UBE2C作为乳腺癌免疫相关生物标志物：基于多重数据库的研究

doi:10.24920/004340

摘要/Abstract

摘要： 目的利用基因表达综合数据库（Gene Expression Omnibus,GEO）筛选靶基因UBE2C,并基于癌症基因组图谱（Cancer Genome Atlas, TCGA）的多个公共生物信息学研究平台探讨UBE2C在乳腺癌中的预后价值及免疫相关性。
方法从GEO下载乳腺癌基因芯片表达数据集,分析获得差异表达基因（differentially expressed genes,DEGs）。通过构建和可视化DEG-蛋白相互作用网络获得枢纽基因。然后利用R语言、STRING和Cytoscape工具确定关键基因UBE2C,并利用外部数据集、TCGA和定量实时聚合酶链式反应（quantitative real-time polymerase chain reaction,qRT-PCR）验证UBE2C差异表达。使用R语言、TIMER和GSEA工具研究UBE2C在乳腺癌中的预后价值和免疫学相关性。
结果 GEO独立数据集、TCGA和qRT-PCR均证实UBE2C在乳腺癌组织中差异上调。预后分析显示UBE2C是一个独立的预后因素。UBE2C高表达降低乳腺癌组织中B细胞、CD4+T细胞、CD8+T细胞、巨噬细胞和髓系树突状细胞免疫浸润水平。UBE2C在乳腺癌中的表达与PDCD1、CD274和CTLA4的表达显著相关。同时,UBE2C的表达与肿瘤突变负荷水平和微卫星不稳定性水平呈显著正相关。基因集富集分析显示,在786个免疫相关基因集中UBE2C表达显著富集。
结论 UBE2C在乳腺癌组织中的表达可预测乳腺癌患者的生存和预后。此外,UBE2C与乳腺癌免疫微环境密切相关,其在乳腺癌中的表达可用于预测乳腺癌患者免疫治疗的效果。因此,UBE2C在乳腺癌的发生和进展中起着至关重要的作用,是一种潜在的免疫相关的预后生物标志物。

关键词: UBE2C, 乳腺癌, 生物标志物, 免疫, 生物信息学

Abstract: Objective To screen the target gene UBE2C and explore its prognostic value and immune correlation in breast cancer (BRCA) using multiple databases..
Methods The microarray expression datasets of BRCA were downloaded from the Gene Expresssion Omnibus database (GEO) and analyzed to obtain differentially expressed genes (DEGs). Hub genes were obtained by constructing and visualizing the protein-protein interaction network of DEGs. Then the key gene UBE2C was determined using R language, STRING, and Cytoscape, and the differential expression of UBE2C was verified using the external datasets, The Cancer Genome Atlas (TCGA) , and quantitative real-time PCR (qRT-PCR). The prognostic value and immunological correlation of UBE2C in BRCA were explored using R language, TIMER, and Gene Set Enrichment Analysis (GSEA).
Results The expression of UBE2C was differentially upregulated in BRCA, as verified by TCGA and qRT-PCR. Prognostic analysis revealed that UBE2C served as an independent prognostic factor. High expression of UBE2C was associated with decreased immune infiltration levels of B cells, CD4+ T cells, CD8+ T cells, macrophages, and myeloid dendritic cells in BRCA tissue. The expression of UBE2C in BRCA showed a significant correlation with PDCD1, CD274, and CTLA4 expressions. There was a positive correlation between the expression of UBE2C and the tumor mutational burden and microsatellite instability. GSEA demonstrated that UBE2C expression significantly enriched 786 immune-related gene sets.
Conclusions UBE2C expression in BRCA tissues can predict the survivals and prognosis of BRCA patients. Also, it is closely related to the BRCA immune microenvironment and can predict the effecacy of immunotherapy in BRCA patients. Therefore, UBE2C may be an potential immune-related prognostic biomarker for BRCA.

Key words: UBE2C, breast Cancer, biomarker, immune, bioinformatics

基金资助: 黑龙江省卫生健康委科研课题（20220202081049、2020-008）、哈尔滨医科大学第五附属医院科研基金（2020-003）

Yue Cui, Hong-Zhi Wang, Ye Song, Shuang Yang, Feng-Ying Sai, De-Jun Yu. UBE2C as an Immune-Related Biomarker for Breast Cancer: A Study Based on Multiple Databases[J/OL].Chinese Medical Sciences Journal, .DOI:10.24920/004340.[Epub ahead of print].

