ESR1 methylation in primary tumors and paired circulating tumor DNA of patients with high-grade serous ovarian cancer

Giannopoulou, Lydia; Mastoraki, Sophia; Buderath, Paul; Strati, Αreti; Pavlakis, Kitty; Kasimir‐Bauer, Sabine; Lianidou, Evi

doi:10.1016/j.ygyno.2018.05.026

Cited by 45 publications

(29 citation statements)

References 39 publications

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“…In addition, there are also reports on the gene expression and prognosis of ovarian cancer for other genes. For example, the degree of methylation of ESR1 in normal ovarian tissues is higher than that in OC tissues, [ 8 ] and patients with hypermethylation of ESR1 in ovarian cancer tissues have better OS, [ 23 ] which is consistent with our results. The association between the degree of ESR1 methylation and the prognosis of OC is more significant in serous and mucinous tissues.…”

Section: Discussionsupporting

confidence: 90%

“…Numerous studies have shown that PTEN, as a key link, is involved in the PI3K/AKT/PTEN drug-resistance pathway and participates in drug resistance in OC by affecting biological processes, such as DNA methylation, cell cycle, apoptosis, and cell proliferation. [ 11 , 20 – 22 ] In addition, it had been reported that changes in gene methylation of ESR1 [ 23 , 24 ] are involved in the development and drug resistance in OC and are associated with prognosis. With reference to MDM2 and CD44, although no previous studies have shown that changes in methylation are associated with OC and drug resistance in OC, numerous studies have indicated that both MDM2 and CD44 genes are involved in drug resistance in OC, and are related to the prognosis of OC.…”

Section: Resultsmentioning

confidence: 99%

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Big data-based identification of methylated genes associated with drug resistance and prognosis in ovarian cancer

et al. 2020

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It is imperative to further the understanding of the drug resistance mechanisms of ovarian cancer (OC) and to identify useful biological markers for prognosis prediction. Cormine, cBioportal, and The Cancer Genome Atlas databases were used to search microarray data of gene methylation related to OC, drug resistance in OC, and prognosis, and to analyze methylated genes potentially inducing the drug resistance in OC. Fifty-five DNA-methylated genes significantly associated with drug resistance in OC were screened, and the regulatory mechanisms underlying changes in methylation levels of these genes were systematically integrated. Enrichment and annotation of biological processes indicated that most of the above DNA-methylated genes were significantly associated with cell proliferation and cell cycle. In addition, pathway enrichment demonstrated that the above DNA-methylated genes were significantly associated with PI3K-AKT and P53 signaling pathways. Among the 55 genes, 4 were significantly associated with OC prognostic disease-free survival, namely bromodomain containing 4, PDZ domain containing 1 ( PDZK1) , phosphatase and tensin homolog, and TNF receptor superfamily member 10c; 5 were significantly related to overall survival, namely bromodomain containing 4, PDZK1 , PIK3C2B , Rh associated glycoprotein, and DYRK ; among them, the degree of methylation of TNF receptor superfamily member 10c, PDZK1 , and Rh associated glycoprotein genes was significantly correlated with mRNA expression. Furthermore, PDZK1 , Rh associated glycoprotein, and TNF receptor superfamily member 10c genes showed significant hypomethylation in drug-resistance tissues of OC, and their mRNAs had significantly high expression. The association between the methylation of these 55 genes and OC and drug resistance in OC, in addition to bioinformatics analyses clarify the important mechanisms of gene methylation in the development, progression, and drug resistance of OC.

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Section: Discussionsupporting

confidence: 90%

Section: Resultsmentioning

confidence: 99%

Big data-based identification of methylated genes associated with drug resistance and prognosis in ovarian cancer

et al. 2020

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“…The most important of these involves the biological importance of our data, which is related to the cell cycle, cellular assembly and organization, DNA replication, recombination, and repair. The central node is ESR1, which has been the focus of breast cancer research for some time and also has clinical implications in endometrial [ 27 ], ovarian [ 28 ], and other types of cancers.…”

