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Background <p>Colorectal cancer (CRC) remains a major global health challenge due to its high morbidity and mortality, even with recent advancements in diagnosis and treatment. Increasing evidence suggests that competitive endogenous RNA (ceRNA) regulatory networks play pivotal roles in the pathogenesis of various cancers, including CRC. However, the potential application of ceRNA networks in CRC diagnosis and their underlying mechanisms remain insufficiently explored.</p> Methods <p>The gene expression profiles and clinical information of CRC were extracted from TCGA database and GEO databases. Differential expression genes (DEGs) were identified using bioinformatics analyses, a ceRNA network was constructed via Cytoscape. Functional enrichment was assessed through GO and KEGG analyses, while hub genes were identified using the STRING database and cytoHubba plugin. Key prognostic genes were determined through univariate/multivariate Cox analysis, Kaplan-Meier analysis and correlation analysis. The expression of prognostically relevant lncRNAs and mRNAs was validated by qRT-PCR and GEO database A prognostic model was developed using univariate/multivariate COX analysis and Lasso regression analysis, and its performance was assessed via ROC and Kaplan-Meier analysis in TCGA and GSE39582 database. Drug sensitivity was predicted using the Cellminer database.</p> Results <p>We identified a ceRNA network comprising 75 differentially expressed lncRNAs (DElncRNAs), 60 DEmiRNAs and 382 DEmRNAs, alongside a PPI network of 330 DEmRNAs. A lncRNA-miRNA-hub gene subnetwork was also constructed, involving 51 DElncRNAs, 21 DEmiRNAs, and 20 hub genes. Notably, MPP2 and FGF14-AS2, both downregulated in CRC, were associated with the prognosis. A prognostic model incorporating N stage, T stage, and FGF14-AS2 expression moderate predictive ability. Additionally, FGF14-AS2 and MPP2 showed correlations with specific chemotherapeutic agents.</p> Conclusions <p>FGF14-AS2 and MPP2 are downregulated in CRC and serve as potential prognostic biomarkers. The prognostic model developed provides moderate predictive value for CRC outcomes.</p>

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Identification of FGF14-AS2/MPP2 axis as prognostic biomarkers in colorectal cancer based on CeRNA network

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月26日

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  • Rongrong Zhou,
  • Zhineng Zeng,
  • Ying Xu,
  • Qiong Tang,
  • Songnan Zhang,
  • Junfeng Zhu

摘要

Background

Colorectal cancer (CRC) remains a major global health challenge due to its high morbidity and mortality, even with recent advancements in diagnosis and treatment. Increasing evidence suggests that competitive endogenous RNA (ceRNA) regulatory networks play pivotal roles in the pathogenesis of various cancers, including CRC. However, the potential application of ceRNA networks in CRC diagnosis and their underlying mechanisms remain insufficiently explored.

Methods

The gene expression profiles and clinical information of CRC were extracted from TCGA database and GEO databases. Differential expression genes (DEGs) were identified using bioinformatics analyses, a ceRNA network was constructed via Cytoscape. Functional enrichment was assessed through GO and KEGG analyses, while hub genes were identified using the STRING database and cytoHubba plugin. Key prognostic genes were determined through univariate/multivariate Cox analysis, Kaplan-Meier analysis and correlation analysis. The expression of prognostically relevant lncRNAs and mRNAs was validated by qRT-PCR and GEO database A prognostic model was developed using univariate/multivariate COX analysis and Lasso regression analysis, and its performance was assessed via ROC and Kaplan-Meier analysis in TCGA and GSE39582 database. Drug sensitivity was predicted using the Cellminer database.

Results

We identified a ceRNA network comprising 75 differentially expressed lncRNAs (DElncRNAs), 60 DEmiRNAs and 382 DEmRNAs, alongside a PPI network of 330 DEmRNAs. A lncRNA-miRNA-hub gene subnetwork was also constructed, involving 51 DElncRNAs, 21 DEmiRNAs, and 20 hub genes. Notably, MPP2 and FGF14-AS2, both downregulated in CRC, were associated with the prognosis. A prognostic model incorporating N stage, T stage, and FGF14-AS2 expression moderate predictive ability. Additionally, FGF14-AS2 and MPP2 showed correlations with specific chemotherapeutic agents.

Conclusions

FGF14-AS2 and MPP2 are downregulated in CRC and serve as potential prognostic biomarkers. The prognostic model developed provides moderate predictive value for CRC outcomes.