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

Identification of Prognostic Biomarkers for Suppressing Tumorigenesis and Metastasis of Hepatocellular Carcinoma through Transcriptome Analysis

Cancer is one of the deadliest diseases developed through tumorigenesis and could be fatal if it reaches the metastatic phase. The novelty of the present investigation is to explore the prognostic biomarkers in hepatocellular carcinoma (HCC) that could develop glioblastoma multiforme (GBM) due to metastasis. The analysis was conducted using RNA-seq datasets for both HCC (PRJNA494560 and PRJNA347513) and GBM (PRJNA494560 and PRJNA414787) from Gene Expression Omnibus (GEO). This study identified 13 hub genes found to be overexpressed in both GBM and HCC. A promoter methylation study showed these genes to be hypomethylated. Validation through genetic alteration and missense mutations resulted in chromosomal instability, leading to improper chromosome segregation, causing aneuploidy. A 13-gene predictive model was obtained and validated using a KM plot. These hub genes could be prognostic biomarkers and potential therapeutic targets, inhibition of which could suppress tumorigenesis and metastasis.

CLSPN is a potential biomarker associated with poor prognosis in low-grade gliomas based on a multi-database analysis

BACKGROUND

The oncogene CLSPN, also known as claspin, has regulatory effects in a variety of tumours; however, it is not clear whether CLSPN is a therapeutic target in low-grade gliomas (LGG). In this study, the prognostic value of CLSPN in LGG and its role as an immunotherapeutic target were evaluated.

METHODS

Transcriptome and methylation data for thousands of patients with glioma were collected from various databases, including The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Gene Expression Omnibus. Subsequently, a series of bioinformatics methods were used to evaluate the relationships between CLSPN and prognosis, clinical features, methylation status, immune cells, and molecular signaling pathways in LGG.

RESULTS

CLSPN expression levels were positively correlated with major malignant characteristics of LGG, and low expression of CLSPN was associated with a better prognosis. The methylation sites cg04263115 and cg06100291 negatively regulated the expression of CLSPN, and increased methylation levels at these sites were related to a longer survival time in patients with LGG. CLSPN was positively correlated with tumour-infiltrating immune cells and showed high copy number variation in these cells. There was a positive regulatory relationship between CLSPN expression and programmed death-1 (PD-1) and programmed cell death ligand 1 (PD-L1). A gene set enrichment analysis revealed that CLSPN activates a variety of cancer signaling pathways.

CONCLUSION

CLSPN was identified as an independent risk factor for LGG with excellent prognostic value.

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.

Multi-omics analysis predicts fibronectin 1 as a prognostic biomarker in glioblastoma multiforme

Glioblastoma (GBM) is one of the most malignant and intractable central nervous system tumors with high recurrence, low survival rate, and poor prognosis. Despite the advances of aggressive, multimodal treatment, a successful treatment strategy is still elusive, often leading to therapeutic resistance and fatality. Thus, it is imperative to search for and identify novel markers critically associated with GBM pathogenesis to improve the existing trend of diagnosis, prognosis, and treatment. Seven publicly available GEO microarray datasets containing 409 GBM samples were integrated and further data mining was conducted using several bioinformatics tools. A total of 209 differentially expressed genes (DEGs) were identified in the GBM tissue samples compared to the normal brains. Gene Ontology (GO) enrichment analysis of the DEGs revealed association of the upregulates genes with extracellular matrix (ECM), conceivably contributing to the invasive nature of GBM while downregulated DEGs were found to be predominantly related to neuronal processes and structures. Alongside, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway analyses described the involvement of the DEGs with various crucial contributing pathways (PI3K-Akt signaling pathway, p53 signaling pathway, insulin secretion, etc.) in GBM progression and pathogenesis. Protein-protein interaction (PPI) network containing 879 nodes and 1237 edges revealed 3 significant modules and consecutive KEGG pathway analysis of these modules showed a significant connection to gliomagenesis. Later, 10 hub genes were screened out based on degree and their expressions were externally validated. Surprisingly, only fibronectin 1 (FN1) high expression appeared to be related to poor prognosis. Subsequently, 109 transcription factors and 211 miRNAs were detected to be involved with the hub genes where FN1 demonstrated the highest number of interactions. Considering its high connectivity and potential prognostic value FN1 could be a novel biomarker providing new insights into the prognosis and treatment for GBM, although experimental validation is required.

