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
DOI: 10.12677/WJCR.2024.141009, PDF,   
作者: 陈学维：贵州中医药大学第二临床医学院，贵州 贵阳；刘云聪：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；朱国庆：贵州省人民医院肿瘤科，贵州 贵阳
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；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。
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 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.
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[J]. 世界肿瘤研究, 2024, 14(1): 55-65. https://doi.org/10.12677/WJCR.2024.141009

参考文献

[1] 刘宗超, 李哲轩, 张阳, 等. 2020全球癌症统计报告解读[J]. 肿瘤综合治疗电子杂志, 2021, 7(2): 1-13.
[2] Arbyn, M., et al. (2020) Estimates of Incidence and Mortality of Cervical Cancer in 2018: A Worldwide Analysis. The Lancet Global Health, 8, E191-E203. [Google Scholar] [CrossRef] 
[3] Chesson, H.W., et al. (2014) The Estimated Lifetime Proba-bility of Acquiring Human Papillomavirus in the United States. Sexually Transmitted Diseases, 41, 660-664. [Google Scholar] [CrossRef] 
[4] Shanmugasundaram, S. and You, J. (2017) Targeting Per-sistent Human Papillomavirus Infection. Viruses, 9, Article 229. [Google Scholar] [CrossRef] [PubMed]
[5] Cibula, D., et al. (2023) ESGO/ESTRO/ESP Guidelines for the Management of Patients with Cervical Cancer—Update 2023. In-ternational Journal of Gynecologic Cancer, 33, 649-666. [Google Scholar] [CrossRef] [PubMed]
[6] Salvatici, M., et al. (2016) Squamous Cell Carcinoma Antigen (SCC-Ag) during Follow-Up of Cervical Cancer Patients: Role in the Early Diagnosis of Recurrence. Gynecologic Oncology, 142, 115-119. [Google Scholar] [CrossRef] [PubMed]
[7] Quackenbush, J. (2001) Computational Analysis of Microarray Data. Nature Reviews Genetics, 2, 418-427. [Google Scholar] [CrossRef] [PubMed]
[8] Petryszak, R., et al. (2014) Expression Atlas Update—A Database of Gene and Transcript Expression from Microarray- and Sequencing-Based Functional Genomics Experiments. Nucleic Acids Research, 42, D926-D932. [Google Scholar] [CrossRef] [PubMed]
[9] Oumeddour, A. (2023) Screening of Potential Hub Genes and Key Path-ways Associated with Breast Cancer by Bioinformatics Tools. Medicine, 102, e33291. [Google Scholar] [CrossRef] 
[10] Ke, Y., Zhuang, X. and You, L. (2022) Identification of Core Genes Shared by Endometrial Cancer and Ovarian Cancer Using an Integrated Approach. Molecular and Cellular Biolo-gy, 68, 140-145. [Google Scholar] [CrossRef] [PubMed]
[11] Yang, D., et al. (2020) Integrated Bioinformatics Analysis for the Screening of Hub Genes and Therapeutic Drugs in Ovarian Cancer. Journal of Ovarian Research, 13, Article No. 10. [Google Scholar] [CrossRef] [PubMed]
[12] Liu, Y., Wan, D.X., Wa, X.J. and Meng, X.H. (2022) Identifica-tion of Candidate Biomarkers Associated with Gastric Cancer Prognosis Based on an Integrated Bioinformatics Analysis. Journal of Gastrointestinal Oncology, 13, 1690-1700. [Google Scholar] [CrossRef] [PubMed]
[13] Sultana, A., et al. (2023) Single-Cell RNA-Seq Analysis to Identify Po-tential Biomarkers for Diagnosis, and Prognosis of Non-Small Cell Lung Cancer by Using Comprehensive Bioinformat-ics Approaches. Translational Oncology, 27, Article ID: 101571. [Google Scholar] [CrossRef] [PubMed]
[14] Xu, Z., et al. (2020) Identifications of Candidate Genes Signifi-cantly Associated with Rectal Cancer by Integrated Bioinformatics Analysis. Technology in Cancer Research & Treat-ment, 19. [Google Scholar] [CrossRef] [PubMed]
[15] Kumar, P., et al. (2022) Identification and Validation of Core Genes as Promising Diagnostic Signature in Hepatocellular Carcinoma Based on Integrated Bioinformatics Approach. Scientific Reports, 12, Article No. 19072. [Google Scholar] [CrossRef] [PubMed]
