WJCR World Journal of Cancer Research 2164-9049 Scientific Research Publishing 10.12677/WJCR.2024.141009 WJCR-79958 WJCR20240100000_19045056.pdf 医药卫生 基于生物信息学分析筛选与鉴定宫颈癌的预后生物标志物 Screening and Identification of Prognostic Biomarkers of Cervical Cancer Based on Bioinformatics Analysis 陈 学维 1 * 刘 云聪 1 3 2 朱 国庆 4 2 贵州中医药大学第二临床医学院，贵州 贵阳 贵州中医药大学第二临床医学院，贵州 贵阳；贵州省人民医院肿瘤科，贵州 贵阳 贵州省人民医院肿瘤科，贵州 贵阳 null 09 01 2024 14 01 55 65 © Copyright 2014 by authors and Scientific Research Publishing Inc. 2014 This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

宫颈癌发病率是女性排名第四的恶性肿瘤，宫颈癌死亡率也是女性恶性肿瘤的第四大恶性疾病。此外，近几十年来，年轻女性患宫颈癌的发病率有所增加。目前，有一些生物标志物(如鳞状细胞癌抗原(SCC-Ag))用于宫颈癌的诊断和预后。但是这些生物标志物缺乏敏感性和特异性，限制了它们的效用。因此，利用生物信息学更好地了解HPV (+)的非肿瘤宫颈组织和HPV (+)的宫颈癌肿瘤组织中差异基因表达及筛选关键诊断和预后基因，为寻找宫颈癌的新机制、更多预后因素和潜在治疗靶点提供进一步的研究思路。 The incidence of cervical cancer is the fourth most malignant disease in women, and the mortality rate of cervical cancer is also the fourth most malignant disease in women. In addition, the inci-dence of cervical cancer in young women has increased in recent decades. Currently, there are some biomarkers (such as squamous cell carcinoma antigen (SCC-Ag)) used for the diagnosis and progno-sis of cervical cancer. However, the lack of sensitivity and specificity of these biomarkers limits their utility. Therefore, using bioinformatics to better understand the differential gene expression in HPV (+) non-tumor cervical tissues and HPV (+) cervical cancer tissues and screen key diagnostic and prognostic genes provides further research ideas for finding new mechanisms of cervical cancer, more prognostic factors and potential therapeutic targets.

 宫颈癌，生物信息分析，差异基因表达，生物标志物，预后与诊断, Cervical Cancer Bioinformatics Analysis Differential Gene Expression Biomarkers Prognosis and Diagnosis 摘要

宫颈癌发病率是女性排名第四的恶性肿瘤，宫颈癌死亡率也是女性恶性肿瘤的第四大恶性疾病。此外，近几十年来，年轻女性患宫颈癌的发病率有所增加。目前，有一些生物标志物(如鳞状细胞癌抗原(SCC-Ag))用于宫颈癌的诊断和预后。但是这些生物标志物缺乏敏感性和特异性，限制了它们的效用。因此，利用生物信息学更好地了解HPV (+)的非肿瘤宫颈组织和HPV (+)的宫颈癌肿瘤组织中差异基因表达及筛选关键诊断和预后基因，为寻找宫颈癌的新机制、更多预后因素和潜在治疗靶点提供进一步的研究思路。

 关键词

宫颈癌，生物信息分析，差异基因表达，生物标志物，预后与诊断

 Screening and Identification of Prognostic Biomarkers of Cervical Cancer Based on Bioinformatics Analysis<sup> </sup>

Xuewei Chen1*, Yuncong Liu1,2#, Guoqing Zhu2

1The Second Clinical Medical School of Guizhou University of Traditional Chinese Medicine, Guiyang Guizhou

2Department of Oncology, Guizhou Provincial People’s Hospital, Guiyang Guizhou

Received: Dec. 19th, 2023; accepted: Jan. 19th, 2024; published: Jan. 29th, 2024

 ABSTRACT

The incidence of cervical cancer is the fourth most malignant disease in women, and the mortality rate of cervical cancer is also the fourth most malignant disease in women. In addition, the incidence of cervical cancer in young women has increased in recent decades. Currently, there are some biomarkers (such as squamous cell carcinoma antigen (SCC-Ag)) used for the diagnosis and prognosis of cervical cancer. However, the lack of sensitivity and specificity of these biomarkers limits their utility. Therefore, using bioinformatics to better understand the differential gene expression in HPV (+) non-tumor cervical tissues and HPV (+) cervical cancer tissues and screen key diagnostic and prognostic genes provides further research ideas for finding new mechanisms of cervical cancer, more prognostic factors and potential therapeutic targets.

