Bub1 is required for maintaining cancer stem cells in breast cancer cell lines

Genome-wide CRISPR screen identifies BUB1 kinase as a druggable vulnerability in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a rare yet highly aggressive malignancy with a severe prognosis. Compounded by the lack of effective treatment modalities, MPM remains a formidable health challenge. Therefore, the identification of actionable liabilities is critical for advancing precision medicine to combat this lethal disease. Here, we exploit an unbiased genome-wide CRISPR screen, integrating and cross-comparing three MPM cell lines with nonmalignant mesothelial cells, to selectively map the gene targets whose depletion indicates a common dependency in MPM cells. This systematic approach unveils a cohort of verifiable genes, among which BUB1, a mitotic checkpoint serine/threonine kinase, emerges as a high-confidence hit in cancer cells. Cellular and molecular studies demonstrate that genetic depletion or pharmacological inhibition of BUB1 profoundly impairs MPM cell survival and growth while inducing G2/M cell cycle arrest, cellular senescence, and apoptosis, and attenuating functional hallmarks of aggressive cancer cells. Transcriptomic profiling of BUB1-depleted cells discloses differential gene expression signatures congruent with cell fate phenotypes, including the reprogramming of mitotic network genes. Mechanistically, BUB1 is indispensable for the proper localization of essential mitotic regulators MAD1, MAD2, and Shugoshin (SGO1), thereby ensuring the functionality of the spindle assembly checkpoint (SAC). Furthermore, BUB1 ablation leads to cytokinesis failure and multinucleation, a phenotype characterized by the downregulation of CDC20, Cyclin A, and Cyclin B, and a reciprocal upregulation of the cyclin-dependent kinase inhibitor p21. Clinically, MPM tumors exhibit elevated levels of BUB1, and high BUB1 expression is associated with shorter patient survival. Our novel findings accentuate comparative CRISPR screens as a powerful platform to explore tumor cell-selective gene essentiality and propose BUB1 kinase as a potential marker and druggable vulnerability with therapeutic implications for MPM.

MELK as a Mediator of Stemness and Metastasis in Aggressive Subtypes of Breast Cancer

Triple-negative breast cancer (TNBC) is the breast cancer subtype with the poorest prognosis and lacks actionable molecular targets for treatment. Maternal embryonic leucine zipper kinase (MELK) is highly expressed in TNBC and has been implicated in poor clinical outcomes, though its mechanistic role in the aggressive biology of TNBC is poorly understood. Here, we demonstrate a role of MELK in TNBC progression and metastasis. Analysis of publicly available datasets revealed that high MELK expression correlates with worse overall survival, recurrence-free survival, and distant metastasis-free survival, and MELK is co-expressed with metastasis-related genes. Functional studies demonstrated that MELK inhibition, using genomic or pharmacologic inhibition, reduces mammosphere formation, migration, and invasion in high-MELK-expressing TNBC cell lines. Conversely, MELK overexpression in low-MELK-expressing cell lines significantly increased invasive capacity in vitro and metastatic potential in vivo, as evidenced by enhanced metastasis to the liver and lungs in a chorioallantoic membrane assay. These findings highlight MELK as a key regulator of TNBC aggressiveness and support its potential as a therapeutic target to mitigate metastasis and improve patient outcomes.

BUB1, miR-495-3p, and E2F1/E2F8 axis is associated with poor prognosis of breast cancer patients and infiltration of Th2 cells in the tumor microenvironment

Breast cancer, the most common cancer in women, is characterized by cell cycle dysregulation and chromosome segregation errors, leading to mitotic catastrophe and genomic instability. Understanding these molecular mechanisms is crucial for better diagnosis and treatment. We used databases like TIMER 2.0, UALCAN, and Oncomine to determine the differential expression of Budding uninhibited by benzimidazole 1 (BUB1) in normal and pan-cancer tissues. we also used the Kaplan-Meier Plotter database to analyze gene expression associations with survival outcomes, bc-GenExMiner v5.0 to analyze BUB1 gene expression and histological subtypes, and ctcRbase and miR-TV to identify microRNAs associated with BUB1 expression in breast cancer. Our data show that BUB1 expression is overexpressed in breast cancer tumors, metastatic tissues, and circulating tumor cells, leading to shorter overall survival, disease-free survival, and relapse-free survival compared to low-expression patients. BUB1 expression is strongly correlated with E2F1/E2F8 expression, suggesting a potential regulatory relationship between these genes. The study revealed a negative correlation between target miRNA miR-495-3p and BUB1 expression in breast cancer tumors, indicating a potential regulatory relationship between these genes. The BUB1 expression was also strongly correlated with the infiltration of CD4+ T helper 2 (Th2) subtypes in the tumors, suggesting a need for further research.

Identification of Novel lncRNAs Related to Colorectal Cancer Through Bioinformatics Analysis

Long noncoding RNA (lncRNA) plays a critical role in cancer cell proliferation, invasion, metastasis, and chemoresistance. The current study introduces novel lncRNAs in colorectal cancer (CRC) through bioinformatics analysis. GSE134834 CRC-related microarray of Gene Expression Omnibus (GEO) was analyzed to identify differentially expressed genes (DEGs) in CRC samples against normal samples. Analysis revealed 6763 DEGs (p < 0.05 and |log fold change (FC)| ≥ 0.5) that include differentially expressed mRNA (DEmRNA) and differentially expressed long noncoding RNA (DElncRNA). Novel lncRNAs were identified, and to better understand the biological function of the identified lncRNAs, gene modules were constructed using weighted gene coexpression network analysis (WGCNA), and finally, two modules for lncRNAs were obtained. The coexpression modules with these lncRNAs were subjected to enrichment analysis in FunRich software to predict their functions through their coexpressed genes. Gene ontology results of modules related to novel lncRNA revealed they significantly enriched the cellular pathways regulation in cancer. The protein-protein interaction (PPI) network of novel lncRNAs-related modules was constructed using Search Tool for the Retrieval of Interacting Genes (STRING) and visualized using the Cytoscape software. Hub genes were screened from the PPI network by the CytoHubba plug-in of Cytoscape. The hub genes were MRTO4, CDK1, CDC20, RPF2, NOP58, NIFK, GTPBP4, BUB1, BUB1B, and BOP1 for the lightpink4 module and BYSL, RPS23 (ribosomal protein S23), RSL1D1 (ribosomal L1 domain containing 1), NAT10, NOP14, GNL2, MRPS12, NOL6 (nucleolar protein 6), IMP4, and RRP12 (ribosomal RNA processing 12 homolog) for the pink module. The expression levels of the top DEmRNA and module hub genes in CRC were validated using the Gene Expression Profiling Interactive Analysis (GEPIA) database. Generally, our findings offer crucial insight into the hub genes and novel lncRNAs in the development of CRC by bioinformatics analysis, information that may prove useful in the identification of new biomarkers and treatment targets in CRC; however, more experimental investigation is required to validate the findings of the present study.

DAB2IP loss in luminal a breast cancer leads to NF-κB-associated aggressive oncogenic phenotypes

Despite proven therapy options for estrogen receptor-positive (ER+) breast tumors, a substantial number of patients with ER+ breast cancer exhibit relapse with associated metastasis. Loss of expression of RasGAPs leads to poor outcomes in several cancers, including breast cancer. Mining the The Cancer Genome Atlas (TCGA) breast cancer RNA-Seq dataset revealed that low expression of the RasGAP DAB2IP was associated with a significant decrease in relapse-free survival in patients with Luminal A breast cancer. Immunostaining demonstrated that DAB2IP loss occurred in grade 2 tumors and higher. Consistent with this, genes upregulated in DAB2IP-low Luminal A tumors were shared with more aggressive tumor subtypes and were associated with proliferation, metastasis, and altered ER signaling. Low DAB2IP expression in ER+ breast cancer cells was associated with increased proliferation, enhanced stemness phenotypes, and activation of IKK, the upstream regulator of the transcription factor NF-κB. Integrating cell-based ChIP-Seq with motif analysis and TCGA RNA-Seq data, we identified a set of candidate NF-κB target genes upregulated with loss of DAB2IP linked with several oncogenic phenotypes, including altered RNA processing. This study provides insight into mechanisms associated with aggressiveness and recurrence within a subset of the typically less aggressive Luminal A breast cancer intrinsic subtype.

DTL promotes the growth and migration of melanoma cells through the ERK/E2F1/BUB1 axis

Melanoma is the most dangerous form of skin cancer. Hence, a better understanding of molecular mechanisms in melanoma pathogenesis is urgently needed, which provides a new insight into the therapy of melanoma. DTL gene is screened out in melanoma pathogenesis by integrated bioinformatics analysis, and its expression is validated in the tissue and cell samples of melanoma. Forced DTL expression facilitates the proliferation, invasion, migration and EMT of melanoma cells, while DTL knockdown suppresses the biological behavior of melanoma cells. In addition, DTL promotes the malignancy of melanoma in vivo. Mechanistically, BUB1 is the crucial downstream target of DTL. Reduced DTL expression suppresses BUB1 expression, while enhanced DTL expression induces BUB1 upregulation. Rescue experiments showed that growing and migrating of melanoma cells induced by DTL are partially impaired by BUB1 inhibition. In addition, the expression of phosphorylated ERK (p-ERK) and the downstream transcription factor E2F1 are reduced when DTL expression is blocked. Meanwhile, BUB1 levels are decreased when the expression of p-ERK or E2F1 is repressed. Notably, the growth and migration of melanoma cells by inhibition of ERK and knockdown of E2F1 was rescued by overexpressing BUB1. DTL gene may be a prognosis marker and represent a unique potential target for melanoma patients. DTL supports the biologically malignant activity of melanoma cells via the ERK/E2F1/BUB1 axis.

