Gene Summary

Gene:CDC20; cell division cycle 20
Aliases: CDC20A, p55CDC, bA276H19.3
Summary:CDC20 appears to act as a regulatory protein interacting with several other proteins at multiple points in the cell cycle. It is required for two microtubule-dependent processes, nuclear movement prior to anaphase and chromosome separation. [provided by RefSeq, Jul 2008]
Databases:OMIM, HGNC, Ensembl, GeneCard, Gene
Protein:cell division cycle protein 20 homolog
Source:NCBIAccessed: 01 September, 2019


What does this gene/protein do?
Show (28)
Pathways:What pathways are this gene/protein implicaed in?
Show (2)

Cancer Overview

Research Indicators

Publications Per Year (1994-2019)
Graph generated 01 September 2019 using data from PubMed using criteria.

Literature Analysis

Mouse over the terms for more detail; many indicate links which you can click for dedicated pages about the topic.

  • Cyclin B1
  • Breast Cancer
  • Databases, Genetic
  • Gene Expression Profiling
  • Liver Cancer
  • Cdc20 Proteins
  • ras-GRF1
  • Protein-Serine-Threonine Kinases
  • Cell Cycle
  • Adenocarcinoma
  • Anaphase-Promoting Complex-Cyclosome
  • Cell Cycle Proteins
  • Neoplastic Cell Transformation
  • Signal Transduction
  • Apoptosis
  • Hepatocellular Carcinoma
  • Cell Proliferation
  • Gene Regulatory Networks
  • Aneuploidy
  • Drug Resistance
  • Cell Cycle Checkpoints
  • HeLa Cells
  • Computational Biology
  • Repressor Proteins
  • Mad2 Proteins
  • Chromosomal Instability
  • Gene Knockdown Techniques
  • Tumor Suppressor Proteins
  • Lung Cancer
  • Mitosis
  • Ubiquitin-Protein Ligase Complexes
  • Chromosome 1
  • Protein Interaction Maps
  • Gene Ontology
  • M Phase Cell Cycle Checkpoints
  • World Health Organization
  • RNA Interference
  • Biomarkers, Tumor
  • Cancer Gene Expression Regulation
Tag cloud generated 01 September, 2019 using data from PubMed, MeSH and CancerIndex

Specific Cancers (3)

Data table showing topics related to specific cancers and associated disorders. Scope includes mutations and abnormal protein expression.

Note: list is not exhaustive. Number of papers are based on searches of PubMed (click on topic title for arbitrary criteria used).

Latest Publications: CDC20 (cancer-related)

Zhou Q, Ren J, Hou J, et al.
Co-expression network analysis identified candidate biomarkers in association with progression and prognosis of breast cancer.
J Cancer Res Clin Oncol. 2019; 145(9):2383-2396 [PubMed] Related Publications
PURPOSE: Breast cancer is one of the most common malignancies among females, and its prognosis is affected by a complex network of gene interactions. Weighted gene co-expression network analysis was used to construct free-scale gene co-expression networks and to identify potential biomarkers for breast cancer progression.
METHODS: The gene expression profiles of GSE42568 were downloaded from the Gene Expression Omnibus database. RNA-sequencing data and clinical information of breast cancer from TCGA were used for validation.
RESULTS: A total of ten modules were established by the average linkage hierarchical clustering. We identified 58 network hub genes in the significant module (R
CONCLUSIONS: AGO2, CDC20, CDCA5, MCM10, MYBL2, and TTK were identified as candidate biomarkers for further basic and clinical research on breast cancer based on co-expression analysis.

Cao Y, Zhu W, Chen W, et al.
Prognostic Value of BIRC5 in Lung Adenocarcinoma Lacking EGFR, KRAS, and ALK Mutations by Integrated Bioinformatics Analysis.
Dis Markers. 2019; 2019:5451290 [PubMed] Free Access to Full Article Related Publications
Objective: This study was aimed at investigating the prognostic significance of Baculoviral IAP repeat containing 5 (BIRC5) in lung adenocarcinoma (LAD) lacking EGFR, KRAS, and ALK mutations (triple-negative (TN) adenocarcinomas).
Methods: The gene expression profiles were obtained from Gene Expression Omnibus (GEO). The identification of the differentially expressed genes (DEGs) was performed by GeneSpring GX. Gene set enrichment analysis (GSEA) was used to execute gene ontology function and pathway enrichment analysis. The protein interaction network was constructed by Cytoscape. The hub genes were extracted by MCODE and cytoHubba plugin from the network. Then, using BIRC5 as a candidate, the prognostic value in LAD and TN adenocarcinomas was verified by the Kaplan-Meier plotter and The Cancer Genome Atlas (TCGA) database, respectively. Finally, the mechanism of BIRC5 was predicted by a coexpressed network and enrichment analysis.
Results: A total of 38 upregulated genes and 121 downregulated genes were identified. 9 hub genes were extracted. Among them, the mRNA expression of 5 genes, namely, BIRC5, MCM4, CDC20, KIAA0101, and TRIP13, were significantly upregulated among TN adenocarcinomas (all
Conclusion: Overexpressed in tumors, BIRC5 is associated with unfavorable overall survival in TN adenocarcinomas. BIRC5 is a potential predictor and therapeutic target in TN adenocarcinomas.