FDI-6 and olaparib synergistically inhibit the growth of pancreatic cancer by repressing BUB1, BRCA1 and CDC25A signaling pathways

Inducing homologous recombination (HR) deficiency is a promising strategy to broaden the indication of PARP1/2 inhibitors in pancreatic cancer treatment. In addition to inhibition kinases, repression of the transcriptional function of FOXM1 has been reported to inhibit HR-mediated DNA repair. We found that FOXM1 inhibitor FDI-6 and PARP1/2 inhibitor Olaparib synergistically inhibited the malignant growth of pancreatic cancer cells in vitro and in vivo. The results of bioinformatic analysis and mechanistic study showed that FOXM1 directly interacted with PARP1. Olaparib induced the feedback overexpression of PARP1/2, FOXM1, CDC25A, CCND1, CDK1, CCNA2, CCNB1, CDC25B, BRCA1/2 and Rad51 to promote the acceleration of cell mitosis and recovery of DNA repair, which caused the generation of adaptive resistance. FDI-6 reversed Olaparib-induced adaptive resistance and inhibited cell cycle progression and DNA damage repair by repressing the expression of FOXM1, PARP1/2, BUB1, CDC25A, BRCA1 and other genes-involved in cell cycle control and DNA damage repair. We believe that targeting FOXM1 and PARP1/2 is a promising combination therapy for pancreatic cancer without HR deficiency.

CKAP2L, as an Independent Risk Factor, Closely Related to the Prognosis of Glioma

Recent studies have found that cytoskeleton-associated protein 2 like (CKAP2L), an important oncogene, is involved in the biological behavior of many malignant tumors, but its function in the malignant course of glioma has not been confirmed. The main purpose of this study was to clarify the relationship between prognostic clinical characteristics of glioma patients and CKAP2L expression using data collected from the GEPIA, HPA, CGGA, TCGA, and GEO databases. CKAP2L expression was significantly increased in glioma. Further, Kaplan-Meier plots revealed that increased expression of CKAP2L was associated with shorter survival time of glioma patients in datasets retrieved from multiple databases. Cox regression analysis indicated that CKAP2L can serve as an independent risk factor but also has relatively reliable diagnostic value for the prognosis of glioma patients. The results of gene set enrichment analysis suggested that CKAP2L may play a regulatory role through the cell cycle, homologous recombination, and N-glycan biosynthesis cell signaling pathways. Several drugs with potential inhibitory effects on CKAP2L were identified in the CMap database that may have therapeutic effects on glioma. Finally, knockdown of CKAP2L inhibited the proliferation and invasion of cells by reducing the expression level of cell cycle-related proteins. This is the first study to demonstrate that high CKAP2L expression leads to poor prognosis in glioma patients, providing a novel target for diagnosis and treatment of glioma.

BUB1B and circBUB1B_544aa aggravate multiple myeloma malignancy through evoking chromosomal instability

Multiple myeloma (MM) is an incurable plasma cell malignancy in the bone marrow characterized by chromosome instability (CIN), which contributes to the acquisition of heterogeneity, along with MM progression, drug resistance, and relapse. In this study, we elucidated that the expression of BUB1B increased strikingly in MM patients and was closely correlated with poor outcomes. Overexpression of BUB1B facilitated cellular proliferation and induced drug resistance in vitro and in vivo, while genetic targeting BUB1B abrogated this effect. Mechanistic studies unveiled that enforced expression of BUB1B evoked CIN resulting in MM poor outcomes mainly through phosphorylating CEP170. Interestingly, we discovered the existence of circBUB1B_544aa containing the kinase catalytic center of BUB1B, which was translated by a circular RNA of BUB1B. The circBUB1B_544aa elevated in MM peripheral blood samples was closely associated with MM poor outcomes and played a synergistic effect with BUB1B on evoking CIN. In addition, MM cells could secrete circBUB1B_544aa and interfere the MM microenvironmental cells in the same manner as BUB1B full-length protein. Intriguingly, BUB1B siRNA, targeting the kinase catalytic center of both BUB1B and circBUB1B_544aa, significantly inhibited MM malignancy in vitro and in vivo. Collectively, BUB1B and circBUB1B_544aa are promising prognostic and therapeutic targets of MM.

Overexpression of GINS4 is associated with poor prognosis and survival in glioma patients

Background

GINS4, an indispensable component of the GINS complex, is vital for a variety of cancer. However, no known empirical research has focused on exploring relationships between GINS4 and glioma. Thus, this study aims to understand and explain the role of GINS4 in glioma.

