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Integration of protein interaction and gene co-expression information for identification of melanoma candidate genes  期刊论文  

  • 编号:
    c6617a13-16e2-4b9e-b6a5-8e817b236c15
  • 作者:
    Wu, Kejia#[1]Wang, Wen#[3]Ye, Yaqi[1];Huang, Junhong[1];Zhou, Yinghui[1];Zhang, Yue[1];Zhang, Xuewenjun[1];Wu, Wenyu(吴文育)*[1,2]
  • 语种:
    英文
  • 期刊:
    MELANOMA RESEARCH ISSN:0960-8931 2019 年 29 卷 2 期 (126 - 133) ; APR
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  • 关键词:
  • 摘要:

    Cutaneous melanoma is an aggressive form of skin cancer that causes death worldwide. Although much has been learned about the molecular basis of melanoma genesis and progression, there is also increasing appreciation for the continuing discovery of melanoma genes to improve the genetic understanding of this malignancy. In the present study, melanoma candidate genes were identified by analysis of the common network from cancer type-specific RNA-Seq co-expression data and protein-protein interaction profiles. Then, an integrated network containing the known melanoma-related genes represented as seed genes and the putative genes represented as linker genes was generated using the subnetwork extraction algorithm. According to the network topology property of the putative genes, we selected seven key genes (CREB1, XPO1, SP3, TNFRSF1B, CD40LG, UBR1, and ZNF484) as candidate genes of melanoma. Subsequent analysis showed that six of these genes are melanoma-associated genes and one (ZNF484) is a cancer-associated gene on the basis of the existing literature. A signature comprising these seven key genes was developed and an overall survival analysis of 461 cutaneous melanoma cases was carried out. This seven-gene signature can accurately determine the risk profile for cutaneous melanoma tumors (log-rank P=3.27E-05) and be validated on an independent clinical cohort (log-rank P=0.028). The presented seven genes might serve as candidates for studying the molecular mechanisms and help improve the prognostic risk assessment, which have clinical implications for melanoma patients. Copyright (c) 2018 Wolters Kluwer Health, Inc. All rights reserved.

  • 推荐引用方式
    GB/T 7714:
    Wu Kejia,Wang Wen,Ye Yaqi, et al. Integration of protein interaction and gene co-expression information for identification of melanoma candidate genes [J].MELANOMA RESEARCH,2019,29(2):126-133.
  • APA:
    Wu Kejia,Wang Wen,Ye Yaqi,Huang Junhong,&Wu Wenyu.(2019).Integration of protein interaction and gene co-expression information for identification of melanoma candidate genes .MELANOMA RESEARCH,29(2):126-133.
  • MLA:
    Wu Kejia, et al. "Integration of protein interaction and gene co-expression information for identification of melanoma candidate genes" .MELANOMA RESEARCH 29,2(2019):126-133.
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