Bub1 up-regulation and hyperphosphorylation promote malignant transformation in SV40 tag-induced transgenic mouse models

Four Novel Prognostic Genes Related to Prostate Cancer Identified Using Co-expression Structure Network Analysis

Prostate cancer (PCa) is one of the most common malignancies for males, but very little is known about its pathogenesis. This study aimed to identify novel biomarkers associated with PCa prognosis and elucidate the underlying molecular mechanism. First, The Cancer Genome Atlas (TCGA) RNA-sequencing data were utilized to identify differentially expressed genes (DEGs) between tumor and normal samples. The DEGs were then applied to construct a co-expression and mined using structure network analysis. The magenta module that was highly related to the Gleason score (r = 0.46, p = 3e-26) and tumor stage (r = 0.38, p = 2e-17) was screened. Subsequently, all genes of the magenta module underwent function annotation. From the key module, CCNA2, CKAP2L, NCAPG, and NUSAP1 were chosen as the four candidate genes. Finally, internal (TCGA) and external data sets (GSE32571, GSE70770, and GSE141551) were combined to validate and predict the value of real hub genes. The results show that the above genes are up-regulated in PCa samples, and higher expression levels show significant association with higher Gleason scores and tumor T stage. Moreover, receiver operating characteristic curve and survival analysis validate the excellent value of hub genes in PCa progression and prognosis. In addition, the protein levels of these four genes also remain higher in tumor tissues when compared with normal tissues. Gene set enrichment analysis and gene set variation analysis for a single gene reveal the close relation with cell proliferation. Meanwhile, 11 small molecular drugs that have the potential to treat PCa were also screened. In conclusion, our research identified four potential prognostic genes and several candidate molecular drugs for treating PCa.

Integrated Network Analysis Reveals FOXM1 and MYBL2 as Key Regulators of Cell Proliferation in Non-small Cell Lung Cancer

Background: Loss of control on cell division is an important factor for the development of non-small cell lung cancer (NSCLC), however, its molecular mechanism and gene regulatory network are not clearly understood. This study utilized the systems bioinformatics approach to reveal the “driver-network” involve in tumorigenic processes in NSCLC.

Methods: A meta-analysis of gene expression data of NSCLC was integrated with protein-protein interaction (PPI) data to construct an NSCLC network. MCODE and iRegulone were used to identify the local clusters and its upstream transcription regulators involve in NSCLC. Pair-wise gene expression correlation was performed using GEPIA. The survival analysis was performed by the Kaplan-Meier plot.

Results: This study identified a local “driver-network” with highest MCODE score having 26 up-regulated genes involved in the process of cell proliferation in NSCLC. Interestingly, the “driver-network” is under the regulation of TFs FOXM1 and MYBL2 as well as miRNAs. Furthermore, the overexpression of member genes in “driver-network” and the TFs are associated with poor overall survival (OS) in NSCLC patients.

Conclusion: This study identified a local “driver-network” and its upstream regulators responsible for the cell proliferation in NSCLC, which could be promising biomarkers and therapeutic targets for NSCLC treatment.

A risk assessment model for the prognosis of osteosarcoma utilizing differentially expressed lncRNAs

The present study was conducted to establish a risk assessment model for evaluating osteosarcoma prognosis based on prognosis-associated long non-coding RNA (lncRNA) expression. Human osteosarcoma expression profiles were obtained from the NCBI GEO and EBI ArrayExpress databases and differently expressed lncRNAs between good and poor prognosis groups were evaluated using Student's t-test and Wilcoxon rank test in R (v. 3.1.0). A multivariate Cox regression was used to establish a risk assessment system based on lncRNA expression levels, with the associated regression coefficients used as the weight. Survival analysis and receiver operating characteristic (ROC) curves were constructed to verify the accuracy of the risk assessment model. Associations between the prognosis, risk assessment model and clinical features were also investigated using univariate and multivariate Cox regression analyses. Furthermore, differentially expressed genes associated with the lncRNAs in the risk assessment model were identified, and functional enrichment analysis was performed. A total of 9 from the 211 differentially expressed lncRNAs were selected to establish the risk assessment model. The risk assessment model exhibited a good prognostic prediction ability, with high area under the curve values in the training and validation sets. Additionally, the calculated risk score based on the 9 selected lncRNAs was identified to be an independent prognostic factor for osteosarcoma. Furthermore, differentially expressed genes were primarily enriched in the cell cycle, oxidative phosphorylation and cell adhesion processes. The present study described a risk assessment model based on 9 significantly differentially expressed lncRNAs, which was identified to have a high accuracy in potentially predicting patient prognosis.

