The Expression and Clinical Significance of MECOM in Ovarian Cancer: An Analysis Based on Database

doi:10.12280/gjfckx.20210375

Abstract

Abstract:

Objective：To explore the expression and its clinical significance of MECOM in ovarian cancer. Methods：The data about MECOM was collected from Oncomine and GEPIA databases; cBioportal, Coexpedia and STRING database were used to analyze the mutation, co-expression and interacting proteins of MECOM in ovarian cancer. Kaplan-Meier Plotter was used to analyze the relationship between the expression level of MECOM mRNA and the prognosis of patients with ovarian cancer. Results：With different types of cancer in Oncomine database, there were 353 studies related to MECOM, and 99 of them showed statistically significance (33 high-regulated and 99 low-regulated), including 10 studies on ovarian cancer, both show high MECOM expression. This result was also confirmed in the GEPIA database. Mutation analysis showed that 30% of ovarian cancer patients had mutations in MECOM gene, including missense mutation, fusion mutation and truncation mutation. Co-expression analysis showed that 275 genes were co-expressed. MECOM may interact with NR2E1, MTA1, HDAC1, TP53, PPARG, EZH2, JUN, MBD3, HDAC2 and CTBP1. The total survival rate of ovarian cancer patients in the group with high MECOM mRNA expression was lower than that with low MECOM mRNA expression (P=0.013). Conclusions：MECOM gene is overexpression in ovarian cancer, and its translated proteins interact with various proteins to exert biological effects. The expression level of MECOM mRNA is related to the survival prognosis of ovarian cancer patients, which is expected to provide a new idea for molecular targeted therapy of ovarian cancer.

Key words: Ovarian neoplasms, MECOM, Database, Genomics, Computational biology

LI Rong, LIU Yu, XU Gan-wei. The Expression and Clinical Significance of MECOM in Ovarian Cancer: An Analysis Based on Database[J]. Journal of International Obstetrics and Gynecology, 2022, 49(1): 43-48.

Figures/Tables 8

References 22

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基因	具体生物学过程	P值
GO：0030198	细胞外基质的调节	4.959×10^-14
GO：0007155	细胞黏附	7.319×10^-9
GO：0008284	细胞增殖的正调控	2.533×10^-6
GO：0030574	胶原蛋白分解代谢的过程	1.183×10^-5
GO：0014066	PI3K的调节	1.411×10^-5
GO：0050900	白细胞游走	2.650×10^-5
GO：0048015	磷脂酰肌醇介导的信号	4.560×10^-5
GO：0008543	成纤维细胞生长因子受体信号通路	1.062×10^-4
GO：0043552	PI3K活性的正调控	1.183×10^-4
GO：0043406	MAPK活性的正调控	1.293×10^-4

基因	具体生物学过程	P值
GO：0030198	细胞外基质的调节	4.959×10^-14
GO：0007155	细胞黏附	7.319×10^-9
GO：0008284	细胞增殖的正调控	2.533×10^-6
GO：0030574	胶原蛋白分解代谢的过程	1.183×10^-5
GO：0014066	PI3K的调节	1.411×10^-5
GO：0050900	白细胞游走	2.650×10^-5
GO：0048015	磷脂酰肌醇介导的信号	4.560×10^-5
GO：0008543	成纤维细胞生长因子受体信号通路	1.062×10^-4
GO：0043552	PI3K活性的正调控	1.183×10^-4
GO：0043406	MAPK活性的正调控	1.293×10^-4

通路	具体信号通路	蛋白数	匹配到的相关蛋白名称
hsa05200	肿瘤信号通路	6	CTBP1、HDAC1、HDAC2、JUN、 PPARG、TP53
hsa05202	肿瘤中的转录失调	4	HDAC1、HDAC2、PPARG、TP53
hsa05203	病毒致癌作用	4	HDAC1、HDAC2、JUN、TP53
hsa05220	慢性骨髓白血病	4	CTBP1、HDAC1、HDAC2、TP53
hsa05016	亨廷顿舞蹈病	4	HDAC1、HDAC2、PPARG、TP53
hsa05169	EB病毒感染	4	HDAC1、HDAC2、JUN、TP53
hsa05206	肿瘤中的小分子核糖核酸	4	EZH2、HDAC1、HDAC2、TP53
hsa04330	Notch信号通路	3	CTBP1、HDAC1、HDAC2
hsa04110	细胞周期	3	HDAC1、HDAC2、TP53
hsa04310	Wnt信号通路	3	CTBP1、JUN、TP53

通路	具体信号通路	蛋白数	匹配到的相关蛋白名称
hsa05200	肿瘤信号通路	6	CTBP1、HDAC1、HDAC2、JUN、 PPARG、TP53
hsa05202	肿瘤中的转录失调	4	HDAC1、HDAC2、PPARG、TP53
hsa05203	病毒致癌作用	4	HDAC1、HDAC2、JUN、TP53
hsa05220	慢性骨髓白血病	4	CTBP1、HDAC1、HDAC2、TP53
hsa05016	亨廷顿舞蹈病	4	HDAC1、HDAC2、PPARG、TP53
hsa05169	EB病毒感染	4	HDAC1、HDAC2、JUN、TP53
hsa05206	肿瘤中的小分子核糖核酸	4	EZH2、HDAC1、HDAC2、TP53
hsa04330	Notch信号通路	3	CTBP1、HDAC1、HDAC2
hsa04110	细胞周期	3	HDAC1、HDAC2、TP53
hsa04310	Wnt信号通路	3	CTBP1、JUN、TP53