参考文献

1. Barzaman K, Karami J, Zarei Z, et al.Breast cancer: Biology, biomarkers, and treatments. Int Immunopharmacol 2020; 84 : 106535. doi: 10.1016/j.intimp.2020.106535.
2. Bray F, Laversanne M, Sung H.Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024; 74(3): 229-63. doi: 10.3322/caac.21834.
3. Zheng RS, Chen R, Han BF, et al. [Cancer incidence and mortality in China, 2022]. Zhong Hua Zhong Liu Za Zhi 2024; 46(3): 221-31. doi: 10.3760/cma.j.cn112152-20240119-00035. (Chinese)
4. Li Z, Chen Z, Hu G, et al.Roles of circular RNA in breast cancer: present and future. Am J Transl Res 2019; 11(7): 3945-54.
5. Liang G, Ling Y, Mehrpour M, et al.Autophagy-associated circRNA circCDYL augments autophagy and promotes breast cancer progression. Mol Cancer 2020; 19(1): 65. doi: 10.1186/s12943-020-01152-2.
6. Huang GZ, Chen ZQ, Wu J, et al.Pan-cancer analyses of the tumor microenvironment reveal that ubiquitin-conjugating enzyme E2C might be a potential immunotherapy target. J Immunol Res 2021; 9250207. doi: 10.1155/2021/9250207.
7. Mo CH, Gao L, Zhu XF, et al.The clinicopathological significance of UBE2C in breast cancer: a study based on immunohistochemistry, microarray and RNA-sequencing data. Cancer Cell Int 2017; 17: 83. doi: 10.1186/s12935-017-0455-1.
8. Wang Y, Wang J, Tang Q, et al.Identification of UBE2C as hub gene in driving prostate cancer by integrated bioinformatics analysis. PLoS One 2021; 16(2): e0247827. doi: 10.1371/journal.pone.0247827.
9. Li R, Pang XF, Huang ZG, et al.Overexpression of UBE2C in esophageal squamous cell carcinoma tissues and molecular analysis. BMC Cancer 2021; 21(1): 996. doi: 10.1186/s12885-021-08634-6.
10. Chiang AJ, Li CJ.UBE2C drives human cervical cancer progression and is positively modulated by mTOR. Biomolecules 2020; 11(1): 37. doi: 10.3390/biom11010037.
11. Li J, Zhi X, Shen X, et al.Depletion of UBE2C reduces ovarian cancer malignancy and reverses cisplatin resistance via downregulating CDK1. Biochem Bioph Res Co 2020; 523(2): 434-40. doi: 10.1016/j.bbrc.2019.12.058.
12. Liu Y, Huang F, Chen H, et al.Expression of UBE2C in lung adenocarcinoma based on database analysis and its clinical significance. Zhong Nan Da Xue Xue Bao Yi Xue Ban 2020; 45(9): 1044-52. doi: 10.11817/j.issn.1672-7347.2020.190189. (Article in English, Chinese)
13. Hao Z, Zhang H, Cowell J.Ubiquitin-conjugating enzyme UBE2C: molecular biology, role in tumorigenesis, and potential as a biomarker.Tumour Biol 2012; 33(3): 723-30. doi: 10.1007/s13277-011-0291-1.
14. Chen DT, Nasir A, Culhane A, et al.Proliferative genes dominate malignancy-risk gene signature in histologically-normal breast tissue. Breast Cancer Res Treat 2010; 119(2): 335-46. doi: 10.1007/s10549-009-0344-y.
15. Liu RZ, Graham K, Glubrecht DD, et al.Association of FABP5 expression with poor survival in triple-negative breast cancer: implication for retinoic acid therapy. Am J Pathol 2011; 178(3): 997-1008. doi: 10.1016/j.ajpath.2010.11.075.
16. Sinn BV, Fu C, Lau R, et al.SET_ER/PR: a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer. NPJ Breast Cancer 2019; 5 : 16. doi: 10.1038/s41523-019-0111-0.
17. Edgar R, Domrachev M, Lash AE.Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 2002; 30(1): 207-10. doi: 10.1093/nar/30.1.207.
18. Barrett T, Wilhite SE, Ledoux P, et al.NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res 2013; 41(Database issue): D991-5. doi: 10.1093/nar/gks1193.
19. Zhang X, Zhang W, Jiang Y, et al.Identification of functional lncRNAs in gastric cancer by integrative analysis of GEO and TCGA data. J Cell Biochem 2019; 120(10): 17898-911. doi: 10.1002/jcb.29058.
