The FOXM1/BUB1B signaling pathway is essential for the tumorigenicity and radioresistance of glioblastoma

(-)-Epicatechin regulates the resistance of lung adenocarcinoma cells to radiotherapy through the downregulation of FOXM1

Radioresistance, particularly as manifested by cancer stem cells (CSCs), is the most common reason for the failure of cancer radiotherapy. It is essential for effective radiotherapy to inhibit cancer cell stemness. Research indicates that (-)-epicatechin (EC) enhances the radiosensitivity of non-small cell lung cancer (NSCLC); however, its influence on cell stemness in lung adenocarcinoma (LUAD) resistant to radiotherapy is still not well understood. In this study, radioresistant cell lines A549R and H1299R were constructed by repeatedly irradiating A549 and H1299 cells with gradient doses of X-rays. CCK-8, cell cloning, flow cytometry, RT-qPCR, Western blot, sphere formation detection, and other methods were used for experimental exploration. This study revealed that the radioresistance of LUAD cells was related to their stemness. By inhibiting KLF4, SOX2, CD133, and ALDH1A1 expression, EC treatment increased radiosensitivity and reduced cell sphere formation. Also, FOXM1 expression was upregulated in LUAD and in radioresistant LUAD cells. Knocking down FOXM1 inhibited the stemness of radioresistant LUAD cells. Mechanistically, EC inhibited radiotherapy-resistant LUAD cell stemness by downregulating FOXM1 expression, thereby increasing radiosensitivity. In summary, our study revealed that EC inhibited radiotherapy resistance in LUAD cells through downregulating FOXM1, and it provides a theoretical framework for treating LUAD clinically.

BUB1b impairs chemotherapy sensitivity via resistance to ferroptosis in lung adenocarcinoma

BUB1 mitotic checkpoint serine/threonine kinase B (BUB1b) has been unequivocally identified as an oncogene in various cancers. However, the potential mechanism by which BUB1b orchestrates the progression of lung adenocarcinoma (LUAD) remains unclear. Here we found that both the transcript and protein levels of BUB1b were dramatically upregulated in tumor tissues and contributed to the dismal prognosis of LUAD patients. Moreover, gain- and loss-of-function assays, conducted both in vitro and in vivo, confirmed that BUB1b enhanced the viability of LUAD cells. Mechanistically, BUB1b forms a complex with OTUD3 and NRF2 and stabilizes the downstream NRF2 signaling pathway to facilitate insensitivity to ferroptosis and chemotherapy. In BALB/c nude mice bearing subcutaneous tumors that overexpress BUB1b, a combined strategy of ML385 targeting and chemotherapy achieved synergistic effects, inhibiting tumor growth and obviously improving survival. Taken together our study uncovered the underlying mechanism by which BUB1b promotes the progression of LUAD and proposed a novel strategy to enhance the efficacy of chemotherapy.

Anti-tumor target screening of sea cucumber saponin Frondoside A: a bioinformatics and molecular docking analysis

Cancer remains the leading cause of death worldwide. In spite of significant advances in targeted and immunotherapeutic approaches, clinical outcomes for cancer remain poor. The aim of the present study was to investigate the potential mechanisms and therapeutic targets of Frondoside A for the treatment of liver, pancreatic, and bladder cancers. The data presented in our study demonstrated that Frondoside A reduced the viability and migration of HepG2, Panc02, and UM-UC-3 cancer cell in vitro. Moreover, we utilized the GEO database to screen and identify for differentially expressed genes (DEGs) in liver, pancreatic, and bladder cancers, which resulted in the identification of 714, 357, and 101 DEGs, respectively. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation were performed using the Metascape database for DEGs that were significantly associated with cancer development. The protein-protein interaction (PPI) networks of the identified DEGs in liver, pancreatic, and bladder cancers were analyzed using Cytoscape 3.9.0 software, and subsequently identified potential key genes that were associated with these networks. Subsequently, their prognostic values were assessed by gene expression level analysis and Kaplan-Meier survival analysis (GEPIA). Furthermore, we utilized TIMER 2.0 to investigate the correlation between the expression of the identified key gene and cancer immune infiltration. Finally, molecular docking simulations were performed to assess the affinity of Frondoside A and key genes. Our results showed a significant correlation between these DEGs and cancer progression. Combined, these analyses revealed that Frondoside A involves in the regulation of multiple pathways, such as drug metabolism, cell cycle in liver cancer by inhibiting the expression of CDK1, TOP2A, CDC20, and KIF20A, and regulates protein digestion and absorption, receptor interaction in pancreatic cancer by down-regulation of ASPM, TOP2A, DLGAP5, TPX2, KIF23, MELK, LAMA3, and ANLN. While in bladder cancer, Frondoside A regulates muscle contraction, complement and coagulation cascade by increase FLNC expression. In conclusion, the present study offers valuable insights into the molecular mechanism underlying the anticancer effects of Frondoside A, and suggests that Frondoside A can be used as a functional food supplement or further developed as a natural anti-cancer drug.

Forkhead box transcription factors (FOXOs and FOXM1) in glioma: from molecular mechanisms to therapeutics

Glioma is the most aggressive and malignant type of primary brain tumor, comprises the majority of central nervous system deaths, and is categorized into different subgroups according to its histological characteristics, including astrocytomas, oligodendrogliomas, glioblastoma multiforme (GBM), and mixed tumors. The forkhead box (FOX) transcription factors comprise a collection of proteins that play various roles in numerous complex molecular cascades and have been discovered to be differentially expressed in distinct glioma subtypes. FOXM1 and FOXOs have been recognized as crucial transcription factors in tumor cells, including glioma cells. Accumulating data indicates that FOXM1 acts as an oncogene in various types of cancers, and a significant part of studies has investigated its function in glioma. Although recent studies considered FOXO subgroups as tumor suppressors, there are pieces of evidence that they may have an oncogenic role. This review will discuss the subtle functions of FOXOs and FOXM1 in gliomas, dissecting their regulatory network with other proteins, microRNAs and their role in glioma progression, including stem cell differentiation and therapy resistance/sensitivity, alongside highlighting recent pharmacological progress for modulating their expression.

Unique progerin C-terminal peptide ameliorates Hutchinson-Gilford progeria syndrome phenotype by rescuing BUBR1

An accumulating body of evidence indicates an association between mitotic defects and the aging process in Hutchinson-Gilford progeria syndrome (HGPS), which is a premature aging disease caused by progerin accumulation. Here, we found that BUBR1, a core component of the spindle assembly checkpoint, was downregulated during HGPS cellular senescence. The remaining BUBR1 was anchored to the nuclear membrane by binding with the C terminus of progerin, thus further limiting the function of BUBR1. Based on this, we established a unique progerin C-terminal peptide (UPCP) that effectively blocked the binding of progerin and BUBR1 and enhanced the expression of BUBR1 by interfering with the interaction between PTBP1 and progerin. Finally, UPCP significantly inhibited HGPS cellular senescence and ameliorated progeroid phenotypes, extending the lifespan of Lmna^G609G/G609G mice. Our findings reveal an essential role for the progerin-PTBP1-BUBR1 axis in HGPS. Therapeutics designed around UPCP may be a beneficial strategy for HGPS treatment.

