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卵巢癌多药耐药相关基因的生物信息学分析

陈昌贤, 胡艳玲, 李力

陈昌贤, 胡艳玲, 李力. 卵巢癌多药耐药相关基因的生物信息学分析[J]. 肿瘤防治研究, 2016, 43(6): 492-496. DOI: 10.3971/j.issn.1000-8578.2016.06.012
引用本文: 陈昌贤, 胡艳玲, 李力. 卵巢癌多药耐药相关基因的生物信息学分析[J]. 肿瘤防治研究, 2016, 43(6): 492-496. DOI: 10.3971/j.issn.1000-8578.2016.06.012
CHEN Changxian, HU Yanling, LI Li. Bioinformatics Analysis of Genes Related to Multidrug Resistance in Ovarian Cancer[J]. Cancer Research on Prevention and Treatment, 2016, 43(6): 492-496. DOI: 10.3971/j.issn.1000-8578.2016.06.012
Citation: CHEN Changxian, HU Yanling, LI Li. Bioinformatics Analysis of Genes Related to Multidrug Resistance in Ovarian Cancer[J]. Cancer Research on Prevention and Treatment, 2016, 43(6): 492-496. DOI: 10.3971/j.issn.1000-8578.2016.06.012

卵巢癌多药耐药相关基因的生物信息学分析

详细信息
    作者简介:

    陈昌贤(1988-),男,硕士,住院医师,主要从事妇科肿瘤临床与基础研究

    通讯作者:

    李力, E-mail:lili@gxmu.edu.cn.

  • 中图分类号: R737.31

Bioinformatics Analysis of Genes Related to Multidrug Resistance in Ovarian Cancer

More Information
  • 摘要:
    目的 

    筛选与挖掘卵巢癌多药耐药相关基因及其生物信息。

    方法 

    基于GSE41499、GSE33482、GSE15372和GSE28739等4套来源不同的卵巢癌化疗耐药与敏感基因芯片表达谱数据集,综合运用差异基因表达分析、基因通路富集分析和文本挖掘等生物信息学方法预测卵巢癌多药耐药相关基因及通路。

    结果 

    MAPK信号通路、泛素介导的蛋白质水解、轴突导向、焦点粘连、神经营养素信号通路、癌症通路、肾细胞癌、柠檬酸循环、类萜骨干生物合成、错配修复和亨廷顿氏舞蹈病等11条基因通路是出现频率相对较高的显著性上调通路(P<0.05),甘油脂、戊醣酸途径、果糖和甘露糖代谢、谷胱甘肽代谢、蛋白酶体、p53信号通路和溶酶体等7条基因通路是出现频率相对较高的显著性下调通路(P<0.05);进一步的文本挖掘发现,ACO1、BDNF、CXCR4、HMGCR和NRP1等5个上调表达基因(P<0.05)和CDKN2C、FAS和SKP2等3个下调表达基因(P<0.05)可能与卵巢癌多药耐药形成相关。

    结论 

    卵巢癌多药耐药机制的形成可能涉及到多种不同的通路和基因,其中ACO1、BDNF、CXCR4、HMGCR、NRP1、CDKN2C、FAS和SKP2等基因可能在其中发挥着关键作用,后续研究将对其进行实验和临床双重验证。

     

    Abstract:
    Objective 

    To screen and mine the genes related to multidrug resistance (MDR) in ovarian cancer(OC) and their biological information.

    Methods 

    Based on four different microarray expression profiles(GSE41499, GSE33482, GSE15372 and GSE28739) between resistant samples and sensitive samples relatedto OC, we performed a comprehensive bioinformatics analysis through gene expression analysis, geneticpathway enrichment analysis and text mining to predict the pathways and their genes related to MDR inOC.

    Results 

    Eleven significantly upregulated pathways were found frequently among four OC microarraydatasets, including MAPK signaling pathway, ubiquitin-mediated proteolysis, axon guidance, focal adhesion,neurotrophin signaling pathway, pathways in cancer, renal cell carcinoma, citrate cycle, terpenoid backbonebiosynthesis, mismatch repair and Huntington’s disease(P<0.05); and seven significantly downregulatedpathways were found frequently, including glycerolipid metabolism, pentose phosphate pathway, fructoseand mannose metabolism, glutathione metabolism, proteasome, p53 signaling pathway and lysosome(P<0.05). By further text mining methods, we found five significantly upregulated genes, including ACO1,BDNF, CXCR4, HMGCR and NRP1(P<0.05), as well as three significantly downregulated genes, includingCDKN2C, FAS and SKP2(P<0.05), might be associated with MDR in OC.

    Conclusion 

    OC MDR mightbe involved in various pathways and genes. ACO1, BDNF, CXCR4, HMGCR, NRP1, CDKN2C, FAS andSKP2 might play crucial roles in those pathways. Follow-up study would validate the roles of those genes inthe experiments and clinical practice.

     

  • 图  1   从文献水平上反映差异基因与一般性耐药、多药耐药和肿瘤耐药的关系图

    Figure  1   Co-occurrence analysis of differentially expressedgenes to exact keyword expression ‘drug resistance’, ‘drugresistance, multiple’ and ‘drug resistance, neoplasm’

    表  1   共同上调通路及其基因

    Table  1   Up-regulated pathways and their corresponding genes

    下载: 导出CSV

    表  2   共同下调通路及其基因

    Table  2   Down-regulated pathways and their corresponding genes

    下载: 导出CSV

    表  3   差异基因与卵巢癌的关系

    Table  3   Relationship between differentially expressed genes and ovarian cancer

    下载: 导出CSV
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出版历程
  • 收稿日期:  2015-07-19
  • 修回日期:  2015-09-22
  • 网络出版日期:  2024-02-04
  • 刊出日期:  2016-05-31

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