BUB1 Mitotic Checkpoint Research Articles

Identification of key candidate genes involved in melanoma metastasis

Metastasis is the most lethal stage of cancer progression. The present study aimed to investigate the underlying molecular mechanisms of melanoma metastasis using bioinformatics. Using the microarray dataset GSE8401 from the Gene Expression Omnibus database, which included 52 biopsy specimens from patients with melanoma metastasis and 31 biopsy specimens from patients with primary melanoma, differentially expressed genes (DEGs) were identified, subsequent to data preprocessing with the affy package, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A protein-protein interaction (PPI) network was constructed. Mutated genes were analyzed with 80 mutated cases with melanoma from The Cancer Genome Atlas. The overall survival of key candidate DEGs, which were within a filtering of degree >30 criteria in the PPI network and involved three or more KEGG signaling pathways, and genes with a high mutation frequency were delineated. The expression analysis of key candidate DEGs, mutant genes and their associated genes were performed on UALCAN. Of the 1,187 DEGs obtained, 505 were upregulated and 682 were downregulated. ‘Extracellular exosome’ processes, the ‘amoebiasis’ pathway, the ‘ECM-receptor interaction’ pathway and the ‘focal adhesion’ signaling pathway were significantly enriched and identified as important processes or signaling pathways. The overall survival analysis of phosphoinositide-3-kinase regulator subunit 3 (PIK3R3), centromere protein M (CENPM), aurora kinase A (AURKA), laminin subunit α 1 (LAMA1), proliferating cell nuclear antigen (PCNA), adenylate cyclase 1 (ADCY1), BUB1 mitotic checkpoint serine/threonine kinase (BUB1), NDC80 kinetochore complex component (NDC80) and protein kinase C α (PRKCA) in DEGs was statistically significant. Mutation gene analysis identified that BRCA1-associated protein 1 (BAP1) had a higher mutation frequency and survival analysis, and its associated genes in the BAP1-associated PPI network, including ASXL transcriptional regulator 1 (ASXL1), proteasome 26S subunit, non-ATPase 3 (PSMD3), proteasome 26S subunit, non ATPase 11 (PSMD11) and ubiquitin C (UBC), were statistically significantly associated with the overall survival of patients with melanoma. The expression levels of PRKCA, BUB1, BAP1 and ASXL1 were significantly different between primary melanoma and metastatic melanoma. Based on the present study, ‘extracellular exosome’ processes, ‘amoebiasis’ pathways, ‘ECM-receptor interaction’ pathways and ‘focal adhesion’ signaling pathways may be important in the formation of metastases from melanoma. The involved genes, including PIK3R3, CENPM, AURKA, LAMA1, PCNA, ADCY1, BUB1, NDC80 and PRKCA, and mutation associated genes, including BAP1, ASXL1, PSMD3, PSMD11 and UBC, may serve important roles in metastases of melanoma.

Comprehensive analysis of microRNA-messenger RNA regulatory network in gemcitabine-resistant bladder cancer cells.

Chemotherapy is still a standard treatment of unresectable bladder cancer or distant metastases. The chemotherapy resistance always occurs after a period of treatment indicating poor prognosis. The current study aimed to explore the molecular mechanism of chemoresistance in bladder cancer cells. The gene expression profiles of GSE77883, including three untreated T24 cells samples and three gemcitabine-resistant T24 cells samples, was downloaded from Gene Expression Omnibus database. The screening of differentially expressed genes (DEGs), gene function analysis, and interaction prediction between microRNAs (miRNAs) and DEGs were performed by R software. The protein-protein interaction (PPI) and miRNA-DEGs networks were constructed and visualized by Cytoscape software. Then, the small molecules, with potential synergistic or antagonistic effects to gemcitabine resistance, were identified using the Connectivity Mapdatabase. Finally, gemcitabine-resistant T24 cell line was established and key genes were validated by quantitative real-time polymerase chain reaction (qRT-PCR). In total, 536 upregulated and 513 downregulated genes were screened and mainly enriched in oxidative stress response and signaling pathways related to extracellular matrix-receptor interaction and focal adhesion. PPI network showed interleukin 6, tumor necrosis factor, kinesin family member 11, and BUB1 mitotic checkpoint serine/threonine kinase B were key genes. The miRNA-DEGs regulatory networks included 18 miRNAs and 185 DEGs, including miR-182-5p, miR-590-3p, miR-320a and serum- and glucocorticoid-regulated kinase 1 (SGK1). Then, the related key genes and miRNAs were confirmed by qRT-PCR. Furthermore, 81 small molecules with antagonistic or synergistic effect to GEM were screened. We have investigated the molecular mechanisms driving GEM-resistance in bladder cancer cells that would contribute to the development of chemotherapy for advanced bladder cancer.

