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The DNA methylation-regulated MCTP1 activates the drug-resistance of esophageal cancer cells.

ABSTRACT: Accumulating studies have demonstrated that drug-resistance remains a great obstacle for the effective treatment of cancers. Esophageal cancer is still one of the most common cancers worldwide, which also suffers from the drug-resistance during clinical treatment. Here we performed drug-resistance profiling assays and identified several drug-resistant and drug-sensitive esophageal cancer cell lines. The following methylation sequencing showed that the MCTP1 gene is hypermethylated in the drug-resistant esophageal cancer cells. As a result, the expression of MCTP1 is down-regulated in the drug-resistant esophageal cancer cells. Down-regulation of MCTP1 also affects the migration and apoptosis of esophageal cancer cells, as revealed by the wound-healing and apoptosis assays. Further investigations proposed two signaling pathways that might involve in the MCTP1-mediated drug-resistance of esophageal cancer cells. All these results suggested that MCTP1 activates the drug-resistance of esophageal cancer cells, which has implications for further design of new biomarker of esophageal cancer treatment.

SUBMITTER: Kong L

PROVIDER: S-EPMC7906193 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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The DNA methylation-regulated MCTP1 activates the drug-resistance of esophageal cancer cells.

Kong Lingsuo L Yang Wan W Chen Lanren L Qian Liting L

Aging 20210211 3

Accumulating studies have demonstrated that drug-resistance remains a great obstacle for the effective treatment of cancers. Esophageal cancer is still one of the most common cancers worldwide, which also suffers from the drug-resistance during clinical treatment. Here we performed drug-resistance profiling assays and identified several drug-resistant and drug-sensitive esophageal cancer cell lines. The following methylation sequencing showed that the MCTP1 gene is hypermethylated in the drug-re ...[more]

PMID: 33571139

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Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) is one of the most severe cancers and is characterized by chemotherapy resistance and poor prognosis associated with epithelial-mesenchymal transition (EMT). In a previous study, a low mitochondrial DNA (mtDNA) copy number was associated with poorer prognosis and induced EMT in ESCC. However, the detailed mechanism related to mtDNA copy number and EMT is unclear. The aim of this study was to clarify the mechanism by which a change in mtDNA copy number contributes to EMT and to examine treatment of chemotherapy resistance in ESCC.MethodsThe association between low mtDNA copy number and chemotherapy resistance was investigated using specimens from 88 patients who underwent surgery after neoadjuvant chemotherapy. Then, the mtDNA content of human ESCC cell lines, TE8 and TE11, was depleted by knockdown of mitochondrial transcription factor A expression. The present study focused on modulation of mitochondrial membrane potential (MMP) and DNA methylation as the mechanisms by which mtDNA copy number affects EMT. mRNA and protein expression, chemotherapy sensitivity, proliferation, MMP and DNA methylation were evaluated, and in vitro and in vivo assays were conducted to clarify these mechanisms.ResultsESCC patients with decreased mtDNA copy number who underwent R0 resection after neoadjuvant chemotherapy had significantly worse pathological response and recurrence-free survival. Additionally, low mtDNA copy number was associated with resistance to chemotherapy in vitro and in vivo. mtDNA controlled MMP, and MMP depolarization induced EMT. Depletion of mtDNA and low MMP induced DNA methylation via a DNA methylation transcription factor (DNMT), and a DNMT inhibitor suppressed EMT and improved chemotherapy sensitivity in mtDNA-depleted ESCC cells, as shown by in vitro and in vivo assays.ConclusionThis study showed that decreased mtDNA copy number induced EMT via modulation of MMP and DNA methylation in ESCC. Therapeutic strategies increasing mtDNA copy number and DNMT inhibitors may be effective in preventing EMT and chemosensitivity resistance.

