Microarray analysis of Long non-coding RNA expression profiles in human gastric cells and tissues with Helicobacter pylori Infection

Zhu, Hong; Wang, Qiang; Yao, Yizheng; Fang, Jian; Sun, Fengying; Ni, Ying; Shen, Yifei; Wang, Hua; Shao, Shihe

doi:10.1186/s12920-015-0159-0

Cited by 49 publications

(40 citation statements)

References 35 publications

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“…Besides, we analyzed gene expression array deposited in Gene Expression Omnibus (GEO, GSE29272), which has the global gene expression of 72 gastric non-cardia tumor and 62 gastric cardia tumor and their paired normal tissues [18]. We also applied a GEO dataset (GSE74577), which was conducted to investigate the gene expression changes in response to H. pylori infection [19]. Additionally, GSE99553 was used to compare methylation level of CpG sites between GC patients with H. pylori infection (n = 28) and non-infected patients (n = 28).…”

Section: Samples and Datasetsmentioning

confidence: 99%

MUC1 is associated with TFF2 methylation in gastric cancer

Liu

et al. 2020

Clin Epigenet

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Background: Emerging evidence has shown that MUC1 and TFF2 play crucial roles in the H. pylori-infected pathogenesis of gastric cancer (GC). A recent study revealed that H. pylori infection induced obviously increased Tff2 methylation levels in Muc1 −/− mice compared with controls. However, little is known of the molecular mechanism on MUC1 regulating the expression of TFF2. Methods: We conducted a correlation analysis of MUC1 and TFF2 in public databases and our adjacent GC tissues. Besides, MUC1 overexpression vector or small interfering RNA (siRNA) was transfected into GC cells to assess the change in TFF2 expression. Furthermore, the methylation status of TFF2 was measured by bisulfite sequencing PCR (BSP).Results: The expression of MUC1 was significantly lower in non-cardia and cardia tumor tissues than that in normal tissues. Downregulation of TFF2 expression was also observed in GC tissues. In addition, we found that MUC1 expression was positively associated with TFF2 expression in GC tissues, especially among GC patients with H. pylori infection. Overexpression of MUC1 in BGC-823 and SGC-7901 cell lines substantially increased the TFF2 expression, whereas knockdown of MUC1 reverted this effect. Moreover, MUC1 was negatively related to the methylation of TFF2 in the co-expression analysis. The results of BSP experiments showed that compared with negative vector group, the methylation level of TFF2 was decreased in GC cells transfected with MUC1 overexpression vector. Additionally, survival analysis indicated that GC patients with lower level of MUC1 or TFF2 had a worse outcome. Conclusion: Our results indicated that MUC1 was associated with the methylation of TFF2, which may have implications for TFF2 expression in GC. These findings warrant further research toward the underlying mechanism of MUC1 influenced the TFF2 methylation.

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Section: Samples and Datasetsmentioning

confidence: 99%

MUC1 is associated with TFF2 methylation in gastric cancer

Liu

et al. 2020

Clin Epigenet

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“…Typically a microarray comprises thousands of spots containing multiple oligonucleotides probes on a platform, which hybridize with RNAs of interest for large‐scale expression analysis (Figure III) . A significant number of microarray‐based methods have been developed for genome‐wide analysis of RNAs . In 2004, Rogler et al developed a reverse format microarray termed an RNA expression microarray (REM).…”

Section: Rna Biomarker Detection Technologiesmentioning

confidence: 99%

“…The applicability of the REM was tested for the specific detection of albumin, Hnf‐4 and Igfbp‐1 and c‐Myc expression. Zhu et al developed another method which detected aberrantly expressed 303 lncRNAs and 565 mRNAs in Helicobacter pylori infected cells. Very recently, Hu et al reported anther microarray assay to explore the role of miRNAs in gefitinib (a common EGFR inhibitor available as cancer drug) resistance.…”

Section: Rna Biomarker Detection Technologiesmentioning

confidence: 99%

RNA Biomarkers: Diagnostic and Prognostic Potentials and Recent Developments of Electrochemical Biosensors

et al. 2017

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Ribonucleic acids (RNAs) are considered as effective and minimally invasive biomarkers for disease diagnosis and prognosis due to their critical role in the regulation of different cellular processes. Over the past several years, the rapid progress in RNA biomarker research has resulted in the development of a large number of high‐performance RNA‐detection methods. Most of these methods are based on molecular‐biology techniques such as quantitative reverse transcription polymerase chain reaction (RT‐qPCR), microarrays, and RNA sequencing. In recent years, considerable attention has also been dedicated to developing RNA biosensors, exploiting micro‐ and nanofabrication technologies, and various readout strategies, including electrochemical and optical transducers. Here, the recent developments of RNA biosensors are concisely reviewed with a special emphasis on electrochemical‐detection approaches. The following points are also highlighted: i) all the types of clinically relevant RNAs (mRNAs, miRNAs, lncRNAs) and their diagnostic and prognostic potential in cancer are outlined, ii) major challenges associated with current techniques are identified, followed by a critical analysis of how these challenges have been addressed by different biosensing approaches, and iii) the current requirements that still need to be met for effective screening of RNA biomarkers in both research and clinical settings.

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“…monocytogenes, Helicobacter pylori , and Campylobacter ( C .) concisus as well as TLR ligands has been recently demonstrated in several studies but the functions of these lncRNAs remain to be elucidated (Ilott et al, 2014; Yi et al, 2014; Yang et al, 2015; Zhu et al, 2015; Yang R. et al, 2016; Westermann et al, 2016). …”

Section: Exploring Lncrna Function Through the Analysis Of Neighborinmentioning

confidence: 99%

A Long Journey Ahead: Long Non-coding RNAs in Bacterial Infections

Bruegge

Einspanier

Sharbati

2017

Front. Cell. Infect. Microbiol.

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Bacterial pathogens have coevolved with their hosts and acquired strategies to circumvent defense mechanisms of host cells. It was shown that bacteria interfere with the expression of mammalian microRNAs to modify immune signaling, autophagy, or the apoptotic machinery. Recently, a new class of regulatory RNAs, long non-coding RNAs (lncRNAs), was reported to have a pivotal role in the regulation of eukaryotic gene expression. A growing body of literature reports on specific involvement of lncRNAs in the host cell response toward bacterial infections. This mini review summarizes recent data that focuses on lncRNA function in host cells during bacterial infection and provides a perspective where future research in this regard may be going.

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Microarray analysis of Long non-coding RNA expression profiles in human gastric cells and tissues with Helicobacter pylori Infection

Cited by 49 publications

References 35 publications

MUC1 is associated with TFF2 methylation in gastric cancer

MUC1 is associated with TFF2 methylation in gastric cancer

RNA Biomarkers: Diagnostic and Prognostic Potentials and Recent Developments of Electrochemical Biosensors

A Long Journey Ahead: Long Non-coding RNAs in Bacterial Infections

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