20. Sun J, Huang J, Lan J, et al.Overexpression of CENPF correlates with poor prognosis and tumor bone metastasis in breast cancer. Cancer Cell Int 2019; 19: 264. doi: 10.1186/s12935-019-0986-8.
21. Yu G, Wang LG, Han Y, et al.clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 2012; 16(5): 284-7. doi: 10.1089/omi.2011.0118.
22. Mootha VK, Lindgren CM, Eriksson KF, et al.PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet 2003; 34(3): 267-73. doi: 10.1038/ng1180.
23. Subramanian A, Tamayo P, Mootha VK, et al.Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 2005; 102(43): 15545-50. doi: 10.1073/pnas.0506580102.
24. Szklarczyk D, Gable AL, Nastou KC, et al.The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res 2021; 49(D1): D605-12. doi: 10.1093/nar/gkaa1074.
25. von Mering C, Huynen M, Jaeggi D, et al. STRING: a database of predicted functional associations between proteins. Nucleic Acids Res 2003; 31(1): 258-61. doi: 10.1093/nar/gkg034.
26. Shannon P, Markiel A, Ozier O, et al.Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003; 13(11): 2498-504. doi: 10.1101/gr.1239303.
27. Chin CH, Chen SH, Wu HH, et al. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Sys Bio2014; 8 Suppl 4 (Suppl 4): S11. doi: 10.1186/1752-0509-8-s4-s11.
28. Gruosso T, Mieulet V, Cardon M, et al.Chronic oxidative stress promotes H2AX protein degradation and enhances chemosensitivity in breast cancer patients. EMBO Mol Med 2016; 8(5): 527-49. doi: 10.15252/emmm.201505891.
29. Liu Z, Mi M, Li X, et al.A lncRNA prognostic signature associated with immune infiltration and tumour mutation burden in breast cancer. J Cell Mol Med 2020; 24(21): 12444-56. doi: 10.1111/jcmm.15762.
30. Xiong Y, Yuan L, Xiong J, et al.An outcome model for human bladder cancer: A comprehensive study based on weighted gene co-expression network analysis. J Cell Mol Med 2020; 24(3): 2342-55. doi: 10.1111/jcmm.14918.
31. Jeong SH, Kim RB, Park SY, et al.Nomogram for predicting gastric cancer recurrence using biomarker gene expression. Eur J Surg Oncol 2020; 46(1): 195-201. doi: 10.1016/j.ejso.2019.09.143.
32. Becht E, Giraldo NA, Lacroix L, et al.Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression. Genome Biol 2016; 17(1): 218. doi: 10.1186/s13059-016-1070-5.
33. Sturm G, Finotello F, Petitprez F, et al.Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics (Oxford, England) 2019; 35(14): i436-45. doi: 10.1093/bioinformatics/btz363.
34. Racle J, de Jonge K, Baumgaertner P, et al. Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data. Elife 2017; 6: e26476. doi: 10.7554/eLife.26476.
35. Li T, Fu J, Zeng Z, et al.TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res 2020; 48(W1): W509-14. doi: 10.1093/nar/gkaa407.
36. Dastsooz H, Cereda M.A comprehensive bioinformatics analysis of UBE2C in cancers. Int J Mol Sci 2019; 20(9). doi: 10.3390/ijms20092228.
37. Jiang X, Yuan Y, Tang L, et al.Comprehensive pan-cancer analysis of the prognostic and immunological roles of the METTL3/lncRNA-SNHG1/miRNA-140-3p/UBE2C Axis. Front Cell Dev Biol 2021; 9 : 765772. doi: 10.3389/fcell.2021.765772.
38. Lu ZN, Song J, Sun TH, et al.UBE2C affects breast cancer proliferation through the AKT/mTOR signaling pathway. Chin Med J (Engl) 2021; 134(20): 2465-74. doi: 10.1097/cm9.0000000000001708.
39. Xiang C, Yan HC.Ubiquitin conjugating enzyme E2 C (UBE2C) may play a dual role involved in the progression of thyroid carcinoma. Cell Death Discov 2022; 8(1): 130. doi: 10.1038/s41420-022-00935-4.
40. Huang R, Liu J, Li H, et al.Identification of hub genes and their correlation with immune infiltration cells in hepatocellular carcinoma based on GEO and TCGA databases. Front Genet 2021; 12 : 647353. doi: 10.3389/fgene.2021.647353.