Examining the key genes and pathways in hepatocellular carcinoma development from hepatitis B virus‑positive cirrhosis.

To identify the key genes and pathways in the development of hepatocellular carcinoma (HCC) from hepatitis B virus (HBV)-positive liver cirrhosis, differentially expressed genes (DEGs) between HCC and liver cirrhosis tissue samples from the GSE17548 gene expression profile dataset were screened. A total of 1,845 DEGs were identified, including 1,803 upregulated and 42 downregulated genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) network analyses were performed. It was identified that the ‘cell cycle’ and ‘progesterone-mediated oocyte maturation’ KEGG pathways were significantly enriched in the DEGs. In addition, the high expression of the hub genes from the PPI network (including cyclin dependent kinase 1, cyclin B1, cyclin B2, mitotic arrest deficient 2 like 1, BUB1 mitotic checkpoint serine/threonine kinase and cyclin A2; P=0.00116, 0.00021, 0.04889, 0.00222, 0.00015 and 0.00647, respectively) was associated with a decrease in overall survival for patients with HCC as identified using survival and expression data from The Cancer Genome Atlas. The identified hub genes and pathways may help to elucidate the molecular mechanisms of HCC progression from HBV-positive liver cirrhosis. Additionally, they may be useful as therapeutic targets or serve as novel biomarkers for HCC prognosis prediction.

Bioinformatics analysis of key differentially expressed genes in well and poorly differentiated endometrial carcinoma.

Endometrial carcinoma (EC) is one of the most common gynecological malignancies. The malignant degree increases between grade (G)1 and G3, and EC of G3 usually presents a high recurrence rate and poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in EC. The microarrays GSE17025, GSE24537 and GSE35784, representing data of Type I EC samples of G1 and G3, were downloaded from the Gene Expression Omnibus. The differentially expressed genes (DEGs) and differentially expressed micro (mi)RNAs (DEMs) were identified, followed by functional enrichment analyses and interaction network construction. In total, 83upregulated and 130downregulated DEGs with the same expression trends in two mRNA datasets were screened. The upregulated DEGs were primarily enriched in 'mitotic cell cycle process', 'cell cycle process' and 'mitotic cell cycle'; while the downregulated DEGs were enriched in 'cellular component assembly involved in morphogenesis', 'cell projection organization' and 'microtubule‑based movement'. From the protein‑protein interaction network, DNA topoisomeraseIIα, kinesin family member11, cyclinB1 and BUB1 mitotic checkpoint serine/threonine were identified as foremost hub genes. One module was extracted and involved in 'mitotic cell cycle process' and 'cell cycle process'. Based on the analysis of DEMs and the miRNA‑target regulatory network, miRNA‑9 may be the most important upregulated DEM, and the DEGs forkhead boxP1 and cyclinE1 may serve vital roles in the differentiation of EC. In conclusion, principal genes were identified that may be determinants of the carcinogenesis of poorly differentiated EC, which may facilitate the examination of potential molecular mechanisms. These genes may additionally help identify candidate biomarkers and novel therapeutic targets for poorly differentiated EC.