BUB1 as a novel marker for predicting the immunotherapy efficacy and prognosis of breast cancer

Background

Budding uninhibited by benzimidazole 1 (BUB1) is a highly conserved serine/threonine kinase, showing prominent importance for proper function during mitosis. However, little is known about BUB1 mRNA expression in breast cancer (BRCA) and its correlation with prognosis and immune infiltration. Hence, we aimed to unveil its potential as groundbreaking biomarkers for immunotherapy efficacy and the prognosis of BRCA.

Methods

Database for Annotation, Visualization, and Integrated Discovery (DAVID) is a potent tool for identifying significant clusters of genes and pathways in the resulting dataset. In this study, gene set enrichment analysis of BUB1 was conducted using DAVID. The clinical characteristics of patients with or without altered BUB1 mRNA expression were compared using cBioPortal. Tumor Immune Estimation Resource (TIMER) is a known as database for comprehensive analysis of tumor-infiltrating immune cells in various cancers. In the present study, the relationship between BUB1 expression and the abundance of immune infiltrates was explored using TIMER in BRCA. Immunohistochemistry staining was performed to analyze the protein expression of BUB1 in tumor tissue specimens. We used PrognoScan and Kaplan-Meier Plotter to evaluate the prognosis of patients with different BUB1 expression levels.

Results

The expression of BUB1 in various tumor tissues was higher than that in adjacent normal tissues. BUB1 was mainly localized to the nucleoplasm and additionally localized to the cytosol. Functional enrichment analyses revealed that the cell cycle was the most significant pathway. Abnormal BUB1 mRNA expression was more frequently detected in invasive ductal carcinoma with higher histological grades and BRCAs with estrogen receptor (ER)-negative, human epidermal growth receptor 2 (HER2)-negative, and basal-like phenotypes. The BUB1 expression was correlated positively with tumor purity, B cells, CD8+ T cells, CD4+ T cells, neutrophils, and dendritic cells, while BUB1 had no significant correlation with macrophages. The results of immunohistochemical staining from clinical samples further confirmed that BUB1 was overexpressed in BRCA compared to benign tumor (fibroadenoma of breast) (P<0.01). BRCA patients with lower BUB1 expression had a better prognosis than those with higher BUB1 expression in overall survival (OS) curves, distant metastasis-free survival (DMFS) curves, and relapse-free survival (RFS) curves (P<0.05).

Conclusions

Our results suggest that BUB1 is a potential molecular biomarker for evaluating the prognosis and predicting the effectiveness of immunotherapy for BRCA.

BUB1 potentiates gastric cancer proliferation and metastasis by activating TRAF6/NF-κB/FGF18 through m6A modification

AIMS

Gastric cancer (GC) is one of the most common malignant tumors of the digestive system. High expression of the mitotic kinase BUB1 has been shown to be associated with the development of many cancers, but the role of BUB1 in GC is still unclear. The current study aimed to investigate the role of BUB1 in GC.

MATERIALS AND METHODS

BUB1 inhibitor, siRNA or BUB1 overexpression plasmid-mediated functional studies were performed in vitro and in vivo to explore the oncogenic role of BUB1 in GC. The expression of BUB1 and FGF18 in GC tumor samples was determined by IHC staining. RNA-seq, Western blot, MeRIP-qPCR and Co-IP assays were used to investigate the molecular mechanisms by which BUB1 regulates GC progression.

KEY FINDINGS

Knockdown of BUB1 significantly inhibited the proliferation and metastasis of GC cells in vitro and in vivo. Moreover, overexpression of BUB1 significantly promoted the proliferation, migration and invasion of GC cells. High expression of BUB1 and FGF18 in GC tissues predicted poor prognosis in GC patients. Mechanistically, BUB1 interacted with METTL3 and induced m6A modification of TRAF6 mRNA, further activating the NF-κB/FGF18 axis in GC cells.

SIGNIFICANCE

Our results confirmed that BUB1 acts as a positive regulator of GC cell proliferation and metastasis by activating the TRAF6/NF-κB/FGF18 pathway through METTL3-mediated m6A methylation. Targeting the BUB1/METTL3/TRAF6/NF-κB/FGF18 axis might be a novel diagnostic and therapeutic strategy in GC.

BUB1 induces AKT/mTOR pathway activity to promote EMT induction in human small cell lung cancer

Small cell lung cancer (SCLC) is a very aggressive tumor. Abnormal expression of BUB1 has been reported in several cancer types, wherein it plays a range of functional roles. This work aimed to elucidate the functional significance and molecular impacts of BUB1 in SCLC. It was found that SCLC cell lines exhibited significant BUB1 upregulation relative to control bronchial cells using data from the Gene Expression Omnibus (GEO) database and verified by immunohistochemical staining. BUB1 was also found to promote the proliferative, migratory, invasive activity of SCLC cells, as shown by CCK-8, 3D migration wound-healing, and Transwell assays, as well as flow cytometry. Additionally, it was found that BUB1 silencing enhanced E-cadherin expression while suppressing N-cadherin, Vimentin, ZEB-1, and Snail levels, as shown by Western immunoblotting. The loss of BUB1 also reduced p-AKT and p-mTOR levels without altering total AKT or mTOR protein levels. In conclusion, BUB1 functions as an oncogenic promoter in SCLC, potentially regulating the epithelial-mesenchymal transition by activation of AKT/mTOR signaling.

Prognostic and Therapeutic Implications of Cell Division Cycle 20 Homolog in Breast Cancer

Cell division cycle 20 homolog (CDC20) is a well-known regulator of cell cycle progression. Abnormal expression of CDC20 leads to mitotic defects, which play a significant role in cancer development. In breast cancer (BC), CDC20 has been identified as a biomarker that has been linked to poor patient outcomes. In this study, we investigated the association of CDC20 with BC prognosis and immune cell infiltration by using multiple online databases, including UALCAN, KM plotter, TIMER2.0, HPA, TNM-plot, bc-GenExMiner, LinkedOmics, STRING, and GEPIA. The results demonstrate that BC patients have an elevated CDC20 expression in tumor tissues compared with the adjacent normal tissue. In addition, BC patients with overexpressed CDC20 had a median survival of 63.6 months compared to 169.2 months in patients with low CDC20 expression. Prognostic analysis of the examined data indicated that elevated expression of CDC20 was associated with poor prognosis and a reduction of overall survival in BC patients. These findings were even more prevalent in chemoresistance triple-negative breast cancer (TNBC) patients. Furthermore, the Gene Set Enrichment Analysis tool indicated that CDC20 regulates BC cells' cell cycle and apoptosis. CDC20 also significantly correlates with increased infiltrating B cells, CD4+ T cells, neutrophils, and dendritic cells in BC. In conclusion, the findings of this study suggest that CDC20 may be involved in immunomodulating the tumor microenvironment and provide evidence that CDC20 inhibition may serve as a potential therapeutic approach for the treatment of BC patients. In addition, the data indicates that CDC20 can be a reliable prognostic biomarker for BC.

Baitouweng decoction suppresses growth of esophageal carcinoma cells through miR-495-3p/BUB1/STAT3 axis

BACKGROUND

Esophageal carcinoma (EC) is one of the most prevalent cancers in human populations worldwide. Baitouweng decoction is one of the most important Chinese medicine formulas, with the potential to treat cancer.

AIM

To investigate the role and mechanism of Baitouweng decoction on EC cells.

METHODS

Differentially expressed genes (DEGs) in EC tissues and normal tissues were screened by the cDNA microarray technique and by bioinformatics methods. The target genes of microRNAs were predicted based on the TargetScan database and verified by dual luciferase gene reporter assay. We used Baitouweng decoction to intervene EC cells, and detected the activity of EC9706 and KYSE150 cells by the MTT method. Cell cycle and apoptosis were measured by flow cytometry. The expression of BUB1 mRNA and miR-495-3p was measured by qRT-PCR. The protein levels of BUB1, STAT3, p-STAT3, CCNB1, CDK1, Bax, Caspase3, and Caspase9 were measured by Western blot analysis. The migration and invasion abilities of the cells were measured by wound-healing assay and Transwell invasion assay, respectively.

RESULTS

DEGs identified are involved in biological processes, signaling pathways, and network construction, which are mainly related to mitosis. BUB1 was the key hub gene, and it is also a target gene of miR-495-3p. Baitouweng decoction could upregulate miR-495-3p and inhibit BUB1 expression. In vitro experiments showed that Baitouweng decoction significantly inhibited the migration and invasion of EC cells and induced apoptosis and G2/M phase arrest. After treatment with Baitouweng decoction, the expression of Bax, Caspase 3, and Caspase 9 in EC cells increased significantly, while the expression of BUB1, CCNB1, and CDK1 decreased significantly. Moreover, the STAT3 signaling pathway may play an important role in this process.

CONCLUSION

Baitouweng decoction has a significant inhibitory effect on EC cell growth. BUB1 is a potential therapeutic target for EC. Further analysis showed that Baitouweng decoction may inhibit the growth of EC cells by upregulating miR-495-3p targeting the BUB1-mediated STAT3 signal pathway.

