• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

利用生物信息学分析鉴定食管腺癌的预后危险因素

Identification of prognostic risk factors for esophageal adenocarcinoma using bioinformatics analysis.

作者信息

Dong Zhiyu, Wang Junwen, Zhan Tingting, Xu Shuchang

机构信息

Department of Gastroenterology, Tongji Hospital, Tongji University School of Medicine, Shanghai, China,

出版信息

Onco Targets Ther. 2018 Jul 25;11:4327-4337. doi: 10.2147/OTT.S156716. eCollection 2018.

DOI:10.2147/OTT.S156716
PMID:30100738
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6065599/
Abstract

PURPOSE

Esophageal adenocarcinoma (EAC) is the most common type of esophageal cancer in Western countries. It is usually detected at an advanced stage and has a poor prognosis. The aim of this study was to identify key genes and miRNAs in EAC.

METHODS

The mRNA microarray data sets GSE1420, GSE26886, and GSE92396 and miRNA data set GSE16456 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were obtained using R software. Functional enrichment analysis was performed using the DAVID database. A protein-protein interaction (PPI) network and functional modules were established using the STRING database and visualized by Cytoscape. The targets of the DEMs were predicted using the miRecords database, and overlapping genes between DEGs and targets were identified. The prognosis-related overlapping genes were identified using Kaplan-Meier analysis and Cox proportional hazard analysis based on The Cancer Genome Atlas (TCGA) database. The differential expression of these prognosis-related genes was validated using the expression matrix in the TCGA database.

RESULTS

Seven hundred and fifteen DEGs were obtained, consisting of 313 upregulated and 402 downregulated genes. The PPI network consisted of 281 nodes; 683 edges were constructed and 3 functional modules were established. Forty-four overlapping genes and 56 miRNA- mRNA pairs were identified. Five genes, , , , , and , were associated with overall survival or relapse-free survival. and were found to be independent prognostic indicators for overall survival, and , , and were considered independent prognostic indicators for relapse-free survival. Among them, the overexpression of and and lower expression of were also identified in EAC tissues based on the expression matrix in the TCGA database.

CONCLUSION

These prognosis-related genes and differentially expressed miRNA have provided potential biomarkers for EAC diagnosis and treatment.

摘要

目的

食管腺癌（EAC）是西方国家最常见的食管癌类型。它通常在晚期被检测到，预后较差。本研究的目的是鉴定EAC中的关键基因和微小RNA（miRNA）。

方法

从基因表达综合数据库下载mRNA微阵列数据集GSE1420、GSE26886和GSE92396以及miRNA数据集GSE16456。使用R软件获得差异表达基因（DEG）和差异表达miRNA（DEM）。使用DAVID数据库进行功能富集分析。使用STRING数据库建立蛋白质-蛋白质相互作用（PPI）网络和功能模块，并通过Cytoscape进行可视化。使用miRecords数据库预测DEM的靶标，并鉴定DEG与靶标之间的重叠基因。基于癌症基因组图谱（TCGA）数据库，使用Kaplan-Meier分析和Cox比例风险分析鉴定与预后相关的重叠基因。使用TCGA数据库中的表达矩阵验证这些与预后相关基因的差异表达。

结果

共获得715个DEG，其中313个基因上调，402个基因下调。PPI网络由281个节点组成；构建了683条边，并建立了3个功能模块。鉴定出44个重叠基因和56个miRNA- mRNA对。5个基因， 、 、 、 和 ，与总生存期或无复发生存期相关。 和 被发现是总生存期的独立预后指标， 、 和 被认为是无复发生存期的独立预后指标。其中，基于TCGA数据库中的表达矩阵，在EAC组织中也鉴定出 和 的过表达以及 的低表达。

结论

这些与预后相关的基因和差异表达的miRNA为EAC的诊断和治疗提供了潜在的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/b8b7e9a6c4ac/ott-11-4327Fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/a390ceea25c4/ott-11-4327Fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/be90ac86abde/ott-11-4327Fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/3f0a1b5e2a56/ott-11-4327Fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/69e88a0fac58/ott-11-4327Fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/8489c432f6ba/ott-11-4327Fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/d78f7790c90d/ott-11-4327Fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/b8b7e9a6c4ac/ott-11-4327Fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/a390ceea25c4/ott-11-4327Fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/be90ac86abde/ott-11-4327Fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/3f0a1b5e2a56/ott-11-4327Fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/69e88a0fac58/ott-11-4327Fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/8489c432f6ba/ott-11-4327Fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/d78f7790c90d/ott-11-4327Fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0c0/6065599/b8b7e9a6c4ac/ott-11-4327Fig7.jpg

