Expression of MMP9, SERPINE1 and miR-134 as prognostic factors in esophageal cancer

Klimczak-Bitner, Anna Agnieszka; Kordek, Radzisław; Bitner, Jan; Musiał, Jacek; Szemraj, Janusz

doi:10.3892/ol.2016.5211

Cited by 29 publications

(20 citation statements)

References 28 publications

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“… 20 Klimczak-Bitner et al demonstrated that the expression of SERPINE1 may be one of the key prognostic genes in esophageal cancer. 21 Pavón et al reported that overexpression of SERPINE1 enhances tumor cell migration and invasion. 22 We found that SERPINE1 was significantly upregulated in gastric tissues and SERPINE1 high expression associated with poor survival.…”

Section: Discussionmentioning

confidence: 99%

Genome-scale analysis identifies SERPINE1 and SPARC as diagnostic and prognostic biomarkers in gastric cancer

Liao¹,

Li²,

Liu³

et al. 2018

OTT

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BackgroundGastric cancer (GC) is one of the most common types of malignancy and is associated with high morbidity and mortality rates around the world. With poor clinical outcomes, potential biomarkers for diagnosis and prognosis are important to investigate.ObjectiveThe aim of this study is to investigate the gene expression module of GC and to identify potential diagnostic and prognostic biomarkers.MethodMicroarray data (GSE13911, GSE29272, GSE54129, and GSE79973), including 293 stomach tumor tissues and 196 normal tissues, were analyzed to identify differentially expressed genes (DEGs). DEGs were identified in four profiles by intersecting four overlapping subsets, including 90 downregulated and 45 upregulated DEGs in common. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway analyses have been showed that extracellular matrix was the most enriched signal pathway. Furthermore, hub genes were analyzed by protein–protein interaction network and clinical outcomes were assessed by Kaplan–Meier survival analysis. Two independent datasets were used to validate the differential expression of two hub genes: Serpin Family E Member 1 (SERPINE1) and Secreted Protein Acidic and Cysteine Rich (SPARC).ResultsValidation of independent datasets indicated that SERPINE1 and SPARC expression were drastically increased in gastric tumor tissues and associated with poor outcomes in GC patients. The expression of SERPINE1 was related to race (Asian and White) (P< 0.05).ConclusionSERPINE1 and SPARC were significantly upregulated in gastric tissues and associated with poor outcomes. The investigations of SERPINE1 and SPARC may promote their predictive and prognostic value in GC.

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Section: Discussionmentioning

confidence: 99%

Genome-scale analysis identifies SERPINE1 and SPARC as diagnostic and prognostic biomarkers in gastric cancer

Liao¹,

Li²,

Liu³

et al. 2018

OTT

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“…Moreover, it has been demonstrated that the miRNA profile of tissues exhibits characteristic changes in certain types of tumors [19,20]. A number of miRNAs have been shown to participate in tumor progression, invasion, and metastasis, including miR-134 [21], miR-145 [22], miR-625 [23], and miR1294 [24]. However, due to clinical heterogeneity, sample insufficiency, and use of various data processing methods, there is inconsistency in the results of these studies.…”

Section: Discussionmentioning

confidence: 99%

A Novel Three-miRNA Signature Identified Using Bioinformatics Predicts Survival in Esophageal Carcinoma