Deregulation of the spindle assembly checkpoint is associated with paclitaxel resistance in ovarian cancer

BackgroundOvarian cancer is the leading gynecologic cancer diagnosed in North America and because related symptoms are not disease specific, this often leads to late detection, an advanced disease state, and the need for chemotherapy. Ovarian cancer is frequently sensitive to chemotherapy at diagnosis but rapid development of drug resistance leads to disease progression and ultimately death in the majority of patients.ResultsWe have generated paclitaxel resistant ovarian cell lines from their corresponding native cell lines to determine driver mechanisms of drug resistance using gene expression arrays. These paclitaxel resistant ovarian cells demonstrate: (1) Increased IC50 for paclitaxel and docetaxel (10 to 75-fold) and cross-resistance to anthracyclines (2) Reduced cell apoptosis in the presence of paclitaxel (3) Gene depletion involving mitotic regulators BUB1 mitotic checkpoint serine/threonine kinase, cyclin BI (CCNB1), centromere protein E (CENPE), and centromere protein F (CENPF), and (4) Functional data validating gene depletion among mitotic regulators.ConclusionsWe have generated model systems to explore drug resistance in ovarian cancer, which have revealed a key pathway related to the spindle assembly checkpoint underlying paclitaxel resistance in ovarian cell lines.

Identification of potential diagnostic and prognostic biomarkers in non-small cell lung cancer based on microarray data.

Non-small cell lung cancer (NSCLC) is the most commonly diagnosed subtype of lung cancer, and the leading cause of cancer-associated mortalities worldwide. However, NSCLC is typically diagnosed at a late stage of disease due to a lack of effective diagnostic methods. In the present study, the GSE19804 dataset was obtained from the Gene Expression Omnibus, and a number of differentially expressed genes were identified between NSCLC and adjacent normal tissues. Based on functional and pathway enrichment analyses, five hub genes (cell-division cycle 20, centromere protein F, kinesin family member 2C, BUB1 mitotic checkpoint serine/threonine kinase and ZW10 interacting kinetochore protein) were selected. After verifying that the mRNA level of these hub genes was also upregulated in NSCLC tissues by using the GSE10072 dataset and in cell lines by reverse transcription-quantitative polymerase chain reaction. The diagnostic and prognostic potentials of these five gene candidates were evaluated using receiver operating characteristic curves and survival analyses. Taken together, the present study identified five candidates that are overexpressed in NSCLC tissues and could also serve as potential diagnostic and prognostic biomarkers for patients with NSCLC.

Bioinformatics analysis of RNA sequencing data reveals multiple key genes in uterine corpus endometrial carcinoma.

In the present study, the RNA sequencing (RNA-seq) data of uterine corpus endometrial carcinoma (UCEC) samples were collected and analyzed using bioinformatics tools to identify potential genes associated with the development of UCEC. UCEC RNA-seq data were downloaded from The Cancer Genome Atlas database. Differential analysis was performed using edgeR software. A false discovery rate <0.01 and |log2(fold change)|>1 were set as the cut-off criteria to screen for differentially expressed genes (DEGs). Differential gene co-expression analysis was performed using R/EBcoexpress package in R. DEGs in the gene co-expression network were subjected to Gene Ontology analysis using the Database for Annotation, Visualization and Integration Discovery. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was also performed on the DEGs using KOBAS 2.0 software. The ConnectivityMap database was used to identify novel drug candidates. A total of 3,742 DEGs were identified among the 552 UCEC samples and 35 normal controls, and comprised 2,580 upregulated and 1,162 downregulated genes. A gene co-expression network consisting of 129 DEGs and 368 edges was constructed. Genes were associated with the cell cycle and the tumor protein p53 signaling pathway. Three modules were identified, in which genes were associated with the mitotic cell cycle, nuclear division and the M phase of the mitotic cell cycle. Multiple key hub genes were identified, including cell division cycle 20, cyclin B2, non-SMC condensin I complex subunit H, BUB1 mitotic checkpoint serine/threonine kinase, cell division cycle associated 8, maternal embryonic leucine zipper kinase, MYB proto-oncogene like 2, TPX2, microtubule nucleation factor and non-SMC condensin I complex subunit G. In addition, the small molecule drug esculetin was implicated in the suppression of UCEC progression. Overall, the present study identified multiple key genes in UCEC and clinically relevant small molecule agents, thereby improving our understanding of UCEC and expanding perspectives on targeted therapy for this type of cancer.