相似文献

1
Identification of prognostic risk factors for esophageal adenocarcinoma using bioinformatics analysis.利用生物信息学分析鉴定食管腺癌的预后危险因素
Onco Targets Ther. 2018 Jul 25;11:4327-4337. doi: 10.2147/OTT.S156716. eCollection 2018.
2
Identification of a transcription factor-microRNA network in esophageal adenocarcinoma through bioinformatics analysis and validation through qRT-PCR.通过生物信息学分析鉴定食管腺癌中转录因子-微小RNA网络并通过qRT-PCR进行验证。
Cancer Manag Res. 2019 Apr 18;11:3315-3326. doi: 10.2147/CMAR.S201274. eCollection 2019.
3
Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis.采用 miRNA-mRNA 整合分析鉴定预测 Barrett 食管进展为食管腺癌的 miRNA 和基因。
PLoS One. 2021 Nov 24;16(11):e0260353. doi: 10.1371/journal.pone.0260353. eCollection 2021.
4
Identification of potential key genes in esophageal adenocarcinoma using bioinformatics.利用生物信息学鉴定食管腺癌中的潜在关键基因
Exp Ther Med. 2019 Nov;18(5):3291-3298. doi: 10.3892/etm.2019.7973. Epub 2019 Sep 5.
5
Identification of genes and pathways in esophageal adenocarcinoma using bioinformatics analysis.利用生物信息学分析鉴定食管腺癌中的基因和信号通路。
Biomed Rep. 2018 Oct;9(4):305-312. doi: 10.3892/br.2018.1134. Epub 2018 Jul 25.
6
Identification of Differentially Expressed Genes and miRNAs Associated with Esophageal Squamous Cell Carcinoma by Integrated Analysis of Microarray Data.基于基因芯片数据的综合分析鉴定食管鳞癌差异表达基因和 miRNA。
Biomed Res Int. 2020 Jul 1;2020:1980921. doi: 10.1155/2020/1980921. eCollection 2020.
7
Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis.生物信息学分析鉴定胃癌中具有预后价值的枢纽基因。
World J Surg Oncol. 2018 Jun 19;16(1):114. doi: 10.1186/s12957-018-1409-3.
8
Biomarker identification and trans-regulatory network analyses in esophageal adenocarcinoma and Barrett's esophagus.食管腺癌和巴雷特食管中的生物标志物鉴定和反式调控网络分析。
World J Gastroenterol. 2019 Jan 14;25(2):233-244. doi: 10.3748/wjg.v25.i2.233.
9
Identification of biomarkers associated with diagnosis and prognosis of gastroesophageal junction adenocarcinoma-a study based on integrated bioinformatics analysis in GEO and TCGA database.基于 GEO 和 TCGA 数据库的综合生物信息学分析鉴定胃食管结合部腺癌诊断和预后相关的生物标志物。
Medicine (Baltimore). 2020 Dec 18;99(51):e23605. doi: 10.1097/MD.0000000000023605.
10
Identification of key genes associated with esophageal adenocarcinoma based on bioinformatics analysis.基于生物信息学分析鉴定与食管腺癌相关的关键基因
Ann Transl Med. 2021 Dec;9(23):1711. doi: 10.21037/atm-21-4015.

引用本文的文献

1
Roles and therapeutic potential of the SLC family in prostate cancer-literature review.SLC家族在前列腺癌中的作用及治疗潜力——文献综述
BMC Urol. 2025 Feb 18;25(1):32. doi: 10.1186/s12894-025-01714-w.
2
TENT5A mediates the cancer-inhibiting effects of EGR1 by suppressing the protein stability of RPL35 in hepatocellular carcinoma.TENT5A通过抑制肝细胞癌中RPL35的蛋白质稳定性来介导EGR1的癌症抑制作用。
Cell Oncol (Dordr). 2024 Dec;47(6):2247-2264. doi: 10.1007/s13402-024-01014-9. Epub 2024 Nov 21.
3
The emerging role of FAM46C as a biomarker and therapeutic target in gastric adenocarcinoma.

