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结直肠癌发病相关关键lncRNA的筛选和鉴定:基于肿瘤基因图谱数据库的生物信息学分析

徐丞 刘占国 罗育其 张一方

徐丞, 刘占国, 罗育其, 张一方. 结直肠癌发病相关关键lncRNA的筛选和鉴定:基于肿瘤基因图谱数据库的生物信息学分析[J]. 分子影像学杂志, 2019, 42(1): 57-62. doi: 10.12122/j.issn.1674-4500.2019.01.14
引用本文: 徐丞, 刘占国, 罗育其, 张一方. 结直肠癌发病相关关键lncRNA的筛选和鉴定:基于肿瘤基因图谱数据库的生物信息学分析[J]. 分子影像学杂志, 2019, 42(1): 57-62. doi: 10.12122/j.issn.1674-4500.2019.01.14
Cheng XU, Zhanguo LIU, Yuqi LUO, Yifang ZHANG. Screening and identification of key lncRNA associate with carcinogenesis and development of CRC: a bioinformatic analysis of TCGA[J]. Journal of Molecular Imaging, 2019, 42(1): 57-62. doi: 10.12122/j.issn.1674-4500.2019.01.14
Citation: Cheng XU, Zhanguo LIU, Yuqi LUO, Yifang ZHANG. Screening and identification of key lncRNA associate with carcinogenesis and development of CRC: a bioinformatic analysis of TCGA[J]. Journal of Molecular Imaging, 2019, 42(1): 57-62. doi: 10.12122/j.issn.1674-4500.2019.01.14

结直肠癌发病相关关键lncRNA的筛选和鉴定:基于肿瘤基因图谱数据库的生物信息学分析

doi: 10.12122/j.issn.1674-4500.2019.01.14
基金项目: 广东省自然科学基金(2015A030310021);华南理工大学中央高校基本科研业务费专项基金(2018MS21)
详细信息
    作者简介:

    徐丞:徐 丞,主治医师,E-mail: 52696468@qq.com

    通讯作者:

    刘占国,教授,主任医师,E-mail: zhguoliu@163.com

Screening and identification of key lncRNA associate with carcinogenesis and development of CRC: a bioinformatic analysis of TCGA

  • 摘要: 目的 探讨长链非编码RNA(lncRNA)在结直肠癌(CRC)中的表达特征及其对患者生存预后判断的潜在价值。 方法 下载肿瘤基因图谱(TCGA)中CRC相关的RNA序列(RNA-seq)数据,进行lncRNA表达差异、功能、通路富集、调控网络及lncRNA-mRNA共表达分析,同时分析lncRNA差异表达对CRC患者预后的影响。 结果 对TCGA 453个CRC临床样本数据进行分析,提示有119个lncRNA存在差异性表达,lncRNA和编码基因存在共表达关系,对基因富集性分析发现,lncRNA参与细胞的多个生物学行为;16个lncRNA对患者生存预后显著相关,其中3个lncRNA BVES-AS1、HAND2-AS1和MAMDC2-AS1为关键lncRNA,可作为预后判断的标志物,同时与miRNA、coding gene存在紧密的调控网络。 结论 lncRNA在CRC中存在差异性表达,起着重要的调控作用,在CRC患者诊断、靶向治疗及预后判断方面具有潜在的应用价值。

     

  • 图  1  lncRNA-coding gene共表达网络

    红色代表显著差异表达上调,绿色代表显著差异表达下调,圆形表示coding gene,三角形表示lncRNA.

    图  2  lncRNA的GO功能富集结果(A)和KEGG pathway富集结果(B

    图  3  BVES-AS1 (A)、HAND2-AS1 (B)、MAMDC2-AS1 (C)的生存曲线及其与miRNA、coding gene的调控网络(D

    三角形为lncRNA,菱形为miRNA,圆形为coding gene.

