去势抵抗性前列腺癌潜在关键基因的生物信息学分析

doi:10.12114/j.issn.1007-9572.2022.02.010

中国全科医学 ›› 2022, Vol. 25 ›› Issue (08): 937-944.DOI: 10.12114/j.issn.1007-9572.2022.02.010

所属专题：肿瘤最新文章合辑

去势抵抗性前列腺癌潜在关键基因的生物信息学分析

董婧婷¹, 衡立¹, 康绍叁¹, 刘健¹, 田志崇¹, 张立国¹, 张金存¹, 李治国², 沈宏^3,^*, 曹凤宏^1,^*

1.063000　河北省唐山市，华北理工大学附属医院泌尿外科
2.063210　河北省唐山市，华北理工大学公共卫生学院
3.063000　河北省唐山市，华北理工大学现代教育中心

收稿日期:2021-10-11 修回日期:2021-12-20 出版日期:2022-03-15 发布日期:2022-03-02
通讯作者: 沈宏,曹凤宏
基金资助:
河北省自然科学基金资助项目(H2019209595);河北省医学科学研究课题计划资助项目(20210212)

Bioinformatic Analysis of Potential Key Genes in Castration-resistant Prostate Cancer Development

DONG Jingting1，HENG Li1，KANG Shaosan1，LIU Jian1，TIAN Zhichong1，ZHANG Liguo1，ZHANG Jincun1，LI Zhiguo2，SHEN Hong3*，CAO Fenghong1*

1.Department of Urology，North China University of Science and Technology Affiliated Hospital，Tangshan 063000，China
2.School of Public Health，North China University of Science and Technology，Tangshan 063210，China
3.Modern Education Technology Center，North China University of Science and Technology，Tangshan 063000，China
*Corresponding authors：SHEN Hong，Engineer；E-mail：shenhong@ncst.edu.cn
CAO Fenghong，Chief physician，Master supervisor；E-mail：caofenghong@163.com

Received:2021-10-11 Revised:2021-12-20 Published:2022-03-15 Online:2022-03-02

摘要/Abstract

摘要： 背景去势抵抗性前列腺癌（CRPC）是男性常见恶性肿瘤疾病之一，病死率高，分子机制仍不十分清楚，且无有效治疗药物。目的应用生物信息学方法挖掘CRPC发生、发展的关键基因，为其诊治提供新思路。方法从基因表达综合数据库（GEO）中下载关于人类原发性前列腺癌（PCa）和CRPC的数据集GSE32269并进行生物信息学分析。使用R语言鉴定CRPC的差异表达基因（DEGs）。通过DAVID软件对DEGs进行基因本体论（GO）富集分析及京都基因和基因组百科全书（KEGG）通路分析。利用STRING在线数据库构建蛋白质-蛋白质相互作用（PPI）网络进一步筛选关键基因，并对关键基因进行生存分析和受试者工作特征（ROC）曲线分析。结果通过对微阵列数据集GSE32269分析共筛选出279个DEGs，进一步通过GO富集分析和KEGG通路分析发现在CRPC发展中，细胞分裂、有丝分裂和细胞周期等信号通路发挥重要作用。PPI网络分析筛选出15个关键基因，对关键基因进行生存分析发现：CDC20、MAD2L1和NUSAP1高表达组CRPC患者总生存率和无病生存率均分别低于CDC20、MAD2L1和NUSAP1低表达组（P<0.05）；且CDC20、MAD2L1和NUSAP1预测CPRC发生的ROC曲线下面积分别为0.933、0.762、0.950，提示其对CRPC具有较高的诊断价值。结论CDC20、MAD2L1和NUSAP1可能是参与CRPC发展的关键候选基因。

关键词: 前列腺癌, 去势抵抗性前列腺癌, 关键基因, 生物信息学

Abstract: Background

Castration-resistant prostate cancer (CRPC) is one of the most prevalent cancers in males with a high fatality rate. Its molecular mechanism is still unclear, and there is no effective treatment.

Objective

To explore the key genes involved in CRPC development using bioinformatic analysis, offering new ideas for the diagnosis and treatment of CRPC.

Methods

The data set GSE32269 which contains human primary prostate cancer and CRPC was downloaded from the Gene Expression Omnibus database for further bioinformatic analysis. R language was used to identify differentially expressed genes (DEGs) in CRPC. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs were further performed by using DAVID. A protein-protein interaction (PPI) network of DEGs was constructed by using STRING database for screening potential key genes. And the identified potential key genes were further analyzed by survival analysis and receiver operating characteristic (ROC) curve analysis.

Results

279 DEGs were identified in microarray dataset GSE32269. GO enrichment analysis and KEGG pathway analysis revealed that cell division, mitosis and cell cycle signaling pathways may play an important role in the development of CRPC. PPI network screening revealed that there were 15 potential key genes, among which CDC20, MAD2L1 and NUSAP1 expressed differentially in CRPC patients: those with highly expressed CDC20, MAD2L1 and NUSAP1 had statistically lower overall survival rate and disease-free survival rate than did those with low expressed CDC20, MAD2L1 and NUSAP1 (P<0.05) . The area under the ROC curve of CDC20, MAD2L1 and NUSAP1 to predict the occurrence of CRPC were 0.933, 0.762, and 0.950, respectively, indicating that each of them may have a high diagnostic value for CRPC.

Conclusion

CDC20, MAD2L1 and NUSAP1 may be key candidate genes associated with the development of CRPC.