Clinical value and potential mechanisms of BUB1B up-regulation in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) has insidious onset, late clinical diagnosis and high recurrence rate, which leads to poor quality of patient life. Therefore, it is necessary to further explore the pathogenesis and therapy targets of NPC. BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) was found to be up-regulated in a variety of cancers, but only two previous study showed that BUB1B was overexpressed in NPC and the sample size was small. The clinical role of BUB1B expression and its underlying mechanism in NPC require more in-depth research. Immunohistochemical samples and public RNA-seq data indicated that BUB1B protein and mRNA expression levels were up-regulated in NPC, and summary receiver operating characteristic curve indicated that BUB1B expression level had a strong ability to distinguish NPC tissues from non-NPC tissues. Gene ontology and Kyoto Encyclopedia of genes and genomes were performed and revealed that BUB1B and its related genes were mainly involved in cell cycle and DNA replication. Protein- Protein Interaction were built to interpret the BUB1B molecular mechanism. Histone deacetylase 2 (HDAC2) could be the upstream regulation factor of BUB1B, which was verified by Chromatin Immunoprecipitation Sequencing samples. In summary, BUB1B was highly expressed in NPC, and HDAC2 may affect cell cycle by regulating BUB1B to promote cancer progression.

A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing

Background: Glioma is the most fatal neoplasm among the primary intracranial cancers. Necroptosis, a form of programmed cell death, is correlated with tumor progression and immune response. But, the role of necroptosis-related genes (NRGs) in glioma has not been well-uncovered.

Methods: Single-cell and bulk RNA sequencing data, obtained from publicly accessed databases, were used to establish a necroptosis-related gene signature for predicting the prognosis of glioma patients. Multiple bioinformatics algorithms were conducted to evaluate the efficacy of the signature. The relative mRNA level of each signature gene was validated by quantitative real-time reverse transcription PCR (qRT-PCR) in glioma cell lines compared to human astrocytes.

Results: In this predicted prognosis model, patients with a high risk score showed a shorter overall survival, which was verified in the testing cohorts. The signature risk score was positively related with immune cell infiltration and some immune check points, such as CD276 (B7-H3), CD152 (CTLA-4), CD223 (LAG-3), and CD274 (PD-L1). Single-cell RNA sequencing analysis confirmed that the glioma microenvironment consists of various immune cells with different markers. The eight NRGs of the signature were detected to be expressed in several immune cells. QRT-PCR results verified that all the eight signature genes were differentially expressed between human astrocytes and glioma cells.

Conclusion: The eight NRGs correlate with the immune microenvironment of glioma according to our bioinformatics analysis. This necroptosis-related gene signature may evaluate the precise methodology of predicting prognosis of glioma and provide a novel thought in glioma investigation.

Bioinformatics Analysis Reveals FOXM1/BUB1B Signaling Pathway as a Key Target of Neosetophomone B in Human Leukemic Cells: A Gene Network-Based Microarray Analysis

Abnormal expression of Forkhead box protein M1 (FOXM1) and serine/threonine kinase Budding uninhibited by benzimidazoles 1 (BUB1B) contributes to the development and progression of several cancers, including chronic myelogenous leukemia (CML). However, the molecular mechanism of the FOXM1/BUB1B regulatory network and the role of Neosetophomone-B (NSP-B) in leukemia remains unclear. NSP-B, a meroterpenoid fungal secondary metabolite, possesses anticancer potential in human leukemic cells lines; however, the underlying mechanism has not been elucidated. The present study aimed to explore the role of NSP-B on FOXM1/BUB1B signaling and the underlying molecular mechanism of apoptosis induction in leukemic cells. We performed gene expression profiling of NSP-B-treated and untreated leukemic cells to search for differentially expressed genes (DEGs). Interestingly BUB1B was found to be significantly downregulated (logFC -2.60, adjusted p = 0.001) in the treated cell line with the highest connectivity score among cancer genes. Analysis of TCGA data revealed overexpression of BUB1B compared to normal in most cancers and overexpression was associated with poor prognosis. BUB1B also showed a highly significant positive correlation with FOXM1 in all the TCGA cancer types. We used human leukemic cell lines (K562 and U937) as an in vitro study model to validate our findings. We found that NSP-B treatment of leukemic cells suppressed the expression of FOXM1 and BUB1B in a dose-dependent manner. In addition, NSP-B also resulted in the downregulation of FOXM1-regulated genes such as Aurora kinase A, Aurora kinase B, CDK4, and CDK6. Suppression of FOXM1 either by siRNA or NSP-B reduced BUB1B expression and enhanced cell survival inhibition and induction of apoptosis. Interestingly combination treatment of thiostrepton and NSP-B suppressed of cell viability and inducted apoptosis in leukemic cells via enhancing the activation of caspase-3 and caspase-8 compared with single-agent treatment. These results demonstrate the important role of the FOXM1/BUB1B pathway in leukemia and thus a potential therapeutic target.

Ketogenic Metabolic Therapy for Glioma

Purpose: This study describes a retrospective case series of patients with glioma who received ketogenic metabolic therapy through dietary adherence and intermittent fasting.

Methods: A retrospective chart review of a single surgeon’s clinic records was performed to identify patients who maintained nutritional ketosis for at least four months between January 2015 and October 2020.

Results: Sixteen patients who met the inclusion criteria constituted a heterogeneous population of patients with diagnoses including eight World Health Organization (WHO) grade IV gliomas (seven glioblastoma, one gliosarcoma), seven WHO grade III gliomas (three oligodendroglioma, four astrocytoma), and one WHO grade II oligodendroglioma. IDH1 mutation status was present for 12 patients, and MGMT methylation status was present for eight patients. The mean (standard deviation [SD]) duration of ketogenic metabolic therapy was 20.6 (13.8) months. The Response Assessment in Neuro-oncology Criteria was applied during the ketogenic metabolic therapy interval, indicating a complete response in eight patients and partial response in eight patients. The mean (SD) progression-free survival while patients maintained ketogenic metabolic therapy was 20.0 (14.4) months.

Conclusion: Ketogenic metabolic therapy appears to convey a survival advantage within this patient series, which highlights the possibility that this therapy, when strictly applied, can augment the standard of care. Further exploration of this modality in a prospective series is warranted to formally explore this therapy.

TRIM56 Reduces Radiosensitization of Human Glioblastoma by Regulating FOXM1-Mediated DNA Repair

Recurrent glioblastoma is characterized by resistance to radiotherapy or chemotherapy. In this study, we investigated the role of TRIM56 in radiosensitization and its potential underlying molecular mechanism. TRIM56 expression levels were measured in glioblastoma tissues and cell lines by immunohistochemical staining, western blot, and qRT-PCR. MTT assay, colony formation assay, and TUNEL assay were used to investigate the effect of TRIM56 on cell viability, cell proliferation, and cell apoptosis. Co-immunoprecipitation was used to clarify the interaction between TRIM56 and FOXM1. Finally, tumor xenograft experiments were performed to analyze the effect of TRIM56 on tumor growth in vivo. The expression of TRIM56 was significantly increased in glioblastoma tissues and cell lines and its expression was associated with poor prognosis of patients with glioblastoma. Moreover, TRIM56 reduced the radiosensitivity of glioblastoma cells and promoted DNA repairment. Mechanistically, TRIM56 promoted FOXM1 protein level, enhanced the stability of FOXM1 by de-ubiquitination, and promoted DNA damage repair through FOXM1 in glioblastoma cells. TRIM56 could reduce the radiosensitivity of glioblastoma in vivo. TRIM56 may suppress the radiosensitization of human glioblastoma by regulating FOXM1-mediated DNA repair. Targeting the TRIM56 may be an effective method to reverse radiotherapy-resistant in glioblastoma recurrent.

