文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
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
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
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 @ 2025

Prediction and analysis of novel key genes ITGAX, LAPTM5, SERPINE1 in clear cell renal cell carcinoma through bioinformatics analysis.

作者信息

Sui Yingli, Lu Kun, Fu Lin

机构信息

Institute of Chronic Disease, School of Basic Medicine, Qingdao University, Qingdao, Shandong, China.

出版信息

PeerJ. 2021 Apr 20;9:e11272. doi: 10.7717/peerj.11272. eCollection 2021.


DOI:10.7717/peerj.11272
PMID:33976979
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8063882/
Abstract

BACKGROUND: Clear Cell Renal Cell Carcinoma (CCRCC) is the most aggressive subtype of Renal Cell Carcinoma (RCC) with high metastasis and recurrence rates. This study aims to find new potential key genes of CCRCC. METHODS: Four gene expression profiles (GSE12606, GSE53000, GSE68417, and GSE66272) were downloaded from the Gene Expression Omnibus (GEO) database. The TCGA KIRC data was downloaded from The Cancer Genome Atlas (TCGA). Using GEO2R, the differentially expressed genes (DEG) in CCRCC tissues and normal samples were analyzed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed in DAVID database. A protein-protein interaction (PPI) network was constructed and the hub gene was predicted by STRING and Cytoscape. GEPIA and Kaplan-Meier plotter databases were used for further screening of Key genes. Expression verification and survival analysis of key genes were performed using TCGA database, GEPIA database, and Kaplan-Meier plotter. Receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of key genes in CCRCC, which is plotted by R software based on TCGA database. UALCAN database was used to analyze the relationship between key genes and clinical pathology in CCRCC and the methylation level of the promoter of key genes in CCRCC. RESULTS: A total of 289 up-regulated and 449 down-regulated genes were identified based on GSE12606, GSE53000, GSE68417, and GSE66272 profiles in CCRCC. The upregulated DEGs were mainly enriched with protein binding and PI3K-Akt signaling pathway, whereas down-regulated genes were enriched with the integral component of the membrane and metabolic pathways. Next, the top 35 genes were screened out from the PPI network according to Degree, and three new key genes ITGAX, LAPTM5 and SERPINE1 were further screened out through survival and prognosis analysis. Further results showed that the ITGAX, LAPTM5, and SERPINE1 levels in CCRCC tumor tissues were significantly higher than those in normal tissues and were associated with poor prognosis. ROC curve shows that ITGAX, LAPTM5, and SERPINE1 have good diagnostic value with good specificity and sensitivity. The promoter methylation levels of ITGAX, LAPTM5 and SERPINE1 in CCRCC tumor tissues were significantly lower than those in normal tissues. We also found that key genes were associated with clinical pathology in CCRCC. CONCLUSION: ITGAX, LAPTM5, and SERPINE1 were identified as novel key candidate genes that could be used as prognostic biomarkers and potential therapeutic targets for CCRCC.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/62c34c0095f5/peerj-09-11272-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/132dda4e6bd1/peerj-09-11272-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/ffa53dc1f843/peerj-09-11272-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/e5dd245fc51d/peerj-09-11272-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/b4c4d0139734/peerj-09-11272-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/a439be8a4f3f/peerj-09-11272-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/594c13286b2d/peerj-09-11272-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/62c34c0095f5/peerj-09-11272-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/132dda4e6bd1/peerj-09-11272-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/ffa53dc1f843/peerj-09-11272-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/e5dd245fc51d/peerj-09-11272-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/b4c4d0139734/peerj-09-11272-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/a439be8a4f3f/peerj-09-11272-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/594c13286b2d/peerj-09-11272-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba56/8063882/62c34c0095f5/peerj-09-11272-g007.jpg

相似文献

[1]
Prediction and analysis of novel key genes ITGAX, LAPTM5, SERPINE1 in clear cell renal cell carcinoma through bioinformatics analysis.

PeerJ. 2021-4-20

[2]
Bioinformatics analysis and verification of gene targets for renal clear cell carcinoma.