Investigation of crucial genes and microRNAs in conventional osteosarcoma using gene expression profiling analysis.

The present study aimed to screen potential genes associated with conventional osteosarcoma (OS) and obtain further information on the pathogenesis of this disease. The microarray dataset GSE14359 was downloaded from the Gene Expression Omnibus. A total of 10 conventional OS samples and two non‑neoplastic primary osteoblast samples in the dataset were selected to identify the differentially expressed genes (DEGs) using the Linear Models for Microarray Data package. The potential functions of the DEGs were predicted using Gene Ontology (GO) and pathway enrichment analyses. Protein‑protein interaction (PPI) data were also obtained using the Search Tool for the Retrieval of Interacting Genes database, and the PPI network was visualized using Cytoscape. Module analysis was then performed using the Molecular Complex Detection module. Additionally, the potential microRNAs (miRNAs) for the upregulated DEGs in the most significant pathway were predicted using the miRDB database, and the regulatory network for the miRNAs‑DEGs was visualized in Cytoscape. In total, 317 upregulated and 670downregulated DEGs were screened. Certain DEGs, including cyclin‑dependent kinase 1 (CDK1), mitotic arrest deficient 2 like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine‑protein kinase (BUB1), were significantly enriched in the cell cycle phase and oocyte meiosis pathway. DEGs, including replication factor C subunit 2 (RFC2), RFC3, RFC4 and RFC5, were significantly enriched in DNA replication and interacted with each other. RFC4 also interacted with other DEGs, including CDK1, MAD2L1, NDC80kinetochore complex and BUB1. In addition, RFC4, RFC3 and RFC5 were targeted by miRNA (miR)‑802, miR‑224‑3p and miR‑522‑3p. The DEGs encoding RFC may be important for the development of conventional OS, and their expression may be regulated by a number of miRNAs, including miR‑802, miR‑224‑3p and miR‑522‑3p.

Microarray expression analysis of MYCN-amplified neuroblastoma cells after inhibition of CDK2.

The study aimed to explore the underlying molecular mechanisms of CDK2 inhibition in neuroblastoma by bioinformatics analysis. Gene expression profile GSE16480 was downloaded from the Gene Expression Omnibus. The differentially expressed genes (DEGs) were identified from IMR32 between each time point and average expression of all time points. Gene significance was calculated using dSVDsig algorithm of dnet package. Protein-protein interaction (PPI) network was built. Then, integrated with gene significance, a core PPI network was detected by dNetPipeline algorithm in dnet package. Finally, pathway enrichment analysis was performed for genes in network. Totally, 1524 DEGs were identified. CCNA2 (cyclin A2), EXO1 (exonuclease 1), RAD51AP1 (RAD51 associated protein 1), TOP2A (topoisomerase (DNA) II alpha) and CDK1 (cyclin-dependent kinase 1) were selected as DEGs with higher connectivity after PPI network analysis. In the network, CCNA2, CDK1, BUB1B (BUB1 mitotic checkpoint serine/threonine kinase B) and CCNB1 (cyclin B1) were involved in cell cycle pathway. Additionally, CCNB1, CDK1, CCNE2 (Cyclin E2), and RRM2B (ribonucleotide reductase subunit M2B) were involved in p53 signaling pathway. Cell cycle and p53 signaling pathway were closely associated with neuroblastoma after CDK2 inhibition. The DEGs, such as CCNA2, CCNB1, CDK1 and RRM2B may be the potential targets for neuroblastoma.

Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis.

The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially-expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA-target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over-represented genes in the integrated miRNA-target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v-myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa-let-7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa-let-7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I α2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle-related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR-129, hsa-mir-145 and hsa-let-7c, respectively. However, further validation of these data is required.