Protooncogenic Role of ARHGAP11A and ARHGAP11B in Invasive Ductal Carcinoma: Two Promising Breast Cancer Biomarkers

Invasive duct carcinoma (IDC) is one of the most common types of breast cancer (BC) in women worldwide, with a high risk of malignancy, metastasis, recurrence, and death. So far, molecular patterns among IDC cases have not been fully defined. However, extensive evidence has shown that dysregulated Rho family small GTPases (Rho GTPases) including Rho GTPase activating proteins (RhoGAPs) have important roles in the invasive features of IDCs. In the current study, we analyzed the expression levels of two RhoGAP genes, ARHGAP11A and ARHGAP11B, in The Cancer Genome Atlas (TCGA) breast cancer (BRCA) and also our 51 IDC tumors compared to their matched normal tissues using quantitative polymerase chain reaction (qPCR). Our TCGA data analysis revealed higher expression of ARHGAP11A and ARHGAP11B in various cancers comprising BCs. Also, we found correlations between these genes and other genes in TCGA-BRCA. Moreover, our methylation analysis showed that their promotor methylation had a negative correlation with their overexpression. QPCR revealed their significant upregulation in our tumor samples. Furthermore, we found that the expression level of ARHGAP11A was considerably lower in women who were breastfeeding. Moreover, it had overexpression in cases who had regular menstrual cycles and early age (younger than 14) at menarche. However, ARHGAP11B had a higher expression in HER2-positive tumors versus HER2-positive and ER-positive tumors. Our study found possible protooncogenic roles for these genes and their involvement in IDC pathogenesis and malignancy. Therefore, they can be considered novel prognostic and diagnostic biomarkers for IDC.

Budding uninhibited by benzimidazoles 1 might be a poor prognosis biomarker promoting the progression of papillary thyroid cancer

BACKGROUND

Papillary thyroid carcinoma (PTC) is one of the most widespread malignant tumors of the endocrine system, with a high incidence. Budding uninhibited by benzimidazoles 1 (BUB1), one of the spindle assembly checkpoint (SAC) genes, is a multitask protein kinase required for eukaryotic chromosome segregation. Although BUB1 has been explored in several types of cancer, its biological role and molecular mechanisms in PTC remain unclear.

METHODS

In this study, we performed an examination of four public datasets along with local PTC cohorts and discovered that BUB1 was elevated in PTC compared to non-cancer tissues. High BUB1 expression was linked with the status of BRAFV600E , RAS, and TERT after statistical analysis.

RESULTS

Clinically, BUB1 is associated with a variety of clinicopathological features in PTC patients. Interestingly, analysis of the TCGA database showed that BUB1 was closely associated with poor prognosis of PTC and significantly correlated with PFS. As determined by regression analysis, BUB1, and T stage were independent predictors of PTC and were related to BRAFV600E and lymph node metastatic status. By RT-qPCR, BUB1 was considerably overexpressed in PTC cell lines in comparison with normal thyroid epithelial cells.

CONCLUSION

We confirmed that the knockdown of BUB1 in BCPAP and TPC1 cell lines significantly inhibited cell proliferation, cloning, and migration in vitro experiments. These results imply that BUB1 may be a significant oncogenic gene that is directly associated with the prognosis of PTC and may represent a future target for therapeutic intervention.

Budding uninhibited by benzimidazoles 1 promotes cell proliferation, invasion, and epithelial-mesenchymal transition via the Wnt/β-catenin signaling in glioblastoma

The pathogenesis and progression of GBM (glioblastoma), as one of the most frequently occurring malignancies of the central nervous system, are regulated by several genes. BUB1 (budding uninhibited by benzimidazoles 1) is a mitotic checkpoint that plays an important role in chromosome segregation as well as in various tumors. However, its role in glioma is unknown. The current study discovered prominently elevated BUB1 in glioma and a significant relationship between BUB1 expression, a high World Health Organization grade, and a poor prognosis in glioma patients. Moreover, BUB1 triggered EMT (epithelial-mesenchymal transition) apart from promoting glioma cell proliferation, migration, and infiltration. Besides, BUB1 promoted EMT by activating the Wnt/β-catenin axis. As implied by our study, BUB1 probably has the potential as a target for GBM management.

Identifying gene expression-based biomarkers in online learning environments

Motivation

Gene expression-based classifiers are often developed using historical data by training a model on a small set of patients and a large set of features. Models trained in such a way can be afterwards applied for predicting the output for new unseen patient data. However, very often the accuracy of these models starts to decrease as soon as new data is fed into the trained model. This problem, known as concept drift, complicates the task of learning efficient biomarkers from data and requires special approaches, different from commonly used data mining techniques.

Results

Here, we propose an online ensemble learning method to continually validate and adjust gene expression-based biomarker panels over increasing volume of data. We also propose a computational solution to the problem of feature drift where gene expression signatures used to train the classifier become less relevant over time. A benchmark study was conducted to classify the breast tumors into known subtypes by using a large-scale transcriptomic dataset (∼3500 patients), which was obtained by combining two datasets: SCAN-B and TCGA-BRCA. Remarkably, the proposed strategy improves the classification performances of gold-standard biomarker panels (e.g. PAM50, OncotypeDX and Endopredict) by adding features that are clinically relevant. Moreover, test results show that newly discovered biomarker models can retain a high classification accuracy rate when changing the source generating the gene expression profiles.

Availability and implementation

github.com/UEFBiomedicalInformaticsLab/OnlineLearningBD.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Identification of Prognostic Markers and Potential Therapeutic Targets in Gastric Adenocarcinoma by Machine Learning Based on mRNAsi Index

Background

Cancer stem cells (CSCs), characterized by self-renewal and therapeutic resistance, play important roles in stomach adenocarcinoma (STAD). However, the molecular mechanism of STAD stem cells is still unclear. In this study, our purpose is to explore the expression of stem cell-related genes in STAD.

Methods

The stemness index based on mRNA expression (mRNAsi) was used to analyze STAD cases in The Cancer Genome Atlas (TCGA). Firstly, mRNAsi was used and analyzed by differential expression, survival analysis, clinical stage, and gender in STAD. Then, weighted gene coexpression network analysis (WGCNA) was used to discover the fascinating modules and key genes. Enrichment analysis was carried out to annotate the functions and pathways of key genes. The gene expression comprehensive database (GEO) in STAD was used to verify the expression levels of key genes in all cancers. Protein-protein interaction networks is used to determine the relationships between key genes.

Results

The mRNAsi was obviously upregulated in tumor cases. With the increase of tumor stage and T stage, the mRNAsi score decreased, and the overall survival rate of high score group patients was better. According to the degree of association with mRNAsi, different modules and key genes were screened out. A total of 6,740 differential genes were found, of which 1,147 genes were downregulated and 5,593 genes were upregulated. 19 key genes (BUB1, BUB1B, KIF14, NCAPH, RACGAP, KIF15, CENPF, TPX2, RAD54L, KIF18B, KIF4A, TTK, SGO2, PLK4, ARHGAP11A, XRCC2, Clorf112, NCAPG, and ORC6) were screened due to significant upregulation in STAD. And they had been proven that enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Among them, 9 genes have been extensively associated to OS, and 3 genes had been associated to receive chemotherapy resistance. PPI protein network suggests that there is a sturdy correlation between these key genes.

Conclusion

A total of 19 key genes were found to play an essential position in retaining the traits of STAD stem cells. These genes can be used to evaluate the prognosis of STAD patients or become specific therapeutic targets.

Bioinformatics analysis reveals three key genes and four survival genes associated with youth-onset NSCLC

Youth-onset non-small cell lung cancer (NSCLC) is a heterogeneous disease. It has a unique clinicopathology and special genetic background. In this study, three key genes, CDC20, CCNB2, and BUB1, have been identified in youth-onset NSCLC tumor tissues based on the TCGA and GEO cohorts. Functional enrichment analysis reveals that the “oocyte meiosis,” “cell cycle,” and the “P53 signaling pathway” are significantly enriched. Additionally, four survival genes, including AKAP12, CRIM1, FEN1, and SLC7A11, that affect the prognosis of youth-onset NSCLC patients are identified in this study. Finally, we construct a risk model to predict the overall survival of youth-onset NSCLC patients, the AUC of the risk model in 1, 3, and 5 years of overall survival is 0.808, 0.844, and 0.728. This study aims to provide a novel idea to explore the pathogenic genes of youth-onset NSCLC.

Identification and Validation of a Potential Stemness-Associated Biomarker in Hepatocellular Carcinoma

Background

Cancer stem cells (CSCs) are typically related to metastasis, recurrence, and drug resistance in malignant tumors. However, the biomarker and mechanism of CSCs need further exploration. This study is aimed at comprehensively depicting the stemness characteristics and identify a potential stemness-associated biomarker in hepatocellular carcinoma (HCC).

Methods

The data of HCC patients from The Cancer Genome Atlas (TCGA) were collected and divided based on the mRNA expression-based stemness index (mRNAsi) in this study. Weighted gene coexpression network analysis (WGCNA) and the protein-protein interaction (PPI) network were performed, and the genes were screened through the Cytoscape software. Then, we constructed a prognostic expression signature using the multivariable Cox analysis and verified using the GEO and ICGC databases. Even more importantly, we used the three-dimensional (3D) fibrin gel to enrich the tumor-repopulating cells (TRCs) to validate the expression of the signature in CSCs by quantitative RT-PCR.

Results

mRNAsi was significantly elevated in tumor and high-mRNAsi score was associated with poor overall survival in HCC. The positive stemness-associated (blue) module with 737 genes were screened based on WGCNA, and Budding uninhibited by benzimidazoles 1 (BUB1) was identified as the hub gene highly related to stemness in HCC. Then, the prognostic value and stemness characteristics were well validated in the ICGC and GSE14520 cohorts. Further analysis showed the expression of BUB1 was elevated in TRCs.

Conclusion

BUB1, as a potential stemness-associated biomarker, could serve as a therapeutic CSCs-target and predicted the clinical outcomes of patients with HCC.