Comput Biol Chem. 2021-6

[3]
Identification of Prognostic Related Hub Genes in Clear-Cell Renal Cell Carcinoma Bioinformatical Analysis.

Chin Med Sci J. 2021-6-30

[4]
Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma.

Front Oncol. 2022-2-28

[5]
Identification of significant genes with prognostic influence in clear cell renal cell carcinoma via bioinformatics analysis.

Transl Androl Urol. 2020-4

[6]
Integration of bioinformatics analysis to identify possible hub genes and important pathways associated with clear cell renal cell carcinoma.

Urologia. 2024-5

[7]
Expression of gasdermin D in clear cell renal cell carcinoma and its effect on its biological function.

Front Oncol. 2023-7-6

[8]
Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases.

Pathol Oncol Res. 2021

[9]
The screening of pivotal gene expression signatures and biomarkers in renal carcinoma.

J Cancer. 2019-10-19

[10]
SERPINE1 and its co-expressed genes are associated with the progression of clear cell renal cell carcinoma.

BMC Urol. 2023-3-23

引用本文的文献

[1]
Genomic and molecular associations with preoperative immune checkpoint inhibition in patients with stage III clear cell renal cell carcinoma.

medRxiv. 2025-8-2

[2]
Identifying conserved metastatic pathways across cancers through integrated transcriptomic and network analysis.

Med Oncol. 2025-7-10

[3]
Identification of the gene signatures related to NK/T cell communication to evaluate the tumor microenvironment and prognostic outcomes of patients with prostate adenocarcinoma.

Front Immunol. 2025-4-16

[4]
Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma.

PLoS One. 2024

[5]
Lysosomal transmembrane protein 5: Impact on immune cell function and implications for immune-related deficiencies.

Heliyon. 2024-8-22

[6]
Cancer selective cell death induction by a bivalent CK2 inhibitor targeting the ATP site and the allosteric αD pocket.

iScience. 2024-1-12

[7]
ZKSCAN5 activates LAPTM5 expression by recruiting SETD7 to promote metastasis in pancreatic ductal adenocarcinoma.

Histol Histopathol. 2024-6

[8]
The Regulation and Double-Edged Roles of the Deubiquitinase OTUD5.

Cells. 2023-4-14

[9]
A 20-Gene Signature Predicting Survival in Patients with Clear Cell Renal Cell Carcinoma Based on Basement Membrane.

J Oncol. 2023-4-8

[10]
Network pharmacology-based analysis of Resinacein S against non-alcoholic fatty liver disease by modulating lipid metabolism.

Front Nutr. 2023-2-14

本文引用的文献

[1]
Immunotherapy in Renal Cell Carcinoma: The Future Is Now.

Int J Mol Sci. 2020-4-5

[2]
FOXM1-Activated LINC01094 Promotes Clear Cell Renal Cell Carcinoma Development via MicroRNA 224-5p/CHSY1.

Mol Cell Biol. 2020-1-16

[3]
Identification of as a Regulator of Glioblastoma Cell Dispersal with Transcriptome Profiling.

Cancers (Basel). 2019-10-25

[4]
First-Line Systemic Therapy for Metastatic Clear-Cell Renal Cell Carcinoma: Critical Appraisal of Emerging Options.

Target Oncol. 2019-12

[5]
The Cancer Genome Atlas of renal cell carcinoma: findings and clinical implications.

Nat Rev Urol. 2019-7-5

[6]
ROC Curves for the Statistical Analysis of Microarray Data.

Methods Mol Biol. 2019

[7]
The Metabolic Basis of Kidney Cancer.

Cancer Discov. 2019-5-14

[8]
Systematic identification of key genes and pathways in clear cell renal cell carcinoma on bioinformatics analysis.

Ann Transl Med. 2019-3

[9]
Metabolomic insights into pathophysiological mechanisms and biomarker discovery in clear cell renal cell carcinoma.

Expert Rev Mol Diagn. 2019-5-2

[10]
Identification of EGFR as a Novel Key Gene in Clear Cell Renal Cell Carcinoma (ccRCC) through Bioinformatics Analysis and Meta-Analysis.

Biomed Res Int. 2019-2-13

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索