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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/OL]. 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/OL]. 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
1
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018[J]. CA Cancer J Clin, 2018, 68(1):7-30.
2
Jayson GC, Kohn EC, Kitchener HC, et al. Ovarian cancer[J]. Lancet, 2014, 384(9951):1376-1388.
3
Torre LA, Trabert B, DeSantis CE, et al. Ovarian cancer statistics, 2018[J]. CA Cancer J Clin, 2018, 68(4):284-296.
4
Bonome T, Lee JY, Park DC, et al. Expression profiling of serous low malignant potential, low-grade, and high-grade tumors of the ovary[J]. Cancer Res, 2005, 65(22):10602-10612.
5
Earp M, Tyrer JP, Winham SJ, et al. Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility[J]. PLoS One, 2018, 13(7):e0197561.
6
Urban RR, Pappas TC, Bullock RG, et al. Bullock RG et al:combined symptom index and second-generation multivariate biomarker test for prediction of ovarian cancer in patients with an adnexal mass[J]. Gynecol Oncol, 2018, 150(2):318-323.
7
US Preventive Services Task Force, Grossman DC, Curry SJ, et al. Screening for Ovarian Cancer: US Preventive Services Task Force Recommendation Statement.[J]. JAMA, 2018, 319(6):588-594.
8
Gamwell LF, Collins O, Vanderhyden BC. The mouse ovarian surface epithelium contains a population of LY6A (SCA-1) expressing progenitor cells that are regulated by Ovulation-Associated factors[J]. Biol Reprod, 2012, 87(4):80.
9
Flesken-Nikitin A, Hwang CI, Cheng CY, et al. Ovarian surface epithelium at the junction area contains a cancer-prone stem cell niche[J]. Nature, 2013, 495(7440):241-245.
10
McCloskey CW, Goldberg RL, Carter LE, et al. A new spontaneously transformed syngeneic model of high-grade serous ovarian cancer with a tumor-initiating cell population[J]. Front Oncol, 2014, 4:53.
11
Roberts PC, Mottillo EP, Baxa AC, et al. Sequential molecular and cellular events during neoplastic progression: a mouse syngeneic ovarian cancer model[J]. Neoplasia, 2005, 7(10):944-956.
12
Franceschini A, Szklarczyk D, Frankild S, et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration [J]. Nucleic Acids Res, 2013, 41(Database issue):D808-D815.
13
Saito R, Smoot ME, Ono K, et al. A travel guide to Cytoscape plugins[J]. Nat Methods, 2012, 9(11):1069-1076.
14
Tomczak K, Czerwińska P, Wiznerowicz M. The cancer genome Atlas (TCGA): an immeasurable source of knowledge[J]. Contemp Oncol (Pozn), 2015, 19(1A):A68-A77.
15
Győrffy B, Surowiak P, Budczies J, et al. Online survival analysis software to assess the prognostic value of biomarkers using transcriptomic data in non-small-cell lung cancer[J]. PLoS One, 2013, 8(12):e82241.
16
Kurose K, Zhou XP, Araki T, et al. Frequent loss of PTEN expression is linked to elevated phosphorylated Akt levels, but not associated with p27 and cyclin D1 expression, in primary epithelial ovarian carcinomas[J]. Am J Pathol, 2001, 158(6):2097-2106.
17
Li H, Zeng J, Shen K. PI3K/AKT/mTOR signaling pathway as a therapeutic target for ovarian cancer[J]. Arch Gynecol Obstet, 2014, 290(6):1067-1078.
18
Rössig L, Jadidi AS, Urbich C, et al. Akt-dependent phosphorylation of p21(Cip1)regulates PCNA binding and proliferation of endothelial cells[J]. Mol Cell Biol, 2001, 21(16):5644-5657.
19
Roby KF, Taylor CC. Sweetwood JP, et al. Development of a syngeneic mouse model for events related to ovarian cancer[J]. Carcinogenesis, 2000, 21(4):585-591.
20
Roberts PC, Schmelz EM. In vitro model of spontaneous mouse OSE transformation[J]. Methods Mol Biol, 2013, 1049:393-408.
21
Ahmed N, Stenvers KL. Getting to know ovarian cancer ascites: opportunities for targeted therapy-based translational research[J]. Front Oncol, 2013, 3:256.
22
Ricci F, Broggini M, Damia G. Revisiting ovarian cancer preclinical models: Implications for a better management of the disease[J]. Cancer Treat Rev, 2013, 39(6):561-568.
23
Campbell IG, Russell SE. Choong DY, et al. Mutation of the PIK3CA gene in ovarian and breast cancer[J]. Cancer Res, 2004, 64(21):7678-7681.
24
Che YL, Luo SJ, Li G, et al. The C3G/Rap1 pathway promotes secretion of MMP-2 and MMP-9 and is involved in serous ovarian cancer metastasis[J]. Cancer Lett, 2015, 359(2):241-249.
25
Hanahan D, Weinberg RA. The hallmarks of cancer[J]. Cell, 2000, 100(1):57-70.