Key words: Prostatic neoplasms, Castration-resistant prostate cancer, Key genes, Bioinformatics

中图分类号:

R737.25

董婧婷,衡立,康绍叁,等. 去势抵抗性前列腺癌潜在关键基因的生物信息学分析[J]. 中国全科医学, 2022, 25(08): 937-944. DOI: 10.12114/j.issn.1007-9572.2022.02.010.

DONG Jingting, HENG Li, KANG Shaosan, LIU Jian, TIAN Zhichong, ZHANG Liguo, ZHANG Jincun, LI Zhiguo, SHEN Hong, CAO Fenghong.

Bioinformatic Analysis of Potential Key Genes in Castration-resistant Prostate Cancer Development [J]. Chinese General Practice, 2022, 25(08): 937-944.

图/表 11

图1 CRPC的DEGs筛选

Figure 1 Identification of differentially expressed genes in castration-resistant prostate cancer

表1 CRPC的DEGs主要参与的生物过程

Table 1 Major biological processes in which differentially expressed genes in castration-resistant prostate cancer being involved

ID	描述
GO:0030198	细胞外基质组织
GO:0007155	细胞黏附
GO:0051301	细胞分裂
GO:0030199	胶原纤维组织
GO:0030574	胶原蛋白分解代谢过程
GO:0000070	有丝分裂姐妹染色单体分离
GO:0006909	吞噬作用
GO:0007067	有丝分裂核分裂
GO:0051988	调节纺锤体微管与着丝点附着
GO:0000281	有丝分裂胞质分裂

表2 CRPC的DEGs主要参与的细胞成分

Table 2 Major cellular components of differentially expressed genes involved in castration-resistant prostate cancer development

ID	描述
GO:0070062	细胞外外泌体
GO:0031012	细胞外基质
GO:0005578	蛋白质细胞外基质
GO:0005615	细胞外空隙
GO:0030496	中间体
GO:0005788	内质网腔
GO:0005581	胶原蛋白三聚物
GO:0005737	细胞质
GO:0051233	中央区
GO:0005604	基底膜

表3 CRPC的DEGs主要参与的分子功能

Table 3 Major molecular functions of differentially expressed genes involved in castration-resistant prostate cancer development

ID	描述
GO:0005201	细胞外基质结构成分
GO:0005515	蛋白质结合
GO:0005518	胶原蛋白质结合
GO:0050840	细胞外基质结合
GO:0005178	整合素结合
GO:0008307	肌肉结构成分
GO:0048407	血小板衍生生长因子结合
GO:0019901	蛋白激酶结合
GO:0008201	肝素结合
GO:0051015	肌动蛋白丝结合

图2 CRPC的DEGs GO富集分析结果

Figure 2 GO enrichment results of differentially expressed genes in castration-resistant prostate cancer

图3 CRPC的DEGs KEGG富集分析结果

Figure 3 KEGG enrichment results of differentially expressed genes involved in castration-resistant prostate cancer development

表4 CRPC的DEGs关键基因详细情况

Table 4 Details of key genes of differentially expressed genes involved in castration-resistant prostate cancer development

关键基因	logFC	P值	MCC	DMNC	MNC
CDC20	1.406 196 669	3.45E-07	9.22E+13	1.387 59	46
CCNB2	1.211 615 251	6.41E-05	9.22E+13	1.372 69	46
PRC1	1.379 662 195	2.93E-06	9.22E+13	1.366 72	46
MAD2L1	1.344 235 673	0.000 588 11	9.22E+13	1.366 72	46
PBK	2.292 914 566	3.17E-05	9.22E+13	1.406 38	45
NUSAP1	1.570 694 653	2.92E-07	9.22E+13	1.394 00	45
RRM2	1.412 761 198	3.44E-07	9.22E+13	1.381 63	45
SMC2	1.412 009 936	1.67E-07	9.22E+13	1.358 42	45
MELK	2.012 790 040	6.81E-09	9.22E+13	1.432 21	44
KIF4A	2.302 338 169	3.25E-09	9.22E+13	1.420 96	44
DTL	1.385 254 880	1.29E-05	9.22E+13	1.408 10	44
ZWINT	1.591 711 536	0.000 340 659	9.22E+13	1.372 74	44
CEP55	1.779 583 266	1.70E-05	9.22E+13	1.440 82	43
RACGAP1	1.577 983 649	5.87E-08	9.22E+13	1.440 82	43
CDKN3	2.135 599 175	0.000 218 876	9.22E+13	1.360 59	43

图4 CRPC的DEGs PPI网络和关键基因

Figure 4 PPI network and key genes involved in castration-resistant prostate cancer development

图5 CDC20、MAD2L1和NUSAP1高表达组与低表达组总生存期比较的生存曲线

Figure 5 Overall survival curves between castration-resistant prostate cancer patients with highly and low expressed CDC20，MAD2L1 and NUSAP1

图6 CDC20、MAD2L1和NUSAP1高表达组与低表达组无病生存期比较的生存曲线

Figure 6 Disease-free survival curves between castration-resistant prostate cancer patients with highly and low expressed CDC20，MAD2L1 and NUSAP1

图7 CDC20、MAD2L1和NUSAP1预测CRPC发生的ROC曲线

Figure 7 ROC curves of CDC20，MAD2L1 and NUSAP1 predicting castration-resistant prostate cancer

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去势抵抗性前列腺癌潜在关键基因的生物信息学分析

Bioinformatic Analysis of Potential Key Genes in Castration-resistant Prostate Cancer Development

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