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中华细胞与干细胞杂志(电子版) ›› 2019, Vol. 09 ›› Issue (02) : 92 -101. doi: 10.3877/cma.j.issn.2095-1221.2019.02.005

论著

GMPS,PR,CD40和p21对卵巢癌预后的预测价值(Prognostic values of GMPS, PR CD40, and p21 in ovarian cancer全译)
王萍1, 张增利2, 马予洁1, 路君1, 赵虎1, 王水良1, 谭建明1,(), 李冰燕2   
  1. 1. 350025 福州,联勤保障部队第九OO医院泌尿外科 福建省移植生物学重点实验室
    2. 215123 苏州大学公共卫生学院营养与食品学教研室
  • 收稿日期:2019-01-23 出版日期:2019-04-01
  • 通信作者: 谭建明
  • 基金资助:
    国家自然科学基金(NSFC81703225); 福建省自然科学基金(2017J01221)

Prognostic values of GMPS, PR, CD40, and p21 in ovarian cancer

Ping Wang1, Zengli Zhang2, Yujie Ma1, Jun Lu1, Hu Zhao1, Shuiliang Wang1, Jianming Tan1,(), Bingyan Li2   

  1. 1. Department of Urology, 900 Hospital of Joint Logistic Team, Fujian Key Laboratory of Transplant Biology, Fuzhou 350025, China
    2. Department of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou 215123, China
  • Received:2019-01-23 Published:2019-04-01
  • Corresponding author: Jianming Tan
引用本文:

王萍, 张增利, 马予洁, 路君, 赵虎, 王水良, 谭建明, 李冰燕. GMPS,PR,CD40和p21对卵巢癌预后的预测价值(Prognostic values of GMPS, PR CD40, and p21 in ovarian cancer全译)[J]. 中华细胞与干细胞杂志(电子版), 2019, 09(02): 92-101.

Ping Wang, Zengli Zhang, Yujie Ma, Jun Lu, Hu Zhao, Shuiliang Wang, Jianming Tan, Bingyan Li. Prognostic values of GMPS, PR, CD40, and p21 in ovarian cancer[J]. Chinese Journal of Cell and Stem Cell(Electronic Edition), 2019, 09(02): 92-101.

目的

通过一个卵巢癌自发恶性转化模型来识别卵巢癌患者的预后标志物。

方法

小鼠卵巢表面上皮细胞(MOSECs)在体外培养可以发生自发恶性转化。使用Illumina HiSeq 2000新一代测序平台和生物信息学分析检测在此模型转化过程中的基因表达和信号传导的改变。使用基因表达互作谱分析(http://gepia.cancer-pku.cn/)识别4个差异表达的核心基因,随后使用TCGA数据库与Kaplan-Meier Plotter在线数据库(www.kmplot.com)研究这些核心基因与卵巢癌患者生存期之间的关系。

结果

数据显示在MOSECs自发恶性转化的初期与晚期差异表达的基因共计263个,其中包括182个上调与81个下调基因。生物信息学数据揭示有4个基因(GMPS、PR、CD40、p21)在卵巢癌发生过程中扮演者重要的角色。此外,使用TCGA数据验证了这4个基因的差异表达及其与卵巢癌患者的预后相关。

结论

本研究使用卵巢癌进展模型分析差异表达的基因,并鉴定出四种(即GMPS、PR、CD40和p21)基因可以作为卵巢癌患者的预后标志物。未来需要前瞻临床研究来进一步验证这四种基因的特征及其临床实用性。

Objective

This study profiled an ovarian cancer progression model to identify prognostic biomarkers for ovarian cancer patients.

Methods

Mouse ovarian surface epithelial cells (MOSECs) underwent spontaneous malignant transformation in vitro cell culture, which were used as a model of ovarian cancer progression for alterations in gene expression and signaling detected using the Illumina HiSeq2000 Next-Generation Sequencing platform and bioinformatical analyses. The differential expression of four selected genes was identified using the gene expression profiling interaction analysis (http://gepia.cancer-pku.cn/) and then associated with survival in ovarian cancer patients using the Cancer Genome Atlas dataset and the online Kaplan-Meier Plotter (www.kmplot.com) data.