BUB1 predicts poor prognosis and immune status in liver hepatocellular carcinoma

Accurate assessment of the tumour immune microenvironment promotes individualized immunotherapy regimens and screens dominant populations suitable for immunotherapy. Therefore, potential molecular markers were investigated to make an overall assessment of the immune microenvironment status of liver hepatocellular carcinoma (LIHC). In this study, a total of 121 differentially expressed genes (DEGs) were identified, and DEGs were enriched in the epithelial-mesenchymal transition, hypoxia, myogenesis, and p53 pathways. A total of 20 hub genes were selected and a strong correlation was identified between these hub genes and prognosis. The expression of budding uninhibited by benzimidazoles 1 (BUB1) was found to be upregulated in LIHC and was strongly related to immune cells and immune checkpoint molecule expression. Immunohistochemistry (IHC) indicated that BUB1 expression was higher in LIHC tissues than in normal liver tissues. BUB1 knockdown resulted in reduced proliferation and vertical migration ability of LIHC cells, and reduced the expression of phospho-SMAD family member 2 and phospho-SMAD family member 3 proteins. IHC showed that BUB1 expression was accompanied by immune cell infiltration into LIHC tissues. These results suggest that BUB1 may serve as a potential prognostic biomarker for LIHC and as an indicator of its immune status.

Statistics and network-based approaches to identify molecular mechanisms that drive the progression of breast cancer

Breast cancer (BC) is one of the most malignant tumors and the leading cause of cancer-related death in women worldwide. So, an in-depth investigation on the molecular mechanisms of BC progression is required for diagnosis, prognosis and therapies. In this study, we identified 127 common differentially expressed genes (cDEGs) between BC and control samples by analyzing five gene expression profiles with NCBI accession numbers GSE139038, GSE62931, GSE45827, GSE42568 and GSE54002, based-on two statistical methods LIMMA and SAM. Then we constructed protein-protein interaction (PPI) network of cDEGs through the STRING database and selected top-ranked 7 cDEGs (BUB1, ASPM, TTK, CCNA2, CENPF, RFC4, and CCNB1) as a set of key genes (KGs) by cytoHubba plugin in Cytoscape. Several BC-causing crucial biological processes, molecular functions, cellular components, and pathways were significantly enriched by the estimated cDEGs including at-least one KGs. The multivariate survival analysis showed that the proposed KGs have a strong prognosis power of BC. Moreover, we detected some transcriptional and post-transcriptional regulators of KGs by their regulatory network analysis. Finally, we suggested KGs-guided three repurposable candidate-drugs (Trametinib, selumetinib, and RDEA119) for BC treatment by using the GSCALite online web tool and validated them through molecular docking analysis, and found their strong binding affinities. Therefore, the findings of this study might be useful resources for BC diagnosis, prognosis and therapies.

Identification of Key Prognostic Genes of Triple Negative Breast Cancer by LASSO-Based Machine Learning and Bioinformatics Analysis

Improved insight into the molecular mechanisms of triple negative breast cancer (TNBC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study is to identify key genes which may affect the prognosis of TNBC patients by bioinformatic analysis. In our study, the RNA sequencing (RNA-seq) expression data of 116 breast cancer lacking ER, PR, and HER2 expression and 113 normal tissues were downloaded from The Cancer Genome Atlas (TCGA). We screened out 147 differentially co-expressed genes in TNBC compared to non-cancerous tissue samples by using weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were constructed, revealing that 147 genes were mainly enriched in nuclear division, chromosomal region, ATPase activity, and cell cycle signaling. After using Cytoscape software for protein-protein interaction (PPI) network analysis and LASSO feature selection, a total of fifteen key genes were identified. Among them, BUB1 and CENPF were significantly correlated with the overall survival rate (OS) difference of TNBC patients (p value < 0.05). In addition, BUB1, CCNA2, and PACC1 showed significant poor disease-free survival (DFS) in TNBC patients (p value < 0.05), and may serve as candidate biomarkers in TNBC diagnosis. Thus, our results collectively suggest that BUB1, CCNA2, and PACC1 genes could play important roles in the progression of TNBC and provide attractive therapeutic targets.

Arginine Depletion in Human Cancers

Arginine is encoded by six different codons. Base pair changes in any of these codons can have a broad spectrum of effects including substitutions to twelve different amino acids, eighteen synonymous changes, and two stop codons. Four amino acids (histidine, cysteine, glutamine, and tryptophan) account for over 75% of amino acid substitutions of arginine. This suggests that a mutational bias, or "purifying selection", mechanism is at work. This bias appears to be driven by C > T and G > A transitions in four of the six arginine codons, a signature that is universal and independent of cancer tissue of origin or histology. Here, we provide a review of the available literature and reanalyze publicly available data from the Catalogue of Somatic Mutations in Cancer (COSMIC). Our analysis identifies several genes with an arginine substitution bias. These include known factors such as IDH1, as well as previously unreported genes, including four cancer driver genes (FGFR3, PPP6C, MAX, GNAQ). We propose that base pair substitution bias and amino acid physiology both play a role in purifying selection. This model may explain the documented arginine substitution bias in cancers.

BUB1 drives the occurrence and development of bladder cancer by mediating the STAT3 signaling pathway

BACKGROUND

The incidence of bladder urothelial carcinoma (UC), a common malignancy of the urinary tract, is approximately three times higher in men than in women. High expression of the mitotic kinase BUB1 is associated with the occurrence and development of several cancers, although the relationship between BUB1 and bladder tumorigenesis remains unclear.

METHODS

Using a microarray approach, we found increased BUB1 expression in human BCa. The association between BUB1 and STAT3 phosphorylation was determined through molecular and cell biological methods. We evaluated the impact of pharmacologic inhibition of BUB1 kinase activity on proliferation and BCa progression in vitro and in vivo.

RESULTS

In this study, we found that BUB1 expression was increased in human bladder cancer (BCa). We further identified through a series of molecular and cell biological approaches that BUB1 interacted directly with STAT3 and mediated the phosphorylation of STAT3 at Ser727. In addition, the findings that pharmacologic inhibition of BUB1 kinase activity significantly suppressed BCa cell proliferation and the progression of bladder cancer in vitro and in vivo were further verified. Finally, we found that the BUB1/STAT3 complex promoted the transcription of STAT3 target genes and that depletion of BUB1 and mutation of the BUB1 kinase domain abrogated this transcriptional activity, further highlighting the critical role of kinase activity in the activation of STAT3 target genes. A pharmacological inhibitor of BUB1 (2OH-BNPP1) was able to significantly inhibit the growth of BCa cell xenografts.

CONCLUSION

This study showed that the BUB1 kinase drives the progression and proliferation of BCa by regulating the transcriptional activation of STAT3 signaling and may be an attractive candidate for therapeutic targeting in BCa.

Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer

Background

Chemotherapy resistance, especially platinum resistance, is the main cause of poor prognosis of ovarian cancer. It is of great urgency to find molecular markers and mechanism related to platinum resistance in ovarian cancer.

Methods

One mRNA dataset (GSE28739) and one miRNA dataset (GSE25202) were acquired from Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) between platinum-resistant and platinum-sensitive ovarian cancer patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed using the DAVID to present the most visibly enriched pathways. Protein–protein interaction (PPI) of these DEGs was constructed based on the information of the STRING database. Hub genes related to platinum resistance were visualized by Cytoscape software. Then, we chose seven interested hub genes to further validate using qRT-PCR in A2780 ovarian cancer cell lines. And, at last, the TF-miRNA-target genes regulatory network was predicted and constructed using miRNet software.

Results

A total of 63 upregulated DEGs, 124 downregulated DEGs, four upregulated miRNAs and six downregulated miRNAs were identified. From the PPI network, the top 10 hub genes were identified, which were associated with platinum resistance. Our further qRT-PCR showed that seven hub genes (BUB1, KIF2C, NUP43, NDC80, NUF2, CCNB2 and CENPN) were differentially expressed in platinum-resistant ovarian cancer cells. Furthermore, the upstream transcription factors (TF) for upregulated DE-miRNAs were SMAD4, NFKB1, SMAD3, TP53 and HNF4A. Three overlapping downstream target genes (KIF2C, STAT3 and BUB1) were identified by miRNet, which was regulated by hsa-miR-494.

Conclusions

The TF-miRNA–mRNA regulatory pairs, that is TF (SMAD4, NFKB1 and SMAD3)-miR-494-target genes (KIF2C, STAT3 and BUB1), were established. In conclusion, the present study is of great significance to find the key genes of platinum resistance in ovarian cancer. Further study is needed to identify the mechanism of these genes in ovarian cancer.

Prognostic Value of BUB1 for Predicting Non-Muscle-Invasive Bladder Cancer Progression

Non-muscle-invasive bladder cancer (NMIBC) is a common disease with a high recurrence rate requiring lifetime surveillance. Although NMIBC is not life-threatening, it can progress to muscle-invasive bladder cancer (MIBC), a lethal form of the disease. The management of the two diseases differs, and patients with MIBC require aggressive treatments such as chemotherapy and radical cystectomy. NMIBC patients at a high risk of progression benefit from early immediate cystectomy. Thus, identifying concordant markers for accurate risk stratification is critical to predict the prognosis of NMIBC. Candidate genetic biomarkers associated with NMIBC prognosis were screened by RNA-sequencing of 24 tissue samples, including 16 NMIBC and eight normal controls, and by microarray analysis (GSE13507). Lastly, we selected and investigated a mitotic checkpoint serine/threonine kinase, BUB1, that regulates chromosome segregation during the cell cycle. BUB1 gene expression was tested in 86 NMIBC samples and 15 controls by real-time qPCR. The performance of BUB1 as a prognostic biomarker for NMIBC was validated in the internal Chungbuk cohort (GSE13507) and the external UROMOL cohort (E-MTAB-4321). BUB1 expression was higher in NMIBC patients than in normal controls (p < 0.05), and the overexpression of BUB1 was correlated with NMIBC progression (log-rank test, p = 0.007). In in vitro analyses, BUB1 promoted the proliferation of bladder cancer cells by accelerating the G2/M transition of the cell cycle. Conclusively, BUB1 modulates the G2/M transition to promote the proliferation of bladder cancer cells, suggesting that it could serve as a prognostic marker in NMIBC.