Method

First, we used the data in the CGGA, TCGA, GEO, GEPIA, and HPA databases to explore the expression level of GINS4 in glioma, the correlation between GINS4 expression and the clinical features of glioma, its impact on the survival of glioma patients, and verified the analysis results through RT-qPCR, IHC, and meta-analysis. Subsequently, GSEA enrichment analysis is used to find the potential molecular mechanism of GINS4 to promote the malignant process of glioma and the anti-glioma drugs that may target GINS4 screened by CMap analysis. Moreover, we further explored the influence of the GINS4 expression on the immune microenvironment of glioma patients through the TIMER database.

Results

Our results suggested that GINS4 was elevated in glioma, and the overexpression of GINS4 was connected with a vast number of clinical features. The next, GINS4 as an independent prognostic factor, which can result in an unfavorable prognosis of glioma. Once more, GINS4 may be participating in the oncogenesis of glioma through JAK-STAT signaling pathways, etc. 6-thioguanine, Doxazosin, and Emetine had potential value in the clinical application of drugs targeting GINS4. Finally, the expression exhibited a close relationship with some immune cells, especially Dendritic cells.

Conclusion

GINS4 is an independent prognostic factor that led to a poor prognosis of glioma. The present study revealed the probable underlying molecular mechanisms of GINS4 in glioma and provided a potential target for improving the prognosis of glioma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00378-0.

Inhibition of BUB1 suppresses tumorigenesis of osteosarcoma via blocking of PI3K/Akt and ERK pathways

Osteosarcoma (OS) is a primary malignant bone tumour that mainly affects teenagers, with patients displaying poor prognosis. Budding uninhibited by benzimidazoles 1 (BUB1), a type of serine/threonine kinase that is linked to pro-tumorigenic phenomena, has not been well studied in OS. Hence, this study aimed to explore the role of BUB1 in OS. The expression of BUB1 in OS specimens and cell lines was assessed using immunohistochemistry and Western blot analysis. Univariate and multivariate analyses were applied to evaluate the impact of BUB1 on patient survival. Cell counting kit-8, wound-healing and Transwell assays, as well as flow cytometry, were used to investigate the influence of BUB1 inhibition on OS in vitro. Moreover, a tumour xenograft model was established to investigate the in vivo effect of BUB1 inhibition on OS tumour growth. Results showed that BUB1 was overexpressed in OS specimens and cell lines. Furthermore, BUB1 overexpression was closely associated with the poor clinical outcomes of patients with OS. Inhibition of BUB1 markedly suppressed cell proliferation and tumour growth, cell migration, invasion and induced cell apoptosis of OS by blocking the PI3K/Akt and ERK signalling pathways. Thus, our study suggested that overexpression of BUB1 protein contributed to poor survival of OS patients and that inhibition of BUB1 resulted in considerable anti-tumour activity associated with proliferation, migration, invasion and apoptosis of OS.

Identification and characterization of N6-methyladenosine modification of circRNAs in glioblastoma

This research systematically profiled the global N6‐methyladenosine modification pattern of circular RNAs (circRNAs) in glioblastoma (GBM). Based on RNA methylation sequencing (MeRIP sequencing or N6‐methyladenosine sequencing) and RNA sequencing, we described the N6‐methyladenosine modification status and gene expression of circRNAs in GBM and normal brain tissues. N6‐methyladenosine–related circRNAs were immunoprecipitated and validated by real‐time quantitative PCR. Bioinformatics analysis and related screening were carried out. Compared with those of the NC group, the circRNAs from GBM exhibited 1370 new N6‐methyladenosine peaks and 1322 missing N6‐methyladenosine peaks. Among the loci associated with altered N6‐methyladenosine peaks, 1298 were up‐regulated and 1905 were down‐regulated. The N6‐methyladenosine level tended to be positively correlated with circRNA expression. Bioinformatics analysis was used to predict the biological function of N6‐methyladenosine–modified circRNAs and the corresponding signalling pathways. In addition, through PCR validation combined with clinical data mining, we identified five molecules of interest (BUB1, C1S, DTHD1, F13A1 and NDC80) that could be initial candidates for further study of the function and mechanism of N6‐methyladenosine–mediated GBM development. In conclusion, our findings demonstrated the N6‐methyladenosine modification pattern of circRNAs in human GBM, revealing the possible roles of N6‐methyladenosine–mediated novel noncoding RNAs in the origin and progression of GBM.