Project description:Cancer cell lines, which are cell cultures derived from tumor samples, represent one of the least expensive and most studied preclinical models for drug development. Accurately predicting drug responses for a given cell line based on molecular features may help to optimize drug-development pipelines and explain mechanisms behind treatment responses. In this study, we focus on DNA methylation profiles as one type of molecular feature that is known to drive tumorigenesis and modulate treatment responses. Using genome-wide, DNA methylation profiles from 987 cell lines in the Genomics of Drug Sensitivity in Cancer database, we used machine-learning algorithms to evaluate the potential to predict cytotoxic responses for eight anti-cancer drugs. We compared the performance of five classification algorithms and four regression algorithms representing diverse methodologies, including tree-, probability-, kernel-, ensemble-, and distance-based approaches. We artificially subsampled the data to varying degrees, aiming to understand whether training based on relatively extreme outcomes would yield improved performance. When using classification or regression algorithms to predict discrete or continuous responses, respectively, we consistently observed excellent predictive performance when the training and test sets consisted of cell-line data. Classification algorithms performed best when we trained the models using cell lines with relatively extreme drug-response values, attaining area-under-the-receiver-operating-characteristic-curve values as high as 0.97. The regression algorithms performed best when we trained the models using the full range of drug-response values, although this depended on the performance metrics we used. Finally, we used patient data from The Cancer Genome Atlas to evaluate the feasibility of classifying clinical responses for human tumors based on models derived from cell lines. Generally, the algorithms were unable to identify patterns that predicted patient responses reliably; however, predictions by the Random Forests algorithm were significantly correlated with Temozolomide responses for low-grade gliomas.

Project description:BACKGROUND: The GBGT1 gene encodes the globoside alpha-1,3-N-acetylgalactosaminyltransferase 1. This enzyme catalyzes the last step in the multi-step biosynthesis of the Forssman (Fs) antigen, a pentaglycosyl ceramide of the globo series glycosphingolipids. While differential GBGT1 mRNA expression has been observed in a variety of human tissues being highest in placenta and ovary, the expression of GBGT1 and the genes encoding the glycosyltransferases and glycosidases involved in the biosynthesis of Fs as well as the possible involvement of DNA methylation in transcriptional regulation of GBGT1 expression have not yet been investigated. RESULTS: RT-qPCR profiling showed high GBGT1 expression in normal ovary surface epithelial (HOSE) cell lines and low GBGT1 expression in all (e.g. A2780, SKOV3) except one (OVCAR3) investigated ovarian cancer cell lines, a finding that was confirmed by Western blot analysis. Hierarchical cluster analysis showed that GBGT1 was even the most variably expressed gene of Fs biosynthesis-relevant glycogenes and among the investigated cell lines, whereas NAGA which encodes the alpha-N-acetylgalactosaminidase hydrolyzing Fs was not differentially expressed. Bisulfite- and COBRA-analysis of the CpG island methylation status in the GBGT1 promoter region demonstrated high or intermediate levels of GBGT1 DNA methylation in all ovarian cancer cell lines (except for OVCAR3) but marginal levels of DNA methylation in the two HOSE cell lines. The extent of DNA methylation inversely correlated with GBGT1 mRNA and protein expression. Bioinformatic analysis of GBGT1 in The Cancer Genome Atlas ovarian cancer dataset demonstrated that this inverse correlation was also found in primary ovarian cancer tissue samples confirming our cell line-based findings. Restoration of GBGT1 mRNA and protein expression in low GBGT1-expressing A2780 cells was achieved by 5-aza-2'-deoxycytidine treatment and these treated cells exhibited increased helix pomatia agglutinin-staining, reflecting the elevated presence of Fs disaccharide on these cells. CONCLUSIONS: GBGT1 expression is epigenetically silenced through promoter hypermethylation in ovarian cancer. Our findings not only suggest an involvement of DNA methylation in the synthesis of Fs antigen but may also explain earlier studies showing differential GBGT1 expression in various human tissue samples and disease stages.

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The DNA methylation-regulated MCTP1 activates the drug-resistance of esophageal cancer cells.

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The DNA methylation-regulated MCTP1 activates the drug-resistance of esophageal cancer cells.

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