In silico analysis of deleterious single nucleotide polymorphisms in human BUB1 mitotic checkpoint serine/threonine kinase B gene

One of the major challenges in the analysis of human genetic variation is to distinguish mutations that are functionally neutral from those that contribute to disease. BubR1 is a key protein mediating spindle-checkpoint activation that plays a role in the inhibition of the anaphase-promoting complex/cyclosome (APC/C), delaying the onset of anaphase and ensuring proper chromosome segregation. Owing to the importance of BUB1B gene in mitotic checkpoint a functional analysis using different in silico approaches was undertaken to explore the possible associations between genetic mutations and phenotypic variation. In this work we found that 3 nsSNPs I82N, P334L and R814H have a functional effect on protein function and stability. A literature search revealed that R814H was already implicated in human diseases. Additionally, 2 SNPs in the 5′ UTR region was predicted to exhibit a pattern change in the internal ribosome entry site (IRES), and eight MicroRNA binding sites were found to be highly affected due to 3′ UTR SNPs. These in silico predictions will provide useful information in selecting the target SNPs that are likely to have functional impact on the BUB1B gene.

Overexpression of BUB1B contributes to progression of prostate cancer and predicts poor outcome in patients with prostate cancer.

BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) is a member of the spindle assembly checkpoint protein family, which has been proven to be associated with many kinds of cancers. The aim of this study was to investigate whether BUB1B was correlated with progression and prognosis in patients with prostate cancer (PCa) and how BUB1B regulated the proliferation, migration, and invasion of PCa cell lines. Compared to benign prostate cells and tissues, both messenger RNA and protein expressions of BUB1B were statistically increased in PCa cell lines and tumor tissues. In vitro studies revealed that BUB1B overexpression enhanced the proliferation, migration, and invasion ability of PCa cell lines, whereas depletion of BUB1B did not affect the cell functions. Microarray analysis showed the positive staining of BUB1B was upregulated in the higher Gleason score group, which also correlated with advanced clinicopathological stage, higher serum prostate-specific antigen, metastasis, overall survival, and prostate-specific antigen failure. Furthermore, the survival analysis indicated that high expression of BUB1B was an independent predictor for shorter biochemical recurrence-free survival, which had no effect on overall survival. BUB1B plays an important role in tumor growth and progression, which can lead to its use as a potential biomarker for the diagnosis and prognosis of PCa.

Identification of genes and pathways associated with pancreatic ductal adenocarcinoma by bioinformatics analyses.

This study aimed to explore the underlying genes and pathways associated with pancreatic ductal adenocarcinoma (PDAC) by bioinformatics analyses. Gene expression profile GSE43795 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between six PDAC and five non-neoplastic pancreatic tissue samples were analyzed using the limma package. Gene ontology (GO) and pathway enrichment analyses of DEGs were performed, followed by functional annotation and protein-protein interaction (PPI) network construction. Finally, the sub-network was identified and pathway enrichment analysis was performed on the contained DEGs. A total of 374 downregulated and 559 upregulated DEGs were identified. The downregulated DEGs were enriched in GO terms associated with digestion and transport and pathways related to metabolism, while the upregulated DEGs were enriched in GO terms associated with the cell cycle and mitosis and pathways associated with the occurrence of cancer including the cell cycle pathway. Following functional annotation, the oncogene pituitary tumor-transforming 1 (PTTG1) was upregulated. In the PPI network and sub-network, cell division cycle 20 (CDC20) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were hub genes with high connectivity degrees. Additionally, DEGs in the sub-network including cyclin B1 (CCNB1) were mainly enriched in the cell cycle and p53 signaling pathways. In conclusion, the cell cycle and p53 signaling pathways may play significant roles in PDAC, and DEGs including CDC20, BUB1B, CCNB1 and PTTG1 may be potential targets for PDAC diagnosis and treatment.

Chelidonine induces mitotic slippage and apoptotic-like death in SGC-7901 human gastric carcinoma cells.