Dysfunction of Sister Chromatids Separation Promotes Progression of Hepatocellular Carcinoma According to Analysis of Gene Expression Profiling

Despite studying the various molecular mechanisms of hepatocellular carcinoma (HCC), effective drugs and biomarkers in HCC therapy are still scarce. The present study was designed to investigate dysregulated pathways, novel biomarkers and therapeutic targets for HCC. The gene expression dataset of GSE14520, which included 362 tumor and their paired non-tumor tissues of HCC, was extracted for processing by the Robust multi-array average (RMA) algorithm in the R environment. SAM methods were leveraged to identify differentially expressed genes (DEGs). Functional analysis of DEGs was performed using DAVID. The GeneMania and Cytohubba were used to construct the PPI network. To avoid individual bias, GSEA and survival analysis were employed to verify the results. The results of these analyses indicated that separation of sister chromatids was the most aberrant phase in the progression of HCC, and the most frequently involved genes, EZH2, GINS1, TPX2, CENPF, and BUB1B, require further study to be used as drug targets or biomarkers in diagnosis and treatment of HCC.

Expression of BAF57 in ovarian cancer cells and drug sensitivity

The SMARCE1 (SWI / SNF-related, matrix-associated, and actin-dependent regulator of chromatin, subfamily e, member 1) encodes BAF57 protein. Previously, we reported that BAF57 is a predictive marker of endometrial carcinoma. In this study, we investigated BAF57 expression in ovarian cancer cell lines and their sensitivities to cisplatin, doxorubicin, paclitaxel, and 5-fluorouracil. BAF57 expression was strongly correlated with sensitivities to cisplatin, doxorubicin, and 5-fluorouracil in 10 ovarian cancer cell lines. Paclitaxel sensitivity was also correlated with BAF57 expression, but without significance. In A2780 ovarian cancer cells, knockdown of BAF57 using specific siRNA increased cell cycle arrest at G₁ phase and the sensitivities to these anticancer agents. cDNA microarray analysis of A2780 cells transfected with BAF57 siRNA showed that 134 genes were positively regulated by BAF57, including ATP-binding cassette, sub-family G (WHITE), member 2 (ABCG2) encoding breast cancer resistance protein (BCRP). We confirmed that knockdown of BAF57 decreased BCRP expression in ovarian cancer cells by Western blot analysis, and that ABCG2 gene expression might be regulated transcriptionally. These results suggested that BAF57 is involved in ovarian cancer cell growth and sensitivity to anticancer agents, and that BAF57 may be a target for ovarian cancer therapy.

AICAR induces Bax/Bak-dependent apoptosis through upregulation of the BH3-only proteins Bim and Noxa in mouse embryonic fibroblasts

