[1]陈 冉,王维伊,杨翊柠.基于TCGA 数据库分析乳腺癌组织RBP7 mRNA 表达与肿瘤免疫细胞浸润及预后的相关性[J].现代检验医学杂志,2024,39(02):75-80+180.[doi:10.3969/j.issn.1671-7414.2024.02.014]
　CHEN Ran,WANG Weiyi,YANG Yining.Correlation of RBP7 mRNA Expression in Breast Cancer Tissues with Tumor Immune Cell Infiltration and Prognosis Based on TCGA Database[J].Journal of Modern Laboratory Medicine,2024,39(02):75-80+180.[doi:10.3969/j.issn.1671-7414.2024.02.014]
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基于TCGA 数据库分析乳腺癌组织RBP7 mRNA 表达与肿瘤免疫细胞浸润及预后的相关性()
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《现代检验医学杂志》[ISSN:/CN:]

卷:
第39卷
期数:
2024年02期
页码:
75-80+180
栏目:
论著
出版日期:
2024-03-31

文章信息/Info

Title:
Correlation of RBP7 mRNA Expression in Breast Cancer Tissues with Tumor Immune Cell Infiltration and Prognosis Based on TCGA Database
文章编号:
1671-7414（2024）02-075-07
作者:
陈 冉; 王维伊; 杨翊柠
（江苏省肿瘤医院，江苏省肿瘤防治研究所，南京医科大学附属肿瘤医院检验科，南京210009）
Author(s):
CHEN Ran;  WANG Weiyi;  YANG Yining
（Department of Clinical Laboratory, Jiangsu Cancer Hospital，Jiangsu Institute of Cancer Research，the Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, China）
关键词:
乳腺癌; 癌症基因组图谱; 视黄醇结合蛋白7; 肿瘤浸润免疫细胞
分类号:
R737.9；R730.43
DOI:
10.3969/j.issn.1671-7414.2024.02.014
文献标志码:
A
摘要:
目的　通过生物信息学的方法探讨视黄醇结合蛋白7（retinol binding protein 7，RBP7）在乳腺癌中的作用。方法　使用R 语言基于癌症基因组图谱（the cancer genome atlas，TCGA）数据库和人类蛋白质图谱（the human protein atlas，HPA）数据库探索基因RBP7 在乳腺癌组织中的差异表达。通过Kaplan-Meier 生存分析和受试者工作特征（receiveroperating characteristic，ROC）曲线，评估RBP7 与乳腺癌临床数据的关系。基于TCGA 数据库分析RBP7 高低表达分组与不同肿瘤浸润免疫细胞（tumor-infiltrating immune cells，TIICs）的相关性。基因组富集分析（gene set enrichmentanalysis，GSEA）评估RBP7 在与表型相关度排序的基因表中的分布趋势。结果　与癌旁组织相比，乳腺癌中RBP7mRNA 表达水平下调，该分子表达在细胞核中。ROC 曲线分析显示RBP7 诊断乳腺癌的曲线下面积（area under curve，AUC）是0.943（95% CI：0.926 ～ 0.960），RBP7 的最佳截断值是6.29，敏感度和特异度分别为82.32%，93.69%。Kaplan-Meier 生存分析显示RBP7 低表达与乳腺癌患者的总生存率相关（HR=0.68，95% CI：0.49 ～ 0.93，P=0.017），RBP7 是乳腺癌发生的独立危险因素。Spearman 相关性揭示RBP7 与乳腺癌中pDC 细胞和NK 细胞呈正相关（r=0.290，0.253，均P<0.05），与Th2 细胞呈负相关(r=-0.217，P<0.05)。GSEA 表明RBP7 富集在脂肪生成、核糖体、肽配体结合受体、钙信号途径等通路中（均P <0.001）。结论　RBP7 影响乳腺癌的发生发展，可能成为乳腺癌潜在生物标志物和治疗靶点。
Abstract:
Objective　To explore the role of retinol binding protein 7 (RBP7) in breast cancer by bioinformatics. Methods　R sofrware was used to explore the differential expression of the RBP7 gene in breast cancer by the cancer genome atlas (TCGA) dataset and the human protein atlas (HPA). Relationship between RBP7 and clinical data of breast cancer was evaluated by Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Correlation between high and low RBP7 expression groups and different tumor-infiltrating immune cells (TIICs) were analyzed based on the TCGA database. Gene set enrichment analysis (GSEA) was used to assess the distribute trends of RBP7 in gene tables sorted by phenotypic relatedness. Results　RBP7 mRNA expression levels were down-regulated in breast cancer compared to paracancerous tissues, which were expressed in the nucleus. ROC curve analysis showed that the area under curve (AUC) of RBP7 for the diagnosis of breast cancer was 0.943 (95% CI: 0.926 ～ 0.960), and the best cut-off value of RBP7 was 6.29, with a sensitivity and specificity of 82.32% and 93.69%, respectively. Kaplan-Meier survival analysis showed that low expression of RBP7 was associated with overall survival rate in breast cancer patients (HR=0.68, 95% CI: 0.49 ～ 0.93, P=0.017), indicating that RBP7 was an independent risk factor for breast cancer. Spearman correlation showed that RBP7 was positively associated with pDC cells and NK cells (r=0.290, 0.253, all P<0.05), and negatively associated with Th2 cells (r=-0.217, P<0.05) in breast cancer. GSEA showed that RBP7 was enriched in pathways such as adipogenesis, ribosome, peptiden ligand binding receptors, and calcium signaling pathway (all P<0.001). Conclusion　RBP7 affects the occurrence and development of breast cancer, which may be a potential biomarker and therapeutic target for breast cancer.

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备注/Memo

备注/Memo:
基金项目： 江苏省卫生健康委科研项目（M2022106）：tRF-17-79MP9PP 作为miR-18a-5p 分子海绵调控THBS1/TGF-β1/Smad3 信号轴介导乳腺癌发生发展的机制研究。
作者简介：陈冉(1986-)，女，本科，主管技师，主要从事临床检验诊断学相关研究，E-mail: 28692095@qq.com。
通讯作者：杨翊柠(1988-)，女，硕士，主管技师，主要从事临床检验诊断学相关研究，E-mail:neko4713@live.cn。
更新日期/Last Update: 2024-03-15