Low expression of microRNA-1908 predicts a poor prognosis for patients with ovarian cancer

Teng, Changcai; Zheng, Hong

doi:10.3892/ol.2017.6714

Cited by 29 publications

(22 citation statements)

References 20 publications

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“…At present, several miRNAs are known to be useful in the early diagnosis of cancers, including miR-21[ 19 ], miR-486[ 20 ], miR-24[ 21 ], and miR-125a-5p[ 22 ]. In addition, miR-191[ 23 ], miR-1908[ 24 ], miR-200c[ 25 ], and miR-217[ 26 ] were found to be potential prognostic indictors in cancer. However, these studies only used a single indictor or a limited number of patients for survival analysis.…”

Section: Discussionmentioning

confidence: 99%

Three-microRNA signature identified by bioinformatics analysis predicts prognosis of gastric cancer patients

Zhang

Dai

2018

WJG

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AIMTo identify multiple microRNAs (miRNAs) for predicting the prognosis of gastric cancer (GC) patients by bioinformatics analysis.METHODSThe original microarray dataset GSE93415, which included 20 GC and 20 tumor adjacent normal gastric mucosal tissues, was downloaded from the Gene Expression Omnibus database and used for screening differentially expressed miRNAs (DEMs). The cut-off criteria were P < 0.05 and fold change > 2.0. In addition, we acquired the miRNA expression profiles and clinical information of 361 GC patients from The Cancer Genome Atlas database to assess the prognostic role of the DEMs. The target genes of miRNAs were predicted using TargetScan, miRDB, miRWalk, and DIANA, and then the common target genes were selected for functional enrichment analysis.RESULTSA total of 110 DEMs including 19 up-regulated and 91 down-regulated miRNAs were identified between 20 pairs of GC and tumor adjacent normal tissues, and the Kaplan-Meier survival analysis found that a three-miRNA signature (miR-145-3p, miR-125b-5p, and miR-99a-5p) had an obvious correlation with the survival of GC patients. Furthermore, univariate and multivariate Cox regression analyses indicated that the three-miRNA signature could be a significant prognostic marker in GC patients. The common target genes of the three miRNAs are added up to 108 and used for Gene Functional Enrichment analysis. Biological Process and Molecular Function analyses showed that the target genes are involved in cell recognition, gene silencing and nucleic acid binding, transcription factor activity, and transmembrane receptor activity. Cellular Component analysis revealed that the genes are portion of nucleus, chromatin silencing complex, and TORC1/2 complex. Biological Pathway analysis indicated that the genes participate in several cancer-related pathways, such as the focal adhesion, PI3K, and mTOR signaling pathways.CONCLUSIONThis study justified that a three-miRNA signature could play a role in predicting the survival of GC patients.

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Section: Discussionmentioning

confidence: 99%

Three-microRNA signature identified by bioinformatics analysis predicts prognosis of gastric cancer patients

Zhang

Dai

2018

WJG

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“…Additionally, another SLRP family member, decorin, binds to EGFR and lowers receptor levels by caveolin-mediated internalization ( Zhu et al, 2005 ; Seidler et al, 2006 ; Ma et al, 2014 ). High expression of PODNL1 correlates with poor prognosis in ovarian cancer ( Teng and Zheng, 2017 ). Methylation of the PODNL1 gene may be important for phenotypic changes that occur during aging ( Heyn et al, 2013 ), and PODNL1 expression is associated with high-grade glioma ( Yan et al, 2013 ).…”