[1]	马俊杰, 张磊, 陆进, 张浩轩. PPP1R14A基因与头颈鳞状细胞癌免疫治疗耐药相关：综合分析单细胞和批量测序结果[J]. Chinese Medical Sciences Journal, 2024, 39(2): 111-121.
[2]	李浩令, 王俊贤, 戴恒文, 刘俊杰, 刘子扬, 邹明远, 张雷, 王文锐. 非凋亡调节性细胞死亡基因对肺腺癌预后的预测价值及其生物学功能[J]. Chinese Medical Sciences Journal, 2023, 38(3): 178-190.
[3]	王海军, 陈炜, 王宏志, 赵鹤龄, 王东浩, 隆云, 邢学忠, 北京肿瘤学会重症医学专业委员会. 肿瘤重症患者急性呼吸衰竭专家共识（2023版）[J]. Chinese Medical Sciences Journal, 2023, 38(3): 163-177.
[4]	陆进, 安韶光, 马俊杰, 杨月, 张磊, 俞鹏, 陶恒, 陈云帆, 张浩轩. TOP2A基因对预测肝细胞癌预后的作用[J]. Chinese Medical Sciences Journal, 2022, 37(4): 331-339.
[5]	徐文琴, 叶静静, 陈天兵. 鉴定并验证与肺腺癌预后相关的新的miRNA-mRNA调节网络[J]. Chinese Medical Sciences Journal, 2022, 37(1): 31-43.
[6]	杨威, 张梅. 抗癌治疗中对心脏毒性效应具有潜在预测价值的生物标志物[J]. Chinese Medical Sciences Journal, 2021, 36(4): 333-341.
[7]	蒋平, 孙桃桃, 陈存武, 黄仁术, 钟枝梅, 娄新建, 刘港, 汪林, 左瑞华. 基于生物信息学分析肾透明细胞癌预后相关关键基因[J]. Chinese Medical Sciences Journal, 2021, 36(2): 127-134.
[8]	王轶,吴婵媛,王迁. 声带竹节病 —— 14例临床病例研究[J]. Chinese Medical Sciences Journal, 2021, 36(1): 43-49.
[9]	张帆, 钟斯然, 杨斯漫, 韦宇婷, 王竞静, 黄金兰, 吴登攀, 钟振国. 基于加权基因共表达网络分析阿尔茨海默病相关核心靶点[J]. Chinese Medical Sciences Journal, 2020, 35(4): 330-341.
[10]	曹剑, 王国蓉, 王志伟, 金征宇. CT纹理分析：结直肠癌KRAS基因突变状态评估的潜在生物标志物[J]. Chinese Medical Sciences Journal, 2020, 35(4): 306-314.
[11]	曾晓淇, 姜珊珊, 彭远洋, 刘民锋, 叶长生, 董建宇. 曲妥珠单抗致重度血小板减少症一例及文献回顾[J]. Chinese Medical Sciences Journal, 2020, 35(4): 377-382.
[12]	高善玉, 陆珺, 赵重波. 一例合并抗谷氨酸脱羧酶相关脑炎的僵人综合征的年轻女性[J]. Chinese Medical Sciences Journal, 2020, 35(4): 387-390.
[13]	王站, 王旭, 王文达, 郑国洋, 郭浩, 张玉石. 术前中性粒细胞与淋巴细胞比值预测可切除泌尿系肿瘤预后的价值：系统综述和荟萃分析[J]. Chinese Medical Sciences Journal, 2020, 35(3): 262-271.
[14]	吴建强, 秦伟伟, 潘利, 王小蓉, 张彪, 单广良, 高友鹤. 中国不同地区健康人尿液蛋白质组的地域差异[J]. Chinese Medical Sciences Journal, 2019, 34(3): 157-167.
[15]	吴焱, 宋歌, 魏春波, 伦文辉. 人类免疫缺陷病毒-1感染急性期双侧面神经麻痹合并脑膜炎1例[J]. Chinese Medical Sciences Journal, 2019, 34(1): 55-59.

优先出版

当期目次

过刊浏览

虚拟专题

作者中心

评阅者中心