Evidence map›Paper›PMID 40396123›Full record

ArticleFrontiers in molecular biosciences2025

Identification of key genes CCL5, PLG, LOX and C3 in clear cell renal cell carcinoma through integrated bioinformatics analysis.

Zhenwei Xie, Cheng Feng, Yude Hong, Libo Chen, Mingyong Li, Weiming Deng

Abstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. A multi-omics prognostic model and functional validation ofTranslational andrology and urology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zhenwei Xie *Department of Kidney Transplantation, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Cheng Feng *Department of Thyroid and Galactophore Surgery, People's Hospital of Longhua, Shenzhen, China.
Yude Hong *Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Libo ChenDepartment of Urology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Mingyong LiDepartment of Urology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Weiming DengDepartment of Urology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Clear Cell Renal Cell Carcinoma (ccRCC) is a malignant tumor with high mortality and recurrence rates and the molecular mechanism of ccRCC genesis remains unclear. In this study, we identified several key genes associated with the prognosis of ccRCC by using integrated bioinformatics. Methods: Two ccRCC expression profiles were downloaded from Gene Expression Omnibus and one dataset was gained from The Cancer Genome Atlas The Robust Rank Aggregation method was used to analyze the three datasets to gain integrated differentially expressed genes The Gene Ontology and KEGG analysis were performed to explore the potential functions of DEGs. The Search Tool for the Retreival of Interacting Genes/Proteins (STRING) and Cytoscape software were used to construct protein-protein interaction network and module analyses to screen the hub genes. Spearman's correlation analysis was conducted to evaluate the interrelationships among the hub genes. The prognostic value was evaluated through K-M survival analysis, Cox regression analysis, and receiver operating characteristic curve analysis to determine their potential as prognostic biomarkers in ccRCC. The expression of hub genes between ccRCC and adjacent normal tissues was analyzed by RT-qPCR, Western blotting, and immunohistochemical (IHC). Result: 125 DEGs were identified using the limma package and RRA method, including 62 up-expressed genes and 63 down-expressed genes. GO and KEGG analysis showed some associated pathways. Spearman's correlation analysis revealed that the hub genes are not only interrelated but also closely associated with immune cell infiltration. Gene expression analysis of the hub genes based on the TCGA-KIRC cohort, along with K-M survival analysis, Cox regression, and ROC curve analysis, consistently demonstrated that CCL5, LOX, and C3 are significantly upregulated in ccRCC and are associated with poor clinical outcomes. In contrast, PLG showed opposite result. These results were further validated at the mRNA and protein levels. Conclusion: Our findings indicate that CCL5, LOX, C3, and PLG are significantly associated with the progression and prognosis of ccRCC, highlighting their potential as prognostic biomarkers. These results provide a foundation for future research aimed at uncovering the underlying mechanisms and identifying potential therapeutic targets for ccRCC.

Indexed as

biomarkersccRCChub genesintegrated bioinformatics analysisprognosis

Identifiers

PMID40396123
PMCPMC12088980

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