[16] Barrett, T., et al. (2013) NCBI GEO: Archive for Functional Genomics Data Sets—Update. Nucleic Acids Research, 41, D991-D995. [Google Scholar] [CrossRef] [PubMed]
[17] Sherman, B.T., et al. (2022) DAVID: A Web Server for Functional En-richment Analysis and Functional Annotation of Gene Lists (2021 Update). Nucleic Acids Research, 50, W216-W221. [Google Scholar] [CrossRef] [PubMed]
[18] Szklarczyk, D., et al. (2023) The STRING Database in 2023: Pro-tein-Protein Association Networks and Functional Enrichment Analyses for Any Sequenced Genome of Interest. Nucleic Acids Research, 51, D638-D646. [Google Scholar] [CrossRef] [PubMed]
[19] Shannon, P., et al. (2003) Cytoscape: A Software Environment for Inte-grated Models of Biomolecular Interaction Networks. Genome Research, 13, 2498-2504. [Google Scholar] [CrossRef] [PubMed]
[20] Tang, Z., et al. (2019) GEPIA2: An Enhanced Web Server for Large-Scale Expression Profiling and Interactive Analysis. Nucleic Acids Research, 47, W556-W560. [Google Scholar] [CrossRef] [PubMed]
[21] Chandrashekar, D.S., et al. (2017) UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses. Neoplasia, 19, 649-658. [Google Scholar] [CrossRef] [PubMed]
[22] Karlsson, M., et al. (2021) A Single-Cell Type Transcriptomics Map of Human Tissues. Science Advances, 7, eabh2169. [Google Scholar] [CrossRef] [PubMed]
[23] Cohen, P.A., Jhingran, A., Oaknin, A. and Denny, L. (2019) Cervical Cancer. The Lancet, 393, 169-182. [Google Scholar] [CrossRef] 
[24] Hunt, T., Nasmyth, K. and Novak, B. (2011) The Cell Cycle. Philosophical Transactions of the Royal Society B: Biological Sciences, 366, 3494-3497. [Google Scholar] [CrossRef] [PubMed]
[25] Nurse, P., Masui, Y. and Hartwell, L. (1998) Understanding the Cell Cycle. Nature Medicine, 4, 1103-1106. [Google Scholar] [CrossRef] [PubMed]
[26] Asghar, U., Witkiewicz, A.K., Turne, N.C. and Knudsen, E.S. (2015) The His-tory and Future of Targeting Cyclin-Dependent Kinases in Cancer Therapy. Nature Reviews Drug Discovery, 14, 130-146. [Google Scholar] [CrossRef] [PubMed]
[27] Wang, X., et al. (2020) Novel CDKs Inhibitors for the Treatment of Solid Tumour by Simultaneously Regulating the Cell Cycle and Transcription Control. Journal of Enzyme Inhibition and Me-dicinal Chemistry, 35, 414-423. [Google Scholar] [CrossRef] [PubMed]
[28] Mondala, P.K., et al. (2021) Selective Antisense Oligonucle-otide Inhibition of Human IRF4 Prevents Malignant Myeloma Regeneration via Cell Cycle Disruption. Cell Stem Cell, 28, 623-636.E9. [Google Scholar] [CrossRef] [PubMed]
[29] Xue, H., Sun, Z., Wu, W., Du, D. and Liao, S. (2021) Identifica-tion of Hub Genes as Potential Prognostic Biomarkers in Cervical Cancer Using Comprehensive Bioinformatics Analysis and Validation Studies. Cancer Management and Research, 13, 117-131. [Google Scholar] [CrossRef] 
[30] Forsburg, S.L. (2004) Eukaryotic MCM Proteins: Beyond Replica-tion Initiation. Microbiology and Molecular Biology Reviews, 68, 109-131. [Google Scholar] [CrossRef] 
[31] Wang, D., Li, Q., Li, Y.C. and Wang, H.Y. (2018) The Role of MCM5 Expression in Cervical Cancer: Correlation with Progression and Prognosis. Biomedicine & Pharma-cotherapy, 98, 165-172. [Google Scholar] [CrossRef] [PubMed]
[32] Laskey, R. (2005) The Croonian Lecture 2001 Hunting the An-tisocial Cancer Cell: MCM Proteins and Their Exploitation. Philosophical Transactions of the Royal Society B: Biological Sciences, 360, 1119-1132. [Google Scholar] [CrossRef] [PubMed]
[33] Zheng, J. (2015) Diagnostic Value of MCM2 Immunocytochemical Staining in Cervical Lesions and Its Relationship with HPV Infection. International Journal of Clinical and Experimental Pathology, 8, 875-880.