Keywords:Cervical Cancer, Bioinformatics Analysis, Differential Gene Expression, Biomarkers, Prognosis and Diagnosis

Copyright © 2024 by author(s) and beplay安卓登录

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

http://creativecommons.org/licenses/by/4.0/

 1. 引言

近年来，宫颈癌(Cervical cancer, CC)的发病及其死亡比例仍呈上升的势头。世界卫生机构国际癌症研究机构(IARC)发布了2020年全球最新癌症数据。在全球患病率前十的癌症中，宫颈癌新发病例约60万例，死亡病例34万例，分别占女性癌症发病和死亡总数的6.5%和7.7% [ 1 ] 。宫颈癌是女性第四大恶性癌症，几乎所有宫颈癌病例(99%)都与高危人瘤病毒(HPV)感染有关，HPV是一种通过性接触传播的极其常见的病毒 [ 2 ] 。人瘤病毒(HPV)是99%宫颈癌的原因，超过70%的女性在其一生中感染HPV [ 3 ] ，虽然大多数HPV感染会自发消退，不会引起任何症状，但持续感染可能会发展为癌症 [ 4 ] 。尽管宫颈癌早期诊断的筛查积极开展，但其发病率依然呈向上坡线条，亚洲人群的发病率一直居高不下，已严重危及着女性们的健康和生活。经过长期的抗肿瘤临床研究治疗的应用，其治疗方式有多元式发展，包括手术、化疗、放疗、靶向药物、介入等相结合的综合治疗 [ 5 ] ，因此需要探索有关宫颈癌诊断与预后的敏感生物标志物。目前，也有一些生物标志物(如鳞状细胞癌抗原(SCC-Ag))用于宫颈癌的诊断和预后，但是这些生物标志物缺乏敏感性和特异性限制了它们的效用 [ 6 ] 。因此需要寻找更多宫颈恶性肿瘤的相关生物标志物，提供诊治方法及预后管理。

生物信息学是一种解释微生物数据，在芯片上读取基因杂交信息以及将数据链接到生物过程(BPs)的方法 [ 7 ] 。基因表达微阵列作为有效大规模获取遗传数据的一种手段，通常用于收集和研究许多人类癌症中的基因芯片分析数据。微阵列为肿瘤相关基因的研究、靶向分子、预后管理和靶向治疗提供了新的方法和良好的前景 [ 8 ] 。随着生物信息学快速发展，越来越多的恶性肿瘤运用生物信息学分析筛选与鉴定关键诊断和预后基因，如乳腺癌 [ 9 ] 、子宫内膜癌 [ 10 ] 、卵巢癌 [ 11 ] 、胃癌 [ 12 ] 、肺癌 [ 13 ] 、直肠癌 [ 14 ] 、肝癌 [ 15 ] 等筛选相关预后基因，为恶性肿瘤寻找潜在治疗靶点基因。

本文利用生物信息学分析了解HPV (+)的非肿瘤宫颈组织和HPV (+)的宫颈癌肿瘤组织中差异基因表达及筛选关键诊断和预后基因，为寻找宫颈癌的新机制、更多预后因素和潜在治疗靶点提供进一步的研究思路。

 2. 材料与方法 2.1. 微阵列数据收集

GEO数据库全称(https://www.ncbi.nlm.nih.gov/geo/)，是由美国国立生物技术信息中心NCBI创建高通量实验数据并维护的基因表达数据库，这是当今最全面的公共基因表达数据资源之一。我们在GEO数据库中下载获得了包含HPV (+)的非肿瘤宫颈组织和HPV (+)的宫颈癌肿瘤组织样本的RNA测序数据集，分别为五个基因表达谱，GSE138080由10个肿瘤样本和10个正常宫颈样本组成。GSE75132由1个肿瘤样本和10个正常宫颈样本组成，GSE29570由45个肿瘤样本和17个正常宫颈样本组成。GSE39001由43个肿瘤样本和6个正常宫颈样本组成。GSE6791由20个肿瘤样本和8个正常宫颈样本组成。

