Bioinformatics analysis of genes associated with poor prognosis in colorectal cancer

WANG Li-jie; CHEN Si; CHANG Cheng; GAO Kai-yue; ZHANG Hai-jia

doi:10.11659/jjssx.10E024091

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Bioinformatics analysis of genes associated with poor prognosis in colorectal cancer

Basic Research | 更新时间：2025-11-25

- Bioinformatics analysis of genes associated with poor prognosis in colorectal cancer
- JOURNAL OF REGIONAL ANATOMY AND OPERATIVE SURGERY Vol. 34, Issue 11, Pages: 955-959(2025)
- 作者机构：
  
  吉林大学白求恩第一医院普通外科中心结直肠肛门外科，吉林长春 130000
- 作者简介：
- 基金信息：
- DOI：10.11659/jjssx.10E024091
  CLC： R735.3
- Received：24 October 2024，
  
  Published：25 November 2025
- 稿件说明：
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王立杰,陈思,常程等.生物信息学分析结直肠癌预后不良相关的基因[J].局解手术学杂志,2025,34(11):955-959.

WANG Li-jie,CHEN Si,CHANG Cheng,et al.Bioinformatics analysis of genes associated with poor prognosis in colorectal cancer[J].JOURNAL OF REGIONAL ANATOMY AND OPERATIVE SURGERY,2025,34(11):955-959.
王立杰,陈思,常程等.生物信息学分析结直肠癌预后不良相关的基因[J].局解手术学杂志,2025,34(11):955-959. DOI： 10.11659/jjssx.10E024091.

WANG Li-jie,CHEN Si,CHANG Cheng,et al.Bioinformatics analysis of genes associated with poor prognosis in colorectal cancer[J].JOURNAL OF REGIONAL ANATOMY AND OPERATIVE SURGERY,2025,34(11):955-959. DOI： 10.11659/jjssx.10E024091.

摘要

目的

通过生物信息学方法筛选与结直肠癌（CRC）预后不良相关的基因。

方法

从基因表达综合数据库（GEO）数据库中获取GSE74602、GSE110223、GSE113513和GSE141174的基因表达谱数据集，包含65例CRC组织和65例正常组织样本。通过GEO2R工具和Venn软件，筛选CRC组织与正常组织之间的差异表达基因（DEGs），并利用Venn软件在DEGs中提取一致性基因。通过STRING数据库构建蛋白质-蛋白质相互作用（PPI）网络识别核心基因，并利用Kaplan-Meier Plotter和GEPIA分析核心基因。再采用京都基因与基因组百科全书（KEGG）通路富集分析13个选定基因。

结果

在4个数据集中共得到171个DEGs，其中上调基因148个，下调基因23个。上调的DEGs在氧化还原过程、碳酸氢盐运输、消化、离子跨膜运输和单碳代谢过程中富集；下调DEGs主要富集于细胞增殖的正调控。生存曲线分析显示，87个基因中有30个与生存预后差显著相关。GEPIA分析显示，与正常组织相比，30个基因中有13个在CRC组织中高表达，其中MYC和FGFR3在CRC通路中显著富集。

结论

本研究筛选出MYC和FGFR3在CRC中显著上调且与预后不良密切相关，二者可能成为CRC患者潜在预后标志物和治疗靶点。

Abstract

Objective

To screen genes associated with poor prognosis of colorectal cancer （CRC） through bioinformatics analysis.

Methods

The gene expression profiles of GSE74602， GSE110223，GSE113513 and GSE141174 were obtained from Gene Expression Omnibus（GEO） database， including samples from 65 CRC tissues and 65 normal tissues. Differentially expressed genes （DEGs） between CRC tissues and normal tissues were screened out by GEO2R tool and Venn software， and the consistent genes were extracted from DEGs by Venn software. A protein-protein interaction （PPI） network was constructed by the STRING database to identify key genes， which were analyzed by Kaplan-Meier Plotter and GEPIA. Kyoto encyclopedia of genes and genomes （KEGG） pathway enrichment analysis was conducted on the 13 selected genes.

Results

There were 171 DEGs obtained from the four datasets，including 148 up-regulated genes and 23 down-regulated genes. Up-regulated DEGs were enriched in the redox processes， bicarbonate transport， digestion， ion trans-membrane transport， and one-carbon metabolism； and down-regulated DEGs were enriched in the positive regulation of cell proliferation. The survival curve analysis showed that 30 of the 87 genes were significantly associated with poor survival prognosis. GEPIA showed that 13 of the 30 genes were highly expressed in CRC tissues compared to normal tissues， among which MYC and FGFR3 markedly enriched in the CRC pathway.

Conclusion

This study identifies that MYC and FGFR3 are significantly up-regulated in CRC and closely associated with poor prognosis， suggesting that they may serve as potential prognostic markers and therapeutic targets for CRC patients.

关键词

Keywords

references

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