本文引用的文献

1
Expression Levels of KMT2C and SLC20A1 Identified by Information-theoretical Analysis Are Powerful Prognostic Biomarkers in Estrogen Receptor-positive Breast Cancer.通过信息理论分析确定的KMT2C和SLC20A1表达水平是雌激素受体阳性乳腺癌强有力的预后生物标志物。
Clin Breast Cancer. 2017 Jun;17(3):e135-e142. doi: 10.1016/j.clbc.2016.11.005. Epub 2016 Nov 23.
2
Differential role of microRNAs in the pathogenesis and treatment of Esophageal cancer.微小 RNA 在食管癌发病机制和治疗中的差异作用。
Biomed Pharmacother. 2016 Aug;82:509-19. doi: 10.1016/j.biopha.2016.05.009. Epub 2016 Jun 4.
3
Potential biomarkers for esophageal cancer.
FAM46C在胃腺癌中作为生物标志物和治疗靶点的新作用。
J Gastrointest Oncol. 2024 Aug 31;15(4):1870-1879. doi: 10.21037/jgo-24-105. Epub 2024 Aug 2.
4
Co‑expression of and is associated with poor prognosis, and is required for the survival of ALDH1‑positive pancreatic cancer stem cells.[具体基因名称1]和[具体基因名称2]的共表达与不良预后相关，并且[具体基因名称2]是醛脱氢酶1阳性胰腺癌干细胞存活所必需的。
Oncol Lett. 2024 Jul 5;28(3):426. doi: 10.3892/ol.2024.14558. eCollection 2024 Sep.
5
Dissecting the Puzzling Roles of FAM46C: A Multifaceted Pan-Cancer Tumour Suppressor with Increasing Clinical Relevance.剖析FAM46C令人困惑的作用：一种具有越来越高临床相关性的多面性泛癌肿瘤抑制因子
Cancers (Basel). 2024 Apr 27;16(9):1706. doi: 10.3390/cancers16091706.
6
SLC20A1 is a prospective prognostic and therapy response predictive biomarker in head and neck squamous cell carcinoma.SLC20A1 是头颈部鳞状细胞癌有前景的预后和治疗反应预测性生物标志物。
Aging (Albany NY). 2024 Feb 26;16(5):4423-4444. doi: 10.18632/aging.205597.
7
TENT5A Increases Glioma Malignancy and Promotes its Progression.TENT5A增加胶质瘤恶性程度并促进其进展。
Recent Pat Anticancer Drug Discov. 2025;20(1):45-54. doi: 10.2174/0115748928280901231206102637.
8
A new pyroptosis-related signature for predicting the immune status and injury of liver ischemia-reperfusion.一种用于预测肝脏缺血再灌注免疫状态和损伤的新的焦亡相关特征。
Am J Transl Res. 2022 Oct 15;14(10):7566-7577. eCollection 2022.
9
High expression of SLC20A1 is less effective for endocrine therapy and predicts late recurrence in ER-positive breast cancer.SLC20A1 高表达对内分泌治疗效果不佳，并预测 ER 阳性乳腺癌的晚期复发。
PLoS One. 2022 May 23;17(5):e0268799. doi: 10.1371/journal.pone.0268799. eCollection 2022.
10
Construction and evaluation of a nomogram for predicting survival in patients with lung cancer.构建并评估列线图预测肺癌患者生存情况
Aging (Albany NY). 2022 Mar 23;14(6):2775-2792. doi: 10.18632/aging.203974.
食管癌的潜在生物标志物。
Springerplus. 2016 Apr 16;5:467. doi: 10.1186/s40064-016-2119-3. eCollection 2016.
4
Profiling of circulating microRNAs in patients with Barrett's esophagus and esophageal adenocarcinoma.巴雷特食管和食管腺癌患者循环微RNA分析
J Gastroenterol. 2016 Jun;51(6):560-70. doi: 10.1007/s00535-015-1133-5. Epub 2015 Nov 19.
5
The Role of Stroma in Tumor Development.基质在肿瘤发展中的作用。
Cancer J. 2015 Jul-Aug;21(4):250-3. doi: 10.1097/PPO.0000000000000127.
6
Early growth response 4 is involved in cell proliferation of small cell lung cancer through transcriptional activation of its downstream genes.早期生长反应因子4通过转录激活其下游基因参与小细胞肺癌的细胞增殖。
PLoS One. 2014 Nov 20;9(11):e113606. doi: 10.1371/journal.pone.0113606. eCollection 2014.
7
The extracellular matrix modulates the hallmarks of cancer.细胞外基质调节癌症的特征。
EMBO Rep. 2014 Dec;15(12):1243-53. doi: 10.15252/embr.201439246. Epub 2014 Nov 8.
8
The Cancer Genome Atlas Pan-Cancer analysis project.癌症基因组图谱泛癌分析项目。
Nat Genet. 2013 Oct;45(10):1113-20. doi: 10.1038/ng.2764.
9
Type IV collagen stimulates pancreatic cancer cell proliferation, migration, and inhibits apoptosis through an autocrine loop.IV 型胶原通过自分泌环刺激胰腺癌细胞增殖、迁移，并抑制细胞凋亡。
BMC Cancer. 2013 Mar 26;13:154. doi: 10.1186/1471-2407-13-154.
10
Wdr66 is a novel marker for risk stratification and involved in epithelial-mesenchymal transition of esophageal squamous cell carcinoma.Wdr66 是食管鳞癌风险分层的新型标志物，并且参与上皮-间充质转化。
BMC Cancer. 2013 Mar 21;13:137. doi: 10.1186/1471-2407-13-137.