Expression and prognosis analyses of BUB1, BUB1B and BUB3 in human sarcoma

Budding Uninhibited By Benzimidazoles are a group of genes encoding proteins that play central roles in spindle checkpoint during mitosis. Improper mitosis may lead to aneuploidy which is found in many types of tumors. As a key mediator in mitosis, the dysregulated expression of BUBs has been proven to be highly associated with various malignancies, such as leukemia, gastric cancer, breast cancer, and liver cancer. However, bioinformatic analysis has not been applied to explore the role of the BUBs in sarcomas. Herein, we investigate the transcriptional and survival data of BUBs in patients with sarcomas using Oncomine, Gene Expression Profiling Interactive Analysis, Cancer Cell Line Encyclopedia, Kaplan-Meier Plotter, LinkedOmics, and the Database for Annotation, Visualization and Integrated Discovery. We found that the expression levels of BUB1, BUB1B and BUB3 were higher in sarcoma samples and cell lines than in normal controls. Survival analysis revealed that the higher expression levels of BUB1, BUB1B and BUB3 were associated with lower overall and disease-free survival in patients with sarcomas. This study implies that BUB1, BUB1B and BUB3 are potential treatment targets for patients with sarcomas and are new biomarkers for the prognosis of sarcomas.

Musashi1 Contribution to Glioblastoma Development via Regulation of a Network of DNA Replication, Cell Cycle and Division Genes

RNA-binding proteins (RBPs) function as master regulators of gene expression. Alterations in their levels are often observed in tumors with numerous oncogenic RBPs identified in recent years. Musashi1 (Msi1) is an RBP and stem cell gene that controls the balance between self-renewal and differentiation. High Msi1 levels have been observed in multiple tumors including glioblastoma and are often associated with poor patient outcomes and tumor growth. A comprehensive genomic analysis identified a network of cell cycle/division and DNA replication genes and established these processes as Msi1's core regulatory functions in glioblastoma. Msi1 controls this gene network via two mechanisms: direct interaction and indirect regulation mediated by the transcription factors E2F2 and E2F8. Moreover, glioblastoma lines with Msi1 knockout (KO) displayed increased sensitivity to cell cycle and DNA replication inhibitors. Our results suggest that a drug combination strategy (Msi1 + cell cycle/DNA replication inhibitors) could be a viable route to treat glioblastoma.

Mitotic kinases as drivers of the epithelial-to-mesenchymal transition and as therapeutic targets against breast cancers

Biological therapies against breast cancer patients with tumors positive for the estrogen and progesterone hormone receptors and Her2 amplification have greatly improved their survival. However, to date, there are no effective biological therapies against breast cancers that lack these three receptors or triple-negative breast cancers (TNBC). TNBC correlates with poor survival, in part because they relapse following chemo- and radio-therapies. TNBC is intrinsically aggressive since they have high mitotic indexes and tend to metastasize to the central nervous system. TNBCs are more likely to display centrosome amplification, an abnormal phenotype that results in defective mitotic spindles and abnormal cytokinesis, which culminate in aneuploidy and chromosome instability (known causes of tumor initiation and chemo-resistance). Besides their known role in cell cycle control, mitotic kinases have been also studied in different types of cancer including breast, especially in the context of epithelial-to-mesenchymal transition (EMT). EMT is a cellular process characterized by the loss of cell polarity, reorganization of the cytoskeleton, and signaling reprogramming (upregulation of mesenchymal genes and downregulation of epithelial genes). Previously, we and others have shown the effects of mitotic kinases like Nek2 and Mps1 (TTK) on EMT. In this review, we focus on Aurora A, Aurora B, Bub1, and highly expressed in cancer (Hec1) as novel targets for therapeutic interventions in breast cancer and their effects on EMT. We highlight the established relationships and interactions of these and other mitotic kinases, clinical trial studies involving mitotic kinases, and the importance that represents to develop drugs against these proteins as potential targets in the primary care therapy for TNBC.

