CXCL14 inhibits the growth and promotes apoptosis of hepatocellular carcinoma cells via suppressing Akt/mTOR pathway

Bi, Jianqiang; Liu, Quanle; Sun, Yu; Hu, Xiuru; Xu, He; Xu, Chengzhen

doi:10.1080/10799893.2020.1837870

Cited by 11 publications

(8 citation statements)

References 37 publications

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“…CXCL14 is low expression in colon cancer, liver cancer and head and neck tumors [16]. Jianqiang Bi et al found that CXCL14 inhibited the growth of HCC cells and promoted apoptosis by inhibiting Akt/mTOR pathway, which may become a potential target for clinical treatment of HCC [17]. This study found that CXCL14 was under-expression in HCC, and its AUC values in the two training sets were 0.952 and 0.978 respectively.…”

Section: Discussionmentioning

confidence: 84%

Identification effective diagnosis biomarkers and immune cell infiltration in liver cancer by bioinformatics analysis and machine learning algorithm

Wang

2023

Preprint

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Objective The aim of this study was to identify the key diagnosis biomarkers of abnormal expression and immune infiltration in liver cancer based on bioinformatics analysis and machine learning algorithm. Methods Three microarray datasets were obtained from Gene Expression Omnibus database, of which GSE88389 and GSE121248 were defined as training sets and GSE45436 was defined as a validation set. Differentially expressed genes (DEGs) were identified and functional and pathway enrichment analysis was performed by Gene Ontology terms (GO), Kyoto Encyclopedia of Genes (KEGG), disease enrichment analysis (DO) and gene enrichment analysis (GSEA). Tumor biomarkers for liver cancer were identified through Lasso and support vector machine (SVM) and validated in the GSE45436. CIBERSORT was performed to analyze the relation between the diagnosis biomarkers for liver cancer and immune cell infiltration. Results A total of 39 differentially expressed genes (DEGs), including 6 up-regulated and 33 down-regulated genes, were obtained based on expression fold change and significance. Analysis of GO, KEGG, DO and GSEA pathways indicated that these DEGs were enriched in collagen-containing extracellular matrix, collagen trimer, plasma lipoprotein particle, bile secretion, tryptophan metabolism, retinol metabolism, chemical carcinogenesis - DNA adducts, C-type lectin receptor signaling pathway, acute porphyria, lung squamous cell carcinoma, cell cycle, DNA replication, proteasome and ribosome. Combination analysis of Lasso and Support vector machine (SVM), three diagnosis value genes of CAP2、CXCL14 and TMEM27 for liver cancer were obtained by Venn diagram. Compared with normal tissue, immune infiltration analysis demonstrated that naive B cells, memory B cells, regulatory T cells and macrophages were highly expressed in hepatocellular carcinoma tissues, while plasma cells and T cells were low expression. Conclusion We identified CAP2、CXCL14 and TMEM27 as potential biomarkers for liver cancer and that can mediate immune cell activity in liver cancer.

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Section: Discussionmentioning

confidence: 84%

Identification effective diagnosis biomarkers and immune cell infiltration in liver cancer by bioinformatics analysis and machine learning algorithm

Wang

2023

Preprint

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“…Upregulated genes ( Fabp4, Col15a1, Cxcl14 and Slc8a1 ) associated to cell apoptosis were detected in M1. These upregulated DEGs implied AgNPs triggered apoptosis in M1 [ [32] , [33] , [34] , [35] ]. Moreover, we also observed that AgNPs resulted in 211 upregulated DEGs and 60 downregulated DEGs in M0, as well as 219 upregulated DEGs and 63 downregulated DEGs in M2 ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Application of silver nanoparticles for improving motor recovery after spinal cord injury via reduction of pro-inflammatory M1 macrophages

Lin

Chen

Tan

et al. 2023

Heliyon

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“…CXCLs were linked to pathogenesis and death rate, and they were involved in inflammation, lung tissue structure and respiratory functions [17]. CXCL14 was insufficiently expressed and exerted its tumor oppressive function in hepatocellular carcinoma and oral cavity squamous cell carcinoma via enhancing cell growth, viability, apoptosis, expansion and metastasis [18,19]. Furthermore, CXCL14 was dysregulated in influenza viruses [20].…”

Section: Discussionmentioning

confidence: 99%

Role of C-X-C motif chemokine ligand 14 promoter region DNA methylation and single nucleotide polymorphism in influenza A severity

Chen

Liang

Zhang

2021

Respiratory Medicine

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The purpose of our experiment is to discuss the function of DNA methylation and single nucleotide polymorphism (SNP) in C-X-C motif chemokine ligand 14 (CXCL14) promoter region in influenza A (H1N1) severity. Methods: Clinic data and blood samples from H1N1 patients were collected. Blood routine indexes were measured. Levels of T lymphocytes were assessed. Importantly, CXCL14 expression and methylation in H1N1 patients and A549 cells were detected through functional assays. Additionally, rs2237061, rs2237062 and rs2547 of CXCL14 were genotyped to analyze the relation of CXCL14 SNP and H1N1 severity. Results: The number of leukocytes, neutrophils and lymphocytes as well as T lymphocytes in H1N1 patients was lower than that in healthy subjects, and that was decreased in severe H1N1 patients compared with the mild H1N1 patients. In HIN1 patients, CXCL14 expression was decreased, while CXCL14 methylation was increased, and CXCL14 expression was further decreased and CXCL14 methylation was further increased in severe H1N1 patients. CXCL14 methylation was negatively correlated with T lymphocytes in H1N1 patients. CXCL14 methylation was elevated in H1N1-infected A549 cells. GA and AA genotypes of rs2547 in CXCL14 were risky genotypes for H1N1, and AA genotype was risky genotype for severe H1N1. Number of T lymphocytes was lower in H1N1 patients carrying AA genotype of rs2547 than that in GA + GG genotype. Conclusion: CXCL14 promoter region DNA methylation and SNP were correlated with H1N1 severity.

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CXCL14 inhibits the growth and promotes apoptosis of hepatocellular carcinoma cells via suppressing Akt/mTOR pathway

Cited by 11 publications

References 37 publications

Identification effective diagnosis biomarkers and immune cell infiltration in liver cancer by bioinformatics analysis and machine learning algorithm

Identification effective diagnosis biomarkers and immune cell infiltration in liver cancer by bioinformatics analysis and machine learning algorithm

Application of silver nanoparticles for improving motor recovery after spinal cord injury via reduction of pro-inflammatory M1 macrophages

Role of C-X-C motif chemokine ligand 14 promoter region DNA methylation and single nucleotide polymorphism in influenza A severity

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