.)

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SCIE

摘要:

Triple-negative breast cancer is the worst prognosis in breast cancer, accounting for 10.0-20.8% of all breast cancers. Considering that triple-negative breast cancer has great heterogeneity and very poor prognosis, clinical medication guidance is in urgent need of a more detailed classification of breast cancer itself. Although many researchers have been dedicated to the clustering of triple-negative breast cancer and have found possible targets based on typing, their results are not closely related to the prognosis. This paper utilizes three clustering methods to retype the patient data with triple-negative breast cancer, and the results show that the triple-negative breast cancer data could be classified into two categories. Eight important genes and three important clinical factors related to the prognosis of two types of triple-negative breast cancer have been obtained. These genes have the following three characteristics: co-expression, differential expression and interaction. In terms of breast cancer control, the prognosis can be controlled as much as possible by regulating gene levels, which provides new directions and ideas for related research on breast cancer prognosis.

关键词:

clustering gene selection retyping triple-negative breast cancer

作者机构:

  • [ 1 ] [Liu, Bo]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China
  • [ 2 ] [Li, Xingrui]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China
  • [ 3 ] [Wang, Huina]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China
  • [ 4 ] [Li, Jianqiang]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China
  • [ 5 ] [Zhao, Shuangtao]Univ Texas MD Anderson Canc Ctr, Dept Gen Med, Houston, TX 77054 USA
  • [ 6 ] [Qu, Guangzhi]Oakland Univ, Dept Comp Sci & Engn, Rochester, MI 48309 USA
  • [ 7 ] [Wang, Fei]Weill Cornell Med Coll, Healthcare Policy & Res, New York, NY USA

通讯作者信息:

  • [Zhao, Shuangtao]Univ Texas MD Anderson Canc Ctr, Dept Gen Med, Houston, TX 77054 USA

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来源 :

EXPERT SYSTEMS

ISSN: 0266-4720

年份: 2020

3 . 3 0 0

JCR@2022

ESI学科: COMPUTER SCIENCE;

ESI高被引阀值:34

JCR分区:2

被引次数:

WoS核心集被引频次: 2

SCOPUS被引频次: 1

ESI高被引论文在榜: 0 展开所有

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