Key signaling networks are dysregulated in patients with the adipose tissue disorder, lipedema

Objectives

Lipedema, a poorly understood chronic disease of adipose hyper-deposition, is often mistaken for obesity and causes significant impairment to mobility and quality-of-life. To identify molecular mechanisms underpinning lipedema, we employed comprehensive omics-based comparative analyses of whole tissue, adipocyte precursors (adipose-derived stem cells (ADSCs)), and adipocytes from patients with or without lipedema.

Methods

We compared whole-tissues, ADSCs, and adipocytes from body mass index–matched lipedema (n = 14) and unaffected (n = 10) patients using comprehensive global lipidomic and metabolomic analyses, transcriptional profiling, and functional assays.

Results

Transcriptional profiling revealed >4400 significant differences in lipedema tissue, with altered levels of mRNAs involved in critical signaling and cell function-regulating pathways (e.g., lipid metabolism and cell-cycle/proliferation). Functional assays showed accelerated ADSC proliferation and differentiation in lipedema. Profiling lipedema adipocytes revealed >900 changes in lipid composition and >600 differentially altered metabolites. Transcriptional profiling of lipedema ADSCs and non-lipedema ADSCs revealed significant differential expression of >3400 genes including some involved in extracellular matrix and cell-cycle/proliferation signaling pathways. One upregulated gene in lipedema ADSCs, Bub1, encodes a cell-cycle regulator, central to the kinetochore complex, which regulates several histone proteins involved in cell proliferation. Downstream signaling analysis of lipedema ADSCs demonstrated enhanced activation of histone H2A, a key cell proliferation driver and Bub1 target. Critically, hyperproliferation exhibited by lipedema ADSCs was inhibited by the small molecule Bub1 inhibitor 2OH-BNPP1 and by CRISPR/Cas9-mediated Bub1 gene depletion.

Conclusion

We found significant differences in gene expression, and lipid and metabolite profiles, in tissue, ADSCs, and adipocytes from lipedema patients compared to non-affected controls. Functional assays demonstrated that dysregulated Bub1 signaling drives increased proliferation of lipedema ADSCs, suggesting a potential mechanism for enhanced adipogenesis in lipedema. Importantly, our characterization of signaling networks driving lipedema identifies potential molecular targets, including Bub1, for novel lipedema therapeutics.

Gene Expression Profiling of Olfactory Neuroblastoma Helps Identify Prognostic Pathways and Define Potentially Therapeutic Targets

Simple Summary

The gene expression profile of ONB defines a group of patients with a dismal prognosis and identifies potentially targetable pathways. Better prognostic stratification may offer new tailored approaches for the treatment and follow-up of ONB. The integration of new therapeutic agents with standard surgical and RT strategies may improve the outcomes in cases with worse prognoses. Furthermore, the ontogenesis of ONB in basal and neural subtypes is mirrored by different transcriptional pathways, paving the way towards different therapeutic approaches.

Abstract

Olfactory neuroblastoma (ONB) is a rare sinonasal neoplasm with a peculiar behavior, for which limited prognostic factors are available. Herein, we investigate the transcriptional pathways altered in ONB and correlate them with pathological features and clinical outcomes. We analyze 32 ONB patients treated with curative intent at two independent institutions from 2001 to 2019 for whom there is available pathologic and clinical data. We perform gene expression profiling on primary ONB samples and carry out functional enrichment analysis to investigate the key pathways associated with disease-free survival (DFS). The median age is 53.5 years; all patients undergo surgery and a pure endoscopic approach is adopted in the majority of cases (81.2%). Most patients have advanced disease (stages III–IV, 81.2%) and 84.4% undergo adjuvant (chemo)radiotherapy. The median follow-up is 35 months; 11 (26.8%) patients relapse. Clinical characteristics (gender, stage and Hyams’ grade) are not associated with the outcomes. In contrast, TGF-beta binding, EMT, IFN-alpha response, angiogenesis, IL2-STAT5 and IL6-JAK-STAT3 signaling pathways are enriched in patients experiencing recurrence, and significantly associated with shorter DFS. Clustering of transcriptional profiles according to pathological features indicates two distinct molecular groups, defined by either cytokeratin-positive or -negative immunostaining. Definition of the characterizing ONB transcriptomic pathways may pave the way towards tailored treatment approaches.

Identification of Potential Therapeutic Genes and Pathways in Phytoestrogen Emodin Treated Breast Cancer Cell Lines via Network Biology Approaches

Phytoestrogens have been investigated for their potential anti-tumorigenic effects in various cancers including breast cancer. Emodin being a phytoestrogen shows anti-carcinogenic properties especially in estrogen receptor positive (ER+) breast cancers. The aim of this study is to identify the molecular mechanism and related biological pathways in both (ER+) MCF-7 and (ER-) MDA-MB-231 breast cancer cell lines upon Emodin treatment via microarray analysis in order to find out therapeutic biomarkers. In both cell lines, first differentially expressed genes were identified, then gene ontology and functional pathway enrichment analyses were performed. Genes regulated through multiple pathways were studied together with literature and a gene cluster was determined for each cell line. Further GeneMANIA and STRING databases were used to study the interactions within the related gene clusters. The results showed that, the genes which are related to cell cycle were significantly regulated in both cell lines. Also, Forkhead Box O1-related genes were found to be prominent in MCF-7 cells. In MDA-MB-231 cells, spindle attachment checkpoint mechanism-related genes were regulated, remarkably. As a result, novel gene regulations reported in this study in response to Emodin will give more information about its metabolism and antiproliferative effect, especially in ER + cells.

Identification of hub genes in triple-negative breast cancer by integrated bioinformatics analysis

Background

Triple negative breast cancer (TNBC) is usually aggressive and accompanied by a poor prognosis. The molecular biological mechanism of TNBC pathogenesis is still unclear, and requires more detailed research. The aim of this study was to screen and verify potential biomarkers of TNBC, and provide new clues for the treatment and diagnosis of TNBC.

Methods

In this work, GSE76250 was downloaded from the Gene Expression Omnibus (GEO) database and included 165 TNBC samples and 33 paired normal breast tissues. The R software and its related software package were used for data processing and analysis. Compared with normal tissues, genes with a false discovery rate (FDR) <0.01 and log fold change (logFC) ≥1 or ≤-1 were identified as differentially expressed genes (DEGs) by limma package. Survival prognoses were analyzed by Kaplan-Meier plotter database.

Results

In total, 160 up-regulated and 180 down-regulated genes were identified. The biological mechanism of enrichment analysis presented that DEGs were significantly enriched in chromosome segregation, extracellular matrix, and extracellular matrix structural constituent, among others. A total of 8 hub genes (CCNB1, CDK1, TOP2A, MKI67, TTK, CCNA2, BUB1, and PLK1) were identified by the protein-protein interaction network (PPIN) and Cytoscape software. Survival prognosis of these hub genes showed that they were negatively correlated with overall survival.

Conclusions

The 8 hub genes and pathways that were identified might be involved in tumorigenesis and become new candidate biomarkers for TNBC treatment.

Overexpression of β-Arrestins inhibits proliferation and motility in triple negative breast cancer cells

β-Arrestins (βArrs) are intracellular signal regulating proteins. Their expression level varies in some cancers and they have a significant impact on cancer cell function. In general, the significance of βArrs in cancer research comes from studies examining GPCR signalling. Given the diversity of different GPCR signals in cancer cell regulation, contradictory results are inevitable regarding the role of βArrs. Our approach examines the direct influence of βArrs on cellular function and gene expression profiles by changing their expression levels in breast cancer cells, MDA-MB-231 and MDA-MB-468. Reducing expression of βArr1 or βArr2 tended to increase cell proliferation and invasion whereas increasing their expression levels inhibited them. The overexpression of βArrs caused cell cycle S-phase arrest and differential expression of cell cycle genes, CDC45, BUB1, CCNB1, CCNB2, CDKN2C and reduced HER3, IGF-1R, and Snail. Regarding to the clinical relevance of our results, low expression levels of βArr1 were inversely correlated with CDC45, BUB1, CCNB1, and CCNB2 genes compared to normal tissue samples while positively correlated with poorer prognosis in breast tumours. These results indicate that βArr1 and βArr2 are significantly involved in cell cycle and anticancer signalling pathways through their influence on cell cycle genes and HER3, IGF-1R, and Snail in TNBC cells.

Identification of candidate biomarkers correlated with the pathogenesis and prognosis of breast cancer via integrated bioinformatics analysis

BACKGROUND

This study was carried out to identify potential key genes associated with the pathogenesis and prognosis of breast cancer (BC).

METHODS

Seven GEO datasets (GSE24124, GSE32641, GSE36295, GSE42568, GSE53752, GSE70947, GSE109169) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between BC and normal breast tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Hub genes related to the pathogenesis and prognosis of BC were verified by employing protein-protein interaction (PPI) network.

RESULTS

Ten hub genes with high degree were identified, including CDK1, CDC20, CCNA2, CCNB1, CCNB2, BUB1, BUB1B, CDCA8, KIF11, and TOP2A. Lastly, the Kaplan-Meier plotter (KM plotter) online database demonstrated that higher expression levels of these genes were related to lower overall survival. Experimental validation showed that all 10 hub genes had the same expression trend as predicted.

CONCLUSION

The findings of this research would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of BC, which could be used as a new biomarker for diagnosis and to guide the combination medicine of BC.

