Overexpression of G2 and S phase-expressed-1 contributes to cell proliferation, migration, and invasion via regulating p53/FoxM1/CCNB1 pathway and predicts poor prognosis in bladder cancer

Liu, Anwei; Zeng, Shuxiong; Lü, Xin; Xiong, Qiao; Xue, Yongping; Tong, Liping; Xu, Weidong; Sun, Yinghao; Zhang, Zhensheng; Xu, Chuanliang

doi:10.1016/j.ijbiomac.2018.11.032

Cited by 49 publications

(52 citation statements)

References 22 publications

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“…GTSE1 has been found to be highly expressed in the tumors such as melanoma and lung cancer and is related to the weak prognosis of the patients (Wu et al, 2017;Xu et al, 2018). Additionally, GTSE1 might be participating in tumorigenesis and progression by modulating p53 phosphorylation (Liu et al, 2010(Liu et al, , 2019.…”

Section: Discussionmentioning

confidence: 99%

Systems Biology Integration and Screening of Reliable Prognostic Markers to Create Synergies in the Control of Lung Cancer Patients

Kaushik

Mehmood

Wei

et al. 2020

Front. Mol. Biosci.

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This study aims to achieve a clearer and stronger understanding of all the mechanisms involved in the occurrence as well as in the progression of lung cancer along with discovering trustworthy prognostic markers. We combined four gene expression profiles (GSE19188, GSE19804, GSE101929, and GSE18842) from the GEO database and screened the commonly differentially expressed genes (CDEGs). We performed differentially expressed group analysis on CDEGs, alteration and mutational analysis, and expression level verification of core differential genes. Systems biology discoveries in our examination are predictable with past reports. Curiously, our examination revealed that screened biomarker adjustments, for the most part, coexist in lung cancer. After screening 952 CDEGs, we found that the up-regulation of neuromedin U (NMU) and GTSE1 in the case of lung cancer is related to poor prognosis. On the other hand, FOS CDKN1C expression is associated with poor prognosis and is responsible for the down-regulation of CDKN1C and FOS. Changes in these qualities are on free pathways to lung cancer and are not usually of combined quality variety. Even though biomarkers were related to both survival occasions in our examination, it gives us another point of view while playing out the investigation of hereditary changes and clinical highlights employing information mining. Based on our results, we found potential and prospective clinical applications in GTSE1, NMU, FOS, and CDKN1C to act as prognostic markers in case of lung cancer.

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Section: Discussionmentioning

confidence: 99%

Systems Biology Integration and Screening of Reliable Prognostic Markers to Create Synergies in the Control of Lung Cancer Patients

Kaushik

Mehmood

Wei

et al. 2020

Front. Mol. Biosci.

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“…Emerging evidence indicated abnormal expression of genes in cell cycle, and apoptosis regulation, like p53, Rb, p27, and TGFβ/IGF2R, is related to etiopathogenesis and prognosis of liver cancer patients [1]. GTSE1 has been demonstrated as a potential biomarker for poor clinical outcome in several types of cancer [10,13,27]. Previous research suggested GTSE1's functional role in hepatocellular carcinoma (HCC) proliferation, colony formation, invasion, and overall survival [9,13].…”

Section: Discussionmentioning

confidence: 99%

“…While in normal condition, GTSE1 is activated by functional p53 binding on the GTSE1 promoter region and encodes GTSE1 protein to cause a delay from G2 to M transition [3,8]. Recent studies revealed that overexpression of GTSE1 contributes to promoting cell proliferation, migration, and invasion in different cancers via translocalizing p53 to the cytoplasm [9,10].…”

Section: Introductionmentioning

confidence: 99%

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GTSE1, CDC20, PCNA, and MCM6 Synergistically Affect Regulations in Cell Cycle and Indicate Poor Prognosis in Liver Cancer