Aberrant Expression of BUB1B Contributes to the Progression of Thyroid Carcinoma and Predicts Poor Outcomes for Patients

Objective: This study aimed to clarify the function and potential mechanism of BUB1B in THCA.

Methods: Expression of BUB1B in THCA was firstly determined, and its important prognostic value was then demonstrated. The potential mechanism was initially predicted by KEGG analysis. To explore the specific function of BUB1B in THCA, we used lentivirus infection to knock down the BUB1B, and then performed flow cytometry, colony formation, transwell, and wound-healing assays. Related protein expression was detected through western blotting. Additionally, we predicted the BUB1B-regulated pathways involved in THCA by GSEA analysis.

Results: BUB1B expression was highly increased in THCA tissues relative to normal controls. We further found that BUB1B was essential for tumor cell proliferation, and BUB1B high expression predicted a shorter PFS time of THCA patients. More importantly, Cox regression determined the BUB1B as an independent prognostic factor for PFS in THCA. BUB1B was initially found to participate in the cell cycle pathway from KEGG analysis. Unexpectedly, we did not detect the disturbing effect on the cell cycle distribution of THCA cells with BUB1B knockdown. But, BUB1B knockdown inhibited the proliferation, invasion, and migration of THCA cells, as well as increased apoptotic cells, and the results were further confirmed by western blotting. Through GSEA analysis, we predicted a positive correlation between BUB1B and metastasis-related pathways such as mTOR and NF-kappa B signaling pathways.

Conclusions: Present study identified BUB1B as a promising clinical prognostic factor in THCA, as well as a potential novel therapeutic target for cancer treatment.

CircPIK3C2A Facilitates the Progression of Glioblastoma via Targeting miR-877-5p/FOXM1 Axis

Glioblastoma is a rare yet lethal type of tumor that poses a crucible for the medical profession, owing to its rapid proliferation and invasion resulting in poor prognosis. Circular RNAs (circRNAs), a subclass of regulatory RNAs, are implicated in the regulation of cancerous progression. This study aims to investigate the roles and underlying mechanism of circPIK3C2A in regulating proliferation and invasion of glioblastoma. qRT-PCR assays showed that the expression level of circPIK3C2A was aberrantly higher in glioblastoma cell lines, in comparison with that in normal glia cells. The ectopic expression of circPIK3C2A promoted the proliferation, invasion and clonal formation of glioblastoma cells, while circPIK3C2A loss-of-function exerted exactly the opposite biological effects on the cells. The construction of subcutaneous xenograft tumor model in nude mice indicated that circPIK3C2A loss-of-function effectively diminished tumor load in vivo and prolonged the survival time of tumor-bearing animals. Luciferase reporter assay confirmed the interaction among circPIK3C2A/miR-877-5p and FOXM1. CircPIK3C2A function as competitive endogenous RNA via sponging miR-877-5p through certain binding sites, thereby modulating the expression of FOXM1. Our results collectively indicate that circPIK3C2A functions as ceRNA by mediating miR-877-5p/FOXM1 axis, providing a novel perspective of applying CircPIK3C2A in the clinical intervention of glioblastoma in the future.

Weighted Gene Correlation Network Analysis Identifies Specific Functional Modules and Genes in Esophageal Cancer

Objective

Esophageal cancer (ESCA) is one of the most aggressive malignancies globally with an undesirable five-year survival rate. Here, this study was conducted for determining specific functional genes linked with ESCA initiation and progression.

Methods

Gene expression profiling of ESCA was curated from TCGA (containing 160 ESCA and 11 nontumor specimens) and GSE38129 (30 paired ESCA and nontumor tissues) datasets. Differential expression analysis was conducted between ESCA and nontumor tissues with adjusted p value <0.05 and |log2fold-change|>1. Weighted gene coexpression network analysis (WGCNA) was conducted for determining the ESCA-specific coexpression modules and genes. Thereafter, ESCA-specific differentially expressed genes (DEGs) were intersected. Functional enrichment analysis was then presented with clusterProfiler package. Protein-protein interaction was conducted, and hub genes were determined. Association of hub genes with pathological staging was evaluated, and survival analysis was presented among ESCA patients.

Results

This study determined 91 ESCA-specific DEGs following intersection of DEGs and ESCA-specific genes in TCGA and GSE38129 datasets. They were remarkably linked to cell cycle progression and carcinogenic pathways like the p53 signaling pathway, cellular senescence, and apoptosis. Ten ESCA-specific hub genes were determined, containing ASPM, BUB1B, CCNA2, CDC20, CDK1, DLGAP5, KIF11, KIF20 A, TOP2A, and TPX2. They were prominently associated with pathological staging. Among them, KIF11 upregulation was in relation to undesirable prognosis of ESCA patients.

Conclusion

Collectively, we determined ESCA-specific coexpression modules and hub genes, which offered the foundation for future research concerning the mechanistic basis of ESCA.

BUB1B (BUB1 Mitotic Checkpoint Serine/Threonine Kinase B) Promotes Lung Adenocarcinoma by Interacting with Zinc Finger Protein ZNF143 and Regulating Glycolysis

Lung adenocarcinoma (LUAD) is one of the most common causes of cancer death in men. BUB1B (BUB1 mitotic checkpoint serine/threonine kinase B) has been reported to contribute to the initiation and development of several cancers. Here, we aimed to explore the potential role of BUB1B in LUAD. We found BUB1B was upregulated in LUAD, suggesting its potential role as a biomarker for LUAD diagnosis. Significantly, LUAD patients with high BUB1B expression had a shorter survival time than those with low BUB1B expression. Knocking-out BUB1B resulted in suppression of cell proliferation, migration, and invasion in vitro, and inhibition of tumor growth in the xenograft experiment. Further analysis revealed that BUB1B regulates glycolysis in LUAD and interacting with ZNF143 in LUAD cells. The interaction was demonstrated by silencing ZNF143, which led to a decrease in proliferation, migration, and invasion in LUAD cells, whereas overexpressing BUB1B had the opposite effects. Our study suggested that the ZNF143/BUB1B axis plays a pivotal role in LUAD progression, which might be a potential target for LUAD management.

Integrative Analysis of Epigenome and Transcriptome Data Reveals Aberrantly Methylated Promoters and Enhancers in Hepatocellular Carcinoma

DNA methylation is a key transcription regulator, whose aberration was ubiquitous and important in most cancers including hepatocellular carcinoma (HCC). Whole-genome bisulfite sequencing (WGBS) was conducted for comparison of DNA methylation in tumor and adjacent tissues from 33 HCC patients, accompanying RNA-seq to determine differentially methylated region-associated, differentially expressed genes (DMR-DEGs), which were independently replicated in the TCGA-LIHC cohort and experimentally validated via 5-aza-2-deoxycytidine (5-azadC) demethylation. A total of 9,867,700 CpG sites showed significantly differential methylation in HCC. Integrations of mRNA-seq, histone ChIP-seq, and WGBS data identified 611 high-confidence DMR-DEGs. Enrichment analysis demonstrated activation of multiple molecular pathways related to cell cycle and DNA repair, accompanying repression of several critical metabolism pathways such as tyrosine and monocarboxylic acid metabolism. In TCGA-LIHC, we replicated about 53% of identified DMR-DEGs and highlighted the prognostic significance of combinations of methylation and expression of nine DMR-DEGs, which were more efficient prognostic biomarkers than considering either type of data alone. Finally, we validated 22/23 (95.7%) DMR-DEGs in 5-azadC-treated LO2 and/or HepG2 cells. In conclusion, integration of epigenome and transcriptome data depicted activation of multiple pivotal cell cycle-related pathways and repression of several metabolic pathways triggered by aberrant DNA methylation of promoters and enhancers in HCC.