Cheng S, Castillo V, Sliva D
CDC20 associated with cancer metastasis and novel mushroom‑derived CDC20 inhibitors with antimetastatic activity.
Int J Oncol. 2019; 54(6):2250-2256 [PubMed] Related Publications
Aberrant expression of cell division cycle 20 (CDC20) is associated with malignant progression and poor prognosis in various types of cancer. The development of specific CDC20 inhibitors may be a novel strategy for the treatment of cancer with elevated expression of CDC20. The aim of the current study was to elucidate the role of CDC20 in cancer cell invasiveness and to identify novel natural inhibitors of CDC20. The authors found that CDC20 knockdown inhibited the migration of chemoresistant PANC‑1 pancreatic cancer cells and the metastatic MDA‑MB‑231 breast cancer cell line. By contrast, the overexpression of CDC20 by plasmid transfection promoted the metastasizing capacities of the PANC‑1 cells and MCF‑7 breast cancer cells. It was also identified that a triterpene mixture extracted from the mushroom Poria cocos (PTE), purified triterpenes dehydropachymic acid, and polyporenic acid C (PPAC) downregulated the expression of CDC20 in PANC‑1 cells dose‑dependently. Migration was also suppressed by PTE and PPAC in a dose‑dependent manner, which was consistent with expectations. Taken together, the present study is the first, to the best of our knowledge, to demonstrate that CDC20 serves an important role in cancer metastasis and that triterpenes from P. cocos inhibit the migration of pancreatic cancer cells associated with CDC20. Further investigations are in progress to investigate the specific mechanism associated with CDC20 and these triterpenes, which may have future potential use as natural agents in the treatment of metastatic cancer.

Zhang Q, Huang H, Liu A, et al.
Cell division cycle 20 (CDC20) drives prostate cancer progression via stabilization of β-catenin in cancer stem-like cells.
EBioMedicine. 2019; 42:397-407 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Cell division cycle 20 (CDC20) is frequently overexpressed in malignant tumours and involved in the differentiation process of hematopoietic stem cells. However, the role of CDC20 in prostate cancer stem-like cells (CSCs) remains poorly understood.
METHODS: The expression of CDC20, CD44, β-catenin were examined in prostate cancer specimens by immunohistochemistry assay, the role of CDC20 on the stem-like properties of prostate CSCs was accessed by real-time quantitive PCR, spheroid formation, in vitro and in vivo limiting dilution assay.
FINDING: CDC20 was associated with malignant progression of prostate cancer, the patients with both high expression CDC20 and CD44 or β-catenin were associated with more aggressive clinicopathological features and poor prognosis. CDC20 was usually enriched in CD44
INTERPRETATION: Our results indicated that CDC20 maintains the self-renewal ability of CD44

Zhang Y, Li J, Yi K, et al.
Elevated signature of a gene module coexpressed with CDC20 marks genomic instability in glioma.
Proc Natl Acad Sci U S A. 2019; 116(14):6975-6984 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Genomic instability (GI) drives tumor heterogeneity and promotes tumor progression and therapy resistance. However, causative factors underlying GI and means for clinical detection of GI in glioma are inadequately identified. We describe here that elevated expression of a gene module coexpressed with CDC20 (CDC20-M), the activator of the anaphase-promoting complex in the cell cycle, marks GI in glioma. The CDC20-M, containing 139 members involved in cell proliferation, DNA damage response, and chromosome segregation, was found to be consistently coexpressed in glioma transcriptomes. The coexpression of these genes was conserved across multiple species and organ systems, particularly in human neural stem and progenitor cells. CDC20-M expression was not correlated with the morphological subtypes, nor with the recently defined molecular subtypes of glioma. CDC20-M signature was an independent and robust predictor for poorer prognosis in over 1,000 patients from four large databases. Elevated CDC20-M signature enabled the identification of individual glioma samples with severe chromosome instability and mutation burden and of primary glioma cell lines with extensive mitotic errors leading to chromosome mis-segregation. AURKA, a core member of CDC20-M, was amplified in one-third of CDC20-M-high gliomas with gene-dosage-dependent expression. MLN8237, a Food and Drug Administration-approved AURKA inhibitor, selectively killed temozolomide-resistant primary glioma cells in vitro and prolonged the survival of a patient-derived xenograft mouse model with a high-CDC20-M signature. Our findings suggest that application of the CDC20-M signature may permit more selective use of adjuvant therapies for glioma patients and that dysregulated CDC20-M members may provide a therapeutic vulnerability in glioma.

Chu Z, Zhang X, Li Q, et al.
CDC20 contributes to the development of human cutaneous squamous cell carcinoma through the Wnt/β‑catenin signaling pathway.
Int J Oncol. 2019; 54(5):1534-1544 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Cell division cycle 20 (CDC20) is a regulatory molecule and serves critical roles at multiple points of the cell cycle. Recent evidence indicates that CDC20 may serve an oncogenic role in a number of human cancer types. However, the role of CDC20 in primary cutaneous squamous cell carcinoma (cSCC) has not been studied, to the best of our knowledge. The aim of the present study was to investigate whether and how CDC20 is involved in the tumorigenesis of cSCC. The results revealed that CDC20 expression was significantly increased in cSCC tissues and cell lines, and its expression was associated with pathological differentiation. Downregulation of CDC20 inhibited cell proliferation, induced cell cycle arrest, promoted apoptosis and reduced migratory ability through inhibition of the Wnt/β‑catenin signaling pathway. Furthermore, all‑trans‑retinoic acid treatment significantly downregulated CDC20 expression in cSCC. The present results revealed that CDC20 may serve a crucial role in human cSCC, and suggested that CDC20 may be a novel biomarker for the prevention, diagnosis and treatment of cSCC.