5-Aminoimidazole-4-carboxamide (AICA) riboside (AICAR) is a nucleoside analogue that is phosphorylated to 5-amino-4-imidazolecarboxamide ribotide (ZMP), which acts as an AMP mimetic and activates AMP-activated protein kinase (AMPK). It has been recently described that AICAR triggers apoptosis in chronic lymphocytic leukemia (CLL) cells, and its mechanism of action is independent of AMPK as well as p53. AICAR-mediated upregulation of the BH3-only proteins BIM and NOXA correlates with apoptosis induction in CLL cells. Here we propose mouse embryonic fibroblasts (MEFs) as a useful model to analyze the mechanism of AICAR-induced apoptosis. ZMP formation was required for AICAR-induced apoptosis, though direct Ampk activation with A-769662 failed to induce apoptosis in MEFs. AICAR potently induced apoptosis in Ampkα1 (-/-) /α2 (-/-) MEFs, demonstrating an Ampk-independent mechanism of cell death activation. In addition, AICAR acts independently of p53, as MEFs lacking p53 also underwent apoptosis normally. Notably, MEFs lacking Bax and Bak were completely resistant to AICAR-induced apoptosis, confirming the involvement of the mitochondrial pathway in its mechanism of action. Apoptosis was preceded by ZMP-dependent but Ampk-independent modulation of the mRNA levels of different Bcl-2 family members, including Noxa, Bim and Bcl-2. Bim protein levels were accumulated upon AICAR treatment of MEFs, suggesting its role in the apoptotic process. Strikingly, MEFs lacking both Bim and Noxa displayed high resistance to AICAR. These findings support the notion that MEFs are a useful system to further dissect the mechanism of AICAR-induced apoptosis.

Characterization of the oncogenic activity of the novel TRIM59 gene in mouse cancer models

A novel TRIM family member, TRIM59 gene was characterized to be upregulated in SV40 Tag oncogene-directed transgenic and knockout mouse prostate cancer models as a signaling pathway effector. We identified two phosphorylated forms of TRIM59 (p53 and p55) and characterized them using purified TRIM59 proteins from mouse prostate cancer models at different stages with wild-type mice and NIH3T3 cells as controls. p53/p55-TRIM59 proteins possibly represent Ser/Thr and Tyr phosphorylation modifications, respectively. Quantitative measurements by ELISA showed that the p-Ser/Thr TRIM59 correlated with tumorigenesis, whereas the p-Tyr-TRIM59 protein correlated with advanced cancer of the prostate (CaP). The function of TRIM59 was elucidated using short hairpin RNA (shRNA)-mediated knockdown of the gene in human CaP cells, which caused S-phase cell-cycle arrest and cell growth retardation. A hit-and-run effect of TRIM59 shRNA knockdown was observed 24 hours posttransfection. Differential cDNA microarrray analysis was conducted, which showed that the initial and rapid knockdown occurred early in the Ras signaling pathway. To confirm the proto-oncogenic function of TRIM59 in the Ras signaling pathway, we generated a transgenic mouse model using a prostate tissue-specific gene (PSP94) to direct the upregulation of the TRIM59 gene. Restricted TRIM59 gene upregulation in the prostate revealed the full potential for inducing tumorigenesis, similar to the expression of SV40 Tag, and coincided with the upregulation of genes specific to the Ras signaling pathway and bridging genes for SV40 Tag-mediated oncogenesis. The finding of a possible novel oncogene in animal models will implicate a novel strategy for diagnosis, prognosis, and therapy for cancer.

Global effects of BKV infection on gene expression in human primary kidney epithelial cells

BK virus (BKV) is a ubiquitous human pathogen that establishes a lifelong persistent infection in kidney epithelial cells. BKV reactivation within these cells results in a lytic infection in immunocompromised patients. Little is known about the specific interactions of BKV and the host cell during persistence and reactivation. We performed global cellular gene expression analyses using microarrays to characterize the global effect of BKV on primary kidney epithelial cells during the viral life cycle. Our results demonstrate that BKV primarily activates genes involved in cell cycle regulation and apoptosis (58% and 44% of upregulated genes at 48 and 72 h post-infection, respectively). Surprisingly, we observed that only four genes were downregulated during infection and that only two genes directly involved in the inflammatory response were differentially expressed. These results provide information about how BKV interacts with a cell type in which it both establishes persistence and undergoes lytic reactivation.