    表  1  差异表达基因统计结果

    Item UP DOWN Total
    lncRNA 97 27 119
    Coding gene 504 352 856
    Total 601 379 975
    下载: 导出CSV

    表  2  与预后相关的lncRNA信息

    Gene name Ensembl ID Chromosomal Location log2FC FDR
    AC079612.1 ENSG00000196758 chr2:240499995-240507788 3.69 2.22E-17
    MAMDC2-AS1 ENSG00000204706 chr9:72648837-72790804 –3.63 2.69E-73
    LINC01555 ENSG00000180869 chr1:85093913-85100703 3.01 2.68E-17
    BVES-AS1 ENSG00000203808 chr6:105584183-105617820 –3.511 1.14E-41
    LINC00922 ENSG00000261742 chr16:65318402-65610203 3.15 2.25E-16
    WT1-AS ENSG00000183242 chr11:32457064-32480315 3.59 1.59E-08
    HOTAIR ENSG00000228630 chr12:54356092-54368740 4.16 1.87E-08
    RP11-353N14.4 ENSG00000262188 chr17:77893156-77899261 3.76 3.05E-28
    LL22NC03-N64E9. ENSG00000271127 chr22:16179617-16181004 3.54 2.40E-13
    PGM5-AS1 ENSG00000224958 chr9:70970105-70972768 –4.59 3.02E-43
    RP11-141J13.5 ENSG00000261863 chr17:4513744-4520945 4.7 8.91E-19
    AC006262.5 ENSG00000268621 chr19:46692423-46706340 6.88 1.54E-17
    HAND2-AS1 ENSG00000237125 chr4:174448421-174512475 –4.72 1.13E-55
    MIR31HG ENSG00000171889 chr9:21455641-21559668 3.3 4.31E-09
    RP11-10A14.5 ENSG00000248538 chr8:9046521-9060364 4.62 6.34E-18
    CTC-529P8.1 ENSG00000250072 chr5:148442880-148489350 3.32 1.29E-18
    下载: 导出CSV
  • [1] Tang RX, Chen WJ, He RQ, et al. Identification of a RNA-Seq based prognostic signature with five lncRNAs for lung squamous cell carcinoma[J]. Oncotarget, 2017, 8(31): 50761-73
    [2] Lun CY, Smyth GK. It's DE-licious:a recipe for dierential expres-sion analyses of RNA-seq experiments using quasi-likelihood methods in edgeR[J]. Methods Mol Biol, 2016, 1418(4): 391-416
    [3] Pohar M, Stare J. Relative survival analysis in R[J]. Comput Methods Programs Biomed, 2006, 81(3): 272-8 doi: 10.1016/j.cmpb.2006.01.004
    [4] Pearson K. Notes on regression and inheritance in the case of two parents[J]. Proceed Royal Society London, 1895, 19(58): 240-2
    [5] Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks[J]. Genome Res, 2003, 13(11): 2498-504 doi: 10.1101/gr.1239303
    [6] Yu G, Wang LG, Han Y, et al. clusterProfiler: an R package for comparing biological themes among gene clusters[J]. OMICS, 2012, 16(5): 284-7 doi: 10.1089/omi.2011.0118
    [7] Chen EY, Tan CM, Kou Y, et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool[J]. BMC Bioinformatics, 2013, 14(2): 128-34
    [8] Enright AJ, John B, Gaul U, et al. MicroRNA targets in Drosophila[J]. Genome Biol, 2003, 5(1): R1-8 doi: 10.1186/gb-2003-5-1-r1
    [9] Uziela K, Honkela A. Probe region expression estimation for RNA-Seq data for improved microarray comparability[J]. PLoS One, 2015, 10(5): e0126545-9 doi: 10.1371/journal.pone.0126545
    [10] Yang F, Lv SX, Lv L, et al. Identification of lncRNA FAM83H-AS1 as a novel prognostic marker in luminal subtype breast cancer[J]. Onco Targets Ther, 2016, 9(11): 7039-45
    [11] Kogo R, Shimamura T, Mimori K, et al. Long noncoding RNA HOTAIR regulates polycomb-dependent chromatin modification and is associated with poor prognosis in colorectal cancers[J]. Cancer Res, 2011, 71(20): 6320-6 doi: 10.1158/0008-5472.CAN-11-1021
