Tumor suppressor BLU promotes paclitaxel antitumor activity by inducing apoptosis through the down-regulation of Bcl-2 expression in tumorigenesis

Novel bioinformatic approaches show the role of driver genes in the progression of cervical cancer: An in-silico study

Background

The goal of this bioinformatics research is to get a comprehensive understanding of the driver genes and their function in the development, progression, and treatment of cervical cancer. This study constitutes a pioneering attempt, adding to our knowledge of genetic diversity and its ramifications.

Material and methods

In this project, we use bioinformatics and systems biology methods to identify candidate transcription factors and the genes they regulate in order to identify microRNAs and LncRNAs that regulate these transcription factors and lead to the discovery of new medicines for the treatment of cervical cancer. From the differentially expressed genes available via GEO's GSE63514 accession, we use driver genes to choose these candidates. We then used the WGCNA tool in R to rebuild the co-expression network and its modules. The hub genes of each module were determined using CytoHubba, a Cystoscope plugin. The biomarker potential of hub genes was analyzed using the UCSC Xena browser and the GraphPad prism program. The TRRUST database is used to locate the TFs that regulate the expression of these genes. In order to learn how drugs, MicroRNAs, and LncRNAs interact with transcription factors, we consulted the Drug Target Information Database (DGIDB), the miRWalk database, and the LncHub database. Finally, the online database Enrichr is utilized to analyze the enrichment of Gene Ontology and KEGG pathways.

Results

By combining the mRNA expression levels of 2041 driver genes from 14 early-stage Cervical cancer and 24 control samples, a co-expression network was built. The cluster analysis shows that the collection of shared genes may be broken down into seven distinct groups, or "modules." According to the average linkage hierarchical clustering and Summary smaller than 2, we found five modules (represented by the colors blue, brown, red, green, and grey) in our research. Then, we identify 5 high-degree genes from these modules that may serve as diagnostic biomarkers (ZBBX, PLCH1, TTC7B, DNAH7, and ZMYND10). In addition, we identify four transcription factors (SRF, RELA, NFKB1, and SP1) that regulate the expression of genes in the co-expression module. Drugs, microRNAs, and long noncoding RNAs are then shown to cooperate with transcription factors. At last, the KEGG database's pathways were mined for information on how the co-expression module fits within them. More clinical trials are required for more trustworthy outcomes, and we collected this data using bioinformatics methods.

Conclusion

The major goal of this research was to identify diagnostic and therapeutic targets for cervical cancer by learning more about the involvement of driver genes in cancer's earliest stages.

Identification and validation of a novel zinc finger protein-related gene-based prognostic model for breast cancer

Background

Breast invasive carcinoma (BRCA) is a commonly occurring malignant tumor. Zinc finger proteins (ZNFs) constitute the largest transcription factor family in the human genome and play a mechanistic role in many cancers' development. The prognostic value of ZNFs has yet to be approached systematically for BRCA.

Methods

We analyzed the data of a training set from The Cancer Genome Atlas (TCGA) database and two validation cohort from GSE20685 and METABRIC datasets, composed of 3,231 BRCA patients. After screening the differentially expressed ZNFs, univariate Cox regression, LASSO, and multiple Cox regression analysis were performed to construct a risk-based predictive model. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and gene set enrichment analyses (GSEA) were utilized to assess the potential relations among the tumor immune microenvironment and ZNFs in BRCA.

Results

In this study, we profiled ZNF expression in TCGA based BRCA cohort and developed a novel prognostic model based on 14 genes with ZNF relations. This model was composed of high and low-score groups for BRCA classification. Based upon Kaplan-Meier survival curves, risk-status-based prognosis illustrated significant differences. We integrated the 14 ZNF-gene signature with patient clinicopathological data for nomogram construction with accurate 1-, 3-, and 5-overall survival predictive capabilities. We then accessed the Genomics of Drug Sensitivity in Cancer database for therapeutic drug response prediction of signature-defined BRCA patient groupings for our selected TCGA population. The signature also predicts sensitivity to chemotherapeutic and molecular-targeted agents in high- and low-risk patients afflicted with BRCA. Functional analysis suggested JAK STAT, VEGF, MAPK, NOTCH TOLL-like receptor, NOD-like receptor signaling pathways, apoptosis, and cancer-based pathways could be key for ZNF-related BRCA development. Interestingly, based on the results of ESTIMATE, ssGSEA, and GSEA analysis, we elucidated that our ZNF-gene signature had pivotal regulatory effects on the tumor immune microenvironment for BRCA.

