CDC20 associated with cancer metastasis and novel mushroom‑derived CDC20 inhibitors with antimetastatic activity

Cheng, Shujie; Castillo, V.; Slíva, Daniel

doi:10.3892/ijo.2019.4791

Cited by 50 publications

(48 citation statements)

References 41 publications

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“… 62 , 63 CDC20 overexpression is related to progression and poor prognosis in various malignant tumors. 64 – 67 Thus, it is a potential target in multiple cancer treatments. 68 A recent study found that increased expression of CDC20 is related to HCC development and progression.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Meng

Liu

et al. 2020

J Int Med Res

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Objective The objective was to identify potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma (HCC). Methods Gene expression profile datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HCC and normal samples were identified via an integrated analysis. A protein–protein interaction network was constructed and analyzed using the STRING database and Cytoscape software, and enrichment analyses were carried out through DAVID. Gene Expression Profiling Interactive Analysis and Kaplan–Meier plotter were used to determine expression and prognostic values of hub genes. Results We identified 11 hub genes ( CDK1, CCNB2, CDC20, CCNB1, TOP2A, CCNA2, MELK, PBK, TPX2, KIF20A, and AURKA) that might be closely related to the pathogenesis and prognosis of HCC. Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways, and hub genes and module 1 were highly associated with cell cycle pathway. Conclusions In this study, we identified key genes of HCC, which indicated directions for further research into diagnostic and prognostic biomarkers that could facilitate targeted molecular therapy for HCC.

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Section: Discussionmentioning

confidence: 99%

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Meng

Liu

et al. 2020

J Int Med Res

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“…Zhang et al (36), reported that high expression of CDC20 in prostate cancer often indicates a poor prognosis. Moreover, a previous study revealed that CDC20 is associated with tumor metastasis (37); thus, future research should focus on CDC20 target inhibitors to develop new drugs to inhibit tumor metastasis.…”

Section: Discussionmentioning

confidence: 99%

Identification of hub genes involved in the occurrence and development of hepatocellular carcinoma via bioinformatics analysis

Cao

Zhang

et al. 2020

Oncol Lett

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Hepatocellular carcinoma (HCC) is a heterogeneous malignancy, which is a major cause of cancer morbidity and mortality worldwide. Thus, the aim of the present study was to identify the hub genes and underlying pathways of HCC via bioinformatics analyses. The present study screened three datasets, including GSE112790, GSE84402 and GSE74656 from the Gene Expression Omnibus (GEO) database, and downloaded the RNA-sequencing of HCC from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) in both the GEO and TCGA datasets were filtered, and the screened DEGs were subsequently analyzed for functional enrichment pathways. A protein-protein interaction (PPI) network was constructed, and hub genes were further screened to create the Kaplan-Meier curve using cBioPortal. The expression levels of hub genes were then validated in different datasets using the Oncomine database. In addition, associations between expression and tumor grade, hepatitis virus infection status, satellites and vascular invasion were assessed. A total of 126 DEGs were identified, containing 70 upregulated genes and 56 downregulated genes from the GEO and TCGA databases. By constructing the PPI network, the present study identified hub genes, including cyclin B1 (CCNB1), cell-division cycle protein 20 (CDC20), cyclin-dependent kinase 1, BUB1 mitotic checkpoint serine/ threonine kinase β (BUB1B), cyclin A2, nucleolar and spindle associated protein 1, ubiquitin-conjugating enzyme E2 C (UBE2C) and ZW10 interactor. Furthermore, upregulated CCNB1, CDC20, BUB1B and UBE2C expression levels indicated worse disease-free and overall survival. Moreover, a meta-analysis of tumor and healthy tissues in the Oncomine database demonstrated that BUB1B and UBE2C were highly expressed in HCC. The present study also analyzed the data of HCC in TCGA database using univariate and multivariate Cox analyses, and demonstrated that BUB1B and UBE2C may be used as independent prognostic factors. In conclusion, the present study identified several genes and the signaling pathways that were associated with tumorigenesis using bioinformatics analyses, which could be potential targets for the diagnosis and treatment of HCC.

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“…CDC20B belong to the cell division cycle 20 (CDC20) family of regulatory proteins that interact with several other proteins at multiple points in the cell cycle and CDC20B is required for nuclear movement prior to anaphase and for chromosome separation (34). It has been reported that aberrant expression of CDC20 is associated with malignant progression and poor prognosis in various types of cancer and it has been shown that CDC20 knockdown inhibits the migration of the chemoresistant PANC-1 pancreatic cancer cells and the metastatic MDA-MB-231 breast cancer cell line (35). Thus, it was suggested that the development of specific CDC20 inhibitors might be a novel strategy for the treatment of cancer with elevated expression of CDC20 (35).…”

Section: Discussionmentioning

confidence: 99%

A prognosis‑predictive nomogram of ovarian cancer with two immune‑related genes: <em>CDC20B</em> and <em>PNPLA5</em>

et al. 2020

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Ovarian carcinoma (OV) is one of the most lethal gynecological malignancies globally, and the overall 5-year survival rate of OV was 47% in 2018 according to American data. To increase the survival rate of patients with OV, many researchers have sought to identify biomarkers that act as both prognosis-predictive markers and therapy targets. However, most of these have not been suitable for clinical application. The present study aimed at constructing a predictive prognostic nomogram of OV using the genes identified by combining The Cancer Genome Atlas (TCGA) dataset for OV with the immune score calculated by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Firstly, the algorithm was used to calculate the immune score of patients with OV in the TCGA-OV dataset. Secondly, differentially expressed genes (DEGs) between low and high immune score tissues were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was performed to predict the functions of these DEGs. Thirdly, univariate, multivariate and Lasso Cox's regression analyses were carried out step by step, and six prognosis-related DEGs were identified. Then, Kaplan-Myer survival curves were generated for these genes and validated by comparing their expression levels to further narrow the range of DEGs and to calculate the risk score. Two genes were identified, cell division cycle 20B and patatin-like phospholipase domain containing 5, which were both shown to have higher expression levels in OV tissues and to be significantly associated with the prognosis of OV. Next, a nomogram was created using these two genes and age, and using the receiver operating characteristic (ROC) curve and calibration curve, the effectiveness of the nomogram was validated. Finally, an external validation was conducted for this nomogram. The ROC showed that the areas under the curve (AUCs) of the 3-and 5-year overall survival predictions for the nomogram were 0.678 and 0.62, respectively. Moreover, the ROC of the external validation model showed that the AUCs of the 3-and 5-year were 0.699 and 0.643, respectively, demonstrating the effectiveness of the generated nomogram. In conclusion, the present study has identified two immune-related genes as biomarkers that reliably predict overall survival in OV. These biomarkers might also be potential molecular targets of immune therapy to treat patients with OV.

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CDC20 associated with cancer metastasis and novel mushroom‑derived CDC20 inhibitors with antimetastatic activity

Cited by 50 publications

References 41 publications

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Identification of hub genes involved in the occurrence and development of hepatocellular carcinoma via bioinformatics analysis

A prognosis‑predictive nomogram of ovarian cancer with two immune‑related genes: <em>CDC20B</em> and <em>PNPLA5</em>

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