Screening and Identification of Key Common and Specific Genes and Their Prognostic Roles in Different Molecular Subtypes of Breast Cancer

Breast cancer is one of the most common cancers. Although the present molecular classification improves the treatment effect and prognosis of breast cancer, the heterogeneity of the molecular subtype remains very complex, and the applicability and effectiveness of treatment methods are still limited leading to poorer patient prognosis than expected. Further identification of more refined molecular typing based on gene expression profile will yield better understanding of the heterogeneity, improving treatment effects and prolonging prognosis of patients. Here, we downloaded the mRNA expression profiles and corresponding clinical data of patients with breast cancer from public databases and performed typical molecular typing using PAM50 (Prediction Analysis of Microarray 50) method. Comparative analyses were performed to screen the common and specific differentially expressed genes (DEGs) between cancer and corresponding para-cancerous tissues in each breast cancer subtype. The GO and KEGG analyses of the DEGs were performed to enrich the common and specific functional progress and signaling pathway involved in breast cancer subtypes. A total of 38 key common and specific DEGs were identified and selected based on the validated results, GO/KEGG enrichments, and the priority of expression, including four common DEGs and 34 specific DEGs in different subtypes. The prognostic value of these key common and specific DEGs was further analyzed to obtain useful potential markers in clinic. Finally, the potential roles and the specific prognostic values of the common and specific DEGs were speculated and summarized in total breast cancer and different subtype breast cancer based on the results of these analyses. The findings of our study provide the basis of more refined molecular typing of breast cancer, potential new therapeutic targets and prognostic markers for different breast cancer subtypes

Identification and Analysis of Potential Key Genes Associated With Hepatocellular Carcinoma Based on Integrated Bioinformatics Methods

BACKGROUND

Hepatocellular carcinoma (HCC) is a type of primary liver tumor with poor prognosis and high mortality, and its molecular mechanism remains incompletely understood. This study aimed to use bioinformatics technology to identify differentially expressed genes (DEGs) in HCC pathogenesis, hoping to identify novel biomarkers or potential therapeutic targets for HCC research.

METHODS

The bioinformatics analysis of our research mostly involved the following two datasets: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). First, we screened DEGs based on the R packages (limma and edgeR). Using the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were carried out. Next, the protein-protein interaction (PPI) network of the DEGs was built in the STRING database. Then, hub genes were screened through the cytoHubba plug-in, followed by verification using the GEPIA and Oncomine databases. We demonstrated differences in levels of the protein in hub genes using the Human Protein Atlas (HPA) database. Finally, the hub genes prognostic values were analyzed by the GEPIA database. Additionally, using the Comparative Toxicogenomics Database (CTD), we constructed the drug-gene interaction network.

RESULTS

We ended up with 763 DEGs, including 247 upregulated and 516 downregulated DEGs, that were mainly enriched in the epoxygenase P450 pathway, oxidation-reduction process, and metabolism-related pathways. Through the constructed PPI network, it can be concluded that the P53 signaling pathway and the cell cycle are the most obvious in module analysis. From the PPI, we filtered out eight hub genes, and these genes were significantly upregulated in HCC samples, findings consistent with the expression validation results. Additionally, survival analysis showed that high level gene expression of CDC20, CDK1, MAD2L1, BUB1, BUB1B, CCNB1, and CCNA2 were connected with the poor overall survival of HCC patients. Toxicogenomics analysis showed that only topotecan, oxaliplatin, and azathioprine could reduce the gene expression levels of all seven hub genes.

CONCLUSION

The present study screened out the key genes and pathways that were related to HCC pathogenesis, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of HCC.

Identification of cancer stem cell-related biomarkers in intestinal-type and diffuse-type gastric cancer by stemness index and weighted correlation network analysis

Background

Cancer stem cells (CSCs) play an important role in drug resistance, recurrence, and metastasis of tumors. Considering the heterogeneity of tumors, this study aimed to explore the key genes regulating stem cells in intestinal-type and diffuse-type gastric cancer.

Methods

RNA-seq data and related clinical information were downloaded from The Cancer Genome Atlas (TCGA). WGCNA was used to clustered differentially expressed genes with similar expression profiles to form modules. Furtherly, based on the mRNA expression-based stemness index (mRNAsi), significant modules and key genes were identified. Next, the expression of key genes was further verified by the Oncomine database.

Results

MRNAsi scores of GC were significantly higher than that of normal tissue. Additionally, mRNAsi scores of intestinal-type GC (IGC) were significantly higher than that of diffuse-type GC (DGC). WGCNA showed that the blue module of IGC and the brown module of DGC were both the most significantly associated with mRNAsi. We screened out 16 and 43 key genes for IGC and DGC and found that these genes were closely related, respectively. Functional analysis showed the relationship between the key genes confirmed in the Oncomine database and the fate of cells.