Sun Y, Xiaoyan H, Yun L, et al.
Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis
Asian Pac J Cancer Prev. 2019; 20(1):145-155 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Ovarian cancer is one of the three major gynecologic cancers in the world. The aim of this study is to find the relationship between ovarian cancer and diabetes mellitus by using the genetic screening technique. By GEO database query and related online tools of analysis, we analyzed 185 cases of ovarian cancer and 10 control samples from GSE26712, and a total of 379 different genes were identified, including 104 up-regulated genes and 275 down-regulated genes. The up-regulated genes were mainly enriched in biological processes, including cell adhesion, transcription of nucleic acid and biosynthesis, and negative regulation of cell metabolism. The down-regulated genes were enriched in cell proliferation, migration, angiogenesis and macromolecular metabolism. Protein-protein interaction was analyzed by network diagram and module synthesis analysis. The top ten hub genes (CDC20, H2AFX, ENO1, ACTB, ISG15, KAT2B, HNRNPD, YWHAE, GJA1 and CAV1) were identified, which play important roles in critical signaling pathways that regulate the process of oxidation-reduction reaction and carboxylic acid metabolism. CTD analysis showed that the hub genes were involved in 1,128 distinct diseases (bonferroni-corrected P<0.05). Further analysis by drawing the Kaplan-Meier survival curve indicated that CDC20 and ISG15 were statistically significant (P<0.05). In conclusion, glycometabolism was related to ovarian cancer and genes and proteins in glycometabolism could serve as potential targets in ovarian cancer treatment.

Zhang MY, Liu XX, Li H, et al.
Elevated mRNA Levels of AURKA, CDC20 and TPX2 are associated with poor prognosis of smoking related lung adenocarcinoma using bioinformatics analysis.
Int J Med Sci. 2018; 15(14):1676-1685 [PubMed] Article available free on PMC after 15/09/2019 Related Publications

Doğan Şiğva ZÖ, Balci Okcanoğlu T, Biray Avci Ç, et al.
Investigation of the synergistic effects of paclitaxel and herbal substances and endemic plant extracts on cell cycle and apoptosis signal pathways in prostate cancer cell lines.
Gene. 2019; 687:261-271 [PubMed] Related Publications
Paclitaxel, which isolated from Taxus brevifolia, is recently started to be used against prostate cancer treatment and it is a very effective compound against cancer. In this study, we aimed to test the synergistic effect of two plant active compounds (sulphoraphane (SFN) and silymarin (SILY)) and several endemic plant species from Turkey (such as Phlomis leucophracta, Rubia davisiana, Alkanna tinctoria), which are known to have anticarcinogenic effect on androgen-independent PC3 and DU145, and androgen-dependent VCaP prostate cancer cell lines, with paclitaxel on the expression of cell cycle signaling and apoptosis regulator genes. Herbal substances and endemic herbal extracts were combined with Paclitaxel drug. IC

Sun C, Cheng X, Wang C, et al.
Gene expression profiles analysis identifies a novel two-gene signature to predict overall survival in diffuse large B-cell lymphoma.
Biosci Rep. 2019; 39(1) [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Diffuse large B-cell lymphoma (DLBCL) is the most common hematologic malignancy, however, specific tumor-associated genes and signaling pathways are yet to be deciphered. Differentially expressed genes (DEGs) were computed based on gene expression profiles from GSE32018, GSE56315, and The Cancer Genome Atlas (TCGA) DLBC. Overlapping DEGs were then evaluated for gene ontology (GO), pathways enrichment, DNA methylation, protein-protein interaction (PPI) network analysis as well as survival analysis. Seventy-four up-regulated and 79 down-regulated DEGs were identified. From PPI network analysis, majority of the DEGs were involved in cell cycle, oocyte meiosis, and epithelial-to-mesenchymal transition (EMT) pathways. Six hub genes including

Zhuang L, Yang Z, Meng Z
Upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in Tumor Tissues Predicted Worse Overall Survival and Disease-Free Survival in Hepatocellular Carcinoma Patients.
Biomed Res Int. 2018; 2018:7897346 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Objective: To evaluate the association between upregulated differentially expressed genes (DEGs) and the outcomes of patients with hepatocellular carcinoma (HCC).
Methods: Using Gene Expression Omnibus (GEO) datasets including GSE45436, GSE55092, GSE60502, GSE84402, and GSE17548, we detected upregulated DEGs in tumors. KEGG, GO, and Reactome enrichment analysis of the DEGs was conducted to clarify their function. The impact of the upregulated DEGs on patients' survival was analyzed based on TCGA profile.
Results: 161 shared upregulated DEGs were identified among GSE45436, GSE55092, GSE60502, and GSE84402 profiles. Cell cycle was the shared pathway/biological process in the gene sets investigation among databases of KEGG, GO, and Reactome. After being validated in GSE17548, 13 genes including BUB1B, CCNA2, CCNB1, CCNE2, CDC20, CDC6, CDC7, CDK1, CDK4, CDKN2A, CHEK1, MAD2L1, and MCM3 in cell cycle pathway were shared in the three databases for enrichment. The expression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 was upregulated in HCC tissues when compared with adjacent normal tissues in 6.67%, 7.5%, 8.06%, 5.56%, and 9.72% of HCC patients, respectively. Overexpression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues accounted for poorer overall survival (OS) and disease-free survival (DFS) in HCC patients (all log rank
Conclusion: Correlated with advanced histologic grade and/or vascular invasion, upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues predicted worse OS and DFS in HCC patients. These genes could be novel therapeutic targets for HCC treatment.