The aim of the present study was to investigate the effect of chelidonine on mitotic slippage and apoptotic-like death in SGC-7901 human gastric cancer cells. The MTT assay was performed to detect the antiproliferative effect of chelidonine. Following treatment with chelidonine (10 µmol/l), the ultrastructure changes in SGC-7901, MCF-7 and HepG2 cells were observed by transmission electron microscopy. The effects of chelidonine on G2/M phase arrest and apoptosis of SGC-7901 cells were determined by flow cytometry. Indirect immunofluorescence assay and laser scanning confocal microscopy (LSCM) were used to detect the phosphorylation level of histone H3 (Ser10) and microtubule formation was detected using LSCM following immunofluorescent labeling. Subsequent to treatment with chelidonine (10 µmol/l), expression levels of mitotic slippage-associated proteins, including BUB1 mitotic checkpoint serine/threonine kinase B (BubR1), cyclin-dependent kinase 1 (Cdk1) and cyclin B1, and apoptosis-associated protein, caspase-3 were examined by western blotting at 24, 48 and 72 h. The half maximal inhibitory concentration of chelidonine was 23.13 µmol/l over 48 h and chelidonine induced G2/M phase arrest of cells. The phosphorylation of histone H3 at Ser10 was significantly increased following treatment with chelidonine for 24 h, indicating that chelidonine arrested the SGC-7901 cells in the M phase. Chelidonine inhibited microtubule polymerization, destroyed microtubule structures and induced cell cycle arrest in the M phase. Giant cells were observed with multiple micronuclei of varying sizes, which indicated that following a prolonged arrest in the M phase, the cells underwent mitotic catastrophe. Western blotting demonstrated that the protein expression levels of BubR1, cyclin B1 and Cdk1 decreased significantly between 48 and 72 h. Low expression levels of BubR1 and inactivation of the cyclin B1-Cdk1 complex results in the cells being arrested at mitosis and leads to mitotic slippage. In addition, apoptotic morphological changes in multinucleated cells were observed, the apoptosis rates increased gradually with administration of chelidonine in a time-dependent manner and the protein levels of caspase-3 increased significantly between 24 and 72 h. Thus, chelidonine induces mitotic slippage, and apoptotic-like death occurs in SGC-7901 cells undergoing mitotic catastrophe. Gastric cancer is a common malignancy, and ranks second in overall cancer-associated mortalities worldwide. The present study demonstrated that chelidonine induces M phase arrest and mitotic slippage of SGC-7901 human gastric carcinoma cells via downregulating the expression of BubR1, Cdk1 and cyclin B1 proteins. With the prolongation of chelidonine treatment, the giant cells with multiple micronuclei underwent mitotic slippage and were maintained in the G1 phase and did not survive. A number of multinucleated cells underwent apoptosis via a caspase-dependent signaling pathway. The current study proposes that chelidonine induces mitotic slippage and apoptotic-like death of SGC-7901 cells.

Combined Immunohistochemistry of PLK1, p21, and p53 for Predicting TP53 Status: An Independent Prognostic Factor of Breast Cancer.

It is difficult to predict the TP53 status by p53 immunohistochemistry (IHC). We aimed to improve the accuracy of p53 IHC with p53-regulated proteins for predicting the TP53 mutation status. TP53 mutations were detected in 19 of 38 breast cancer patients (50%). Five of 7 cases of protein-truncating mutation of TP53 were completely negative for p53 IHC, whereas 11 of 12 cases of TP53 point mutation were strongly positive for p53 IHC. Therefore, to avoid false negatives, we extracted p53-dependent universally downregulated genes using microarray analysis from 38 breast cancer patients and 2 p53-inducible cell lines. From 9 commonly repressed genes, we evaluated 3 genes, baculoviral IAP repeat-containing 5 (BIRC5), polo-like kinase 1 (PLK1), and BUB1 mitotic checkpoint serine/threonine kinase (BUB1), which were previously identified as p53-dependent repressed genes. PLK1≥Allred total score (TS) 5 showed the highest correlation with TP53 mutation. To decrease false positivity, we evaluated p21 IHC. Although strong staining of p21 was observed in 4 cases (10.5%), all 4 were wild-type TP53. Thus, p53 mutation-like (p53mt-like) IHC was identified by p53 TS7,8 with PLK1≥TS 5 and p21 TS≤6. p53 mt-like IHC correlated with TP53 mutation (predictive value=0.94). In other 157 breast cancer cases, p53 mt-like was an independent prognostic marker in multivariate analysis and a strong prognostic factor. Stratification with p53 mt-like IHC identified patients with a poorer prognosis. In conclusion, we identified reliable IHC conditions to predict the TP53 status of breast cancer patients.

