ArticleInternational journal of biological sciences2017
Co-expression network analysis identified FCER1G in association with progression and prognosis in human clear cell renal cell carcinoma.
Article in International journal of biological sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.
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80 citing papers in PubMed, 122 citations in OpenAlex.
- Review
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- Prognostic value of FCER1G expression and M2 macrophage infiltration in esophageal squamous cell carcinoma.Discover oncology · 2025Article
- Integrated pan-cancer analysis revealed therapeutic targets in the ABC transporter protein family.PloS one · 2025Article
- Diagnostic value of procalcitonin and hemocyte parameters in neonates with bloodstream infection: Role of activated hemocyte-related genes.Pediatric discovery · 2024Article
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- Single cell and spatial transcriptomics analysis of kidney double negative T lymphocytes in normal and ischemic mouse kidneys.Scientific reports · 2023Article
- Identification of potential prognostic markers for lung adenocarcinoma using comprehensive analysis.Molecular medicine reports · 2023Article
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- Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma.Journal of oncology · 2023Article
- Identification and Analysis of Crucial Genes inJournal of oncology · 2023Article
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- A Prognostic Nomogram for Hepatocellular Carcinoma Based on Wound Healing and Immune Checkpoint Genes.Journal of clinical and translational hepatology · 2022Article
- FCER1G Gene Hypomethylation in Patients with Rheumatoid Arthritis.Journal of clinical medicine · 2022Article
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- Multi-omics data identified TP53 and LRP1B as key regulatory gene related to immune phenotypes via EPCAM in HCC.Cancer medicine · 2022Article
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- Bioinformatics role of the WGCNA analysis and co-expression network identifies of prognostic marker in lung cancer.Saudi journal of biological sciences · 2022Article
- Identification of co-expression hub genes for ferroptosis in kidney renal clear cell carcinoma based on weighted gene co-expression network analysis and The Cancer Genome Atlas clinical data.Scientific reports · 2022Article
20 more citing papers are in PubMed but not listed here.
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In current study, the microarray data GSE66272 containing ccRCC and adjacent normal tissues was analyzed to identify 4042 differentially expressed genes, on which weighted gene co-expression network analysis was performed. Then 12 co-expressed gene modules were identified. The highest association was found between blue module and pathological stage (r = -0.77) by Pearson's correlation analysis. Functional enrichment analysis revealed that biological processes of blue module focused on inflammatory response, immune response, chemotaxis (all p < 1e-10). In the significant module, a total of 38 network hub genes were identified, FCER1G exhibited the highest correlation (r = 0.95) with ccRCC progression. In addition, FCER1G was hub node in the protein-protein interaction network of the genes in blue module as well. Thus, FCER1G was subsequently selected for validation. In the test set GSE53757 and RNA-sequencing data, FCER1G expression was also positively correlated with four stages of ccRCC progression (p < 0.001). Receiver operating characteristic (ROC) curve indicated that FCER1G could distinguish localized (pathological stage I, II) from non-localized (pathological stage III, IV) ccRCC (AUC=0.74, p < 0.001). Besides, FCER1G could be a prognostic gene in clinical practice as well, revealed by survival analysis based on RNA-sequencing data (p < 0.05). In conclusion, using weighted gene co-expression analysis, FCER1G was identified and validated in association with ccRCC progression and prognosis, which might improve the prognosis by influencing immune-related pathways.
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