Zheng

Shi

et al. 2019

Analytical Cellular Pathology

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GTSE1 is well correlated with tumor progression; however, little is known regarding its role in liver cancer prognosis. By analyzing the hepatocellular carcinoma (HCC) datasets in GEO and TCGA databases, we showed that high expression of GTSE1 was correlated with advanced pathologic stage and poor prognosis of HCC patients. To investigate underlying molecular mechanism, we generated GTSE1 knockdown HCC cell line and explored the effects of GTSE1 deficiency in cell growth. Between GTSE1 knockdown and wild-type HCC cells, we identified 979 differentially expressed genes (520 downregulated and 459 upregulated genes) in the analysis of microarray-based gene expression profiling. Functional enrichment analysis of DEGs suggested that S phase was dysregulated without GTSE1 expression, which was further verified from flow cytometry analysis. Moreover, three other DEGs: CDC20, PCNA, and MCM6, were also found contributing to GTSE1-related cell cycle arrest and to be associated with poor overall survival of HCC patients. In conclusion, GTSE1, together with CDC20, PCNA, and MCM6, may synergistically promote adverse prognosis in HCC by activating cell cycle. Genes like GTSE1, CDC20, PCNA, and MCM6 may be promising prognostic molecular biomarkers in liver cancer.

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“…It has been reported that GTSE1 is highly expressed in tumors such as liver cancer and melanoma, and is associated with poor prognosis of patients [18,19]. Moreover, GTSE1 may be involved in tumorigenesis and progression by regulating p53 phosphorylation [20,21]. In another liver cancer study, it was also proved that the down-regulation of GTSE1 has a good effect of promoting apoptosis, reducing anti-apoptotic ability and enhancing the sensitivity of chemotherapeutic drugs [22].…”

Section: Gepia Analysismentioning

confidence: 99%

Screening prognostic markers for non-small cell lung cancer based on data mining and bioinformatics analysis

Han¹,

Aman²,

Wei³

et al. 2020

Preprint

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Background At present, non-small cell lung cancer has a high morbidity and mortality, and the recurrence and metastasis situation is serious. It is impossible to accurately predict the prognosis of cancer patients clinically. Biomarker is a kind of biomolecule with wide application prospects, and its potential in cancer prognosis is gradually revealed, and it is expected to be applied clinically. Results We integrated four gene expression profiles (GSE19188, GSE19804, GSE101929 and GSE18842) from the GEO database and screened the commonly differentially expressed genes using the GEO2R online tool. We screened 952 commonly differentially expressed genes. Gene ontology analysis showed that CDEGs were mainly enriched in biological processes such as cell adherin, angiogenesis and positive regulation of angiogenesis, and KEGG pathways such as ECM-receptor interaction and cell adherin molecules (CAMs). Up-regulation of G2 and S phase-expressed protein 1(GTSE1) expression is associated with poor prognosis of lung adenocarcinoma(LADE) and lung squamous cell carcinoma(LUSC). Up-regulation of Neuromedin-U(NMU) expression, down-regulation of Proto-oncogene c-Fos(FOS) and Cyclin-dependent kinase inhibitor 1C(CDKN1C) is only associated with poor prognosis of LADE. Conclusions We believe that GTSE1, NMU, FOS, and CDKN1C have potential application value as prognostic markers for lung adenocarcinoma, and are of great significance for lung adeno carcinoma efficacy evaluation and relapse monitoring. At the same time, GTSE1 may also be used as a new target for cancer treatment New ways.

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Overexpression of G2 and S phase-expressed-1 contributes to cell proliferation, migration, and invasion via regulating p53/FoxM1/CCNB1 pathway and predicts poor prognosis in bladder cancer

Cited by 49 publications

References 22 publications

Systems Biology Integration and Screening of Reliable Prognostic Markers to Create Synergies in the Control of Lung Cancer Patients

Systems Biology Integration and Screening of Reliable Prognostic Markers to Create Synergies in the Control of Lung Cancer Patients

GTSE1, CDC20, PCNA, and MCM6 Synergistically Affect Regulations in Cell Cycle and Indicate Poor Prognosis in Liver Cancer

Screening prognostic markers for non-small cell lung cancer based on data mining and bioinformatics analysis

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