Increased BUB1B/BUBR1 expression contributes to aberrant DNA repair activity leading to resistance to DNA-damaging agents

There has been accumulating evidence for the clinical benefit of chemoradiation therapy (CRT), whereas mechanisms in CRT-recurrent clones derived from the primary tumor are still elusive. Herein, we identified an aberrant BUB1B/BUBR1 expression in CRT-recurrent clones in bladder cancer (BC) by comprehensive proteomic analysis. CRT-recurrent BC cells exhibited a cell-cycle-independent upregulation of BUB1B/BUBR1 expression rendering an enhanced DNA repair activity in response to DNA double-strand breaks (DSBs). With DNA repair analyses employing the CRISPR/cas9 system, we revealed that cells with aberrant BUB1B/BUBR1 expression dominantly exploit mutagenic nonhomologous end joining (NHEJ). We further found that phosphorylated ATM interacts with BUB1B/BUBR1 after ionizing radiation (IR) treatment, and the resistance to DSBs by increased BUB1B/BUBR1 depends on the functional ATM. In vivo, tumor growth of CRT-resistant T24R cells was abrogated by ATM inhibition using AZD0156. A dataset analysis identified FOXM1 as a putative BUB1B/BUBR1-targeting transcription factor causing its increased expression. These data collectively suggest a redundant role of BUB1B/BUBR1 underlying mutagenic NHEJ in an ATM-dependent manner, aside from the canonical activity of BUB1B/BUBR1 on the G2/M checkpoint, and offer novel clues to overcome CRT resistance.

High SGO2 Expression Predicts Poor Overall Survival: A Potential Therapeutic Target for Hepatocellular Carcinoma

Shugoshin2 (SGO2) may participate in the occurrence and development of tumors by regulating abnormal cell cycle division, but its prognostic value in hepatocellular carcinoma (HCC) remains unclear. In this study, we accessed The Cancer Genome Atlas (TCGA) database to get the clinical data and gene expression profile of HCC. The expression of SGO2 in HCC tissues and nontumor tissues and the relationship between SGO2 expression, survival, and clinicopathological parameters were analyzed. The SGO2 expression level was significantly higher in HCC tissues than in nontumor tissues (p < 0.001). An analysis from the Oncomine and Gene Expression Profiling Interactive Analysis 2 (GEPIA2) databases also demonstrated that SGO2 was upregulated in HCC (all p < 0.001). A logistic regression analysis revealed that the high expression of SGO2 was significantly correlated with gender, tumor grade, pathological stage, T classification, and Eastern Cancer Oncology Group (ECOG) score (all p < 0.05). The overall survival (OS) of HCC patients with higher SGO2 expression was significantly poor (p < 0.001). A multivariate analysis showed that age and high expression of SGO2 were independent predictors of poor overall survival (all p < 0.05). Twelve signaling pathways were significantly enriched in samples with the high-SGO2 expression phenotype. Ten proteins and 34 genes were significantly correlated with SGO2. In conclusion, the expression of SGO2 is closely related to the survival of HCC. It may be used as a potential therapeutic target and prognostic marker of HCC.

Identification of the hub genes and prognostic indicators of gastric cancer and correlation of indicators with tumor-infiltrating immune cell levels

Aims: To identify the hub genes and prognostic indicators of gastric cancer (GC) and determine the correlation between prognostic indicators and the tumor-infiltrating immune cell levels so as to provide useful information for future GC diagnosis and treatment. Methods: The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset and two microarray datasets were used to screen the overlapping differentially expressed genes (DEGs) between normal gastric and GC tissue samples. Hub genes were screened via protein-protein interaction networks and module analysis of the overlapping DEGs. Their expression was validated at the cell level and tissue level using the ONCOMINE database. The prognostic indicators of overall survival (OS) and disease-free survival was identified by Cox proportional hazards regression analysis based on tumor grade and cancer stage. The expression of hub genes was validated at the cell level. The correlation of prognostic indicators with the tumor-infiltrating immune cell levels was analyzed using Tumor IMmune Estimation Resource. Results: Ten hub genes, namely CDC6, CDC20, BUB1B, TOP2A, CDK1, AURKA, CCNA2, CCNB1, MAD2L1, and KIF11, were screened and their upregulation in the GC tissue was verified. Three prognostic factors, namely LUM, VCAN, and EFNA4, were identified; their expression was higher in GC cells than in normal cells. LUM, VCAN, and EFNA4 were correlated with tumor-infiltrating immune cell levels in GC. Significance: The identified hub genes and prognostic indicators of GC could be useful indicators for future GC diagnosis and treatment.

BUB1B Overexpression Is an Independent Prognostic Marker and Associated with CD44, p53, and PD-L1 in Renal Cell Carcinoma

INTRODUCTION

BUB1 mitotic checkpoint serine/threonine kinase B encoded by BUB1B gene is a member of the spindle assembly checkpoint family. Several reports have demonstrated that overexpression of BUB1B is associated with cancer progression and prognosis.

OBJECTIVE

This study aims to clarify the expression and function of BUB1B in renal cell carcinoma (RCC).

METHODS

The expression of BUB1B was determined using immunohistochemistry and bioinformatics analysis in RCC. The effects of BUB1B knockdown on cell growth and invasion were evaluated. We analyzed the interaction between BUB1B, cancer stem cell markers, p53, and PD-L1 in RCC.

RESULTS

In 121 cases of RCC, immunohistochemistry showed that 30 (25%) of the RCC cases were positive for BUB1B. High BUB1B expression was significantly correlated with high nuclear grade, T stage, and M stage. A Kaplan-Meier analysis showed that the high expression of BUB1B was associated with poor overall survival after nephrectomy. High BUB1B expression was associated with CD44, p53, and PD-L1 in RCC. Knockdown of BUB1B suppressed cell growth and invasion in RCC cell lines. Knockdown of BUB1B also suppressed the expression of CD44 and increased the expression of phospho-p53 (Ser15). In silico analysis showed that BUB1B was associated with inflamed CD8+, exhausted T-cell signature, IFN-γ signature, and the response to nivolumab.

CONCLUSION

These results suggest that BUB1B plays an oncogenic role and may be a promising predictive biomarker for survival in RCC.