[34] Amaro, F.S., et al. (2014) Correlation of MCM2 Detection with Stage and Virology of Cervical Cancer. The International Journal of Biological Markers, 29, 363-371. [Google Scholar] [CrossRef] [PubMed]
[35] Wang, J., et al. (2020) A Novel Four-Gene Prognostic Signature as a Risk Biomarker in Cervical Cancer. International Journal of Genomics, 2020, Article ID: 4535820. [Google Scholar] [CrossRef] 
[36] Li, Y., et al. (2018) Multifaceted Regulation and Functions of Rep-lication Factor C Family in Human Cancers. American Journal of Cancer Research, 8, 1343-1355.
[37] Bachtiary, B., et al. (2006) Gene Expression Profiling in Cervical Cancer: An Exploration of Intratumor Heterogeneity. Clinical Cancer Research, 12, 5632-5640. [Google Scholar] [CrossRef] 
[38] Niu, G., Wang, D.P., Pei, Y.F. and Sun, L. (2017) Systematic Identification of Key Genes and Pathways in the Development of Invasive Cervical Cancer. Gene, 618, 28-41. [Google Scholar] [CrossRef] [PubMed]
[39] Martinez, I., Wang, J., Hobson, K.F., Ferris, R.L. and Khan, S.A. (2007) Identification of Differentially Expressed Genes in HPV-Positive and HPV-Negative Oro-pharyngeal Squamous Cell Carcinomas. European Journal of Cancer, 43, 415-432.
[40] Liu, S.M., Chen, W. and Wang, J. (2014) Distinguishing between Cancer Cell Differentiation and Resistance Induced by All-Trans Retinoic Acid Using Transcriptional Profiles and Functional Pathway Analysis. Scientific Reports, 4, Article No. 5577. [Google Scholar] [CrossRef] [PubMed]
[41] Marsili, S., et al. (2021) Gene Co-Expression Analysis of Human RNASEH2A Reveals Functional Networks Associated with DNA Replication, DNA Damage Response, and Cell Cycle Regulation. Biology, 10, Article 221. [Google Scholar] [CrossRef] [PubMed]
[42] Huang, Z., Li, F. and Li, Q. (2021) Expression Profile of RNA Binding Protein in Cervical Cancer Using Bioinformatics Approach. Cancer Cell International, 21, Article No. 647. [Google Scholar] [CrossRef] [PubMed]
[43] Zhang, J., et al. (2021) Long Noncoding RNA LINC01287 Promotes Proliferation and Inhibits Apoptosis of Lung Adenocarcinoma Cells via the miR-3529-5p/RNASEH2A Axis under the Competitive Endogenous RNA Pattern. Environmental Toxicology, 36, 2093-2104. [Google Scholar] [CrossRef] [PubMed]
[44] Yang, M. (2021) Long Noncoding RNA LINC01287 Promotes Prolifera-tion and Inhibits Apoptosis of Lung Adenocarcinoma Cells via the miR-3529-5p/RNASEH2A Axis under the Competi-tive Endogenous RNA Pattern. Environmental Toxicology, 36, 2093-2104. [Google Scholar] [CrossRef] [PubMed]
[45] Chen, Y.X., et al. (2020) An Integrative Multi-Omics Network-Based Ap-proach Identifies Key Regulators for Breast Cancer. Computational and Structural Biotechnology Journal, 18, 2826-2835. [Google Scholar] [CrossRef] [PubMed]
[46] Perucca, P., et al. (2018) A Damaged DNA Binding Protein 2 Mu-tation Disrupting Interaction with Proliferating-Cell Nuclear Antigen Affects DNA Repair and Confers Proliferation Ad-vantage. Biochimica et Biophysica Acta (BBA)—Molecular Cell Research, 1865, 898-907. [Google Scholar] [CrossRef] [PubMed]
[47] Oleynikova, N.A., et al. (2018) Coexpression of CD44 and Ki-67 in Colons Neoplast. Arkhiv Patologii, 80, 27-36. [Google Scholar] [CrossRef] [PubMed]

为你推荐