MicroRNA expression and PTEN protein levels in uterine corpus endometrial carcinoma (UCEC)

2014 ◽  
Vol s1 (01) ◽  
Author(s):  
Wenbin Liu Pradeep Chaluvally
eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Israr Khan ◽  
John Kerwin ◽  
Kate Owen ◽  
Erin Griner ◽  

The Reproducibility Project: Cancer Biology seeks to address growing concerns about reproducibility in scientific research by conducting replications of selected experiments from a number of high-profile papers in the field of cancer biology. The papers, which were published between 2010 and 2012, were selected on the basis of citations and Altmetric scores (<xref ref-type="bibr" rid="bib9">Errington et al., 2014</xref>). This Registered report describes the proposed replication plan of key experiments from ‘A coding-independent function of gene and pseudogene mRNAs regulates tumour biology’ by <xref ref-type="bibr" rid="bib26">Poliseno et al. (2010)</xref>, published in Nature in 2010. The key experiments to be replicated are reported in Figures 1D, 2F-H, and 4A. In these experiments, Poliseno and colleagues report microRNAs miR-19b and miR-20a transcriptionally suppress both PTEN and PTENP1 in prostate cancer cells (Figure 1D; <xref ref-type="bibr" rid="bib26">Poliseno et al., 2010</xref>). Decreased expression of PTEN and/or PTENP1 resulted in downregulated PTEN protein levels (Figure 2H), downregulation of both mRNAs (Figure 2G), and increased tumor cell proliferation (Figure 2F; <xref ref-type="bibr" rid="bib26">Poliseno et al., 2010</xref>). Furthermore, overexpression of the PTEN 3′ UTR enhanced PTENP1 mRNA abundance limiting tumor cell proliferation, providing additional evidence for the co-regulation of PTEN and PTENP1 (Figure 4A; <xref ref-type="bibr" rid="bib26">Poliseno et al., 2010</xref>). The Reproducibility Project: Cancer Biology is collaboration between the Center for Open Science and Science Exchange, and the results of the replications will be published in eLife.


2019 ◽  
Vol 45 (7) ◽  
pp. 1414-1417 ◽  
Author(s):  
Akio Kamiya ◽  
Yoshihiro Ikura ◽  
Noriaki Iizuka ◽  
Toru Yokokawa ◽  
Hiroki Kato ◽  
...  

2017 ◽  
Vol 313 (2) ◽  
pp. L230-L239 ◽  
Author(s):  
Satoru Yanagisawa ◽  
Jonathan R. Baker ◽  
Chaitanya Vuppusetty ◽  
Peter Fenwick ◽  
Louise E. Donnelly ◽  
...  

The phosphatidylinositol 3-kinase (PI3K) pathway is activated in chronic obstructive pulmonary disease (COPD), but the regulatory mechanisms for this pathway are yet to be elucidated. The aim of this study was to determine the expression and role of phosphatase and tensin homolog deleted from chromosome 10 (PTEN), a negative regulator of the PI3K pathway, in COPD. PTEN protein expression was measured in the peripheral lung of COPD patients compared with smoking and nonsmoking controls. The direct influence of cigarette smoke extract (CSE) on PTEN expression was assessed using primary lung epithelial cells and a cell line (BEAS-2B) in the presence or absence of l-buthionine-sulfoximine (BSO) to deplete intracellular glutathione. The impact of PTEN knockdown by RNA interference on cytokine production was also examined. In peripheral lung, PTEN protein was significantly decreased in patients with COPD compared with the subjects without COPD ( P < 0.001) and positively correlated with the severity of airflow obstruction (forced expiratory volume in 1-s percent predicted; r = 0.50; P = 0.0012). Conversely, phosphorylated Akt, as a marker of PI3K activation, showed a negative correlation with PTEN protein levels ( r = −0.41; P = 0.0042). In both primary bronchial epithelial cells and BEAS-2B cells, CSE decreased PTEN protein, which was reversed by N-acetyl cysteine treatment. PTEN knockdown potentiated Akt phosphorylation and enhanced production of proinflammatory cytokines, such as IL-6, CXCL8, CCL2, and CCL5. In conclusion, oxidative stress reduces PTEN protein levels, which may result in increased PI3K signaling and amplification of inflammation in COPD.


2020 ◽  
Author(s):  
Cankun Zhou ◽  
Chaomei Li ◽  
Fangli Yan ◽  
Yuhua Zheng

Abstract Background: Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis especially when at an advanced stage. In the present study, we explored the potential of an immune-related gene signature to predict overall survival in UCEC patients.Methods: We analyzed expression data of 616 UCEC patients from The Cancer Genome Atlas database and the International Cancer Genome Consortium as well as immune genes from the ImmPort database and identified the signature. We constructed a transcription factor regulatory network based on Cistrome databases and performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using Cox regression analysis then constructed a prognostic model. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content.Results: Results indicated that the immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic model revealed a ten-gene prognosis signature , comprising PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC . This can be used as an independent tool to predict the prognosis of UCEC owing to the observed risk-score. In addition, levels of B cells and neutrophils were significantly correlated with the patient's risk score, and the expression of ten genes is associated with immune cell infiltrates.Conclusions: In summary, we present a 10-gene signature with the potential to predict the prognosis of UCEC. This is expected to guide future development of individualized treatment approaches.


2021 ◽  
Vol Volume 13 ◽  
pp. 9329-9343
Author(s):  
Xiaojiao Zheng ◽  
Lv Xiuyi ◽  
Linyan Zhu ◽  
Kejun Xu ◽  
Cong Shi ◽  
...  

2019 ◽  
Vol 120 (10) ◽  
pp. 18465-18477 ◽  
Author(s):  
Dong Ouyang ◽  
Ruyi Li ◽  
Yaxian Li ◽  
Xueqiong Zhu

2020 ◽  
Vol 11 (21) ◽  
pp. 6390-6401 ◽  
Author(s):  
Yizi Wang ◽  
Fang Ren ◽  
Zixuan Song ◽  
Xiaoying Wang ◽  
Xiaoxin Ma

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