Conclusions

In this study, 16 and 43 genes related to the characteristics of CSCs were identified in IGC and DGC, respectively. These genes were both associated with cell cycle, which could serve as therapeutic targets for the inhibition of stem cells from both types of GC.

Identification of the potential biomarkers in patients with glioma: a weighted gene co-expression network analysis

Glioma is the most common brain tumor with high mortality. However, there are still challenges for the timely and accurate diagnosis and effective treatment of the tumor. One hundred and twenty-one samples with grades II, III and IV from the Gene Expression Omnibus database were used to construct gene co-expression networks to identify hub modules closely related to glioma grade, and performed pathway enrichment analysis on genes from significant modules. In gene co-expression network constructed by 2345 differentially expressed genes from 121 gene expression profiles for glioma, we identified the black and blue modules that associated with grading. The module preservation analysis based on 118 samples indicates that the two modules were replicable. Enrichment analysis showed that the extracellular matrix genes were enriched for blue module, while cell division genes were enriched for black module. According to survival analysis, 21 hub genes were significantly up-regulated and one gene was significantly down-regulated. What’s more, IKBIP, SEC24D, and FAM46A are the genes with little attention among the 22 hub genes. In this study, IKBIP, SEC24D, and FAM46A related to glioma were mentioned for the first time to the current knowledge, which might provide a new idea for us to study the disease in the future. IKBIP, SEC24D and FAM46A among the 22 hub genes identified that are related to the malignancy degree of glioma might be used as new biomarkers to improve the diagnosis, treatment and prognosis of glioma.

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.

Identification of drug targets and potential molecular mechanisms for Wantong Jingu Tablet extract in treatment of rheumatoid arthritis: bioinformatics analysis of fibroblast-like synoviocytes

Background

Rheumatoid arthritis-fibroblast-like synoviocytes (RA-FLSs) play important roles in pathogenesis of rheumatoid arthritis (RA). Wantong Jingu Tablet (WJT), a mixture of traditional Chinese medicine, is a potentially effective therapy for RA, but its underlying mechanism is unclear. In this study, we explore the effects of WJT on human RA-FLSs and the underlying molecular mechanism.

Methods

The major components of WJT were determined using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS). Cell proliferative ability was evaluated by CCK-8, colony formation assay, and EdU incorporation assay. Cell apoptotic capacity was examined by caspase-3 and caspase-9 activity test. Protein levels of Bax and Bcl-2 were investigated by western blotting. High-throughput sequencing and bioinformatics analysis were conducted to screen and identify targeted genes, followed by identification by qRT-PCR and western blotting.

Results

In this study, we have identified 346 compounds in WJT. Our results showed that WJT inhibited the RA-FLSs proliferation, and promoted apoptosis in a dose- and time-dependent manner. More importantly, 184 differentially expressed genes (DEGs) has been screened after WJT treatment based on DEGSeq2 and 278 DEGs was identified by DEGSeq2 combined with WGCNA. Then, 10 hub genes were identified based on two different analyses, while the expression levels of only SMC3, THOC1, BUB1, and STAG2 were decreased after WJT treatment, which was identical to the sequencing profiles.

Conclusions

WJT exerted its anti-proliferation and pro-apoptosis effects possibly through suppressing the expression of SMC3, THOC1, BUB1, and STAG2 in RA-FLSs. Thus, therapeutics targeting these genes may be a promising strategy for rescuing RA.

Identification of Glioma Cancer Stem Cell Characteristics Based on Weighted Gene Prognosis Module Co-Expression Network Analysis of Transcriptome Data Stemness Indices

Glioma is the most common primary brain tumor in humans and the most deadly. Stem cells, which are characterized by therapeutic resistance and self-renewal, play a critical role in glioma, and therefore the identification of stem cell-related genes in glioma is important. In this study, we collected and evaluated the epigenetically regulated-mRNA expression-based stemness index (EREG-mRNAsi) of The Cancer Genome Atlas (TCGA, http://www.ncbi.nlm.nih.gov/ ) for glioma patient samples, corrected through tumor purity. After EREG-mRNAsi correction, glioma pathological grade and survival were analyzed. The differentially expressed gene (DEG) co-expression network was constructed by weighted gene co-expression network analysis (WGCNA) in TCGA glioma samples to find modules of interest and key genes. Gene ontology (GO) and pathway-enrichment analysis were performed to identify the function of significant genetic modules. Protein-protein interaction (PPI) and co-expression network analysis of key genes was performed for further analysis. In this experiment, we found that corrected EREG-mRNAsi was significantly up-regulated in glioma samples and increased with glioma grade, with G4 having the highest stemness index. Patients with higher corrected EREG-mRNAsi scores had worse overall survival. Fifty-one DEGs in the brown gene module were found to be positively related to EREG-mRNAsi via WGCNA. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that chromosome segregation and cell cycle molecular function were the major functions in key DEGs. Among these key DEGs, BUB1 showed high connectivity and co-expression, and also high connectivity in PPI. Fifty-one key genes were verified to play a critical role in glioma stem cells. These genes may serve as primary therapeutic targets to inhibit the activity of glioma stem cells.

