Evidence map›Paper›PMID 41296134›Full record

ArticleDiscover oncology2025

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

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

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Rongrong Zhou *Department of Clinical Laboratory, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
Zhineng Zeng *Department of Clinical Laboratory, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
Ying XuDepartment of Clinical Laboratory, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
Qiong TangDepartment of pathology, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
Songnan ZhangDepartment of Clinical Laboratory, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
Junfeng ZhuDepartment of Clinical Laboratory, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China. zhujunfeng@lnu.edu.cn.

Funding

National Natural Science Foundation of China 82360113Natural Science Foundation of Guangxi 2024GXNSFAA010059Natural Science Foundation of Guangxi Zhuang Autonomous Region 2021GXNSFAA325001
6 · The paper itself

Abstract

backgroundColorectal 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.

methodsThe 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.

resultsWe 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.

conclusionsFGF14-AS2 and MPP2 are downregulated in CRC and serve as potential prognostic biomarkers. The prognostic model developed provides moderate predictive value for CRC outcomes.

Indexed as

CeRNAColorectal cancerFGF14-AS2MPP2Prognosis

Identifiers

PMID41296134
PMCPMC12748477

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