Conclusion

Our findings shed light on the potential contribution of ZNFs to the pathogenesis of BRCA and may inform clinical practice to guide individualized treatment.

ZMYND10, an epigenetically regulated tumor suppressor, exerts tumor-suppressive functions via miR145-5p/NEDD9 axis in breast cancer

Background

Recent studies suggested that ZMYND10 is a potential tumor suppressor gene in multiple tumor types. However, the mechanism by which ZMYND10 inhibits breast cancer remains unclear. Here, we investigated the role and mechanism of ZMYND10 in breast cancer inhibition.

Results

ZMYND10 was dramatically reduced in multiple breast cancer cell lines and tissues, which was associated with promoter hypermethylation. Ectopic expression of ZMYND10 in silenced breast cancer cells induced cell apoptosis while suppressed cell growth, cell migration and invasion in vitro, and xenograft tumor growth in vivo. Furthermore, molecular mechanism studies indicated that ZMYND10 enhances expression of miR145-5p, which suppresses the expression of NEDD9 protein through directly targeting the 3'-untranslated region of NEDD9 mRNA.

Conclusions

Results from this study show that ZMYND10 suppresses breast cancer tumorigenicity by inhibiting the miR145-5p/NEDD9 signaling pathway. This novel discovered signaling pathway may be a valid target for small molecules that might help to develop new therapies to better inhibit the breast cancer metastasis.

Tumor suppressor BLU promotes TRAIL-induced apoptosis by downregulating NF-κB signaling in nasopharyngeal carcinoma

A putative tumor suppressor BLU mapped on the chromosomal 3p21 region, is frequently lost in human tumors including nasopharyngeal carcinoma (NPC). To explore the underlying mechanism of tumor suppression by BLU, its potential to promote apoptosis induced by TRAIL, an effector molecule elaborated by natural killer-T (NKT) cells was investigated. BLU was re-expressed in NPC-derived HNE1 cells by recombinant adenoviral infection and the cells were challenged with recombinant TRAIL. The growth inhibition of BLU was assayed and apoptosis was examined by flow cytometry-based tetramethylrhodamine ethyl ester (TMRE) and annexin V staining, cleavage of pro-caspase-8 and poly ADP ribose polymerase (PARP). The modulation of NF-κB pathway by BLU was evaluated by the reporter activity and estimation of the level of the molecules involved such as IKKalpha, p65 NF-κB, as well as NF-κB induced anti-apoptotic factors cFLIPL and cIAP2. The expression of BLU exerted in vitro and in vivo growth inhibitory effect and promoted TRAIL-induced apoptosis. This phenomenon was validated by FACS-based assays of mitochondrial membrane potential (BLU vs. Vector 87.8% ± 7.7% and 72.1%±6.7% at 6h exposure to TRAIL) and phosphatidylserine turnover (BLU vs. vector: 28.7%±2.9% and 22.6%±2.5%), as well as, enhanced caspapse-8 cleavage. Similar with the findings that BLU promotes chemotherapeutic agent-induced apoptosis, it also augmented death receptor-induced pathway through NF-κB pathway inhibition. In conclusion, BLU suppressed tumor formation by strengthening the antitumor immunity.