Results

The data showed 263 aberrantly expressed genes, including 182 up-regulated and 81 down-regulated genes between the early and late stages of tumor progression in MOSECs. The bioinformatic data revealed that four genes [i.e., guanosine 5'-monophosphate synthase (GMPS), progesterone receptor (PR), CD40, and p21 (cyclin-dependent kinase inhibitor 1A) ] played an important role in ovarian cancer progression. Furthermore, the Cancer Genome Atlas dataset validated the differential expression of these four genes, which were associated with prognosis in ovarian cancer patients.

Conclusion

This study profiled differentially expressed genes using the ovarian cancer progression model and identified four (i.e., GMPS, PR, CD40, and p21) as prognostic markers for ovarian cancer patients. Future studies of prospective patients could further verify the clinical usefulness of this four-gene signature.

图1 MOSE-I和MOSE-II细胞的特征注:a、b图为细胞MOSE-I(第20代)和MOSEC-II(第90代)体外培养,并在明场倒置显微镜下以20倍的放大率拍照。d、f图为软琼脂克隆形成试验将MOSE-I和MOSEC-II在软琼脂中培养14 d并拍照(×20)。h、i图为平板克隆形成试验,使MOSE-I和MOSEC-II生长14 d,用结晶紫溶液染色并拍照。c、f上的数据由Image J软件生成,而i上的数据来自EVOS XL成像系统,通过Student's t检验分析分析组间差异性。***P < 0.0001
表1 MOSE-I和MOSE-II细胞之间的差异表达基因
图2 使用火山图表示所有差异表达基因(DEGs)注:X轴表示倍数变化(logs值),而Y轴表示P值(logs值)。每个原点代表不同的基因,红色(绿色)显示处于不同标准(P值和倍数变化阈值)的上调或下调基因。以P < 0.05为差异有统计学意义,而4倍变化被设定为阈值
表2 在所有差异基因中,点度中心值大于5的核心基因
图3 DEGs形成的中枢基因的功能和通路富集分析注:a图为KEGG通路分析富集了DEGs形成的中枢基因参与的信号通路。b图为DEGs的GO分析揭示基因所参与得生物过程。c图为DEGs的GO术语分析基因所参与的细胞成分。d图为DEGs的GO术语揭示所参与的分子功能
图4 差异表达基因形成的蛋白质-蛋白质相互作用网络注:红色和绿色圆圈分别代表上调和下调基因。该节点代表它们在蛋白质之间的关系中的作用的基因和边缘。节点的颜色深浅表示节点的中介中心性,中介中心性值越高其节点的颜色越深,否则越浅。而节点大小与点度中心性成比例,其值越大,节点直径越大。连接两节点的线越粗,两种蛋白质之间的连接越紧密
图5 前四个核心基因的鉴定与卵巢癌患者的存活率的关联性注:a图为Oncoprint分析,以确定四个基因改变最显著的核心基因。cBioPortal分析核心基因改变的比例和分布。红色表示基因扩增,而蓝色表示基因缺失和粉红色基因上调。b图为通过改变这四种基因的表达分析其与卵巢癌总生存期(OS)的Kaplan-Meier曲线。c图为通过改变这四种基因的表达分析与卵巢癌的无病生存(DFS)的Kaplan-Meier曲线。所有原始数据均来自TCGA与GEO数据库
图6 GMPS,PR,CD40和p21在卵巢癌和正常组织之间的差异表达以及与卵巢癌患者的无复发存活率的关系注:a ~ d图为通过改变这四种基因的表达分层绘制无复发生存期(RFS)的Kaplan-Meier曲线。e ~ h图为卵巢癌和正常组织之间GMPS,PR,CD40和p21的差异表达
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