Section: Discussionmentioning

confidence: 99%

Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

Chen

Ling

et al. 2020

BioMed Research International

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Background. The molecular mechanism by which hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) is still unknown. The genomic expression profile and bioinformatics methods were used to investigate the potential pathogenesis and therapeutic targets for HBV-associated HCC (HBV-HCC). Methods. The microarray dataset GSE55092 was downloaded from the Gene Expression Omnibus (GEO) database. The data was analyzed by the bioinformatics software to find differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, ingenuity pathway analysis (IPA), and protein-protein interaction (PPI) network analysis were then performed on DEGs. The hub genes were identified using Centiscape2.2 and Molecular Complex Detection (MCODE) in the Cytoscape software (Cytoscape_v3.7.2). The survival data of these hub genes was downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA). Results. A total of 2264 mRNA transcripts were differentially expressed, including 764 upregulated and 1500 downregulated in tumor tissues. GO analysis revealed that these DEGs were related to the small-molecule metabolic process, xenobiotic metabolic process, and cellular nitrogen compound metabolic process. KEGG pathway analysis revealed that metabolic pathways, complement and coagulation cascades, and chemical carcinogenesis were involved. Diseases and biofunctions showed that DEGs were mainly associated with the following diseases or biological function abnormalities: cancer, organismal injury and abnormalities, gastrointestinal disease, and hepatic system disease. The top 10 upstream regulators were predicted to be activated or inhibited by Z-score and identified 25 networks. The 10 genes with the highest degree of connectivity were defined as the hub genes. Cox regression revealed that all the 10 genes (CDC20, BUB1B, KIF11, TTK, EZH2, ZWINT, NDC80, TPX2, MELK, and KIF20A) were related to the overall survival. Conclusion. Our study provided a registry of genes that play important roles in regulating the development of HBV-HCC, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of HCC.

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“…For example, the C2 CD4 D , WNT6 and COL23 A1 genes’ methylation status is not only significantly altered in OC patients’ ctDNA, but different responses to platinum-based therapy can also be associated with their methylation levels [53]. Moreover, Giannopolou et al [54] discovered altered ESR1 gene methylation levels in the ctDNA samples of high-grade serous OC patients, and these abnormalities are very similar to those in primary tumours [54].…”

Section: Discussionmentioning

confidence: 99%

Aberrant Methylation Status of Tumour Suppressor Genes in Ovarian Cancer Tissue and Paired Plasma Samples

Dvorska

Braný

Nagy

et al. 2019

IJMS

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Ovarian cancer is a highly heterogeneous disease and its formation is affected by many epidemiological factors. It has typical lack of early signs and symptoms, and almost 70% of ovarian cancers are diagnosed in advanced stages. Robust, early and non-invasive ovarian cancer diagnosis will certainly be beneficial. Herein we analysed the regulatory sequence methylation profiles of the RASSF1, PTEN, CDH1 and PAX1 tumour suppressor genes by pyrosequencing in healthy, benign and malignant ovarian tissues, and corresponding plasma samples. We recorded statistically significant higher methylation levels (p < 0.05) in the CDH1 and PAX1 genes in malignant tissues than in controls (39.06 ± 18.78 versus 24.22 ± 6.93; 13.55 ± 10.65 versus 5.73 ± 2.19). Higher values in the CDH1 gene were also found in plasma samples (22.25 ± 14.13 versus 46.42 ± 20.91). A similar methylation pattern with positive correlation between plasma and benign lesions was noted in the CDH1 gene (r = 0.886, p = 0.019) and malignant lesions in the PAX1 gene (r = 0.771, p < 0.001). The random forest algorithm combining methylation indices of all four genes and age determined 0.932 AUC (area under the receiver operating characteristic (ROC) curve) prediction power in the model classifying malignant lesions and controls. Our study results indicate the effects of methylation changes in ovarian cancer development and suggest that the CDH1 gene is a potential candidate for non-invasive diagnosis of ovarian cancer.

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ESR1 methylation in primary tumors and paired circulating tumor DNA of patients with high-grade serous ovarian cancer

Cited by 45 publications

References 39 publications

Big data-based identification of methylated genes associated with drug resistance and prognosis in ovarian cancer

Big data-based identification of methylated genes associated with drug resistance and prognosis in ovarian cancer

Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

Aberrant Methylation Status of Tumour Suppressor Genes in Ovarian Cancer Tissue and Paired Plasma Samples

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