 2.2. DEG的识别

我们通过GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r/)鉴定了DEG，GEO2R是一种通过使用Bioconductor的GEOquery和limma R软件包可以获得GEO数据库中两个基因表达谱之间的DEG的方法 [ 16 ] 。它被设置为通过调整后的p值 < 0.05和logFC (倍数变化) > −1或logFC (倍数变化) < 1来筛选DEG，我们使用维恩图来找到重叠的DEG。

 2.3. GO和KEGG富集分析

DAVID是(http://david.abcc.ncifcrf.gov/) (版本2021) [ 17 ] 是一个公共在线生物信息学数据库，有助于识别最重要的富集功能基因和生物学途径，为了进一步分析DEGs，使用DAVID在线工具进行了基因本体(GO)和京都基因和基因组百科全书(KEGG)富集分析。GO分析用于注释基因的生物过程(BP)，细胞学成分(CC)和分子功能(MF)和KEGG富集分析用于了解相关的信号通路。P值 < 0.05被认为具有统计学意义。

 2.4. PPI网络和关键模块分析及hub基因筛选

我们使用检索相互作用基因的搜索工具STRING (http://string-db.org/) (版本11.5)基于置信度分数的数据库，获取DEGs的PPI信息，选择每个综合得分 > 0.4的PPI为显着的相互作用对 [ 18 ] 。更重要的是，我们通过Cytoscape (版本3.10.0)进一步可视化了PPI [ 19 ] 。Cytoscape中的分子复合物检测(MCODE)插件用于过滤网络中的关键模块，度截止值 = 2，节点得分截止值 = 0.2，k核心 = 2，最大深度 = 100。为了从Cytoscape可视化PPI网络中识别枢纽基因，我们应用了另一种插件CytoHubba，按MMC法排序，鉴定出枢纽基因。

 2.5. 验证枢纽基因和蛋白表达

我们得出枢纽基因后，运用GEPIA2 [ 20 ] 、UALCAN [ 21 ] 、HPA数据库 [ 22 ] 中分析在宫颈癌在组织中的表达，验证关键枢纽基因在癌症中的生存预后分析。

 3. 结果 3.1. 宫颈癌DEG识别

我们通过GEO2R在线工具对5个数据集的相交筛选出39个共同差异基因表达，并通过如下(表1)及韦恩图展示(图1)。

Differential gene expression (DEG
39个共同基因表达
ACTL6A、BIRC5、BUB1、CCNB2、CDC6、CDK1、CDKN2A、CKS1B、CKS2、DHFR、EGR1、EZH2、FEN1、FOSB、GINS2、GMNN、H2AFZ、HLTF、HMMR、KIF15、KIF23、KIF2C、MCM2、MCM6、MMP9、NCAPG、NDC80、NUSAP1、PCNA、PRC1、PTGDS、PTTG1、RFC4、RFC5、RGS2、RNASEH2A、STMN1、TTK、ZWINT

表1. 差异基因表达

图1. 韦恩图。中差异表达基因的鉴定GSE138080，GSE75132，GSE29570，GSE39001和GSE6791基因表达谱数据集。这5个数据集显示有39个基因重叠的差异表达基因

 3.2. GO与KEGG富集分析

为了分析DEGs的生物学分类，使用DAVID进行GO功能和KEGG途径富集分析。GO分析结果表明，差异表达基因生物学过程(BP)的变化主要集中在细胞分裂、脱氧核糖核酸复制、脱氧核糖核酸修复等。细胞组分(CC)的变化主要集中在纺锤、核质、细胞核、动粒、细胞周期蛋白依赖性蛋白激酶全酶复合物等(图2)。分子功能(MF)的变化主要集中在蛋白质结合、ATP结合、ATP水解活性、微管结合、脱氧核糖核酸结合等。KEGG通路分析集中在细胞周期、脱氧核糖核酸复制、错配修复、癌症中的微核糖核酸、p53信号通路、人T细胞白血病病毒1感染等(图3)。