    [12] Xi WD, Liu YJ, Sun XB, et al. Bioinformatics analysis of RNA-seq data revealed critical genes in colon adenocarcinoma[J]. Eur Rev Med Pharmacol Sci, 2017, 21(13): 3012-20
    [13] Lian Y, Yan C, Ding J, et al. A novel lncRNA, LL22NC03-N64E91, represses KLF2 transcription through binding with EZH2 in colorectal cancer[J]. Oncotarget, 2017, 8(35): 59435-45
    [14] Lee S, Midas PY. Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data[J]. Methods, 2017, 124(1): 13-24
    [15] Hong SJ, Chen XN, Jin L, et al. Canonical correlation analysis for RNA-seq co-expression networks[J]. Nucleic Acids Res, 2013, 41(8): e95-103 doi: 10.1093/nar/gkt145
    [16] Glover AR, Zhao JT, Ip JC, et al. Long noncoding RNA profiles of adrenocortical cancer can be used to predict recurrence[J]. Endocr Relat Cancer, 2015, 22(1): 99-109 doi: 10.1530/ERC-14-0457
    [17] Zhang W, Chang JW, Lin LL, et al. Network-Based isoform quantification with RNA-Seq data for cancer transcriptome analysis[J]. PLoS Comput Biol, 2015, 11(12): e1004465-73 doi: 10.1371/journal.pcbi.1004465
    [18] Lopes-Ramos C, Koyama FC, Habr-Gama AA, et al. Comprehensive evaluation of the effectiveness of gene expression signatures to predict complete response to neoadjuvant chemoradiotherapy and guide surgical intervention in rectal cancer[J]. Cancer Genet, 2015, 208(6): 319-26 doi: 10.1016/j.cancergen.2015.03.010
    [19] Li JW, Xue W, Lv JL, et al. Identification of potential long non-coding RNA biomarkers associated with the progression of colon cancer[J]. Oncotarget, 2017, 8(44): 75834-43
    [20] Hosseini ES, Meryet-Figuiere M, Sabzalipoor H, et al. Dysregulated expression of long noncoding RNAs in gynecologic cancers[J]. Mol Cancer, 2017, 16(1): 107-12 doi: 10.1186/s12943-017-0671-2
    [21] Zhang M, Liu Y, Yu B, et al. Over-expression of long non-coding RNA GAPLINC promotes colorectal cancer cell metastasis and poor prognosis[J]. Int J Clin Exp Med, 2016, 9(2): 3203-8
    [22] Hao LY, Fu JY, Tian YW, et al. Systematic analysis of lncRNAs, miRNAs and mRNAs for the identification of biomarkers for osteoporosis in the mandible of ovariectomized mice[J]. Int J Mol Med, 2017, 40(3): 689-702 doi: 10.3892/ijmm.2017.3062
    [23] Guo QY, Cheng Y, Liang T, et al. Comprehensive analysis of lncRNA-mRNA co-expression patterns identifies immune-associated lncRNA biomarkers in ovarian cancer malignant progression[J]. Sci Rep, 2015, 5(20): 17683-92
    [24] Zhu M, Chen Q, Liu X, et al. lncRNA H19/miR-675 axis represses prostate cancer metastasis by targeting TGFBI[J]. FEBS J, 2014, 281(16): 3766-75 doi: 10.1111/febs.2014.281.issue-16
    [25] Menges CW, Kadariya Y, Altomare DA, et al. Tumor suppressor alterations cooperate to drive aggressive mesotheliomas with enriched cancer stem cells via a p53-miR-34a-c-Met axis[J]. Cancer Res, 2014, 74(4): 1261-71 doi: 10.1158/0008-5472.CAN-13-2062
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出版历程
  • 收稿日期:  2018-10-22
  • 刊出日期:  2019-01-01

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