Hu S, Liao Y, Chen L
Identification of Key Pathways and Genes in Anaplastic Thyroid Carcinoma via Integrated Bioinformatics Analysis.
Med Sci Monit. 2018; 24:6438-6448 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
BACKGROUND To provide a better understanding of anaplastic thyroid carcinoma (ATC) at the molecular level, this study aimed to identify the genes and key pathways associated with ATC by using integrated bioinformatics analysis. MATERIAL AND METHODS Based on the microarray data GSE9115, GSE65144, and GSE53072 derived from the Gene Expression Omnibus, the differentially expressed genes (DEGs) between ATC samples and normal controls were identified. With DEGs, we performed a series of functional enrichment analyses. Then, a protein-protein interaction (PPI) network was constructed and visualized, with which the hub gene nodes were screened out. Finally, modules analysis for the PPI network was performed to further investigate the potential relationships between DEGs and ATC. RESULTS A total of 537 common DEGs were screened out from all 3 datasets, among which 247 genes were upregulated and 275 genes were downregulated. GO analysis indicated that upregulated DEGs were mainly involved in cell division and mitotic nuclear division and the downregulated DEGs were significantly enriched in ventricular cardiac muscle cell action potential. KEGG pathway analysis showed that the upregulated DEGs were mainly enriched in cell cycle and ECM-receptor interaction and the downregulated DEGs were mainly enriched in thyroid hormone synthesis, insulin resistance, and pathways in cancer. The top 10 hub genes in the constructed PPI network were CDK1, CCNB1, TOP2A, AURKB, CCNA2, BUB1, AURKA, CDC20, MAD2L1, and BUB1B. The modules analysis showed that genes in the top 2 significant modules of PPI network were mainly associated with mitotic cell cycle and positive regulation of mitosis, respectively. CONCLUSIONS We identified a series of key genes along with the pathways that were most closely related with ATC initiation and progression. Our results provide a more detailed molecular mechanism for the development of ATC, shedding light on the potential biomarkers and therapeutic targets.

Zhang B, Lu HY, Xia YH, et al.
Long non-coding RNA EPIC1 promotes human lung cancer cell growth.
Biochem Biophys Res Commun. 2018; 503(3):1342-1348 [PubMed] Related Publications
Long non-coding RNA (LncRNA) EPIC1 (Lnc-EPIC1) is a MYC-interacting LncRNA. In the present study, the expression and potential function of Lnc-EPIC1 in human lung cancer cells are tested. We show that Lnc-EPIC1 expression is significantly higher in established/primary human lung cancer cells than that in human lung epithelial cells. Lnc-EPIC1 is also elevated in human lung cancer tissues. Silencing of Lnc-EPIC1 by targeted siRNA significantly inhibited human lung cancer cell growth, survival and proliferation, whiling inducing G1-S cell cycle arrest and cell apoptosis. MYC targets, including Cyclin A1, CDC20 and CDC45, were downregulated by Lnc-EPIC1 siRNA. MYC knockout by CRISPR/Cas-9 gene-editing method mimicked actions by Lnc-EPIC1 siRNA in A549 cells. Conversely, forced overexpression of Lnc-EPIC1 by a lentiviral construct increased expression of MYC targets to promote A549 cell growth. Lnc-EPIC1 directly associated with MYC protein in the nuclei of A549 cells. Significantly MYC knockout abolished Lnc-EPIC1 silencing- or overexpression-induced actions in human lung cancer cells. Together, our results show that Lnc-EPIC1 promotes human lung cancer cell growth possibly by targeting MYC.

Zhang Y, Xia Q, Lin J
Identification of the potential oncogenes in glioblastoma based on bioinformatic analysis and elucidation of the underlying mechanisms.
Oncol Rep. 2018; 40(2):715-725 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Glioblastoma (GBM) is a common malignant tumour in the human brain, but its molecular mechanisms have not been systematically evaluated. The aim of this study was to identify potential key oncogenes associated with the progression of GBM and to elucidate their mechanisms. The gene expression profile of GSE50161, selected from the Gene Expression Omnibus database, was analysed to find cancer‑associated genes and gene functions in GBM. In total, 486 differentially expressed genes, including 128 upregulated genes, were identified. The function and pathway enrichment of these genes were analysed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Survival analysis for three selected partially upregulated genes, CDK1, CCNB1 and CDC20, showed that their high expression was significantly associated with poor survival in GBM. CDK1 was selected for validation of its function and molecular mechanism in GBM. This gene was significantly overexpressed in GBM cancer tissues and cells compared with normal control cells. In addition, knockdown of CDK1 clearly inhibited GBM cell proliferation. Notably, we demonstrated that CDK1 was involved in the Akt signalling pathway, where it promotes the process involved in GBM malignancy.

Wen P, Chidanguro T, Shi Z, et al.
Identification of candidate biomarkers and pathways associated with SCLC by bioinformatics analysis.
Mol Med Rep. 2018; 18(2):1538-1550 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Small cell lung cancer (SCLC) is one of the highly malignant tumors and a serious threat to human health. The aim of the present study was to explore the underlying molecular mechanisms of SCLC. mRNA microarray datasets GSE6044 and GSE11969 were downloaded from Gene Expression Omnibus database, and the differentially expressed genes (DEGs) between normal lung and SCLC samples were screened using GEO2R tool. Functional and pathway enrichment analyses were performed for common DEGs using the DAVID database, and the protein‑protein interaction (PPI) network of common DEGs was constructed by the STRING database and visualized with Cytoscape software. In addition, the hub genes in the network and module analysis of the PPI network were performed using CentiScaPe and plugin Molecular Complex Detection. Finally, the mRNA expression levels of hub genes were validated in the Oncomine database. A total of 150 common DEGs with absolute fold‑change >0.5, including 66 significantly downregulated DEGs and 84 upregulated DEGs were obtained. The Gene Ontology term enrichment analysis suggested that common upregulated DEGs were primarily enriched in biological processes (BPs), including 'cell cycle', 'cell cycle phase', 'M phase', 'cell cycle process' and 'DNA metabolic process'. The common downregulated genes were significantly enriched in BPs, including 'response to wounding', 'positive regulation of immune system process', 'immune response', 'acute inflammatory response' and 'inflammatory response'. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified that the common downregulated DEGs were primarily enriched in the 'complement and coagulation cascades' signaling pathway; the common upregulated DEGs were mainly enriched in 'cell cycle', 'DNA replication', 'oocyte meiosis' and the 'mismatch repair' signaling pathways. From the PPI network, the top 10 hub genes in SCLC were selected, including topoisomerase IIα, proliferating cell nuclear antigen, replication factor C subunit 4, checkpoint kinase 1, thymidylate synthase, minichromosome maintenance protein (MCM) 2, cell division cycle (CDC) 20, cyclin dependent kinase inhibitor 3, MCM3 and CDC6, the mRNA levels of which are upregulated in Oncomine SCLC datasets with the exception of MCM2. Furthermore, the genes in the significant module were enriched in 'cell cycle', 'DNA replication' and 'oocyte meiosis' signaling pathways. Therefore, the present study can shed new light on the understanding of molecular mechanisms of SCLC and may provide molecular targets and diagnostic biomarkers for the treatment and early diagnosis of SCLC.

