BLU enhances the effects of anti-angiogenic activity in combination with gemcitabine-based chemotherapeutic agents

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.

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.

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.