Identification of core genes for early diagnosis and the EMT modulation of ovarian serous cancer by bioinformatics perspective

Ovarian serous carcinoma (OSC), as a common malignant tumor, poses a serious threat to women's health in that epithelial-mesenchymal transformation (EMT)-related modulation becomes heavily implicated in the invasion and progression of OSC. In this study, two core genes (BUB1B and NDC80) among the 16 hub genes have been identified to be involved in the molecular regulation of EMT and associated with the poor early survival of OSC at stages I+II. Through the Gene Regulatory Networks (GRN) analysis of 15 EMT regulators and core genes, it was revealed that TFAP2A and hsa-miR-655 could elaborately modulate EMT development of OSC. Next genetic variation analysis indicated that EMT regulator ELF3 would also serve as a crucial part in the occurrence and progression of OSC. Eventually, survival investigation suggested that TFAP2A, ELF3 and hsa-miR-655 were significantly associated with the overall survival of progressive OSC patients. Thus, combined with diversified bioinformatic analyses, BUB1B, NDC80, TFAP2A, ELF3 and hsa-miR-655 may act as the key biomarkers for early clinical diagnosis and prognosis evaluation of OSC patients as well as potential therapeutic target-points.

BUB1B promotes extrahepatic cholangiocarcinoma progression via JNK/c-Jun pathways

Currently, the controversy regarding the expression profile and function of BUB1B in different malignancies still exist. In this project, we aimed to explore the role and molecular mechanism of BUB1B in the progression of extrahepatic cholangiocarcinoma (ECC). The expression levels of BUB1B in human ECC were evaluated by immunohistochemistry, western blot, and real-time PCR. The role and mechanism of BUB1B in CCA cell proliferation and invasion were investigated in both in vitro and in vivo functional studies. To indicate the clinical significance, a tissue microarray was performed on 113 ECC patients, followed by univariate and multivariate analyses. The expression of BUB1B was increased in both human CCA tissues and CCA cells. Results from loss-of-function and gain-of-function experiments suggested that the inhibition of BUB1B decreased the proliferation and invasiveness of CCA cells in vitro and in vivo, while overexpression of BUB1B achieved the opposite effect. Furthermore, the activation of c-Jun N-terminal kinase-c-Jun (JNK)-c-Jun pathway was regulated by BUB1B. BUB1B regulated the proliferation and invasiveness of CAA cells in a JNK-c-Jun-dependent manner. Clinically, ECC patients with BUB1B high expression had worse overall survival and recurrence-free survival than those with BUB1B low expression. Multivariate analysis identified that BUB1B was an independent predictor for postoperative recurrence and overall survival of ECC patients. In conclusion, BUB1B promoted ECC progression via JNK/c-Jun pathways. These findings suggested that BUB1B could be a potential therapeutic target and a biomarker for predicting prognosis for ECC patients.

Identification of CDK1 as a candidate marker in cutaneous squamous cell carcinoma by integrated bioinformatics analysis

BACKGROUND

Cutaneous squamous cell carcinoma (cSCC) is a relatively common cancer that accounts for nearly 50% of non-melanoma skin cancer cases. However, the genotypes that are linked with poor prognosis and/or high relapse rates and pathogenic mechanisms of cSCC are not fully understood. To address these points, three gene expression datasets were analyzed to identify candidate biomarker genes in cSCC.

METHODS

The GSE117247, GSE32979, and GSE98767 datasets comprising a total of 32 cSCC samples and 31 normal skin tissue samples were obtained from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified and underwent pathway enrichment analyses with the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG). A putative DEG protein-protein interaction (PPI) network was also established that included hub genes. The expression of CDK1, MAD2L1, BUB1 ans CDC20 were examined in the study.

RESULTS

A total of 335 genes were identified, encompassing 219 found to be upregulated and 116 genes that were downregulated in cSCC, compared to normal tissue. Enriched functions of these DEGs were associated with Ephrin receptor signaling and cell division; cytosol, membrane, and extracellular exosomes; ATP-, poly(A) RNA-, and identical protein binding. We also established a PPI network comprising 332 nodes and identified KIF2C, CDC42, AURKA, MAD2L1, MYC, CDK1, FEN1, H2AFZ, BUB1, BUB1B, CKS2, CDC20, CCT2, ACTR2, ACTB, MAPK14, and HDAC1 as candidate hub genes. The expression of CDK1 are significantly higher in the cSCC tissues than that in normal skin.

CONCLUSIONS

The DEGs identified in this study are potential therapeutic targets and biomarkers for cSCC. CDK1 is a gene closely related to the occurrence and development of cSCC, which may play an important role. Bioinformatics analysis shows that it is involved in the important pathway of the pathogenesis of cSCC, and may be recognized and applied as a new biomarker in the future diagnosis and treatment of cSCC.

Comprehensive circular RNA expression profiling constructs a ceRNA network and identifies hsa_circ_0000673 as a novel oncogene in distal cholangiocarcinoma

Circular RNAs (circRNAs) play an important role in cholangiocarcinoma (CCA) development; however, the expression and functions of circRNAs in distal CCA (dCCA) remain unknown. Herein, we explored the expression profile of circRNAs in six paired dCCA tumor and adjacent normal tissue samples using microarray. A total of 171 differentially expressed (DE) circRNAs were identified in dCCA tissues. Host genes of DE circRNAs were enriched in the cellular cytoskeleton and adheren junction. Bioinformatics analyses were used to establish a circRNA-microRNA-mRNA network for dCCA. Protein-protein interaction networks were constructed, and five hub genes were associated with the regulation of the cell cycle based on gene set enrichment analyses. Five DE circRNAs were validated with qRT-PCR in 40 pairs of dCCA tissues, and hsa_circ_0000673 showed promising diagnostic performance in distinguishing dCCA from normal tissues (AUC = 0.85, p < 0.01). Overexpression of hsa_circ_0000673 was associated with tumor invasion (p = 0.001), poor differentiation (p = 0.041), and residual tumor (p = 0.044). In vitro experiments indicated that inhibition of hsa_circ_0000673 suppressed the proliferation, migration, and invasion of CCA cells. This research provided a landscape of dysregulated circRNAs in dCCA and identified hsa_circ_0000673 as a potential biomarker and therapeutic target for dCCA.

BUB1B promotes hepatocellular carcinoma progression via activation of the mTORC1 signaling pathway

Background and Aims

Accumulating studies identified that BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) is integrally involved in the initiation and development of tumors. Nevertheless, the precise biological role and underlying mechanisms of BUB1B in hepatocellular carcinoma (HCC) remain indistinct.

Method

To figure out the role of BUB1B in HCC, we first assessed its expression using The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. We then verified BUB1B expression in HCC tissues, nontumor tissues, and HCC cell lines through western blotting, quantitative reverse transcription‐polymerase chain reaction, and immunohistochemistry. To explore the specific function of BUB1B in HCC in vivo and in vitro, we performed the flow cytometry, Cell Counting Kit‐8, 5‐ethynyl‐2′‐deoxyuridine incorporation, colony formation, Transwell, wound‐healing, subcutaneous tumor growth, and metastasis assays. Additionally, we identified the BUB1B‐regulated pathways involved in HCC by using gene set enrichment analysis.

Results

Our data displayed that higher BUB1B expression was detected in HCC tissues and HCC cell lines. The overexpression of BUB1B was positively correlated with adverse clinicopathological characteristics. Survival analyses showed that lower recurrence‐free and overall survival rates were correlated with the overexpression of BUB1B in patients with HCC. Moreover, the malignancy of HCC was facilitated by BUB1B both in vivo and in vitro. Lastly, the results were confirmed by western blots, which showed that BUB1B upregulated mTORC1 signaling pathway in HCC. Meanwhile, the oncogenic effect of BUB1B will be impaired when the mTORC1 signaling pathway was inhibited by rapamycin.