Zhang

Dai

2020

BioMed Research International

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Objective. We identified differentially expressed microRNAs (DEMs) between esophageal carcinoma (ESCA) tissues and normal esophageal tissues. We then constructed a novel three-miRNA signature to predict the prognosis of ESCA patients using bioinformatics analysis. Materials and Methods. We combined two microarray profiling datasets from the Gene Expression Omnibus (GEO) database and RNA-seq datasets from the Cancer Genome Atlas (TCGA) database to analyze DEMs in ESCA. The clinical data from 168 ESCA patients were selected from the TCGA database to assess the prognostic role of the DEMs. The TargetScan, miRDB, miRWalk, and DIANA websites were used to predict the miRNA target genes. Functional enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery (David), and protein-protein interaction (PPI) networks were obtained using the Search Tool for the Retrieval of Interacting Genes database (STRING). Results. With cut-off criteria of P<0.05 and |log2FC| > 1.0, 33 overlapping DEMs, including 27 upregulated and 6 downregulated miRNAs, were identified from GEO microarray datasets and TCGA RNA-seq count datasets. The Kaplan–Meier survival analysis indicated that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) was significantly associated with the overall survival of ESCA patients. The results of univariate and multivariate Cox regression analysis showed that the three-miRNA signature was a potential prognostic factor in ESCA. Furthermore, the gene functional enrichment analysis revealed that the target genes of the three miRNAs participate in various cancer-related pathways, including viral carcinogenesis, forkhead box O (FoxO), vascular endothelial growth factor (VEGF), human epidermal growth factor receptor 2 (ErbB2), and mammalian target of rapamycin (mTOR) signaling pathways. In the PPI network, three target genes (MAPK1, RB1, and CLTC) with a high degree of connectivity were selected as hub genes. Conclusions. Our results revealed that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) is a potential novel prognostic biomarker for ESCA.

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“…40 Another study suggested that increased MMP9 expression was associated with gastric cancer cell invasion. 41 In addition, MMP9 activity has been reported to be correlated with prognosis of other cancers, including cancers of the lung, 42 colorectum, 43 esophagus, 44 and breast. 45 Importantly, transcript levels of MMP9 were also observed to be increased in melanoma tumors, compared with that of melanocyte controls.…”

Section: Discussionmentioning

confidence: 99%

Genetic variants in the metzincin metallopeptidase family genes predict melanoma survival

Wang

Liu

et al. 2017

Molecular Carcinogenesis

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Metzincins are key molecules in the degradation of the extracellular matrix and play an important role in cellular processes such as cell migration, adhesion, and cell fusion of malignant tumors, including cutaneous melanoma (CM). We hypothesized that genetic variants of the metzincin metallopeptidase family genes would be associated with CM-specific survival (CMSS). To test this hypothesis, we first performed Cox proportional hazards regression analysis to evaluate the associations between genetic variants of 75 metzincin metallopeptidase family genes and CMSS using the dataset from the genome-wide association study (GWAS) from The University of Texas MD Anderson Cancer Center (MDACC) which included 858 non-Hispanic white patients with CM, and then validated using the dataset from the Harvard GWAS study which had 409 non-Hispanic white patients with invasive CM. Four independent SNPs (MMP16 rs10090371 C>A, ADAMTS3 rs788935 T>C, TLL2 rs10882807 T>C and MMP9 rs3918251 A>G) were identified as predictors of CMSS, with a variant-allele attributed hazards ratio (HR) of 1.73 (1.32-2.29, 9.68E-05), 1.46 (1.15-1.85, 0.002), 1.68 (1.31-2.14, 3.32E-05) and 0.67 (0.51-0.87, 0.003), respectively, in the meta-analysis of these two GWAS studies. Combined analysis of risk genotypes of these four SNPs revealed a decreased CMSS in a dose-response manner as the number of risk genotypes increased (P < 0.001). An improvement was observed in the prediction model (area under the curve [AUC] = 81.4% vs. 78.6%), when these risk genotypes were added to the model containing non-genotyping variables. Our findings suggest that these genetic variants may be promising prognostic biomarkers for CMSS.

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Expression of MMP9, SERPINE1 and miR-134 as prognostic factors in esophageal cancer

Cited by 29 publications

References 28 publications

Genome-scale analysis identifies SERPINE1 and SPARC as diagnostic and prognostic biomarkers in gastric cancer

Genome-scale analysis identifies SERPINE1 and SPARC as diagnostic and prognostic biomarkers in gastric cancer

A Novel Three-miRNA Signature Identified Using Bioinformatics Predicts Survival in Esophageal Carcinoma

Genetic variants in the metzincin metallopeptidase family genes predict melanoma survival

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