Identification of breast cancer prognostic modules via differential module selection based on weighted gene Co-expression network analysis

Breast cancer is a complex cancer which includes many different subtypes. Identifying prognostic modules, i.e., functionally related gene networks that play crucial roles in cancer development is essential in breast cancer study. Different subtypes of breast cancer correspond to different treatment methods. The purpose of this study is to use a new method to divide breast cancer into different prognostic modules, so as to provide scientific basis for improving clinical management. The method is based on comparing similarities between modules detected from different weighted gene co-expression networks. The method was applied on genomic data of breast cancer from The Cancer Genome Atlas database and was applied to select differential modules between two groups of patients with significant differences in survival times. It was compared with a previously proposed module selection method. The result shows that our method outperforms the previously proposed one. Moreover, within the identified two differential modules, the first one is highly enriched with genes involved in hormone responds, the second one is highly related with biological process engaged in M-phase. The two modules were further validated by log-rank test in the validation dataset GSE3494. Both of the two modules show significantly different with p-values less than 0.02. The identified two modules confirmed previous findings including importance of biological networks in breast cancer involved in hormone response and M-phase. Out of the top twenty hub genes in the two modules, fifteen genes were previously shown to be prognostic markers for breast cancer.

Identification of grade-related genes and construction of a robust genomic-clinicopathologic nomogram for predicting recurrence of bladder cancer

BACKGROUND

Bladder cancer (BC) is a common tumor in the urinary system with a high recurrence rate. The individualized treatment and follow-up after surgery is the key to a successful outcome. Currently, the surveillance strategies are mainly depending on tumor stage and grade. Previous evidence has proved that tumor grade was a significant and independent risk factor of BC recurrence. Exploring the grade-related genes may provide us a new approach to predict prognosis and guide the post-operative treatment in BC patients.

METHODS

In this study, the weighted gene co-expression network analysis was applied to identify the hub gene module correlated with BC grade using GSE71576. After constructing a protein-protein interaction (PPI) network with the hub genes inside the hub gene module, we identified some potential core genes. TCGA and another independent dataset were used for further validation.

RESULTS

The results revealed that the expression of AURKA, CCNA2, CCNB1, KIF11, TTK, BUB1B, BUB1, and CDK1 were significantly higher in high-grade BC, showing a strong ability to distinguish BC grade. The expression levels of the 8 genes in normal, paracancerous, tumorous, and recurrent bladder tissues were progressively increased. By conducting survival analysis, we proved their prognostic value in predicting the recurrence of BC. Eventually, we constructed a prognostic nomogram by combining the 8-core-gene panel with clinicopathologic features, which had shown great performance in predicting the recurrence of BC.

CONCLUSION

We identified 8 core genes that revealed a significant correlation with the tumor grade as well as the recurrence of BC. Finally, we proved the value of a novel prognostic nomogram for predicting the relapse-free survival of BC patients after surgery, which could guide their treatment and follow-up.

Identification of Metastasis-Associated Biomarkers in Synovial Sarcoma Using Bioinformatics Analysis

Synovial sarcoma (SS) is a highly aggressive soft tissue tumor with high risk of local recurrence and metastasis. However, the mechanisms underlying SS metastasis are still largely unclear. The purpose of this study is to screen metastasis-associated biomarkers in SS by integrated bioinformatics analysis. Two mRNA datasets (GSE40018 and GSE40021) were selected to analyze the differentially expressed genes (DEGs). Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), functional and pathway enrichment analyses were performed for DEGs. Then, the protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. The module analysis of the PPI network and hub genes validation were performed using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the hub genes were performed using WEB-based GEne SeT AnaLysis Toolkit (WebGestalt). The expression levels and survival analysis of hub genes were further assessed through Gene Expression Profiling Interactive Analysis (GEPIA) and the Kaplan-Meier plotter database. In total, 213 overlapping DEGs were identified, of which 109 were upregulated and 104 were downregulated. GO analysis revealed that the DEGs were predominantly involved in mitosis and cell division. KEGG pathways analysis demonstrated that most DEGs were significantly enriched in cell cycle pathway. GSEA revealed that the DEGs were mainly enriched in oocyte meiosis, cell cycle and DNA replication pathways. A key module was identified and 10 hub genes (CENPF, KIF11, KIF23, TTK, MKI67, TOP2A, CDC45, MELK, AURKB, and BUB1) were screened out. The expression and survival analysis disclosed that the 10 hub genes were upregulated in SS patients and could result in significantly reduced survival. Our study identified a series of metastasis-associated biomarkers involved in the progression of SS, and may provide novel therapeutic targets for SS metastasis.

Prognostic Prediction Using a Stemness Index-Related Signature in a Cohort of Gastric Cancer

Background

With characteristic self-renewal and multipotent differentiation, cancer stem cells (CSCs) have a crucial influence on the metastasis, relapse and drug resistance of gastric cancer (GC). However, the genes that participates in the stemness of GC stem cells have not been identified.

Methods

The mRNA expression-based stemness index (mRNAsi) was analyzed with differential expressions in GC. The weighted gene co-expression network analysis (WGCNA) was utilized to build a co-expression network targeting differentially expressed genes (DEG) and discover mRNAsi-related modules and genes. We assessed the association between the key genes at both the transcription and protein level. Gene Expression Omnibus (GEO) database was used to validate the expression levels of the key genes. The risk model was established according to the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Furthermore, we determined the prognostic value of the model by employing Kaplan-Meier (KM) plus multivariate Cox analysis.

Results

GC tissues exhibited a substantially higher mRNAsi relative to the healthy non-tumor tissues. Based on WGCNA, 17 key genes (ARHGAP11A, BUB1, BUB1B, C1orf112, CENPF, KIF14, KIF15, KIF18B, KIF4A, NCAPH, PLK4, RACGAP1, RAD54L, SGO2, TPX2, TTK, and XRCC2) were identified. These key genes were clearly overexpressed in GC and validated in the GEO database. The protein-protein interaction (PPI) network as assessed by STRING indicated that the key genes were tightly connected. After LASSO analysis, a nine-gene risk model (BUB1B, NCAPH, KIF15, RAD54L, KIF18B, KIF4A, TTK, SGO2, C1orf112) was constructed. The overall survival in the high-risk group was relatively poor. The area under curve (AUC) of risk score was higher compared to that of clinicopathological characteristics. According to the multivariate Cox analysis, the nine-gene risk model was a predictor of disease outcomes in GC patients (HR, 7.606; 95% CI, 3.037-19.051; P < 0.001). We constructed a prognostic nomogram with well-fitted calibration curve based on risk score and clinical data.

Conclusion

The 17 mRNAsi-related key genes identified in this study could be potential treatment targets in GC treatment, considering that they can inhibit the stemness properties. The nine-gene risk model can be employed to predict the disease outcomes of the patients.

Differential expression of lung adenocarcinoma transcriptome with signature of tobacco exposure

Smoking accounts for almost 80-90% of lung cancer cases, which is also the most frequent cause of cancer-related deaths in humans. With over 60 carcinogens in tobacco smoke, cells dividing at the time of carcinogen exposure are at particular risk of neoplasia. The present study aimed to investigate global gene expression differences in lung adenocarcinoma (LUAD) tumour samples of current smokers and non-smokers, in an attempt to elucidate biological mechanisms underlying divergent smoking effects. Current and non-smoker tumour samples were analysed using bioinformatics tools, examining differences in molecular drivers of cancer initiation and progression, as well as evaluating the effect of smoking and sex on epithelial mesenchymal transition (EMT). As a result, we identified 1150 differentially expressed genes showing visible differences in the expression profiles between the smoking subgroups. The genes were primarily involved in cell cycle, DNA replication, DNA repair, VEGF, GnRH, ErbB and T cell receptor signalling pathways. Our results show that smoking clearly affected E2F transcriptional activity and DNA repair pathways including mismatch repair, base excision repair and homologous recombination. We observed that sex could modify the effects of PLA2G2A and PRG4 in LUAD tumour samples, whereas sex and smoking status might possibly have a biological effect on the EMT-related genes: HEY2, OLFM1, SFRP1 and STRAP. We also identified potential epigenetic changes smoking solely might have on EMT-related genes, which may serve as potential diagnostic and prognostic biomarkers for LUAD patients.

Aberrant BUB1 Overexpression Promotes Mitotic Segregation Errors and Chromosomal Instability in Multiple Myeloma

Chromosome instability (CIN), the hallmarks of cancer, reflects ongoing chromosomal changes caused by chromosome segregation errors and results in whole chromosomal or segmental aneuploidy. In multiple myeloma (MM), CIN contributes to the acquisition of tumor heterogeneity, and thereby, to disease progression, drug resistance, and eventual treatment failure; however, the underlying mechanism of CIN in MM remains unclear. Faithful chromosomal segregation is tightly regulated by a series of mitotic checkpoint proteins, such as budding uninhibited by benzimidazoles 1 (BUB1). In this study, we found that BUB1 was overexpressed in patient-derived myeloma cells, and BUB1 expression was significantly higher in patients in an advanced stage compared to those in an early stage. This suggested the involvement of aberrant BUB1 overexpression in disease progression. In human myeloma-derived cell lines (HMCLs), BUB1 knockdown reduced the frequency of chromosome segregation errors in mitotic cells. In line with this, partial knockdown of BUB1 showed reduced variations in chromosome number compared to parent cells in HMCLs. Finally, BUB1 overexpression was found to promote the clonogenic potency of HMCLs. Collectively, these results suggested that enhanced BUB1 expression caused an increase in mitotic segregation errors and the resultant emergence of subclones with altered chromosome numbers and, thus, was involved in CIN in MM.

Bioinformatics analysis of BUB1 expression and gene regulation network in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma is the most common type of lung cancer with high morbidity and mortality. Potential mechanisms and therapeutic targets of lung adenocarcinoma need further study. BUB1 (BUB1 mitotic checkpoint serine/threonine kinase) encodes a serine/threonine protein kinase which is critical in mitosis. It is associated with poor prognosis in multiple cancer types.