Conclusion

We highlighted that BUB1B played an oncogenic role in HCC and was identified as a possible clinical prognostic factor and a potential novel therapeutic target for HCC.

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.

Comparative proteomic analysis uncovers potential biomarkers involved in the anticancer effect of Scutellarein in human gastric cancer cells

Scutellarein (SCU), a flavone that belongs to the flavonoid family and abundantly present in Scutellaria baicalensis a flowering plant in the family Lamiaceae, has been reported to exhibit anticancer effects in several cancer cell lines including gastric cancer (GC). Although our previous study documented the mechanisms of Scutellarein‑induced cytotoxic effects, the literature shows that the proteomic changes that are associated with the cellular response to SCU have been poorly understood. To avoid adverse side‑effects and significant toxicity of chemotherapy in patients who react poorly, biomarkers anticipating therapeutic responses are imperative. In the present study, we utilized a comparative proteomic analysis to identify proteins associated with Scutellarein (SCU)‑induced cell death in GC cells (AGS and SNU484), by integrating two‑dimensional gel electrophoresis (2‑DE), mass spectrometry (MS), and bioinformatics to analyze the proteins. Proteomic analysis between SCU‑treated and DMSO (control) samples successfully identified 41 (AGS) and 31 (SNU484) proteins by MALDI‑TOF/MS analysis and protein database search. Comparative proteomics analysis between AGS and SNU484 cells treated with SCU revealed a total of 7 protein identities commonly expressed and western blot analysis validated a subset of identified critical proteins, which were consistent with those of the 2‑DE outcome. Molecular docking studies also confirmed the binding affinity of SCU towards these critical proteins. Phosphatidylinositol 4,5‑bisphosphate 3‑kinase catalytic subunit β isoform (PIK3CB) protein expression was accompanied by a distinct group of cellular functions, including cell growth, and proliferation. Cancerous inhibitor of protein phosphatase 2A (CIP2A), is one of the oncogenic molecules that have been shown to promote tumor growth and resistance to apoptosis and senescence‑inducing therapies. In the present study, both PIK3CB and CIP2A proteins were downregulated in SCU‑treated cells, which boosts our previous results of SCU to induce apoptosis and inhibits GC cell growth by regulating these critical proteins. The comparative proteomic analysis has yielded candidate biomarkers of response to SCU treatment in GC cell models and further validation of these biomarkers will help the future clinical development of SCU as a novel therapeutic drug.

Genomic analyses of early responses to radiation inglioblastoma reveal new alterations at transcription,splicing, and translation levels

High-dose radiation is the main component of glioblastoma therapy. Unfortunately, radio-resistance is a common problem and a major contributor to tumor relapse. Understanding the molecular mechanisms driving response to radiation is critical for identifying regulatory routes that could be targeted to improve treatment response. We conducted an integrated analysis in the U251 and U343 glioblastoma cell lines to map early alterations in the expression of genes at three levels: transcription, splicing, and translation in response to ionizing radiation. Changes at the transcriptional level were the most prevalent response. Downregulated genes are strongly associated with cell cycle and DNA replication and linked to a coordinated module of expression. Alterations in this group are likely driven by decreased expression of the transcription factor FOXM1 and members of the E2F family. Genes involved in RNA regulatory mechanisms were affected at the mRNA, splicing, and translation levels, highlighting their importance in radiation-response. We identified a number of oncogenic factors, with an increased expression upon radiation exposure, including BCL6, RRM2B, IDO1, FTH1, APIP, and LRIG2 and lncRNAs NEAT1 and FTX. Several of these targets have been previously implicated in radio-resistance. Therefore, antagonizing their effects post-radiation could increase therapeutic efficacy. Our integrated analysis provides a comprehensive view of early response to radiation in glioblastoma. We identify new biological processes involved in altered expression of various oncogenic factors and suggest new target options to increase radiation sensitivity and prevent relapse.

Identification of Hub Genes in Atypical Teratoid/Rhabdoid Tumor by Bioinformatics Analyses

Atypical teratoid/rhabdoid tumor (ATRT) is a devastating intracranial tumor in children. Currently, its molecular mechanisms cannot be studied effectively because patient samples are limited, and many factors are involved in its pathogenesis. In this study, we analyzed three gene expression profile data sets obtained from the Gene Expression Omnibus (GEO) database to identify genes that participate in ATRT. The datasets were integrated and analyzed using the RobustRankAggreg method to screen for differentially expressed genes (DEGs). We identified 197 DEGs, including 94 downregulated and 103 upregulated genes which were then used for gene set enrichment analysis. The results showed that the downregulated genes were mainly enriched in synaptic vesicle cycle, nicotine addiction, and GABAergic synapse, whereas the upregulated genes were enriched in the cell cycle, p53 signaling pathway, and cellular senescence. Consistent with these results, gene set enrichment analysis showed that E2F targets, G2M checkpoints, and MYC targets were significantly enriched in datasets. Protein-protein interaction (PPI) network revealed that CDK1, CCNA2, BUB1B, CDC20, KIF11, KIF20A, KIF2C, NCAPG, NDC80, NUSAP1, PBK, RRM2, TPX2, TOP2A, and TTK were hub genes. NetworkAnalyst algorithm was used to predict the transcription factor (TF), and the results showed that MYC, SOX2, and KDM5B could regulate these hub genes. In conclusion, the present study brings a new perspective of ATRT pathogenesis and the strategy targeted to cell cycle related gene may be promising treatments for the disease.

Identification of potential crucial genes and molecular mechanisms in glioblastoma multiforme by bioinformatics analysis

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor of the adult central nervous system and is associated with poor prognosis. The present study aimed to identify the hub genes in GBM in order to improve the current understanding of the underlying mechanism of GBM. The RNA-seq data were downloaded from The Cancer Genome Atlas database. The edgeR package in R software was used to identify differentially expressed genes (DEGs) between two groups: Glioblastoma samples and normal brain samples. Gene Ontology (GO) functional enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed using Database for Annotation, Visualization and Integrated Discovery software. Additionally, Cytoscape and Search Tool for the Retrieval of Interacting Genes/Proteins tools were used for the protein-protein interaction network, while the highly connected modules were extracted from this network using the Minimal Common Oncology Data Elements plugin. Next, the prognostic significance of the candidate hub genes was analyzed using UALCAN. In addition, the identified hub genes were verified by reverse transcription-quantitative (RT-q) PCR. In total, 1,483 DEGs were identified between GBM and control samples, including 954 upregulated genes and 529 downregulated genes (P<0.01; fold-change >16) and these genes were involved in different GO terms and signaling pathways. Furthermore, CDK1, BUB1, BUB1B, CENPA and GNG3 were identified as key genes in the GBM samples. The UALCAN tool verified that higher expression level of CENPA was relevant to poorer overall survival rates. In conclusion, CDK1, BUB1, BUB1B, CENPA and GNG3 were found to be potential biomarkers for GBM. Additionally, ‘cell cycle’ and ‘γ-aminobutyric acid signaling’ pathways may serve a significant role in the pathogenesis of GBM.

