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中华临床医师杂志(电子版)

中华临床医师杂志(电子版) ›› 2022, Vol. 16 ›› Issue (02) : 112 -123. doi: 10.3877/cma.j.issn.1674-0785.2022.02.002

临床研究

运用生物信息学方法分析RAS通路中相关基因与宫颈癌转移之间关系的研究
黄巧巧1, 陈军莹1,†(), 黄锦冰1, 徐文生1, 陈二玲1   
  1. 1. 530021　南宁，广西医科大学第一附属医院妇产科
  • 收稿日期:2021-09-06 出版日期:2022-02-15
  • 通信作者: 陈军莹
  • 基金资助:
    国家自然科学基金地区项目(81860457); 中国博士后科学基金面上项目(2019M663411); 广西自然科学基金面上项目(2017GXNSFAA198106); 广西医疗卫生适宜技术开发与推广应用项目(S2018107)

Analysis of relationship between RAS pathway related genes and cervical cancer metastasis using bioinformatics methods

Qiaoqiao Huang1, Junying Chen1(), Jinbing Huang1, Wensheng Xu1, Erling Chen1   

  1. 1. Department of Obstetrics and Gynecology, the First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
  • Received:2021-09-06 Published:2022-02-15
  • Corresponding author: Junying Chen
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引用本文：

黄巧巧, 陈军莹, 黄锦冰, 徐文生, 陈二玲. 运用生物信息学方法分析RAS通路中相关基因与宫颈癌转移之间关系的研究[J]. 中华临床医师杂志(电子版), 2022, 16(02): 112-123.

Qiaoqiao Huang, Junying Chen, Jinbing Huang, Wensheng Xu, Erling Chen. Analysis of relationship between RAS pathway related genes and cervical cancer metastasis using bioinformatics methods[J]. Chinese Journal of Clinicians(Electronic Edition), 2022, 16(02): 112-123.

目的

探究与宫颈癌发展密切相关的信号通路关键分子，运用生物信息学方法来分析RAS蛋白信号通路与宫颈癌转移之间关系。

方法

分析受miR-3162-5p调控的信号通路，选出与宫颈癌发展相关的高分通路，运用Oncomine检索通路中的基因在宫颈癌中的表达情况，筛选出差异表达基因，利用STRING和Cytoscape构建了蛋白质-蛋白质相互作用网络（PPI）和模块分析。

结果

本研究运用生物信息学方法共筛选出了77个差异表达基因，包括31个高表达基因、42个低表达基因和4个有不同表达趋势的基因。从其中鉴定出24个关键基因，生存分析表明，非受体蛋白酪氨酸磷酸酶11型（PTPN11）、血管内皮生长因子A（VEGFA）、胰岛素样生长因子1（IGF1）、成纤维细胞生长因子受体2（FGFR2）、G蛋白亚单位γ7（GNG7）和原癌基因KIT配体（KITLG）可能参与宫颈癌的发生发展、侵袭或复发。免疫组织化学结果提示PTPN11在宫颈癌组织和宫颈非癌上皮中表达差异，差异具有统计学意义（P＜0.05）。

结论

本研究中发现的差异基因和关键基因有助于了解宫颈癌发生和发展的分子机制，并为宫颈癌的诊断和治疗提供候选靶点。

关键词: 宫颈鳞癌, RAS通路, 差异基因, 生存分析, 免疫组织化学法
Objective

To analyze the relationship between the Ras signaling pathway and cervical cancer metastasis using bioinformatics methods, in order to explore the key molecules of signal pathways closely related to the development of cervical cancer.

Methods

The signaling pathways regulated by miR-3162-5p were analyzed and high-scoring pathways related to the development of cervical cancer were selected. Oncomine was used to retrieve the expression of genes in the pathway in cervical cancer, and the differentially expressed genes were screened out. Protein-protein interaction network (PPI) and module analysis were constructed using STRING and Cytoscape.