SKA1/2/3 serves as a biomarker for poor prognosis in human lung adenocarcinoma

Background

Spindle and kinetochore associated complex subunit 1/2/3 (SKA1/2/3), which stabilized spindle microtubules attaching to kinetochore (KT) in the middle stage of mitosis, were dysregulated, and closely related to prognosis in several malignant tumors. Nevertheless, the potential clinical value of SKA1/2/3, especially in terms of prognosis and development of NSCLC, had not been fully elucidated.

Methods

ONCOMINE, GEPIA, UALCAN, TCGA, STRING and other databases were used to analyze the expression of SKA1/2/3 in patients with lung adenocarcinoma (LUAD) and its clinical value, and to explore the possible regulatory mechanism of SKA in the occurrence and development of LUAD.

Results

In patients with LUAD, SKA1/2/3 mRNA expression level was significantly up-regulated, and AUC was 0.9558, 0.7034 and 0.9775, respectively. Increased SKA 1/2/3 expression was associated with smoking, tissue typing, and poor prognosis in LUAD patients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) showed that SKA1/2/3 was mainly enriched in DNA replication, cell cycle, homologous recombination, p53 signaling pathway, etc. Hub genes in protein-protein interactions are CDK1, BUB1, CCNA2, CDC20, CCNB2, CCNB1, BUB1B, AURKB, TOP2A and MAD2L1. Hub gene expression in LUAD is increased, and its increased expression is related to poor prognosis of LUAD patients. Finally, the expression of SKA1/2/3 and its correlation with clinicopathological features were verified in 30 clinical LUAD samples.

Conclusions

SKA1/2/3 may serve as a potential prognostic biomarker and target for LUAD. In addition, SKA 1/2/3 may affect the prognosis of LUAD through DNA replication, cell cycle, homologous recombination and p53 signaling pathway.

Bioinformatical Analysis of Gene Expression Omnibus Database Associates TAF7/CCNB1, TAF7/CCNA2, and GTF2E2/CDC20 Pathways with Glioblastoma Development and Prognosis

OBJECTIVE

This study bioinformatically analyzed aberrant genes and pathways for associations with glioblastoma development and prognosis.

METHODS

The Gene Expression Omnibus (GEO) database was searched and 4 GEO datasets (GSE4290, GSE50161, GSE116520, and GSE90598) were retrieved for limma and RobustRankAggreg package analyses of differentially expressed genes (DEGs) between glioblastoma and normal brain tissues. Functional enrichment analysis was conducted for the main biological functions of these DEGs, whereas the hub genes were identified using the protein-protein interaction network and confirmed for transcriptional and translational levels using the Cancer Genome Atlas, the Genotype-Tissue Expression, and the Human Protein Atlas data. The prognostic values of these hub genes were analyzed using the Chinese Glioma Genome Atlas. Their transcriptional factor regulation network was constructed to assess the roles in glioblastoma development and progression.

RESULTS

A total of 473 DEGs (182 upregulated and 291 downregulated) were identified and the hub genes (including CCNB1, CDC20, CCNB2, BUB1, and CCNA2) were shown in module 1 and enriched in the cell cycle or p53 signaling pathway. The highly expressed CCNB1, CDC20, BUB1, and CCNA2 in patients with glioblastoma were associated with poor overall survival, whereas TAF7 could upregulate expression of CCNB1 and CCNA2 and GTF2E2 could upregulate CDC20 expression in glioblastoma.

CONCLUSIONS

This study showed several DEGs in glioblastoma, and aberrant expression of their hub genes was associated with glioblastoma pathogenesis and poor prognosis, especially the signaling axes of TAF7/CCNB1, TAF7/CCNA2, and GTF2E2/CDC20.