Wen DY, Lin P, Pang YY, et al.
Expression of the Long Intergenic Non-Protein Coding RNA 665 (LINC00665) Gene and the Cell Cycle in Hepatocellular Carcinoma Using The Cancer Genome Atlas, the Gene Expression Omnibus, and Quantitative Real-Time Polymerase Chain Reaction.
Med Sci Monit. 2018; 24:2786-2808 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
BACKGROUND Long non-coding RNAs (lncRNAs) have a role in physiological and pathological processes, including cancer. The aim of this study was to investigate the expression of the long intergenic non-protein coding RNA 665 (LINC00665) gene and the cell cycle in hepatocellular carcinoma (HCC) using database analysis including The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and quantitative real-time polymerase chain reaction (qPCR). MATERIAL AND METHODS Expression levels of LINC00665 were compared between human tissue samples of HCC and adjacent normal liver, clinicopathological correlations were made using TCGA and the GEO, and qPCR was performed to validate the findings. Other public databases were searched for other genes associated with LINC00665 expression, including The Atlas of Noncoding RNAs in Cancer (TANRIC), the Multi Experiment Matrix (MEM), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) networks. RESULTS Overexpression of LINC00665 in patients with HCC was significantly associated with gender, tumor grade, stage, and tumor cell type. Overexpression of LINC00665 in patients with HCC was significantly associated with overall survival (OS) (HR=1.47795%; CI: 1.046-2.086). Bioinformatics analysis identified 469 related genes and further analysis supported a hypothesis that LINC00665 regulates pathways in the cell cycle to facilitate the development and progression of HCC through ten identified core genes: CDK1, BUB1B, BUB1, PLK1, CCNB2, CCNB1, CDC20, ESPL1, MAD2L1, and CCNA2. CONCLUSIONS Overexpression of the lncRNA, LINC00665 may be involved in the regulation of cell cycle pathways in HCC through ten identified hub genes.

Wang Z, Yang B, Zhang M, et al.
lncRNA Epigenetic Landscape Analysis Identifies EPIC1 as an Oncogenic lncRNA that Interacts with MYC and Promotes Cell-Cycle Progression in Cancer.
Cancer Cell. 2018; 33(4):706-720.e9 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
We characterized the epigenetic landscape of genes encoding long noncoding RNAs (lncRNAs) across 6,475 tumors and 455 cancer cell lines. In stark contrast to the CpG island hypermethylation phenotype in cancer, we observed a recurrent hypomethylation of 1,006 lncRNA genes in cancer, including EPIC1 (epigenetically-induced lncRNA1). Overexpression of EPIC1 is associated with poor prognosis in luminal B breast cancer patients and enhances tumor growth in vitro and in vivo. Mechanistically, EPIC1 promotes cell-cycle progression by interacting with MYC through EPIC1's 129-283 nt region. EPIC1 knockdown reduces the occupancy of MYC to its target genes (e.g., CDKN1A, CCNA2, CDC20, and CDC45). MYC depletion abolishes EPIC1's regulation of MYC target and luminal breast cancer tumorigenesis in vitro and in vivo.

Liu WT, Wang Y, Zhang J, et al.
A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.
Cancer Lett. 2018; 425:43-53 [PubMed] Related Publications
Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA

Wu F, Lin Y, Cui P, et al.
Cdc20/p55 mediates the resistance to docetaxel in castration-resistant prostate cancer in a Bim-dependent manner.
Cancer Chemother Pharmacol. 2018; 81(6):999-1006 [PubMed] Related Publications
PURPOSE: At least to date, no effective treatment for advanced castration-resistant prostate cancer (CRPC) has been established. Recent studies indicated that cell division cycle 20 homolog (Cdc20) overexpression is associated with poor prognosis in patients with castration-resistant prostate cancer. However, the mechanism of Cdc20 in the development of docetaxel resistance in CRPC remains elusive.
METHODS: In this study, the transcription of Cdc20 was confirmed in three independent CRPC cell lines derived from different tissues, including LNCaP, PC3, and DU145. Docetaxel resistant (DR) cell lines were generated within the background of DU145 and PC3. The protein levels of Cdc20 and the biological phenotype were detected in both wild-type and DR cell lines. To further explore the mechanism of Cdc20 overexpression, stable cell lines with Cdc20 or Bcl-2 interacting mediator of cell death (Bim) deprivation were generated and examined for biological parameters. In addition, a specific Cdc20 inhibitor was used in DR cell lines to explore the potential solution for docetaxel resistant CRPC.
RESULTS: Here, we identified Cdc20 is overexpressed in docetaxel resistant CRPC cell lines, including LNCaP, PC3, and DU145. We also reported that DR cell lines, which mimic the recurrent prostate cancer cells after docetaxel treatment, have higher levels of Cdc20 protein compared with the CRPC cell lines. Interestingly, the protein levels of Bim, an E3 ligase substrate of Cdc20, were decreased in DR cell lines compared with the wild-type, while the mRNA levels were similar. More importantly, in DR cell lines, the biological phenotype induced by Cdc20 deletion could be significantly reversed by the additional knockdown of Bim. As a result, docetaxel resistant prostate cancer cells treated with the pharmacological Cdc20 inhibitor became sensitive to docetaxel treatment.
CONCLUSIONS: In conclusion, our data collectively demonstrated that Cdc20 overexpression facilitates the docetaxel resistant of the CRPC cell lines in a Bim-dependent manner. Furthermore, additionally targeting Cdc20 might be a promising solution for the treatment of the CRPC with docetaxel resistance.

