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首页> 外文期刊>Functional & integrative genomics >Integrated analysis of transcription factors and targets co-expression profiles reveals reduced correlation between transcription factors and target genes in cancer
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Integrated analysis of transcription factors and targets co-expression profiles reveals reduced correlation between transcription factors and target genes in cancer

机译:转录因子的综合分析和靶标共表达谱揭示了癌症中转录因子和靶基因之间的相关性降低

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摘要

Transcription factors are recognized as the key regulators of gene expression. However, the changes in the correlation of transcription factors and their target genes between normal and tumor tissues are usually ignored. In this research, we used mRNA expression profile data from The Cancer Genome Atlas which included 5726 samples across 11 major human cancers to perform co-expression analysis by the Pearson correlation coefficients. Then, integrating 81,357 pairs of transcription factors and target genes from transcription factors databases to find out the changes in the co-expression correlation of these gene pairs from normal to tumor tissues. Based on the changes in the number of co-expressed TF-TG pairs and changes in the level of co-expression, we found the generally reduced correlation between transcription factors and their target genes in cancer. Additionally, we screened out universal and specific transcription factors-target genes pairs which may significant influence particular cancer. Then, we obtained 423 cancer cell line expression profiles from Broad Institute Cancer Cell Line Encyclopedia to verify our results. Some of these pairs like XRCC5-XRCC6 have been reported to involve in multiple cancers, while pairs like IRF1-PSMB9 without any previous articles related to tumor but involve in the biological processes of cancer, which are of great potential to be therapeutic targets. Our research may provide insights to better understand the tumor development mechanisms and find potential therapeutic targets.
机译:转录因子被认为是基因表达的关键调节因子。然而,通常忽略正常和肿瘤组织之间转录因子和其靶基因的相关性的变化。在本研究中,我们使用来自癌症基因组地图集的mRNA表达谱数据,其包括在11个主要人体癌症的5726个样品中,通过Pearson相关系数进行共表达分析。然后,从转录因子数据库中积分81,357对转录因子和靶基因,以从正常到肿瘤组织中找出这些基因对的共表达相关性的变化。基于共表达的TF-TG对数的变化和共表达水平的变化,我们发现转录因子与其癌症中的靶基因之间的相关性普遍降低。此外,我们筛选出普遍和特定的转录因子 - 靶基因对,这些靶基因对可能重大影响特定癌症。然后,我们获得了来自广泛研究所癌细胞系百科全书的423个癌细胞系表达谱来验证我们的结果。据报道,一些这些对XRCC5-XRCC6涉及多种癌症,而没有与肿瘤有关的任何先前与肿瘤有关的与癌症有关的与癌症有关的对的对,这是具有巨大的癌症的癌症。我们的研究可以提供更好地理解肿瘤发育机制并找到潜在的治疗目标的见解。

著录项

  • 来源
    《Functional & integrative genomics》 |2019年第1期|共14页
  • 作者单位

    South China Univ Technol Sch Biol &

    Biol Engn Guangzhou Higher Educ Mega Ctr 382 Zhonghuan Rd East Guangzhou 510006 Guangdong Peoples R China;

    South China Univ Technol Sch Biol &

    Biol Engn Guangzhou Higher Educ Mega Ctr 382 Zhonghuan Rd East Guangzhou 510006 Guangdong Peoples R China;

    South China Univ Technol Sch Biol &

    Biol Engn Guangzhou Higher Educ Mega Ctr 382 Zhonghuan Rd East Guangzhou 510006 Guangdong Peoples R China;

    South China Univ Technol Sch Biol &

    Biol Engn Guangzhou Higher Educ Mega Ctr 382 Zhonghuan Rd East Guangzhou 510006 Guangdong Peoples R China;

    Sun Yat Sen Univ Collaborat Innovat Ctr Canc Med State Key Lab Oncol South China Dept Lab Med Canc Ctr Guangzhou Guangdong Peoples R China;

    Sun Yat Sen Univ Collaborat Innovat Ctr Canc Med State Key Lab Oncol South China Dept Lab Med Canc Ctr Guangzhou Guangdong Peoples R China;

    South China Univ Technol Sch Biol &

    Biol Engn Guangzhou Higher Educ Mega Ctr 382 Zhonghuan Rd East Guangzhou 510006 Guangdong Peoples R China;

    South China Univ Technol Sch Biol &

    Biol Engn Guangzhou Higher Educ Mega Ctr 382 Zhonghuan Rd East Guangzhou 510006 Guangdong Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 基因工程(遗传工程);遗传学;
  • 关键词

    Co-expression; Integrative analysis; Transcription factor; Tumorigenesis; Therapeutic target;

    机译:共表达;综合分析;转录因子;肿瘤发生;治疗目标;

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