图2. GO富集气泡图。BP、CC、MF富集显著取P < 0.05有统计学意义

图3. KEGG气泡图。取富集显著以P < 0.05有统计学意义

 3.3. PPI网络和关键模块分析及Hub基因筛选

为了更好地了解差异表达基因之间的关系，我们利用STRING (https://cn.string-db.org/cgi/)在线工具对各种差异表达基因，构建了39个DEG的PPI网络(图4)可视化，包括39个节点和420条边。为了从PPI网络中识别枢纽基因，我们应用后Cytoscape的Cytohubba插件。按MMC法排序，筛选出前27个枢纽基因，为了更精确验证筛选关键枢纽基因，再利用分子复合物检测(MCODE)插件过滤网络中的关键模块，由27个节点和674条边，筛选出27个关键枢纽DEG进行可视化(图5)。

 3.4. 宫颈癌与正常宫颈组织中Hub基因的差异表达分析

为了验证CESE和正常宫颈组织中枢纽基因的差异表达，我们利用基于GEPIA2网站的TCGA和GTEx数据库对27个枢纽基因进行了分析。表达分析显示这些关键基因在宫颈癌组织中均高表达，而在正常宫颈癌组织中均低表达。

图4. 蛋白质–蛋白质相互作用(PPI网络)。包括39个节点和420条边，P值 < 0.05为显著

 3.5. 验证枢纽基因和蛋白表达

将27个关键枢纽基因分别GEPIA2、UALCAN、HPA数据库中验证宫颈癌差异基因分析表达。在GEPIA2的总生存分析表明，其MCM2，RFC4，RFC5，PRC1，GINS2，PCNA和RNASEH2A蛋白在宫颈癌有较好的预后相关性(图6)其P值 < 0.05有统计学差异，通过UALCAN数据库亦能验证关键基因在宫颈癌基因表达显示上调，此外，在HPA数据库查询宫颈癌患者的临床免疫组化标本及生存曲线验证显示，其CDK1，MCM2，RFC4，RFC5，PCNA，GINS2，RNASEH2A高表达预后越好，因此可能有利于宫颈癌的诊断与预相关。

图5. 枢纽基因。由27个节点和674条边，计算筛选出27个关键枢纽DEG

图6. Kaplan-Meier曲线。CDK1，MCM2，RFC4，RFC5，PCNA和RNASEH2A中P值 < 0.05有统计学差异。有较好的预后关系

 4. 讨论

宫颈癌是最常见的女性恶性肿瘤之一，宫颈癌的防治有了很大的进步 [ 23 ] 。然而，宫颈癌进展的分子机制尚不清楚。随着高通量技术的进步，通过分析微阵列数据集，已经确定了癌症进展的新型生物标志物。

在我们的研究中，功能富集最多的属细胞周期和脱氧核糖核酸修复，癌症的发生离不开细胞分裂的病理表现 [ 24 ] ，而细胞周期的不同阶段对决定细胞分裂适当性的生理线索有反应 [ 25 ] 。细胞周期蛋白依赖性激酶(CDK)是驱动所有细胞周期转换的关键调节酶，并且它们的活性受到严格控制，以确保细胞分裂成功，其CDK1成为有丝分裂进展的关键决定因素 [ 26 ] ，细胞周期蛋白治疗是细胞周期的治疗，细胞周期蛋白依赖性刺激的CDK、Polo样激酶和WEE激酶是细胞周期治疗药物的主要靶点 [ 27 ] 。患者对细胞周期治疗的反应支持细胞周期在宫颈癌治疗中的重要性 [ 28 ] 。本研究中CDK1在宫颈癌组织中呈高表达，其生存曲线显示高表达比低表达的预后较好，这与之前研究生物信息学鉴定宫颈癌验证预后生物标志物一致 [ 29 ] 。

