吉林大学学报(医学版) ›› 2021, Vol. 47 ›› Issue (2): 438-452.doi: 10.13481/j.1671-587X.20210225

• 临床研究 • 上一篇    下一篇

基于m6A调节基因表达水平对子宫内膜癌免疫浸润及其预后影响的生物信息学分析

郑兰1,2,朴松哲3,徐然1,王馨悦1,王艺璇1,林贞花1(),杨洋1()   

  1. 1.延边大学医学院病理学教研室 吉林省科技厅妇科肿瘤生物信息学重点实验室,吉林 延吉 133002
    2.温州医科大学附属台州医院妇产科,浙江 临海 317005
    3.温州医科大学附属台州医院 泌尿外科,浙江 临海 317005
  • 收稿日期:2020-10-14 出版日期:2021-03-28 发布日期:2021-03-25
  • 通讯作者: 林贞花,杨洋 E-mail:zhlin720@ybu.edu.cn;yangyang@ybu.edu.cn
  • 作者简介:郑 兰(1982-),女,吉林省延吉市人,主治医师,在读博士研究生,主要从事肿瘤基础方面的研究。
  • 基金资助:
    国家自然科学基金地区基金项目(31760313);中央引导地方科技发展资金项目(202002021JC)

Bioinformatics analysis based on effect of expression levels of m6A regulators on immune infiltration and prognosis of uterine corpus endometrial carcinoma

Lan ZHENG1,2,Songzhe PIAO3,Ran XU1,Xinyue WANG1,Yixuan WANG1,Zhenhua LIN1(),Yang YANG1()   

  1. 1.Department of Pathology,Key Laboratory of Gynecologic Tumor Bioinformatics,Jilin Provincial Science and Technology Department,College of Medical Sciences,Yanbian University,Yanji 133002,China
    2.Department of Obstetrics and Gynecology,Affiliated Taizhou Hospital,Wenzhou Medical University,Linhai 317005,China
    3.Department of Urology,Affiliated Taizhou Hospital,Wenzhou Medical University,Linhai 317005,China
  • Received:2020-10-14 Online:2021-03-28 Published:2021-03-25
  • Contact: Zhenhua LIN,Yang YANG E-mail:zhlin720@ybu.edu.cn;yangyang@ybu.edu.cn

摘要: 目的

通过生物信息学工具探讨20个m6A调节基因在子宫内膜癌(UCEC)组织中的表达水平并筛选与预后有关的核心基因,阐明核心基因与免疫浸润程度的关系。

方法

利用肿瘤基因组图谱(TCGA)数据库下载符合本研究要求的547例UCEC和35例癌旁组织中m6A调节基因的转录组数据、临床病理指标和生存期数据;利用基因表达汇编(GEO)数据库下载GSE17025芯片数据,包含81例UCEC样本和12例正常子宫内膜样本。利用基因表达分析工具(GEO2R)和R软件筛选差异表达的m6A调节基因,进一步对差异表达基因(DEGs)进行生存分析和独立预后分析,选取与UCEC患者总体生存期(OS)关联最强的DEGs作为核心基因;应用STRING数据库构建蛋白互作(PPI)网络,采用R软件对DEGs进行相关性分析;利用UALCAN数据库分析核心基因表达水平与UCSC不同临床病理学指标的关联性;应用肿瘤免疫评估资源(TIMER)数据库和基因表达谱数据动态分析(GEPIA)数据库研究核心基因与肿瘤免疫浸润程度及免疫浸润标记物的相关性;利用Kaplan-Meier Plotter数据库基于免疫细胞亚组中核心基因的表达水平进行生存分析。

结果

大多数m6A调节基因在UCEC组织和癌旁组织样本中的表达水平比较差异有统计学意义(P<0.05),其中IGF2BP3 mRNA在UCEC组织中呈高水平表达(P<0.05),IGF2BP3 mRNA高水平表达患者OS较IGF2BP3 mRNA低水平表达患者缩短(P<0.05),且单因素[风险比(HR)=1.106,95%可信区间(CI):1.019~1.202,P=0.016]和多因素Cox回归分析结果(HR=1.097,95% CI:1.003~1.199,P=0.043)均显示IGF2BP3可作为评估患者OS的独立危险因子;IGF2BP3 mRNA在晚期、绝经前UCEC患者肿瘤组织和子宫内膜浆液性腺癌组织中呈高水平表达(P<0.05);IGF2BP3 mRNA表达水平与UCEC中CD8+T细胞(r=0.126,P<0.05)、中性粒细胞(r=0.324,P<0.01)和树突状细胞(DC)(r=0.120,P<0.05)免疫浸润程度呈正相关关系;IGF2BP3 mRNA表达水平与UCEC中肿瘤相关巨噬细胞(TAMs)、巨噬细胞(M1和M2)、辅助性T细胞(Th1、Th2和Th17)和调节性T细胞(Treg)标记物呈正相关关系(0.1≤r ≤1.0,P<0.05);在B细胞、CD8+T细胞、Treg细胞和Th2 细胞低浸润亚组中IGF2BP3 mRNA高水平表达患者OS比IGF2BP3 mRNA低水平表达患者短(P<0.05)。