Guo W, Zhong K, Wei H, et al.
Long non-coding RNA SPRY4-IT1 promotes cell proliferation and invasion by regulation of Cdc20 in pancreatic cancer cells.
PLoS One. 2018; 13(2):e0193483 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) play a critical role in the development of human cancers including pancreatic cancer. Long non-coding RNA SPRY4-IT1 (sprouty4-intron transcript 1) has been reported to play an oncogenic role in various types of human carcinomas. However, the role of SPRY4-IT1 in pancreatic cancer is unclear. The objective of this study was to determine the function of SPRY4-IT1 on proliferation and invasion in pancreatic cancer. In the current study, we dissected the function and mechanism of SPRY4-IT1 by multiple approaches including Real-time RT-PCR, Western blotting analysis, MTT assay, Wound healing assay, Transwell assay, and transfection. We found that down-regulation of SPRY4-IT1 inhibited cell growth and induced cell apoptosis in pancreatic cancer cells. Moreover, SPRY4-IT1 knockdown induced cell cycle arrest at G0/G1 phase. Furthermore, inhibition of SPRY4-IT1 retarded cell migration and invasion in pancreatic cancer cells. Overexpression of SPRY4-IT1 enhanced cell growth and invasion, and inhibited cell apoptosis in pancreatic cancer cells. Mechanistically, suppression of SPRY4-IT1 inhibited the expression of Cdc20 in pancreatic cancer cells. Our findings demonstrated that inhibition of SPRY4-IT1 could be a potential therapeutic approach for the treatment of pancreatic cancer.

He X, Zhang C, Shi C, Lu Q
Meta-analysis of mRNA expression profiles to identify differentially expressed genes in lung adenocarcinoma tissue from smokers and non-smokers.
Oncol Rep. 2018; 39(3):929-938 [PubMed] Related Publications
Compared to other types of lung cancer, lung adenocarcinoma patients with a history of smoking have a poor prognosis during the treatment of lung cancer. How lung adenocarcinoma-related genes are differentially expressed between smoker and non-smoker patients has yet to be fully elucidated. We performed a meta-analysis of four publicly available microarray datasets related to lung adenocarcinoma tissue in patients with a history of smoking using R statistical software. The top 50 differentially expressed genes (DEGs) in smoking vs. non‑smoking patients are shown using heat maps. Additionally, we conducted KEGG and GO analyses. In addition, we performed a PPI network analysis for 8 genes that were selected during a previous analysis. We identified a total of 2,932 DEGs (1,806 upregulated, 1,126 downregulated) and five genes (CDC45, CDC20, ANAPC7, CDC6, ESPL1) that may link lung adenocarcinoma to smoking history. Our study may provide new insights into the complex mechanisms of lung adenocarcinoma in smoking patients, and our novel gene expression signatures will be useful for future clinical studies.

Shi SQ, Ke JJ, Xu QS, et al.
Integrated network analysis to identify the key genes, transcription factors, and microRNAs involved in hepatocellular carcinoma.
Neoplasma. 2018; 65(1):66-74 [PubMed] Related Publications
HCC (hepatocellular carcinoma), which can be induced by cirrhosis and viral hepatitis infection, is the most frequent form of liver cancer. This study is performed to investigate the mechanisms of HCC. GSE57957 was obtained from Gene Expression Omnibus database, including 39 HCC samples and 39 adjacent non-tumorous samples. The DEGs (differentially expressed genes) were screened using the limma package in R, and then were conducted with enrichment analysis using "BioCloud" platform. Using STRING database, WebGestalt tool, as well as ITFP and TRANSFAC databases, PPI (protein-protein interaction) pairs, miRNA (microRNA)-target pairs, and TF (transcription factor)-target pairs separately were predicted. Followed by integrated network was constructed by Cytoscape software and module analysis was performed using the MCODE plugin of Cytoscape software. There were 518 DEGs identified from the HCC samples, among which 17 up-regulated genes (including MCM2, MCM6, and CDC20) and 5 down-regulated genes could also function as TFs. In the integrated network for the down-regulated genes, FOS and ESR1 had higher degrees, and both of them were targeted by miR-221 and miR-222. Additionally, MCM2 had interaction with MCM6 in the up-regulated module with the highest score. MCM2, MCM6, CDC20, FOS, ESR1, miR-221 and miR-222 might affect the pathogenesis of HCC.

Piao J, Sun J, Yang Y, et al.
Target gene screening and evaluation of prognostic values in non-small cell lung cancers by bioinformatics analysis.
Gene. 2018; 647:306-311 [PubMed] Related Publications
BACKGROUND: Non-small cell lung cancer (NSCLC) is the major leading cause of cancer-related deaths worldwide. This study aims to explore molecular mechanism of NSCLC.
METHODS: Microarray dataset was obtained from the Gene Expression Omnibus (GEO) database, and analyzed by using GEO2R. Functional and pathway enrichment analysis were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Then, STRING, Cytoscape and MCODE were applied to construct the Protein-protein interaction (PPI) network and screen hub genes. Following, overall survival (OS) analysis of hub genes was performed by using the Kaplan-Meier plotter online tool. Moreover, miRecords was also applied to predict the targets of the differentially expressed microRNAs (DEMs).
RESULTS: A total of 228 DEGs were identified, and they were mainly enriched in the terms of cell adhesion molecules, leukocyte transendothelial migration and ECM-receptor interaction. A PPI network was constructed, and 16 hub genes were identified, including TEK, ANGPT1, MMP9, VWF, CDH5, EDN1, ESAM, CCNE1, CDC45, PRC1, CCNB2, AURKA, MELK, CDC20, TOP2A and PTTG1. Among the genes, expressions of 14 hub genes were associated with prognosis of NSCLC patients. Additionally, a total of 11 DEMs were also identified.
CONCLUSION: Our results provide some potential underlying biomarkers for NSCLC. Further studies are required to elucidate the pathogenesis of NSCLC.