Integration and bioinformatics analysis of DNA-methylated genes associated with drug resistance in ovarian cancer

The main obstacle to the successful treatment of ovarian cancer is the development of drug resistance to combined chemotherapy. Among all the factors associated with drug resistance, DNA methylation apparently plays a critical role. In this study, we performed an integrative analysis of the 26 DNA-methylated genes associated with drug resistance in ovarian cancer, and the genes were further evaluated by comprehensive bioinformatics analysis including gene/protein interaction, biological process enrichment and annotation. The results from the protein interaction analyses revealed that at least 20 of these 26 methylated genes are present in the protein interaction network, indicating that they interact with each other, have a correlation in function, and may participate as a whole in the regulation of ovarian cancer drug resistance. There is a direct interaction between the phosphatase and tensin homolog (PTEN) gene and at least half of the other genes, indicating that PTEN may possess core regulatory functions among these genes. Biological process enrichment and annotation demonstrated that most of these methylated genes were significantly associated with apoptosis, which is possibly an essential way for these genes to be involved in the regulation of multidrug resistance in ovarian cancer. In addition, a comprehensive analysis of clinical factors revealed that the methylation level of genes that are associated with the regulation of drug resistance in ovarian cancer was significantly correlated with the prognosis of ovarian cancer. Overall, this study preliminarily explains the potential correlation between the genes with DNA methylation and drug resistance in ovarian cancer. This finding has significance for our understanding of the regulation of resistant ovarian cancer by methylated genes, the treatment of ovarian cancer, and improvement of the prognosis of ovarian cancer.

Tumor suppressor genes and their underlying interactions in paclitaxel resistance in cancer therapy

Objectives

Paclitaxel (PTX) is frequently used in the clinical treatment of solid tumors. But the PTX-resistance is a great obstacle in cancer treatment. Exploration of the mechanisms of drug resistance suggests that tumor suppressor genes (TSGs) play a key role in the response of chemotherapeutic drugs. TSGs, a set of genes that are often inactivated in cancers, can regulate various biological processes. In this study, an overview of the contribution of TSGs to PTX resistance and their underlying relationship in cancers are reported by using GeneMANIA, a web-based tool for gene/protein function prediction.

Methods

Using PubMed online database and Google web site, the terms “paclitaxel resistance” or “taxol resistance” or “drug resistance” or “chemotherapy resistance”, and “cancer” or “carcinoma”, and “tumor suppressor genes” or “TSGs” or “negative regulated protein” or “antioncogenes” were searched and analyzed. GeneMANIA data base was used to predict gene/protein interactions and functions.

Results

We identified 22 TSGs involved in PTX resistance, including BRCA1, TP53, PTEN, APC, CDKN1A, CDKN2A, HIN-1, RASSF1, YAP, ING4, PLK2, FBW7, BLU, LZTS1, REST, FADD, PDCD4, TGFBI, ING1, Bax, PinX1 and hEx. The TSGs were found to have direct and indirect relationships with each other, and thus they could contribute to PTX resistance as a group. The varied expression status and regulation function of the TSGs on cell cycle in different cancers might play an important role in PTX resistance.

Conclusion

A further understanding of the roles of tumor suppressor genes in drug resistance is an important step to overcome chemotherapy tolerance. Tumor suppressor gene therapy targets the altered genes and signaling pathways and can be a new strategy to reverse chemotherapy resistance.

Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity

Many complex traits, as drug response, are associated with changes in biological pathways rather than being caused by single gene alterations. Here, a predictive framework is presented in which gene expression data are recoded into activity statuses of signal transduction circuits (sub-pathways within signaling pathways that connect receptor proteins to final effector proteins that trigger cell actions). Such activity values are used as features by a prediction algorithm which can efficiently predict a continuous variable such as the IC50 value. The main advantage of this prediction method is that the features selected by the predictor, the signaling circuits, are themselves rich-informative, mechanism-based biomarkers which provide insight into or drug molecular mechanisms of action (MoA).

Inactivation of BLU is associated with methylation of Sp1-binding site of BLU promoter in gastric cancer

BLU is a candidate tumor suppressor gene, which is epigenetically inactivated in many human malignancies. However, the expression and biological functions of BLU in gastric cancer has not yet been reported. In the present study, we identified a functional BLU promoter which was regulated by the transcription activator Sp1. Bisulfite sequencing and qRT-PCR assays indicated that the silence of BLU expression in gastric cancer was significantly associated with DNA hypermethylation of BLU promoter including -39 CpG site located in the Sp1 transcription element. The expression of BLU was notably restored in AGS and SGC7901 cells following the demethylation-treatment with 5'-Aza-2'-deoxycytidine. Moreover, the results from ChIP, EMSA and luciferase reporter gene showed that -39 CpG methylation could prevent Sp1 from binding to the promoter of BLU and decreased transcription activity of the BLU gene by ~70%. In addition, knockdown of BLU significantly promoted cellular proliferation and colony formation in gastric cancer cells. In conclusion, we identified a novel functional BLU promoter and proved that BLU promoter activity was regulated by Sp1. Furthermore, we found that hypermethylated -39 CpG in BLU proximal promoter directly reduced its binding with Sp1, which may be one of the mechanisms accounting for the inactivation of BLU in gastric cancer.