Identification of potential therapeutic targets for melanoma using gene expression analysis.

Metastatic melanoma represents asignificant cause of death in patients with melanoma and the frequency is increasing. The aim of this study was to identify potential therapeutic targets for metastatic melanoma. Gene expression profile GSE44660 was downloaded from Gene Expression Omnibus database. Atotal of 22 samples were analyzed in our study, including 3 specimens of normal melanocytes, 12 specimens of melanoma LNM (lymph node metastasis) and 7 specimens of MBM (melanoma brain metastasis). DEGs (differentially expressed genes) in LNM and MBM were identified respectively using Limma package. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways analyses of common DEGs between two comparison groups were performed using DAVID, followed by cancer-related genes and transcription factor analysis. PPI (protein-protein interaction) network was constructed by STRING, and significant key genes were selected. Totally, 401 common DEGs were identified. Disease analysis showed that ICAM1 (intercellular adhesion molecule 1) and NBN (nibrin) were related to melanoma. In the PPI network, BIRC5 (baculoviral IAP repeat containing 5), BUB1 (BUB1mitotic checkpoint serine/threonine kinase), GMNN (geminin, DNA replication inhibitor), AURKA (aurora kinase A), TOP2A (topoisomerase (DNA) II alpha) and BUB1B (BUB1mitotic checkpoint serine/threonine kinase B) were with higher degree more than 50. ICAM1, NBN, BIRC5, BUB1, BUB1B, GMNN, AURKA and TOP2A may play key roles in the progression and development of melanoma. They may be used as specific therapeutic targets in the treatment of metastatic melanoma. However, further experiments are still needed to confirm our results.

Spindle checkpoint protein Bub1 corrects mitotic aberrancy induced by human T-cell leukemia virus type I Tax

Bub1 is a component of the mitotic spindle checkpoint apparatus. Abnormality of this apparatus is known to cause multinuclei formation, a hallmark of chromosomal instability (CIN). A549, aneuploid cell line, aberrantly passed through the mitotic phase and became multinuclei morphology in the presence of nocodazole. Time-lapse videomicroscopy showed unreported bizarre morphology, which we named 'mitotic lobulation' in A549 cells just before the exit from mitosis and multinuclei formation. External expression of wild-type Bub1-EGFP clearly suppressed the multinuclei formation by retaining A549 cells at the mitotic phase during 48 h of time-lapse observation. This suppressive effect on mitotic aberrancy should not be mere restoration of normal Bub1 function, because A549 cells express proper amount of Bub1, which distributed cytoplasm during interphase and concentrated at kinetochore in metaphase. Furthermore, external expression of wild-type Bub1-EGFP suppressed multinuclei formation induced by Tax both in A549 and HeLa cells. Tax is known to induce mitotic abnormality by binding and inactivating Mad1. These observations, therefore, suggest functional redundancy between Bub1 and other mitotic checkpoint protein(s) and a possibility of correction of mitotic aberrancy by external Bub1 expression.