MCM2是DNA复制许可复合物的一个组成部分，小染色体维持蛋白家族是一组与DNA复制和基因组稳定性密切相关的蛋白质。本研究GO分析结果表明，差异表达基因生物学过程(BP)的变化主要集中在细胞分裂、脱氧核糖核酸复制等。而高度保守的MCM复合蛋白可能具有解旋酶活性，对于DNA复制的启动至关重要。作为真核生物DNA复制的主要调节因子，微染色体维持(MCM)蛋白在DNA复制的启动和延伸中起着重要作用 [ 30 ] 。MCM在临床肿瘤的早期诊断、分类和预后中具有重要的参考价值 [ 31 ] 。已有研究表明，MCM蛋白已成为宫颈癌筛查和早期诊断的非常有希望的标志物 [ 32 ] 。MCM2过表达在CC中经常发生，特别是在持续高危HPV感染的病例中 [ 33 ] 。许多研究主要集中在癌前病变相关生物标志物的分析上，但只有少数研究证实了MCM2表达对侵袭性CC进展的预后影响 [ 34 ] 。相比之下，在我们的研究中，MCM2在CC进展中发挥了保护作用，但我们也观察到CC组织中MCM2的高表达水平，预后越好，与Wang等发现MCM2是CC的预后生物标志物的结论一致 [ 35 ] 。

人类复制因子C (replication factor C, RFC)是由RFC1、RFC2、RFC3、RFC4和RFC5五个同步亚基组成的多聚体蛋白，这些亚基在进化过程中高度保守 [ 36 ] 。RFC4在DNA损伤检查点途径中起重要作用，在许多癌种中也出现过表达现象。RFC5在癌组织或细胞中的表达显著上调，并且其表达随着肿瘤进展而升高，本研究发现在CC等RFC4与RFC5中表达上调，相关研究也证实，RFC4在多种肿瘤中均出现表达增高，如Bachtiary等 [ 37 ] 发现，RFC4在Ⅲ级宫颈癌中的表达高于Ⅱ级宫颈癌；Niu等 [ 38 ] 发现RFC4在宫颈鳞癌中的表达明显高于高级别鳞状上皮内病变，且与宫颈癌的进展和预后相关；Martinez等发现HPV阳性的头颈部鳞状细胞癌组织中RFC5表达显著上调，高于正常口腔黏膜组织和HPV阴性的口咽鳞状细胞癌组织 [ 39 ] 。此外，RFC4可能是一种潜在的预后生物标志物和治疗靶点 [ 40 ] 。据报道 [ 41 ] ，RFC5在癌组织或细胞中显著上调，其表达随着癌症进展而升高，其生存预后越好。

RNASEH2A是一种编码基因的蛋白质，其RNASEH2A相关疾病包括与癌症进展和细胞周期相关的Aicardi-Goutieres综合征 [ 42 ] 。在我们的研究中，它与宫颈癌的总生存率有关，这与之前的研究一致 [ 43 ] ，并且该基因在肺癌 [ 44 ] 和乳腺癌 [ 45 ] 中起着类似的作用。同样，我们发现RNASEH2A在宫颈癌中高表达，并参与RNA分解代谢过程，有望成为宫颈癌的分子诊断标志物和治疗靶点。PCNA是DNA聚合酶的辅助蛋白，可调节DNA合成 [ 46 ] 。PCNA被认为是评估细胞增殖活性的指标。PCNA上调与5年生存率、晚期疾病分期和宫颈癌更高的WHO分级相关，提示PCNA可能是宫颈癌预后和诊断的生物标记物 [ 47 ] ，这与本研究结果一致。

本文研究基于GEO数据库筛选关于宫颈健康组织与宫颈癌组织之间差异基因表达及筛选关键诊断和预后基因，为寻找宫颈癌的新机制、更多预后因素和潜在治疗靶点提供进一步的研究思路，并最后在UALCAN和HPA数据库验证有利于宫颈癌预后标志物分别有CDK1，MCM2，RFC4，RFC5，PCNA，RNASEH2A蛋白基因与宫颈癌的预后相关，可能是宫颈癌诊断与预后的生物标志物。

 文章引用

陈学维,刘云聪,朱国庆. 基于生物信息学分析筛选与鉴定宫颈癌的预后生物标志物Screening and Identification of Prognostic Biomarkers of Cervical Cancer Based on Bioinformatics Analysis[J]. 世界肿瘤研究, 2024, 14(01): 55-65. https://doi.org/10.12677/WJCR.2024.141009

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