METHODS

Oncomine database was used to determine the differential expression of BUB1 in normal and lung adenocarcinoma tissues, while UALCAN was used to perform analysis of the relative expression and survival of BUB1 between tumor and normal tissues in different tumor subgroups. We used the cBioPortal for Cancer Genomics to perform gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the top 50 altered neighbor genes of BUB1. The LinkedOmics database was used to determine differential gene expression with BUB1 and to perform functional analysis. The kinase, miRNA and transcription factor target networks correlated with BUB1 were also analyzed by LinkedOmics database.

RESULTS

The results revealed that BUB1 was highly expressed in lung adenocarcinoma patients. BUB1 involved multiple tumor-related pathways, such as cell cycle, oocyte meiosis and p53 signaling pathway. BUB1 is associated with tumor-associated kinases, microRNAs and transcription factors.

CONCLUSIONS

Our study analyzed BUB1 expression and potential gene regulation networks in lung adenocarcinoma based on bioinformatics analysis, guiding further study on the role and regulation of BUB1 in lung adenocarcinoma. BUB1 may hopefully become a novel marker and therapeutic target for lung adenocarcinoma.

Upregulation of ECT2 is associated with transcriptional program of cancer stem cells and predicts poor clinical outcome in gastric cancer

Gastric cancer remains the third leading cause of cancer-associated mortality worldwide. The identification of prognostic indicators that are associated with clinical characteristics is urgently required. The aim of the present study was to determine the involvement of epithelial cell transforming 2 (ECT2) in gastric cancer. The results of the present study demonstrated that ECT2 expression was upregulated in human gastric cancer samples. Furthermore, high ECT2 expression was associated with advanced Tumor-Node-Metastasis stage and deeper tumor invasion. ECT2 upregulation was further confirmed in several independent publicly available clinical cohorts from the Gene Expression Omnibus database. In addition, patients with gastric cancer, with high ECT2 expression exhibited a significantly shorter overall survival time than those with low ECT2 expression, and Cox regression analysis demonstrated that ECT2 expression was an independent prognostic marker for overall survival time. Characterization of the transcriptome profiles of ECT2 upregulated gastric tumors indicated that ECT2 upregulation may be associated with transcriptional features of cancer stem cells (CSCs). Additionally, BUB1 mitotic checkpoint serine/threonine kinase and E2F transcription factor 7, two genes previously reported to account for the functionality of CSCs, were strongly enriched in ECT2^High gastric cancer samples. Taken together, the results of the present study suggest that ECT2 may serve as a novel marker for CSCs and may be a potential prognostic indicator in gastric cancer.

Targeting MAD2 modulates stemness and tumorigenesis in human Gastric Cancer cell lines

Rationale: Gastric cancer (GC) is a solid tumor that contains subpopulations of cancer stem cells (CSCs), which are considered drivers of tumor initiation and metastasis; responsible for therapeutic resistance; and promoters of tumor relapse. The balance between symmetric and asymmetric division is crucial for stem cell maintenance. The objective of this study is to evaluate the role of MAD2, a key protein for proper mitotic checkpoint activity, in the tumorigenesis of GC.

Methods: Gastric cancer stem cells (GCSCs) were obtained from MKN45, SNU638 and ST2957 cell lines. Pluripotency and stemness markers were evaluated by RT-qPCR and autofluorescence and membrane markers by flow cytometry. Relevant signal transduction pathways were studied by WB. We analysed cell cycle progression, migration and invasion after modulation of MAD2 activity or protein expression levels in these in vitro models. In vivo assays were performed in a nude mouse subcutaneous xenograft model.

Results: We found that NANOG, CXCR4 and autofluorescence are common and consistent markers for the GCSCs analysed, with other markers showing more variability. The three main signalling pathways (Wnt/β-catenin; Hedgehog and Notch) were activated in GCSCs. Downregulation of MAD2 in MKN45^CSCs decreased the expression of markers CXCR4, CD133, CD90, LGR5 and VIM, without affecting cell cycle profile or therapy resistance. Moreover, migration, invasion and tumor growth were clearly reduced, and accordingly, we found that metalloprotease expression decreased. These results were accompanied by a reduction in the levels of transcription factors related with epithelial-to-mesenchymal transition.

Conclusions: We can conclude that MAD2 is important for GCSCs stemness and its downregulation in MKN45^CSCs plays a central role in GC tumorigenesis, likely through CXCR4-SNAI2-MMP1. Thus, its potential use in the clinical setting should be studied as its functions appear to extend beyond mitosis.

Hybrid Stem Cell States: Insights Into the Relationship Between Mammary Development and Breast Cancer Using Single-Cell Transcriptomics

Similarities between stem cells and cancer cells have implicated mammary stem cells in breast carcinogenesis. Recent evidence suggests that normal breast stem cells exist in multiple phenotypic states: epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M). Hybrid E/M cells in particular have been implicated in breast cancer metastasis and poor prognosis. Mounting evidence also suggests that stem cell phenotypes change throughout the life course, for example, through embryonic development and pregnancy. The goal of this study was to use single cell RNA-sequencing to quantify cell state distributions of the normal mammary (NM) gland throughout developmental stages and when perturbed into a stem-like state in vitro using conditional reprogramming (CR). Using machine learning based dataset alignment, we integrate multiple mammary gland single cell RNA-seq datasets from human and mouse, along with bulk RNA-seq data from breast tumors in the Cancer Genome Atlas (TCGA), to interrogate hybrid stem cell states in the normal mammary gland and cancer. CR of human mammary cells induces an expanded stem cell state, characterized by increased expression of embryonic stem cell associated genes. Alignment to a mouse single-cell transcriptome atlas spanning mammary gland development from in utero to adulthood revealed that NM cells align to adult mouse cells and CR cells align across the pseudotime trajectory with a stem-like population aligning to the embryonic mouse cells. Three hybrid populations emerge after CR that are rare in NM: KRT18+/KRT14+ (hybrid luminal/basal), EPCAM+/VIM+ (hybrid E/M), and a quadruple positive population, expressing all four markers. Pseudotime analysis and alignment to the mouse developmental trajectory revealed that E/M hybrids are the most developmentally immature. Analyses of single cell mouse mammary RNA-seq throughout pregnancy show that during gestation, there is an enrichment of hybrid E/M cells, suggesting that these cells play an important role in mammary morphogenesis during lactation. Finally, pseudotime analysis and alignment of TCGA breast cancer expression data revealed that breast cancer subtypes express distinct developmental signatures, with basal tumors representing the most “developmentally immature” phenotype. These results highlight phenotypic plasticity of normal mammary stem cells and provide insight into the relationship between hybrid cell populations, stemness, and cancer.

BUB1 promotes proliferation of liver cancer cells by activating SMAD2 phosphorylation

Budding uninhibited by benzimidazoles 1 (BUB1) is a mitotic checkpoint serine/threonine kinase that has been reported as an oncogene or tumor suppressor gene in various types of cancer, including breast cancer, pancreatic ductal adenocarcinoma, prostate and gastric cancers. However, its role in liver cancer remains unclear. The present study aimed to explore the biological function of BUB1 in liver cancer. The present study demonstrated that BUB1 mRNA expression levels and the intensity of immunohistochemical staining were significantly increased in liver cancer tissues compared with normal tissues. The role of BUB1 in cell proliferation was also determined. Overexpression of BUB1 significantly promoted cell proliferation, whereas knockdown of BUB1 expression inhibited the proliferation of liver cancer cell lines. In experiments investigating the underlying mechanism, overexpression of BUB1 increased the levels of SMAD2 phosphorylation, whereas knockdown of BUB1 reduced the levels of SMAD2 phosphorylation. Therefore, BUB1 may promote proliferation of liver cancer cells by activating phosphorylation of SMAD2, and BUB1 may serve as a potential target in the diagnosis and/or treatment of liver cancer.

mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Cancer stem cells (CSCs), characterized by self-renewal and unlimited proliferation, lead to therapeutic resistance in lung cancer. In this study, we aimed to investigate the expressions of stem cell-related genes in lung adenocarcinoma (LUAD). The stemness index based on mRNA expression (mRNAsi) was utilized to analyze LUAD cases in the Cancer Genome Atlas (TCGA). First, mRNAsi was analyzed with differential expressions, survival analysis, clinical stages, and gender in LUADs. Then, the weighted gene co-expression network analysis was performed to discover modules of stemness and key genes. The interplay among the key genes was explored at the transcription and protein levels. The enrichment analysis was performed to annotate the function and pathways of the key genes. The expression levels of key genes were validated in a pan-cancer scale. The pathological stage associated gene expression level and survival probability were also validated. The Gene Expression Omnibus (GEO) database was additionally used for validation. The mRNAsi was significantly upregulated in cancer cases. In general, the mRNAsi score increases according to clinical stages and differs in gender significantly. Lower mRNAsi groups had a better overall survival in major LUADs, within five years. The distinguished modules and key genes were selected according to the correlations to the mRNAsi. Thirteen key genes (CCNB1, BUB1, BUB1B, CDC20, PLK1, TTK, CDC45, ESPL1, CCNA2, MCM6, ORC1, MCM2, and CHEK1) were enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Eight of the thirteen genes have been reported to be associated with the CSC characteristics. However, all of them have been previously ignored in LUADs. Their expression increased according to the pathological stages of LUAD, and these genes were clearly upregulated in pan-cancers. In the GEO database, only the tumor necrosis factor receptor associated factor-interacting protein (TRAIP) from the blue module was matched with the stemness microarray data. These key genes were found to have strong correlations as a whole, and could be used as therapeutic targets in the treatment of LUAD, by inhibiting the stemness features.

