ArticleExperimental and therapeutic medicine2020
Identification of hub genes in peripheral blood mononuclear cells for the diagnosis of hepatocellular carcinoma using a weighted gene co-expression network analysis.
Article in Experimental and therapeutic medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 8 citations in OpenAlex.
- Predictive three-biomarker panel in peripheral blood mononuclear cells for detecting hepatocellular carcinoma.Scientific reports · 2024Article
- Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies.NPJ precision oncology · 2023Article
- Upregulation of TMEM40 is associated with the malignant behavior and promotes tumor progression in cervical cancer.Discover oncology · 2023Article
- Identification of pyroptosis‑related genes in neuropathic pain based on bioinformatics analysis.Experimental and therapeutic medicine · 2023Article
- SPARC: a potential target for functional nanomaterials and drugs.Frontiers in molecular biosciences · 2023Review
- C8B in Complement and Coagulation Cascades Signaling Pathway is a predictor for Survival in HBV-Related Hepatocellular Carcinoma Patients.Cancer management and research · 2021Article
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Authors and funding
4 authors at 3 institutions in 1 country.
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Abstract
Human hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive tract that is prevalent worldwide. Improving diagnosis methods for HCC helps to improve patient survival rate. The present study aimed to identify novel HCC biomarkers for the diagnosis of HCC through analyzing gene changes on peripheral blood mononuclear cells (PBMCs) and verifying these in additional samples. The gene expression profiles GSE49515 (including 10 specimens from normal patients and 10 specimens from patients with HCC) and GSE58208 (including 5 specimens from normal patients and 10 specimens from patients with HCC) were downloaded from the online Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) in PBMCs between healthy controls and patients with HCC were identified using R software. A total of 935 DEGs, including 686 upregulated DEGs and 249 downregulated DEGs, were identified in the present study. In order to identify any internal associations, these DEGs were used to construct weighted gene co-expression networks (WGCNA). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of genes in each module were conducted using the online database DAVID. Furthermore, hub genes with high module membership were identified in a co-expression network and receiver operating characteristic curves were used to verify the diagnostic values of these eight hub genes. Furthermore, the expression and diagnosis value of the eight hub genes were also verified in additional samples. The results of the present study suggested that secreted protein acidic and cysteine rich(SPARC), transmembrane protein 40 (TMEM40), solute carrier family 25 member 44, formyl peptide receptor 2 (FPR2), complement C8 β chain, N-myristoyltransferase 1, protein kinase C δ(PRKCD) and protein phosphatase, Mg
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