FOXM1 promotes proliferation in human hepatocellular carcinoma cells by transcriptional activation of CCNB1

Chai, Na; Xie, Hui; Yin, Jiaqi; Sa, Ke-di; Guo, Yi; Wang, Meng; Li, Jun; Zhang, Xiaofang; Zhang, Xiang; Yin, Hong; Nie, Yongzhan; Wu, Kaichun; Yang, An‐Gang; Zhang, Rui

doi:10.1016/j.bbrc.2018.04.201

Cited by 89 publications

(70 citation statements)

References 39 publications

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“…Previous studies have reported that the CCNB1-Cdk1 complex is a key regulator of mitotic entry 25 . Importantly, Chai et al noted that CCNB1 is highly expressed in HCC and is closely related to the poor prognosis of HCC patients, consistent with our results 26 . Gu et al showed that CCNB1 is directly suppressed by miR-144 as a therapy targeting HCC 27 .…”

Section: Discussionsupporting

confidence: 93%

Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis

Zhou

Hao

et al. 2019

Cell Transplant

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Hepatocellular carcinoma (HCC) is a widespread, common type of cancer in Asian countries, and the need for biomarker-matched molecularly targeted therapy for HCC has been increasingly recognized. However, the effective treatment for HCC is unclear. Therefore, identifying additional hub genes and pathways as novel prognostic biomarkers for HCC is necessary. In this study, the expression profiles of GSE121248, GSE45267 and GSE84402 were obtained from the Gene Expression Omnibus (GEO), including 132 HCC and 90 noncancerous liver tissues. Differentially expressed genes (DEGs) between HCC and noncancerous samples were identified by GEO2 R and Venn diagrams. In total, 109 DEGs were identified in these datasets, including 24 upregulated genes and 85 downregulated genes. Subsequently, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) preliminary analyses of the DEGs were performed using DAVID. The protein–protein interaction (PPI) network of the DEGs was constructed with the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized in Cytoscape. Module analysis of the PPI network was performed using MCODE to get hub genes. Moreover, the influence of the hub genes on overall survival was determined with Kaplan–Meier plotter. All hub genes were analyzed by Gene Expression Profiling Interactive Analysis (GEPIA) and KEGG. Overall, the hub genes DTL, CDK1, CCNB1, RACGAP1, ECT2, NEK2, BUB1B, PBK, TOP2A, ASPM, HMMR, RRM2, CDKN3, PRC1, and ANLN were upregulated in HCC, and the survival rate was lower for HCC with increased expression of these hub genes. CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway, and CCNB1, CDK1, and BUB1B were enriched in the cell cycle. In brief, we screened 15 hub genes and pathways to identify potential prognostic markers for HCC treatment. However, the specific occurrence and development of HCC with expression of the hub genes should be verified in vivo and in vitro.

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Section: Discussionsupporting

confidence: 93%

Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis

Zhou

Hao

et al. 2019

Cell Transplant

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“…Siomycin A, a FOXM1 inhibitor, downregulate the level of FOXM1in the metastatic melanoma cell lines and induce cell apoptosis [24]. Down regulation of FOXM1 expression the proliferation and migration of hepatocellular carcinoma and renal cancer [25][26][27]. It was also reported that FOXM1 could promote gastric cancer cell migration and invasion [28].…”

Section: Introductionmentioning

confidence: 99%

FOXM1 functions collaboratively with PLAU to promote gastric cancer progression

Ai¹,

Zhang²,

Lian³

et al. 2020

J. Cancer

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Background: Gastric cancer (GC) is one of the main mortality cause worldwide. Previously, we found Forkhead box protein (FOXM1) or Urokinase-type plasminogen activator (PLAU) are independent prognostic markers of GC. This study aims to explore the combining prognostic efficacy and the potential insights underlying additive effect of FOXM1 to PLAU in GC progression through in-silico analyses. Method: The expression of FOXM1 and PLAU were profiled in 33 cancer types using public data. A merged GC expression dataset containing 598 samples was used for evaluating prognostic significance of FOXM1/PLAU. Gene Set Enrichment Analysis (GSEA) was performed to elucidate the mechanisms underlying FOXM1/PLAU promoted GC progression. The Cancer Genome Atlas (TCGA) was used for analyzing the association between FOXM1/PLAU and tumor immune infiltration. Genomic and proteomic differences between FOXM1+PLAU+ and FOXM1-PLAU-groups were also computed using TCGA GC data. Drugs targeting FOXM1/PLAU associated gene expression pattern was analyzed using LINCs database. Results: FOXM1 and PLAU are overexpressed in 17/33 cancer types including GC. Kaplan-Meier analyses indicate that the FOXM1+PLAU+ subgroup have the worst prognosis, while FOXM1-PLAU-subgroup have the best survival. Bioinformatics analysis indicated that FOXM1+PLAU+ associated genes are enriched in TGF-beta, DNA repair and drug resistance signaling pathways; FOXM1 and PLAU expression are negatively correlated with tumor immune infiltration. Genomic and proteomic differences between FOXM1+PLAU+ and FOXM1-PLAU-groups were presented. Data mining from LINCs suggested several chemicals or drugs that could target the gene expression pattern of FOXM1+PLAU+ patients. Conclusion: FOXM1+PLAU+ can serve as effective prognostic biomarkers and potential therapeutic targets for GC. Due to the additive effect of these two genes, screening for drugs or chemicals that targeting the expression patterns PLAU+FOXM1+ subgroup may exert important clinical impact on GC management.

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“…Many previous studies have unveiled important genes in HCC. For example, ZNF233 [33], FOXM1 [34], and CKS2 [35] could promote the proliferation of HCC cells. linc-POU3F3 [36,37] RUNX2, and SLP-2 [38] were found to enhance the invasion and migration of HCC cells.…”

Section: Discussionmentioning

confidence: 99%

Effect of CELSR3 on the Cell Cycle and Apoptosis of Hepatocellular Carcinoma Cells

Xie

Dang

et al. 2020

J. Cancer

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Cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) has been reported in cancers but its role and potential molecular mechanism in hepatocellular carcinoma (HCC) is unclear. Therefore, we aimed to investigate the clinical value and molecular mechanism of CELSR3 in HCC using an in vitro experiment, a meta-analysis and bioinformatics. The in vitro experiment determined the promoting effect of CELSR3 in the proliferation, invasion, and migration of HCC cells. CELSR3 knockout causes S-phage arrest in HCC cells. CELSR3 can also inhibit the apoptosis of HCC cells. The expression of the CELSR3 gene and protein was significantly elevated in HCC. Elevated CELSR3 was correlated to the bigger tumor size, higher pathological stage, and the worse overall survival of HCC. Methylation analysis revealed that the hypomethylation of CELSR3 regulated by DNMT1, DNMT3A, and DNMT3B may be the underlying mechanism of upregulated CELSR3. Biological enrichment analysis uncovered that the cell cycle, DNA replication, and PI3K-Akt signaling pathways were important pathways regulated by CELSR3 and its co-expressed genes in HCC. Taken together, upregulated CELSR3 is an important regulator in the progression and prognosis of HCC. The hypomethylation of CELSR3 and its regulation in the cell cycle may be the potential molecular mechanism in HCC.

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FOXM1 promotes proliferation in human hepatocellular carcinoma cells by transcriptional activation of CCNB1

Cited by 89 publications

References 39 publications

Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis

Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis

FOXM1 functions collaboratively with PLAU to promote gastric cancer progression

Effect of CELSR3 on the Cell Cycle and Apoptosis of Hepatocellular Carcinoma Cells

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