26
Evan GI, Vousden KH. Proliferation, cell cycle and apoptosis in cancer[J]. Nature, 2001, 411(6835):342-348.
27
Reddy BA, van der Knaap JA, Bot AG, et al. Nucleotide biosynthetic enzyme GMP synthase is a TRIM21-controlled relay of p53 stabilization[J]. Mol Cell, 2014, 53(3):458-470.
28
Holzer K, Drucker E, Roessler S, et al. Proteomic analysis reveals GMP synthetase as p53 repression target in liver cancer[J]. Am J Pathol, 2017, 187(2):228-235.
29
Jönsson JM, Skovbjerg Arildsen N, Malander S, et al. Sex Steroid Hormone Receptor Expression Affects Ovarian Cancer Survival[J]. Transl Oncol, 2015, 8(5):424-433.
30
Lee P, Rosen DG, Zhu C, et al. Expression of progesterone receptor is a favorable prognostic marker in ovarian cancer[J]. Gynecol Oncol, 2005, 96(3):671-677.
31
Lenhard M, Tereza L, Heublein S, et al. Steroid hormone receptor expression in ovarian cancer: progesterone receptor B as prognostic marker for patient survival[J]. BMC Cancer, 2012, 12:553.
32
Sieh W, Köbel M, Longacre TA, et al. Hormone-receptor expression and ovarian cancer survival: an Ovarian Tumor Tissue Analysis consortium study[J]. Lancet Oncol, 2013, 14(9):853-862.
33
Feng Z, Wen H, Bi R, et al. A clinically applicable molecular classification for high-grade serous ovarian cancer based on hormone receptor expression[J]. Sci Rep, 2016, 6:25408.
34
Tangjitgamol S, Manusirivithaya S, Khunnarong J, et al. Expressions of estrogen and progesterone receptors in epithelial ovarian cancer: a clinicopathologic study[J]. Int J Gynecol Cancer, 2009, 19(4):620-627.
35
van Kruchten M, van der Marel P, de Munck L, et al. Hormone receptors as a marker of poor survival in epithelial ovarian cancer[J]. Gynecol Oncol, 2015, 138(3):634-639.
36
Wong KK, Lu KH, Malpica A, et al. Significantly greater expression of ER, PR, and ECAD in advanced-stage low-grade ovarian serous carcinoma as revealed by immunohistochemical analysis[J]. Int J Gynecol Pathol, 2007, 26(4):404-409.
37
Grewal IS, Flavell RA. CD40 and CD154 in cell-mediated immunity[J]. Annu Rev Immunol, 1998, 16:111-135.
38
Van Kooten C, Banchereau J. CD40-CD40 ligand[J]. J Leukoc Biol, 2000, 67(1):2-17.
39
Qin L, Qiu H, Zhang M, et al. Soluble CD40 ligands sensitize the epithelial ovarian cancer cells to cisplatin treatment[J]. Biomed Pharmacother, 2016, 79:166-175.
40
Zhou Y, He J. Gou LT, et al. Expression of CD40 and growth-inhibitory activity of CD40 agonist in ovarian carcinoma cells[J]. Cancer Immunol Immunother, 2012, 61(10):1735-1743.
41
Xiong Y, Gj H. Zhang H, et al. p21 is a universal inhibitor of cyclin kinases[J]. Nature, 1993, 366(6456):701-704.
42
Alves MR, E Melo NC, Barros-Filho MC, et al: Downregulation of AGR2, p21, and cyclin D and alterations in p53 function were associated with tumor progression and chemotherapy resistance in epithelial ovarian carcinoma[J]. Cancer Med. 2018. doi: 10.1002/cam4.1530.
43
Shang D, Wu Y. Ding Y, et al. Identification of a pyridine derivative inducing senescence in ovarian cancer cell lines via P21 activation[J]. Clin Exp Pharmacol Physiol, 2018, 45(5):452-460.
44
Cheng X, Xia W. Yang JY, et al. Activation of p21(CIP1/WAF1)in mammary epithelium accelerates mammary tumorigenesis and promotes lung metastasis[J]. Biochem Biophys Res Commun, 2010, 403(1):103-107.
45
Hawthorne VS, Huang WC. Neal CL, et al. ErbB2-mediated Src and signal transducer and activator of transcription 3 activation leads to transcriptional up-regulation of p21Cip1 and chemoresistance in breast cancer cells[J]. Mol Cancer Res, 2009, 7(4):592-600.
46
Liu X, Yu H. Cai H, et al. Expression of CD24, p21, p53, and c-myc in alpha-fetoprotein-producing gastric cancer:correlation with clinicopathologic characteristics and survival[J]. J Surg Oncol, 2014, 109(8):859-864.
47
Taghavi N, Biramijamal F, Sotoudeh M, et al. Association of p53/p21 expression with cigarette smoking and prognosis in esophageal squamous cell carcinoma patients[J]. World J Gastroenterol, 2010, 16(39):4958-4967.
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