Integrative analyses of noncoding RNAs reveal the potential mechanisms augmenting tumor malignancy in lung adenocarcinoma

Precise noncoding RNA (ncRNA)-based network prediction is necessary to reveal ncRNA functions and pathological mechanisms. Here, we established a systemic pipeline to identify prognostic ncRNAs, predict their functions and explore their pathological mechanisms in lung adenocarcinoma (LUAD). After in silico and experimental validation based on evaluations of prognostic value in multiple LUAD cohorts, we selected the PTTG3P pseudogene from among other prognostic ncRNAs (MIR497HG, HSP078, TBX5-AS1, LOC100506990 and C14orf64) for mechanistic studies. PTTG3P upregulation in LUAD cells shortens the metaphase to anaphase transition in mitosis, increases cell viability after cisplatin or paclitaxel treatment, facilitates tumor growth that leads to poor survival in orthotopic lung models, and is associated with a poor survival rate in LUAD patients in the TCGA cohort who received chemotherapy. Mechanistically, PTTG3P acts as an ncRNA that interacts with the transcription factor FOXM1 to regulate the transcriptional activation of the mitotic checkpoint kinase BUB1B, which augments tumor growth and chemoresistance and leads to poor outcomes for LUAD patients. Overall, we established a systematic strategy to uncover prognostic ncRNAs with functional prediction methods suitable for pan-cancer studies. Moreover, we revealed that PTTG3P, due to its upregulation of the PTTG3P/FOXM1/BUB1B axis, could be a therapeutic target for LUAD patients.

The genetic association between type 2 diabetic and hepatocellular carcinomas

Background

Type 2 diabetes mellitus (T2DM) and hepatocellular carcinoma (HCC) are both major health problems throughout the world. It has been reported that T2DM is an independent risk factor for HCC, although the pathophysiology is still unclear.

Methods

In order to identify differentially expressed genes (DEGs) in T2DM and HCC, gene expression datasets for T2DM (GSE15653), HCC (GSE60502) and metformin-treated cells (GSE69850) were obtained from the Gene Expression Omnibus database repository. Protein-protein interaction (PPI) networks for the DEGs were constructed and gene clusters selected for functional enrichment analysis. Ten genes with the highest degree of connectivity were selected as hub genes and prognostic analysis together with analysis of gene expression and protein distribution were performed for these genes. Lastly, we investigated associations between the hub genes and genes associated with metformin treatment in hepatocarcinoma cells.

Results

In total, 256 common DEGs, including 155 up-regulated genes and 101 down-regulated genes, were identified. Enrichment analyses showed that the genes of the major module were largely associated with the cell cycle. All of the 10 hub genes (CCNA2, CCNB1, MAD2L1, BU1B, RACGAP1, CHEK1, BUB1, ASPM, NCAPG and TTK) have a strong association with lower overall survival in liver cancer patients and four genes (CCNA2, CCNB1, CHEK1 and BUB1) have reduced expression in metformin-treated samples.

Conclusions

This study identified a number of genes that may play important roles in the association of T2DM and HCC, including four genes which may be the target of metformin treatment for diabetes and HCC. The specific mechanisms involved remain to be identified.

Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is a widespread, common type of cancer in Asian countries, and the need for biomarker-matched molecularly targeted therapy for HCC has been increasingly recognized. However, the effective treatment for HCC is unclear. Therefore, identifying additional hub genes and pathways as novel prognostic biomarkers for HCC is necessary. In this study, the expression profiles of GSE121248, GSE45267 and GSE84402 were obtained from the Gene Expression Omnibus (GEO), including 132 HCC and 90 noncancerous liver tissues. Differentially expressed genes (DEGs) between HCC and noncancerous samples were identified by GEO2 R and Venn diagrams. In total, 109 DEGs were identified in these datasets, including 24 upregulated genes and 85 downregulated genes. Subsequently, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) preliminary analyses of the DEGs were performed using DAVID. The protein-protein interaction (PPI) network of the DEGs was constructed with the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized in Cytoscape. Module analysis of the PPI network was performed using MCODE to get hub genes. Moreover, the influence of the hub genes on overall survival was determined with Kaplan-Meier plotter. All hub genes were analyzed by Gene Expression Profiling Interactive Analysis (GEPIA) and KEGG. Overall, the hub genes DTL, CDK1, CCNB1, RACGAP1, ECT2, NEK2, BUB1B, PBK, TOP2A, ASPM, HMMR, RRM2, CDKN3, PRC1, and ANLN were upregulated in HCC, and the survival rate was lower for HCC with increased expression of these hub genes. CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway, and CCNB1, CDK1, and BUB1B were enriched in the cell cycle. In brief, we screened 15 hub genes and pathways to identify potential prognostic markers for HCC treatment. However, the specific occurrence and development of HCC with expression of the hub genes should be verified in vivo and in vitro.

Identification of candidate genes associated with the pathogenesis of small cell lung cancer via integrated bioinformatics analysis

The pathogenesis of small cell lung cancer (SCLC), a highly metastatic malignant tumor, remains unclear. In the present study, important genes and pathways that are involved in the pathogenesis of SCLC were identified. The following four datasets were downloaded from the Gene Expression Omnibus: GSE60052, GSE43346, GSE15240 and GSE6044. The differentially expressed genes (DEGs) between the SCLC samples and the normal samples were analyzed using R software. The limma package was used for every dataset. The RobustRankAggreg package was used to integrate the DEGs from the four datasets. Functional and pathway enrichment analyses were conducted using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases with FunRich software and R software, respectively. In addition, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database and Cytoscape software. Hub genes and significant modules were identified using Molecular Complex Detection in Cytoscape software. Finally, the expression values of hub genes were determined using the Oncomine online database. In total, 412 DEGs were identified following the integration of the four datasets, with 146 upregulated genes and 266 downregulated genes. The upregulated DEGs were primarily enriched in the cell cycle, cell division and microtubule binding. The downregulated DEGs were primarily enriched in the complement and coagulation cascades, the cytokine-mediated signaling pathway and protein binding. Eight hub genes and 1 significant module correlated to the cell cycle pathway were identified based on a subset of the PPI network. Finally, five hub genes were identified as highly expressed in SCLC tissue compared with normal tissue. The cell cycle pathway may be the pathway most closely associated with the pathogenesis of SCLC. NDC80, BUB1B, PLK1, CDC20 and MAD2L1 should be the focus of follow-up studies regarding the diagnosis and treatment of SCLC.

Identification of Biomarkers for Controlling Cancer Stem Cell Characteristics in Bladder Cancer by Network Analysis of Transcriptome Data Stemness Indices

Background: Stem cells characterized by self-renewal and therapeutic resistance play crucial roles in bladder cancer (BLCA). However, the genes modulating the maintenance and proliferation of BLCA stem cells are still unclear. In this study, we aimed to characterize the expression of stem cell-related genes in BLCA.

Methods: The mRNA expression-based stemness index (mRNAsi) of The Cancer Genome Atlas (TCGA) was evaluated and corrected by tumor purity. Corrected mRNAsi were further analyzed with regard to muscle-invasive bladder cancer molecular subtypes, survival analysis, pathological staging characteristics, and outcomes after primary treatment. Next, weighted gene co-expression network analysis was used to find modules of interest and key genes. Functional enrichment analysis was performed to functionally annotate the modules and key genes. The expression levels of key genes in all cancers were validated using Oncomine and Gene Expression Omnibus (GEO) database containing molecular subtypes in BLCA. Protein interaction networks were used to identify upstream genes, and the relationships between genes were analyzed at the protein and transcription levels.