Erratum: A double missense variation of theBUB1 gene and a defective mitotic spindle checkpoint in the pancreatic cancer cell line Hs766T

Certain samples of the cell line Hs766T within our laboratory were contaminated by the cell line RKO in the past. This affected two published papers (Hempen et al., 2002; Sohn et al., 2002, 2003). We recently identified that the reported BUB1 alteration is present in RKO cells and is not present in Hs766T cells. RKO cells are known to have an intact mitotic checkpoint (Cahill et al., 1998). Using current cell lines having identities confirmed by the sequencing of their other known mutant genes, we confirm the finding of a mitotic checkpoint defect among pancreatic cancers having CIN (chromosomal instability): the maximal mitotic index under colcemid (0.1 ug/ml) treatment is 85% for RKO cells (colorectal cancer, MSI, microsatellite instability), 9.4% for Hs766T cells (pancreatic, CIN), 23% for Su86.86 cells (pancreatic, CIN), and 44% for BxPC3 cells (pancreatic, CIN). The reported double missense mutation of the mitotic checkpoint BUB1 gene is thus associated not with a defective mitotic checkpoint in a CIN line as we had reported, but interestingly occurs in an MSI line having an intact checkpoint. The prevalence rate of BUB1 and other mitotic checkpoint gene mutations in MSI cell lines has not yet been reported. Presumably, BUB1 missense mutations do not always create a significant functional defect. © 2005 Wiley-Liss, Inc.

Differential expression of the MAD2, BUB1 and HSP27 genes in Barrett’s oesophagus—their association with aneuploidy and neoplastic progression

Chromosomal instability (CIN) leading to aneuploidy is a ubiquitous and early event in the progression of Barrett’s oesophagus, but its origins are unknown. Hence, the transcriptional levels of components of the mitotic spindle checkpoint (important in ensuring precise chromosome segregation) were examined in Barrett’s lesions and correlated with the degree of aneuploidy present in the tissues. Gene expression levels of the MAD2 and BUB1 mitotic spindle checkpoint genes were assessed in 37 Barrett’s patients (with histology ranging from metaplasia to adenocarcinoma) by real-time RT-PCR. In addition, the transcriptional levels of HSP27 were also examined as firstly, its expression is known to be down regulated in Barrett’s metaplasia (BM) and thus was included as a positive control for the real-time RT-PCR assay. While, secondly, the expression pattern of this gene during Barrett’s neoplastic progression was investigated, as this has not been previously assessed. Both over and under expression of the MAD2 and BUB1 mitotic spindle checkpoint genes were detected at all Barrett’s histological stages with no apparent selective trend with neoplastic progression. In addition, no correlation with aneuploidy was established, indicating an alternative mechanism must underlie Barrett’s associated chromosomal instability. HSP27 expression was reduced in metaplasia and then significantly increased with progression. Gender-related differences were observed and HSP27 expression was higher in poorly-differentiated adenocarcinomas than in well-differentiated forms. HSP27 transcriptional patterns therefore present potential as a prognostic tool to predict the aggressiveness of oesophageal adenocarcinomas (OA).

Expression of BUB1 protein in gastric cancer correlates with the histological subtype, but not with DNA ploidy or microsatellite instability.

During mitosis, the spindle checkpoint delays the onset of anaphase until all chromosomes have attached properly to the mitotic spindle, preventing chromosome missegregation. BUB (budding uninhibited by benzimidazole) 1 is one of the key components of this checkpoint. BUB1 mutations are rare in cancer tissues and no mutations have been identified in gastric cancer. In mice, immunodepletion of BUB1 abolished the spindle checkpoint. Thus, aberrant expression of BUB1 protein could impair mitotic checkpoint function, resulting in aneuploidy, a common phenomenon in gastric cancer. In the present study, an antibody was generated against BUB1 and its expression was studied in gastric cancer tissue sections (n = 80) by immunohistochemistry. Nuclear BUB1 expression was found in all gastric cancer cases. The proportion of tumour cells expressing BUB1 was significantly greater in diffuse-type than in intestinal-type gastric carcinoma (p < 0.001). No correlation was found between BUB1 expression and deoxyribonucleic acid (DNA) ploidy, microsatellite instability or any other histopathological parameters investigated. To the authors' knowledge, this is the first study of BUB1 protein expression in gastric cancer tissues. Different BUB1 protein expression levels in intestinal- and diffuse-type gastric cancer may provide further evidence of a potential link between different genetic pathways and morphological phenotype in gastric carcinogenesis. However, further studies are needed to establish whether there is an association between BUB1 protein expression level and mitotic spindle checkpoint function in gastric cancer.