Results

A total of 77 differentially expressed genes were screened by bioinformatics methods, including 31 highly expressed genes, 42 lowly expressed genes, and 4 genes with different expression trends. Among them, 24 key genes were identified. Survival analysis showed that protein tyrosine phosphatase non-receptor type 11 (PTPN11), vascular endothelial growth factor A (VEGFA), insulin like growth factor 1 (IGF1), fibroblast growth factor receptor 2 (FGFR2), G protein subunit gamma 7 (GNG7), and KIT ligand (KITLG) may be involved in the occurrence, development, invasion, and recurrence of cervical cancer. The results of immunohistochemistry suggested that PTPN11 was expressed differentially between cervical cancer tissue and cervical non-cancerous epithelium, and the difference was statistically significant (P＜0.05).

Conclusion

The differential genes and key genes identified in this study are helpful to understand the molecular mechanism of cervical cancer occurrence and development, and provide candidate targets for the diagnosis and treatment of this malignancy.

Key words: Cervical squamous cell carcinoma, RAS pathway, Differential genes, Survival analysis, Immunohistochemistry
表1 受miR-3162-5p调控的高分信号通路
顺序 通路 P值 基因数
1 粘蛋白型O-聚糖生物合成（hsa00512） 2.106410x10-8 6
2 脂肪酸链延伸（hsa00062） 0.001115 4
3 吗啡成瘾（hsa05032） 0.001223 12
4 GABA能突触（hsa04727） 0.002484 13
5 尼古丁成瘾（hsa05033） 0.008949 10
6 细胞因子-细胞因子受体相互作用（hsa04060） 0.010831 28
7 TGF-β信号通路（hsa04350） 0.022676 13
8 Ras信号通路（hsa04014） 0.025450 34
9 苯丙胺成瘾（hsa05031） 0.031152 12
10 脂肪酸代谢（hsa01212） 0.040433 6
表2 通过Oncomine数据库筛选出的差异基因
表达 基因
高表达差异基因（31个） PDGFA，VEGFA，EFNA，IGF1R，MET，PTPN11，GNB1，GNB4，GNB5，GNG5，CALML4，MRAS，RRAS2，NF1，PAK2，PIK3CA，AKT1，AKT3，IKBKG，IKBKA，MAP2K1，MAPK1，ETS2，BRAP，RAP1B，MAPK9，TBK1，CDC42，PLCE，ABL2，RAB5C
低表达差异基因（42个） TGFA，FGF1，FGF2，FGF7，FGF22，BDNF，NTF3，IGF1，IGF2，PDGFC，PDGFD，KITLG，ANGPT2，FGFR1，FGFR2，NTRK2，PDGFRB，KIT，FLT1，TEK，EPHA2，GAB1，GAB2，SHC2，SHC3，GNG7，GNG11，GRIN1，GRIN2B，CALML3，CALML5，RASAL1，RASAL2，PIK3R1，PLA2G3，PLA2G1B，cPLA2-beta，KSR1，RALB，MAPK10，PRKCB，RAB5A
既存在高表达趋势又存在低表达趋势差异基因（4个） RASGRF1，RAC2，PLD1，PRKCA
图1 用Cytoscape可视化软件构建的PPI网络图注：红色标记为高表达基因；蓝色标记为低表达基因；粉色标记为不同的表达趋势；节点越大，表示基因在网络中与其他基因相关的可信度越高
图2 用Cytoscape可视化软件构建的24个关键基因的网络图注：红色标记为高表达基因；蓝色标记为低表达基因；节点越大，表示基因在网络中与其他基因相关的可信度越高