结论

IGF2BP3 mRNA表达水平在UCEC组织中明显升高,IGF2BP3 mRNA高水平表达可促进UCEC组织中免疫浸润,提示UCEC患者预后不良;IGF2BP3可能成为判定UCEC患者预后的分子标志物和新的治疗靶点。

关键词: 子宫内膜癌, N6-甲基腺嘌呤, 免疫浸润, 生物信息学

Abstract: Objective

To analyze the expression levels of 20 m6A-related genes in uterine corpus endometrial carcinoma (UCEC) tissue with the bioinformatics methods data and to screen the hub genes related to prognosis, and to explore the correlations between the expression levels of hub genes and the immune infiltration degrees in UCEC.

Methods

The transcriptome sequencing, clinicopathological and survival data of 547 UCEC and 35 normal controls were obtained from The Cancer Genome Atlas (TCGA) database. The GSE17025 datasets that contained 81 samples of UCEC and 12 samples of adjacent cancer tissue were downloaded from Gene Expression Omnibus (GEO) database. Using the GEO2R online analysis tools and R software, the differentially expressed genes (DEGs) between UCEC tissue and adjacent normal tissue were identified. Survival analysis and Cox regression were carried out for DEGs. The genes that were significantly associated with overall survival (OS) were identified as the hub genes; protein-protein interaction (PPI) network of 20 m6A regulators and correlation analysis of the DEGs were performed using STRING database and R software, respectively. The correlations between the expression levels of hub genes and the clinicopathological features of UCEC were analyzed using the UALCAN database; the correlations between the target genes and immune infiltration degrees and the markers of immune cells were explored via Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA) database. Furthermore, survival analysis based on the expression of target genes was conducted in the related immune cell subgroup using Kaplan-Meier Plotter database.

Results

Most of the 20 m6A regulators were significantly differentially expressed in UCEC tissue compared with the adjacent normal tissue (P<0.05); the IGF2BP3 mRNA was highly expressed in UCEC tissue (P<0.05).High IGF2BP3 expression was correlated with shorter OS (P<0.05). Furthermore, both univariate [hazard ratio (HR)=1.106, 95% condifence interval (CI): 1.019-1.202, P=0.016] and multivariate (HR=1.097, 95% CI: 1.003-1.199,P=0.043) Cox regression analysis results showed that IGF2BP3 could be used as an independent risk factor for OS evaluation. IGF2BP3 mRNA exhibited higher expression in the UCEC tissue of advanced stage and pre-menopause patients and endometrial serous adenocarcinoma tissue (P<0.05). The expression level of IGF2BP3 mRNA was positively associated with the degrees of immune infiltration by CD8+T cells (r=0.126, P<0.05),neutrophils (r=0.324,P<0.01) and dendritic cells (DC)(r=0.120, P<0.05) in UCEC. The expression level of IGF2BP3 mRNA was positively associated with the markers of tumor-associated macrophages(TAMs), macrophages (M1 and M2), helper T cells (Th1, Th2, and Th17) and regulatory T cells (Treg) in UCEC (0.1≤r ≤1,P<0.05). The patients with high expression of IGF2BP3 mRNA had a shorter OS than those with low expression of IGF2BP3 mRNA in the low infiltration subgroup of B cells, Treg cells, and Th2 cells (P<0.05).

Conclusion

The expression level of IGF2BP3 mRNA in UCEC tissue is significantly increased, which promotes the immune infiltration of UCEC and indicates the poor prognosis of UCEC patients. IGF2BP3 could be served as a prognostic molecular biomarker of UCEC and indicate the poor prognosis of UCEC patients, and may become a novel target for cancer therapy.

Key words: endometrial cancer, N6-methyladenosine, immune infiltration, bioinformatics

中图分类号: 

  • R737.33