Horning AM, Wang Y, Lin CK, et al.
Single-Cell RNA-seq Reveals a Subpopulation of Prostate Cancer Cells with Enhanced Cell-Cycle-Related Transcription and Attenuated Androgen Response.
Cancer Res. 2018; 78(4):853-864 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Increasing evidence suggests the presence of minor cell subpopulations in prostate cancer that are androgen independent and poised for selection as dominant clones after androgen deprivation therapy. In this study, we investigated this phenomenon by stratifying cell subpopulations based on transcriptome profiling of 144 single LNCaP prostate cancer cells treated or untreated with androgen after cell-cycle synchronization. Model-based clustering of 397 differentially expressed genes identified eight potential subpopulations of LNCaP cells, revealing a previously unappreciable level of cellular heterogeneity to androgen stimulation. One subpopulation displayed stem-like features with a slower cell doubling rate, increased sphere formation capability, and resistance to G

Budczies J, Denkert C, Győrffy B, et al.
Chromosome 9p copy number gains involving PD-L1 are associated with a specific proliferation and immune-modulating gene expression program active across major cancer types.
BMC Med Genomics. 2017; 10(1):74 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
BACKGROUND: Inhibition of the PD-L1/PD-1 immune checkpoint axis represents one of the most promising approaches of immunotherapy for various cancer types. However, immune checkpoint inhibition is successful only in subpopulations of patients emphasizing the need for powerful biomarkers that adequately reflect the complex interaction between the tumor and the immune system. Recently, recurrent copy number gains (CNG) in chromosome 9p involving PD-L1 were detected in many cancer types including lung cancer, melanoma, bladder cancer, head and neck cancer, cervical cancer, soft tissue sarcoma, prostate cancer, gastric cancer, ovarian cancer, and triple-negative breast cancer.
METHODS: Here, we applied functional genomics to analyze global mRNA expression changes associated with chromosome 9p gains. Using the TCGA data set, we identified a list of 75 genes that were strongly up-regulated in tumors with chromosome 9p gains across many cancer types.
RESULTS: As expected, the gene set was enriched for chromosome 9p and in particular chromosome 9p24 (36 genes and 23 genes). Furthermore, we found enrichment of two expression programs derived from genes within and beyond 9p: one implicated in cell cycle regulation (22 genes) and the other implicated in modulation of the immune system (16 genes). Among these were specific cytokines and chemokines, e.g. CCL4, CCL8, CXCL10, CXCL11, other immunoregulatory genes such as IFN-G and IDO1 as well as highly expressed proliferation-related kinases and genes including PLK1, TTK, MELK and CDC20 that represent potential drug targets.
CONCLUSIONS: Collectively, these data shed light on mechanisms of immune escape and stimulation of proliferation in cancer with PD-L1 CNG and highlight additional vulnerabilities that may be therapeutically exploitable.

Parmar MB, Meenakshi Sundaram DN, K C RB, et al.
Combinational siRNA delivery using hyaluronic acid modified amphiphilic polyplexes against cell cycle and phosphatase proteins to inhibit growth and migration of triple-negative breast cancer cells.
Acta Biomater. 2018; 66:294-309 [PubMed] Related Publications
Triple-negative breast cancer is an aggressive form of breast cancer with few therapeutic options if it recurs after adjuvant chemotherapy. RNA interference could be an alternative therapy for metastatic breast cancer, where small interfering RNA (siRNA) can silence the expression of aberrant genes critical for growth and migration of malignant cells. Here, we formulated a siRNA delivery system using lipid-substituted polyethylenimine (PEI) and hyaluronic acid (HA), and characterized the size, ζ-potential and cellular uptake of the nanoparticulate delivery system. Higher cellular uptake of siRNA by the tailored PEI/HA formulation suggested better interaction of complexes with breast cancer cells due to improved physicochemical characteristics of carrier and HA-binding CD44 receptors. The siRNAs against specific phosphatases that inhibited migration of MDA-MB-231 cells were then identified using library screen against 267 protein-tyrosine phosphatases, and siRNAs to inhibit cell migration were further validated. We then assessed the combinational delivery of a siRNA against CDC20 to decrease cell growth and a siRNA against several phosphatases shown to decrease migration of breast cancer cells. Combinational siRNA therapy against CDC20 and identified phosphatases PPP1R7, PTPN1, PTPN22, LHPP, PPP1R12A and DUPD1 successfully inhibited cell growth and migration, respectively, without interfering the functional effect of the co-delivered siRNA. The identified phosphatases could serve as potential targets to inhibit migration of highly aggressive metastatic breast cancer cells. Combinational siRNA delivery against cell cycle and phosphatases could be a promising strategy to inhibit both growth and migration of metastatic breast cancer cells, and potentially other types of metastatic cancer.
STATEMENT OF SIGNIFICANCE: The manuscript investigated the efficacy of a tailored polymeric siRNA delivery system formulation as well as combinational siRNA therapy in metastatic breast cancer cells to inhibit malignant cell growth and migration. The siRNA delivery was undertaken by non-viral means with PEI/HA. We identified six phosphatases that could be critical targets to inhibit migration of highly aggressive metastatic breast cancer cells. We further report on specifically targeting cell cycle and phosphatase proteins to decrease both malignant cell growth and migration simultaneously. Clinical gene therapy against metastatic breast cancer with effective and safe delivery systems is urgently needed to realize the potential of molecular medicine in this deadly disease and our studies in this manuscript is intended to facilitate this endeavor.