Noncoding RNA blockade of autophagy is therapeutic in medullary thyroid cancer

Micro-RNAs are dysregulated in medullary thyroid carcinoma (MTC) and preliminary studies have shown that miRNAs may enact a therapeutic effect through changes in autophagic flux. Our aim was to study the in vitro effect of miR-9-3p on MTC cell viability, autophagy and to investigate the mRNA autophagy gene profile of sporadic versus hereditary MTC. The therapeutic role of miR-9-3p was investigated in vitro using human MTC cell lines (TT and MZ-CRC-1 cells), cell viability assays, and functional mechanism studies with a focus on cell cycle, apoptosis, and autophagy. Post-miR-9-3p transfection mRNA profiling of cell lines was performed using a customized, quantitative RT-PCR gene array card. This card was also run on clinical tumor samples (sporadic: n = 6; hereditary: n = 6) and correlated with clinical data. Mir-9-3p transfection resulted in reduced in vitro cell viability; an effect mediated through autophagy inhibition. This was accompanied by evidence of G2 arrest in the TT cell line and increased apoptosis in both cell lines. Atg5 was validated as a predicted miR-9-3p mRNA target in TT cells. Post-miR-9-3p transfection array studies showed a significant global decline in autophagy gene expression (most notably in PIK3C3, mTOR, and LAMP-1). Autophagy gene mRNAs were generally overexpressed in sporadic (vs. hereditary MTC) and Beclin-1 overexpression was shown to correlate with residual disease. Autophagy is a tumor cell survival mechanism in MTC that when disabled, is of therapeutic advantage. Beclin-1 expression may be a useful prognostic biomarker of aggressive disease.

Anti-angiogenic pathway associations of the 3p21.3 mapped BLU gene in nasopharyngeal carcinoma

Zinc-finger, MYND-type containing 10 (ZMYND10), or more commonly called BLU, expression is frequently downregulated in nasopharyngeal carcinoma (NPC) and many other tumors due to promoter hypermethylation. Functional evidence shows that the BLU gene inhibits tumor growth in animal assays, but the detailed molecular mechanism responsible for this is still not well understood. In current studies, we find that 93.5% of early-stage primary NPC tumors show downregulated BLU expression. Using a PCR array, overexpression of the BLU gene was correlated to the angiogenesis network in NPC cells. Moreover, expression changes of the MMP family, VEGF and TSP1, were often detected in different stages of NPC, suggesting the possibility that BLU may be directly involved in the microenvironment and anti-angiogenic activity in NPC development. Compared with vector-alone control cells, BLU stable transfectants, derived from poorly-differentiated NPC HONE1 cells, suppress VEGF165, VEGF189 and TSP1 expression at both the RNA and protein levels, and significantly reduce the secreted VEGF protein in these cells, reflecting an unknown regulatory mechanism mediated by the BLU gene in NPC. Cells expressing BLU inhibited cellular invasion, migration and tube formation. These in vitro results were further confirmed by in vivo tumor suppression and a matrigel plug angiogenesis assay in nude mice. Tube-forming ability was clearly inhibited, when the BLU gene is expressed in these cells. Up to 70-90% of injected tumor cells expressing increased exogenous BLU underwent cell death in animal assays. Overexpressed BLU only inhibited VEGF165 expression in differentiated squamous NPC HK1 cells, but also showed an anti-angiogenic effect in the animal assay, revealing a complicated mechanism regulating angiogenesis and the microenvironment in different NPC cell lines. Results of these studies indicate that alteration of BLU gene expression influences anti-angiogenesis pathways and is important for the development of NPC.