Findings: mRNAsi was significantly upregulated in cancer tissues. Corrected mRNAsi in BLCA increased as tumor stage increased, with T3 having the highest stem cell characteristics. Lower corrected mRNAsi scores had better overall survival and treatment outcome. The modules of interest and key genes were determined based on topological overlap measurement clustering results and the inclusion criteria. For 13 key genes (AURKA, BUB1B, CDCA5, CDCA8, KIF11, KIF18B, KIF2C, KIFC1, KPNA2, NCAPG, NEK2, NUSAP1, and RACGAP1), enriched gene ontology terms related to cell proliferation (e.g., mitotic nuclear division, spindle, and microtubule binding) were determined. Their expression did not differ according to the pathological stages of BLCA, and these genes were clearly overexpressed in many types of cancers. In GEO database, the expression levels of 13 key genes were higher in basal subtype with the highest stem cell characteristics than in luminal and its subtypes. AURKB and PLK1 may be regulated upstream of other key genes, and the key genes were found to be strongly correlated with each other and with upstream genes.

Interpretation: The 13 key genes identified in this study were found to play important roles in the maintenance of BLCA stem cells. Controlling the upstream genes AURKB and PLK1 may have applications in the treatment of BLCA. These genes may act as therapeutic targets for inhibiting the stemness characteristics of BLCA.

Identification of five hub genes as monitoring biomarkers for breast cancer metastasis in silico

BACKGROUND

Breast cancer is one of the most common endocrine cancers among females worldwide. Distant metastasis of breast cancer is causing an increasing number of breast cancer-related deaths. However, the potential mechanisms of metastasis and candidate biomarkers remain to be further explored.

RESULTS

The gene expression profiles of GSE102484 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to screen for the most potent gene modules associated with the metastatic risk of breast cancer, and a total of 12 modules were identified based on the analysis. In the most significant module (R2 = 0.68), 21 network hub genes (MM > 0.90) were retained for further analyses. Next, protein-protein interaction (PPI) networks were used to further explore the biomarkers with the most interactions in gene modules. According to the PPI networks, five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) were identified as key genes associated with breast cancer progression. Furthermore, the prognostic value and differential expression of these genes were validated based on data from The Cancer Genome Atlas (TCGA) and Kaplan-Meier (KM) Plotter. Receiver operating characteristic (ROC) curve analysis revealed that the mRNA expression levels of these five hub genes showed excellent diagnostic value for breast cancer and adjacent tissues. Moreover, these five hub genes were significantly associated with worse distant metastasis-free survival (DMFS) in the patient cohort based on KM Plotter.

CONCLUSION

Five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) associated with the risk of distant metastasis were extracted for further research, which might be used as biomarkers to predict distant metastasis of breast cancer.

Bioinformatics analysis of a long non‑coding RNA and mRNA regulation network in rats with middle cerebral artery occlusion based on RNA sequencing

Long non‑coding RNAs (lncRNAs) have been proven to be critical gene regulators of development and disease. The main aim of the present study was to elucidate the lncRNA‑mRNA regulation network in ischemic stroke induced by middle cerebral artery occlusion (MCAO) using RNA sequencing (RNA‑seq) in rats. lncRNA expression profiles were screened in brain tissues to identify a number of differentially expressed lncRNAs (DELs) and genes (DEGs) by RNA‑seq. Reverse transcription‑quantitative polymerase chain reaction was performed to further confirm the lncRNA expression data. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to mine mRNA functions, and a lncRNA‑mRNA network was constructed. Additionally, cis‑ and trans‑regulatory gene analyses of DELs were predicted. A total of 134 DELs (fold change >2, false discovery rate <0.05) and 1,006 DEGs (fold change >2 and P<0.05) were identified. Eighteen lncRNAs were predicted to regulate heme oxygenase 1, mitotic checkpoint serine/threonine kinase B, chemokine ligand 2 and DNA Topoisomerase IIα, amongst other genes. These genes are all associated with a cellular response to inorganic substances, alkaloids, estradiol, reactive oxygen species, metal ions, oxidative stress, and are associated with metabolic pathways, chemokine signaling pathways, malaria, Parkinson's disease, the cell cycle and other GO and KEGG pathway enrichments. The present study identifies novel DELs and an lncRNA‑mRNA regulatory network that may allow for an improved understanding of the molecular mechanism of ischemic stroke induced by MCAO.

Comparative Proteomic Profiling of Tumor-Associated Proteins in Human Gastric Cancer Cells Treated with Pectolinarigenin

Pectolinarigenin (PEC), a natural flavonoid that is present in citrus fruits, has been reported to exhibit antitumor effects in several cancers. Though the mechanism of PEC-induced cytotoxicity effects has been documented, the proteomic changes that are associated with the cellular response to this flavonoid are poorly understood in gastric cancer cells. In this study, a comparative proteomic analysis was performed to identify proteins associated with PEC-induced cell death in two human gastric cancer cell lines: AGS and MKN-28. Two-dimensional gel electrophoresis (2-DE) revealed a total of 29 and 56 protein spots with significant alteration were screened in AGS and MKN-28 cells respectively. In total, 13 (AGS) and 39 (MKN28) proteins were successfully identified by mass spectrometry from the differential spots and they are known to be involved in signal transduction, apoptosis, transcription and translation, cell structural organization, and metabolism, as is consistent with multiple effects of PEC on tumor cells. Notably, novel target proteins like Probable ATP-dependent RNA helicase DDX4 (DDX4) and E3 ubiquitin-protein ligase LRSAM1 (LRSAM1) along with the commonly differential expressed proteins on both the cell lines that are treated with PEC were confirmed by immunoblotting. The DDX4 accelerates cell cycle progression by abrogating the G2 checkpoint when overexpressed in cancer cells, while the aberrant expression of LRSAM1 may be involved in the cancer pathology. Thus, proteomic analysis provides vital information about target proteins that are important for PEC-induced cell death in gastric cancer cells.

Gene set enrichment analysis and meta-analysis to identify six key genes regulating and controlling the prognosis of esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is a common malignancy with high mortality. Because of the lack of clarity in the relevant genes and mechanisms involved, and the current difficulty for oncotherapy in providing therapeutic solutions, there is an urgent need to study this matter. While gene probe studies have been used to select the most virulent genes and pathways, paucity of case controls during gene screening and lack of conclusive results to expound the etiology and pathogenesis of the disease, have reduced study reliability.

Methods

We chose six datasets from independent studies in the Gene Expression Omnibus (GEO) database and used gene set enrichment analysis and meta-analysis to select key genes and pathways.

Results

We found four down-regulated and four up-regulated pathways through gene set enrichment analysis, and 406 differential genes through meta-analysis. Based on The Cancer Genome Atlas (TCGA), 995 differentially expressed genes were screened out. Comparing the 406 gene set with the 995 gene set, we found 19 common genes, of which 6 had a common pathway and were screened out as key genes regulating and controlling the prognosis of ESCC.

Conclusions

Among the 19 genes, we found three genes that affect the chemotherapy of ESCC: BUB1B, BUB1, and TTK. Another three genes NDC1, NUP107, and NUP155 on the RNA transport pathway were also found. Altogether, these six genes are not only crucial in the development of ESCC, but also determine the prognosis of patients. The key genes and pathways identified in the present study will be used for the next stage in our study, which will involve gene elimination and other experimentation methods.