Effect of KNL1 on the proliferation and apoptosis of colorectal cancer cells

Objective:

To identify the expression of kinetochore scaffold 1 (KNL1) in colorectal tumor tissues and to clarify the role of this gene in the proliferation capability of colorectal cancer cells.

Methods:

A total of 108 paired colorectal tumor and normal tissue samples were collected from patients with colorectal cancer and subjected to quantitative polymerase chain reaction and immunohistochemistry analyses. Expression levels of KNL1 mRNA and protein were compared between tumor and normal tissues, and KNL1 levels were evaluated in relation to the patients’ tumor differentiation, sex, lymph node metastasis, TNM stage, infiltration depth, age, and tumor location. Survival curves were also constructed and compared between patients with tumor samples with and without KLN1 protein expression. KNL1 was under-expressed in colorectal cancer cells in vitro using lentiviral transfection with short hairpin RNA, and its function was evaluated by proliferation, colony-formation, and apoptosis assays. Expression levels of BUB1 protein were also compared between tumor and normal tissues, and the correlation between KNL1 expression and BUB1 expression in colorectal cancer tissues was examined.

Results:

KNL1 mRNA and protein were both highly expressed in colorectal tumor tissues compared with paired normal tissues. KNL1 downregulation significantly inhibited colorectal cancer cell proliferation and colony formation, and promoted apoptosis. KNL1 protein expression was significantly associated with tumor differentiation, but not with sex, lymph node metastasis, TNM stage, infiltration depth, age, or tumor location. KNL1 protein expression was also significantly associated with poorer survival. Moreover, there was a significant correlation between KNL1 and BUB1 in colorectal cancer tissues.

Conclusions:

KNL1 plays an effective role in decreasing apoptosis and promoting the proliferation of colorectal cancer cells, suggesting that its inhibition may represent a promising therapeutic approach in patients with colorectal cancer.

Co-Expression Network Analysis Identified Genes Associated with Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma

Objective: Cancer stem cells are self-renewal cells in tumors and can produce heterogeneous tumor cells, which play an important role in the development of lung squamous cell carcinoma (LSCC). In our research, we aimed to explore the expression of genes related to LSCC stem cells.Methods: We downloaded the RNAseq data, the pathological and prognostic profiles of LSCC cases from the public database TCGA. The mRNA expression-based stiffness index (mRNAsi) of LSCC was calculated and the prognostic value of mRNAsi was discussed. Then, we constructed a weighted gene co-expression network analysis (WGCNA) to screen key genes related to mRNAsi of LSCC.Results: MRNAsi is an independent prognostic factor in LSCC. We screened 5 key genes (BUB1, BIRC5, CCNB2, KIF15 and SPAG5) related to mRNAsi of LSCC based on WGCNA. The key genes were highly expressed in the tumor samples compared to the normal samples. In addition, there is a strong interaction between proteins of these key genes and a strong co-expression relationship at the transcriptional level.Conclusions: To conclude, mRNAsi play an important role in LSCC. Five key genes (BUB1, BIRC5, CCNB2, KIF15 and SPAG5) related to mRNAsi were screened, which may act as therapeutic targets for inhibiting the stem cell characteristics of LSCC.

Identification of Hub Genes Using Co-Expression Network Analysis in Breast Cancer as a Tool to Predict Different Stages

Background

Breast cancer has a high mortality rate and is the most common cancer of women worldwide. Our gene co-expression network analysis identified the genes closely related to the pathological stage of breast cancer.

Material/Methods

We performed weighted gene co-expression network analysis (WGCNA) from the Gene Expression Omnibus (GEO) database, and performed pathway enrichment analysis on genes from significant modules.

Results

A non-metastatic sample (374) of breast cancer from GSE102484 was used to construct the gene co-expression network. All 49 hub genes have been shown to be upregulated, and 19 of the 49 hub genes are significantly upregulated in breast cancer tissue. The roles of the genes CASC5, CKAP2L, FAM83D, KIF18B, KIF23, SKA1, GINS1, CDCA5, and MCM6 in breast cancer are unclear, so in order to better reveal the staging of breast cancer markers, it is necessary to study those hub genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes indicated that 49 hub genes were enriched to sister chromatid cohesion, spindle midzone, microtubule motor activity, cell cycle, and something else. Additionally, there is an independent data set – GSE20685 – for module preservation analysis, survival analysis, and gene validation.

Conclusions

This study identified 49 hub genes that were associated with pathologic stage of breast cancer, 19 of which were significantly upregulated in breast cancer. Risk stratification, therapeutic decision making, and prognosis predication might be improved by our study results. This study provides new insights into biomarkers of breast cancer, which might influence the future direction of breast cancer research.

Serine/threonine kinase BUB1 promotes proliferation and radio-resistance in glioblastoma

BUB1 (Budding uninhibited by benzimidazoles 1), a mitotic checkpoint serine/threonine kinase, has been linked in numerous cancers to pro-tumorigenic phenomena including elevation of cellular proliferation, tumor growth, metastatic potential, and poorer patient prognosis. However, the role of BUB1 in glioblastoma remains poorly investigated. In this study, clinical analyses determined significant enrichment of BUB1 in glioblastoma with direct correlation of elevated expression to poorer prognosis in glioma patients. Genetic inhibition of BUB1 in glioblastoma tumor cells via shRNA silencing diminished both proliferative ability and tumorigenicity in vitro and in vivo. Silencing of BUB1 was additionally determined to promote the cytotoxic effect of irradiation on glioblastoma tumor cells, and investigation of the underlying pathways revealed the roles of DNA mismatch repair, spliceosome and c-Myc pathways. Mechanistically, FOXM1 was determined to positively regulate transcription of BUB1 via direct promoter region binding. For validation, pharmacologic inhibition through administration of a BUB1 inhibitor demonstrated attenuated glioblastoma cellular proliferation in vitro as well as delayed tumor growth with prolonged survival in vivo. Collectively, this study demonstrates a novel therapeutic target for glioblastoma in the form of BUB1, which plays a pivotal role in GBM proliferative and radio-resistance capacities in a FOXM1-dependant manner.

[Expression of NUF2 in breast cancer and its clinical significance]

OBJECTIVE

To investigate the expression of the cell division- associated gene NUF2 in breast cancer and its clinical significance.

METHODS

The expression of NUF2 in breast cancer tissues was analyzed using Oncomine database. The relationship between the expression of NUF2 and the prognosis of breast cancer was analyzed using the Kaplan-Meier Plotter database. Gene set enrichment analysis (GSEA) and GEO database were used to investigate the effect of NUF2 on gene enrichment. The String database was utilized to analyze the proteins associated with NUF2. The TIMER database was analyzed to assess the correlations of NUF2 with BUB1, MAD2L1 and MYC. The expressions of NUF2 mRNA in 8 pairs of breast cancer tissues and adjacent tissues were verified by q-PCR.

RESULTS

Compared with that in normal breast tissue, NUF2 was significantly overexpressed in breast cancer (P &lt; 0.001). The overall survival time (HR = 1.52, P = 0.015) and the recurrence-free survival time (HR = 1.85, P = 3.2e-14) of the patients with high NUF2 expression were significantly shorter than those of patients with low NUF2 expression. In patients with high NUF2 expression, the enriched genes were involved mainly in cell cycle, P53, G2/M, DNA repair, MYC, and PI3K-AKT-MTOR signaling pathways, which were associated with tumor proliferation, invasion, metastasis and stemness. Combination of the results of String database, gene enrichment and TIMER database analyses suggested that NUF2 interacted directly with BUB1, MAD2L1, and MYC, which could promote the progression of breast cancer. The results of q-PCR showed that NUF2 expression was up-regulated in 6 cancer tissues and down-regulated in 2 cancer tissues.

CONCLUSIONS

NUF2 gene is overexpressed in breast cancer, and its expression level is important in predicting the prognosis of breast cancer.

Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis

BACKGROUND

Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer (BC) and links to poor outcomes. As the molecular mechanism of BLBC has not yet been completely discovered, identification of key pathways and hub genes of this disease is an important way for providing new insights into exploring the mechanisms of BLBC initiation and progression.

OBJECTIVE

The aim of this study was to identify potential gene signatures of the development and progression of the BLBC via bioinformatics analysis.

METHODS AND RESULTS

The differential expressed genes (DEGs) including 40 up-regulated and 21 down-regulated DEGs were identified between GSE25066 and GSE21422 microarrays, and these DEGs were significantly enriched in the terms related to oncogenic or suppressive roles in BLBC progression. In addition, KEGG pathway and GSEA (Gene Set Enrichment Analysis) enrichment analyses were performed for DEGs between the basal type and non-basal-type breast cancer from GSE25066 microarray. These DEGs were enriched in pathways such as cell cycle, cytokine-cytokine receptor interaction, chemokine signaling pathway, central carbon metabolism signaling and TNF signaling pathway. Moreover, the protein-protein interaction (PPI) network was constructed with those 61 DEGs using the Cytoscape software, and the biological significance of putative modules was established using MCODE. The module 1 was found to be closely related with a term of mitosis regulation and enriched in cell cycle pathway, and thus confirmed the pathological characteristic of BLBC with a high mitotic index. Furthermore, prediction values of the top 10 hub genes such as CCNB2, BUB1, NDC80, CENPE, KIF2C, TOP2A, MELK, TPX2, CKS2 and KIF20A were validated using Oncomine and Kaplan-Meier plotter.

CONCLUSION

Our results suggest the intriguing possibility that the hub genes and modules in the PPI network contributed to in-depth knowledge about the molecular mechanism of BLBC, paving a way for more accurate discovery of potential treatment targets for BLBC patients.