Section: Emerging Targets In Glioblastomamentioning

confidence: 99%

Current Challenges and Opportunities in Treating Glioblastoma

et al. 2018

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Glioblastoma multiforme (GBM), the most common and aggressive primary brain tumor, has a high mortality rate despite extensive efforts to develop new treatments. GBM exhibits both intra- and intertumor heterogeneity, lending to resistance and eventual tumor recurrence. Large-scale genomic and proteomic analysis of GBM tumors has uncovered potential drug targets. Effective and “druggable” targets must be validated to embark on a robust medicinal chemistry campaign culminating in the discovery of clinical candidates. Here, we review recent developments in GBM drug discovery and delivery. To identify GBM drug targets, we performed extensive bioinformatics analysis using data from The Cancer Genome Atlas project. We discovered 20 genes, BOC, CLEC4GP1, ELOVL6, EREG, ESR2, FDCSP, FURIN, FUT8-AS1, GZMB, IRX3, LITAF, NDEL1, NKX3-1, PODNL1, PTPRN, QSOX1, SEMA4F, TH, VEGFC, and C20orf166AS1 that are overexpressed in a subpopulation of GBM patients and correlate with poor survival outcomes. Importantly, nine of these genes exhibit higher expression in GBM versus low-grade glioma and may be involved in disease progression. In this review, we discuss these proteins in the context of GBM disease progression. We also conducted computational multi-parameter optimization to assess the blood-brain barrier (BBB) permeability of small molecules in clinical trials for GBM treatment. Drug delivery in the context of GBM is particularly challenging because the BBB hinders small molecule transport. Therefore, we discuss novel drug delivery methods, including nanoparticles and prodrugs. Given the aggressive nature of GBM and the complexity of targeting the central nervous system, effective treatment options are a major unmet medical need. Identification and validation of biomarkers and drug targets associated with GBM disease progression present an exciting opportunity to improve treatment of this devastating disease.

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“…As shown, in both experimental conditions we observed a variable number of deregulated genes, mainly related to EMT, cellular adhesion, extracellular matrix remodeling, invasion and other cell activities, while a distinct cluster of genes was observed to be deregulated exclusively in cells co-cultured with ML-Ddx4 + cells from the A2 patient ( Figure 5 c). In particular, upregulated DEGs included SIRT1 , which is involved in stemness [ 28 ] and chemoresistance [ 29 ], SNAIL2, which participates in EMT and collagen remodeling [ 30 , 31 ], and SIRT2 , CTGF , IL-11 and MMP13 , involved in cell migration, invasiveness as well as resistance to platinum and paclitaxel [ 32 , 33 , 34 , 35 , 36 ]. Other upregulated DEGs, such as MCM-6 , TGFB-1 , HMGA2 and FOXM1 , are involved in similar cancer-related processes [ 37 , 38 , 39 , 40 , 41 , 42 ], while downregulated DEGs, such as LOX and TIMP-1 (which are associated with poor cancer prognosis [ 43 , 44 , 45 ]), were observed in A2780 co-cultured with both A1 and A2 derived ML-Ddx4 + cells.…”

Section: Resultsmentioning

confidence: 99%

DEAD-Box Helicase 4 (Ddx4)+ Stem Cells Sustain Tumor Progression in Non-Serous Ovarian Cancers

D’Oronzo

Silvestris

Lovero

et al. 2020

IJMS

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DEAD-Box Helicase 4 (Ddx4)+ ovarian stem cells are able to differentiate into several cell types under appropriate stimuli. Ddx4 expression has been correlated with poor prognosis of serous ovarian cancer (OC), while the potential role of Ddx4+ cells in non-serous epithelial OC (NS-EOC) is almost unexplored. The aim of this study was to demonstrate the presence of Ddx4+ cells in NS-EOC and investigate the effect of follicle-stimulating hormone (FSH) on this population. Increased Ddx4 expression was demonstrated in samples from patients with advanced NS-EOC, compared to those with early-stage disease. Under FSH stimulation, OC-derived Ddx4+ cells differentiated into mesenchymal-like (ML) cells, able to deregulate genes involved in cell migration, invasiveness, stemness and chemoresistance in A2780 OC cells. This effect was primarily induced by ML-cells deriving from advanced NS-EOC, suggesting that a tumor-conditioned germ cell niche inhabits its microenvironment and is able to modulate, in a paracrine manner, tumor cell behavior through transcriptome modulation.

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Low expression of microRNA-1908 predicts a poor prognosis for patients with ovarian cancer

Cited by 29 publications

References 20 publications

Three-microRNA signature identified by bioinformatics analysis predicts prognosis of gastric cancer patients

Three-microRNA signature identified by bioinformatics analysis predicts prognosis of gastric cancer patients

Current Challenges and Opportunities in Treating Glioblastoma

DEAD-Box Helicase 4 (Ddx4)+ Stem Cells Sustain Tumor Progression in Non-Serous Ovarian Cancers

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