表3 关键基因GO分析和KEGG通路富集结果
条目 描述 基因数目 率值
GO：0007169 跨膜受体蛋白酪氨酸激酶信号通路 15 8.42E-17
GO：0007167 酶联受体蛋白信号通路 16 5.02E-16
GO：0030334 细胞迁移调控 11 1.08E-10
GO：0007166 细胞表面受体连接的信号转导 20 2.93E-10
GO：0040012 运动调节 11 3.91E-10
GO：0051270 细胞运动调节 11 4.12E-10
GO：0008284 正向调控细胞增殖 13 8.80E-10
GO：0030335 细胞迁移的正向调控 9 1.76E-09
GO：0051272 对细胞运动的正向调节 9 3.89E-09
GO：0040017 运动的正向调节 9 3.89E-09
GO：0007243 蛋白激酶级联反应 12 8.53E-09
GO：0016310 磷酸化 14 9.92E-08
GO：0007242 细胞内信号级联 16 1.11E-07
GO：0006793 磷代谢过程s 14 1.13E-06
GO：0042127 细胞增殖调节 13 1.58E-06
表4 关键基因中英文名称及英文缩写
基因名称 英文全称 中文名称
GNG7 G protein subunit gamma 7 G蛋白亚基γ7
GNG11 G protein subunit gamma 11 G蛋白亚基γ11
FGF7 fibroblast growth factor 7 成纤维细胞生长因子7
PDGFRB platelet derived growth factor receptor beta 血小板源性生长因子受体β
FGF22 fibroblast growth factor 22 成纤维细胞生长因子22
FGFR1 fibroblast growth factor receptor 1 成纤维细胞生长因子受体1
FGF2 fibroblast growth factor 2 成纤维细胞生长因子2
PIK3R1 phosphoinositide-3-kinase regulatory subunit 1 磷酸肌醇-3-激酶调节亚基1
IGF1 insulin like growth factor 1 胰岛素样生长因子1
FLT1 fms related tyrosine kinase 1 fms相关的酪氨酸激酶1
FGFR2 fibroblast growth factor receptor 2 成纤维细胞生长因子受体2
FGF1 fibroblast growth factor 1 成纤维细胞生长因子1
KIT KIT proto-oncogene receptor tyrosine kinase KIT原癌基因受体酪氨酸激酶
KITLG KIT ligand KIT配体
GAB1 GRB2 associated binding protein 1 GRB2相关结合蛋白1
PTPN11 protein tyrosine phosphatase，non-receptor type 11 非受体蛋白酪氨酸磷酸酶11型
GNB5 G protein subunit beta 5 G蛋白亚基5
IGF1R insulin like growth factor 1 receptor 胰岛素样生长因子1受体
MAPK1 mitogen-activated protein kinase 1 丝裂原活化蛋白激酶1
GNG5 G protein subunit gamma 5 G蛋白亚基γ5
AKT1 AKT serine/threonine kinase 1 AKT丝氨酸/苏氨酸激酶1
PIK3CA phosphatidylinositol-4，5-bisphosphate 3-kinase catalytic subunit alpha 磷脂酰肌醇-4，5-二磷酸3-激酶催化亚基
AKT3 AKT serine/threonine kinase 3 AKT丝氨酸/苏氨酸激酶3
VEGFA vascular endothelial growth factor A 血管内皮生长因子A
图3 24个关键基因的蛋白相互作用网络注：用cBioPortal分析的24个关键基因及其共表达基因。黑体轮廓的节点代表枢纽基因；黑色轮廓的节点代表共同表达的基因
图4 关键基因差异表达在宫颈癌中的生存分析图。图a为关键基因差异表达在宫颈癌中总体生存率；图b为关键基因差异表达在宫颈癌中无病生存率
图5 GEPIA在线平台检索关键基因与宫颈癌EMT的相关关系图注：GEPIA为基因表达谱交互分析；EMT为肿瘤细胞上皮-间质化；CDH1为钙粘蛋白1；CDH2为钙粘蛋白2；SNAI2为蜗牛家族转录抑制因子2；TPM为相关基因被另一基因标准化，数据库使用非对数标度进行计算，使用对数标度轴进行可视化
图6 免疫组织化学结果（×200）。图a~c为宫颈癌组织中的染色结果，图a为PTPN11（n=17）；图b为GNG11（n=14）；图c为VEGFA（n=15）；图d~f为正常宫颈组织中的染色结果，图d为PTPN11（n=3）；图e为GNG11（n=3）；图f为VEGFA（n=3）
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