Shi G, Wang Y, Zhang C, et al.
Identification of genes involved in the four stages of colorectal cancer: Gene expression profiling.
Mol Cell Probes. 2018; 37:39-47 [PubMed] Related Publications
BACKGROUND: Colorectal cancer (CRC) is a common cancer with high morbidity and mortality. However, its molecular mechanism is not clear, nor the genes related to CRC stages.
METHODS: Gene expression data in CRC and healthy colorectal tissues were obtained from gene expression omnibus. Limma package was used to identify the differentially expressed genes (DEGs) between control and CRC (stage I, II, III, and IV), obtaining 4 DEG sets. VennPlex was utilized to find all DEGs and intersection DEGs. Functional interactions between all DEGs and protein-protein interactions (PPIs) between intersection DEGs were analyzed using ReactomeFIViz and STRING, respectively, and networks were visualized. Known CRC-related genes were down-loaded from Comparative Toxicogenomics Database and mapped to PPI network.
RESULTS: Totally, 851, 760, 729, and 878 DEGs were found between control and CRC stage I, II, III, and IV, respectively. Taken together, 1235 DEGs were found, as well as 128 up-regulated intersection DEGs, 365 down-regulated intersection DEGs, and 0 contra-regulated DEG. A functional interaction network of all DEGs and a PPI network of intersection DEGs were constructed, in which CDC20, PTTG1, and MAD2L1 interacted with BUB1B; UGT2B17 interacted with ADH1B; MCM7 interacted with MCM2. BUB1B, ADH1B, and MCM2 were known CRC-related genes. Gradually upregulated expressions of CDC20, PTTG1, MAD2L1, UGT2B17, and MCM7 in stage I, II, III, and IV CRC were confirmed by using quantitative PCR. Besides, up-regulated intersection DEGs enriched in pathways about Cell cycle, DNA replication, and p53 signaling.
CONCLUSION: CDC20, PTTG1, MAD2L1, UGT2B17, and MCM7 might be CRC stage-related genes.

Yi J, Wei X, Li X, et al.
A genome-wide comprehensive analysis of alterations in driver genes in non-small-cell lung cancer.
Anticancer Drugs. 2018; 29(1):10-18 [PubMed] Related Publications
Lung cancer is one of the most common malignancies and the leading cause of cancer-related deaths worldwide. Although many oncogenes and tumor suppressors have been uncovered in the past decades, the pathogenesis and mechanisms of lung tumorigenesis and progression are unclear. The advancement of high-throughput sequencing technique and bioinformatics methods has led to the discovery of some unknown important protein-coding genes or noncoding RNAs in human cancers. In this study, we tried to identify and validate lung cancer driver genes to facilitate the diagnosis and individualized treatment of patients with this disease. To analyze distinct gene profile in lung cancer, the RNA sequencing data from TCGA and microarray data from Gene Expression Omnibus were used. Then, shRNA-pooled screen data and CRISPR-Cas9-based screen data in lung cancer cells were used to validate the functional roles of identified genes. We found that thousands of gene expression patterns are altered in lung cancer, and genomic alterations contribute to the dysregulation of these genes. Furthermore, we identified some potential lung cancer driver genes, such as TBX2, MCM4, SLC2A1, BIRC5, and CDC20, whose expression is significantly upregulated in lung cancer, and the copy number of these genes is amplified in the genome of patients with lung cancer. More importantly, overexpression of these genes is associated with poorer survival of patients with lung cancer, and knockdown or knockout of these genes results in decreased cell proliferation in lung cancer cells. Taken together, the genomewide comprehensive analysis combined with screen data analyses may provide a valuable help for identifying cancer driver genes for diagnosis and prevention of patients with lung cancer.

Grey W, Ivey A, Milne TA, et al.
The Cks1/Cks2 axis fine-tunes Mll1 expression and is crucial for MLL-rearranged leukaemia cell viability.
Biochim Biophys Acta Mol Cell Res. 2018; 1865(1):105-116 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
The Cdc28 protein kinase subunits, Cks1 and Cks2, play dual roles in Cdk-substrate specificity and Cdk-independent protein degradation, in concert with the E3 ubiquitin ligase complexes SCF

Li L, Lei Q, Zhang S, et al.
Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis.
Oncol Rep. 2017; 38(5):2607-2618 [PubMed] Article available free on PMC after 15/09/2019 Related Publications
Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the molecular mechanisms of HCC are still not well understood. To identify the candidate genes in the carcinogenesis and progression of HCC, microarray datasets GSE19665, GSE33006 and GSE41804 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. A total of 273 DEGs were identified, consisting of 189 downregulated genes and 84 upregulated genes. The enriched functions and pathways of the DEGs include protein activation cascade, complement activation, carbohydrate binding, complement and coagulation cascades, mitotic cell cycle and oocyte meiosis. Sixteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell division, cell cycle and nuclear division. Survival analysis showed that BUB1, CDC20, KIF20A, RACGAP1 and CEP55 may be involved in the carcinogenesis, invasion or recurrence of HCC. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of HCC, and provide candidate targets for diagnosis and treatment of HCC.

Disclaimer: This site is for educational purposes only; it can not be used in diagnosis or treatment.

Cite this page: Cotterill SJ. CDC20, Cancer Genetics Web: Accessed:

Creative Commons License
This page in Cancer Genetics Web by Simon Cotterill is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Note: content of abstracts copyright of respective publishers - seek permission where appropriate.

 [Home]    Page last revised: 01 September, 2019     Cancer Genetics Web, Established 1999