Promotive effect of Talin‐1 protein on gastric cancer progression through PTK2‐PXN‐VCL‐E‐Cadherin‐CAPN2‐MAPK1 signaling axis

Yan, Huixin; Guo, Min; Zou, Jue; Xiao, Feng; Lee, Yi; He, Ying; He, Bosheng

doi:10.1002/jcla.23555

Cited by 8 publications

(4 citation statements)

References 24 publications

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“…In addition, VCL expression in patients with stage III + IV showed an increased trend compared to that in patients with stage I + II in our study. VCL were also detected in patients with cervical cancer, and VCL expression was associated with TNM stage, this was in line with previous study ( Yan et al, 2020 ).…”

Section: Discussionsupporting

confidence: 92%

Integrated Analysis of ceRNA Regulatory Network Associated With Tumor Stage in Cervical Cancer

Zhang

et al. 2021

Front. Genet.

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ObjectiveTo analyze the abnormally expressed genes involved in cervical cancer occurrence and development.Materials and MethodsIntegrated bioinformatics methods were used to analyze differentially expressed (DE) RNAs, including mRNAs, microRNAs (miRNAs), and long non-coding RNAs (lncRNAs), in stage I, II, III, and IV cervical cancer patients from the TCGA database to fully reveal the dynamic changes caused by cervical cancer.ResultsFirst, DE RNAs in cervical cancer tissues from stage I, II, III, and IV patients and normal cervical tissues were identified and divided into different profiles. Several DE RNA profiles were down-regulated or up-regulated in stage I, III, and IV patients. GO and KEGG analysis of DE mRNA profile 1, 2, 4, 5, 6 and 22 which were significantly down-regulated or up-regulated showed that DE mRNAs are involved in cell division, DNA replication, cell adhesion, the positive and negative regulation of RNA polymerase ll promoter transcription. Besides, DE RNA profiles with significant differences in patient stages were analyzed to perform a competing endogenous RNA (ceRNA) regulatory network of lncRNA, miRNA, and mRNA. The protein-protein interaction (PPI) network of DE mRNAs in the ceRNA regulatory network was also constructed. The network had nine central genes (up-regulated genes: CDKN2A, GSK3B, BIRC5, CYCS, MAD2L1; down-regulated genes: PTEN, FOXO3, CCND2, TGFBR2). Survival analysis found that 5 lncRNAs, 9 mRNAs, and 4 miRNAs can be used as prognostic indicators of cervical cancer. Finally, combined with cluster analysis results, we further screened 2 DE RNAs (AMZ2P1 and HDAC5) using clinical samples, suggesting that AMZ2P1, and HDAC5 may act as diagnostic biomarkers for the development of cervical cancer.ConclusionThis research provides new effective targets and reliable biological markers for the diagnosis and prognosis of cervical cancer.

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Section: Discussionsupporting

confidence: 92%

Integrated Analysis of ceRNA Regulatory Network Associated With Tumor Stage in Cervical Cancer

Zhang

et al. 2021

Front. Genet.

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“…It codistributed with integrins in the cell surface membrane in order to assist in the attachment of adherent cells to extracellular matrices and of lymphocytes to other cells. Overexpression of TLN1 activated the progression of gastric cance through PTK2-PXN-VCL-E-Cadherin-CAPN2-MAPK1signaling axis [33]. Besides this, TLN1 overexpression promoted hepatocellular carcinoma epithelial-mesenchymal transition and induced metastasis [34].…”

Section: Discussionmentioning

confidence: 99%

CircRNA_400029 promotes the aggressive behaviors of cervical cancer by regulation of miR-1285-3p/TLN1 axis

Ma¹,

Liu²,

Yang³

et al. 2022

J. Cancer

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Background: Cervical cancer (CC) is the highest incidence of female malignant tumor in China. Circular RNAs (circRNAs) has been reported to affect CC progression by altering mRNA stability at the transcriptional level or binding to miRNAs to produce competitive endogenous RNA (ceRNA). For this purpose, our study was aimed to investigate the function effects and the potential regulatory mechanism of the circRNA_400029 in CC cells. Materials and methods:The expression levels of circRNA_400029 and miR-1285-3p were detected by real time polymerase chain reaction (RT-PCR). Similarly, the mRNA and protein levels of TLN1 (Talin 1) was detected by RT-PCR and Western blot. Cell-Counting Kit-8 (CCK-8), EdU and Flow cytometry assay were used to detect cell proliferation, cell cycle and apoptosis. Then the Transwell assays were used to test cell migration and invasion. Besides this, the functional targets were confirmed by Dual luciferase reporter assays. Tumor xenograft in nude mice checked the result in vivo. Results: To begin with, circRNA_400029 was upregulated in CC cells and tissue. Knockdown circRNA_400029 inhibited cell proliferation, migration and invasion while induced cell apoptosis. Interestingly, miR-1285-3p targeted circRNA_400029 and down-regulated of miR-1285-3p could reverse the effects of circRNA_400029 weak-expression on progression and apoptosis of CC cells. Moreover, TLN1 was up-regulated in CC cells and identified as a direct target of miR-1285-3p. Meanwhile, we found that miR-1285-3p negatively regulated the function of TLN1.Finally, the circRNA_ 400029/miR-1285-3p/TLN1 axis could affect tumor growth in vivo. Conclusion:The overexpressed circRNA_400029 promoted CC proliferation, migration and invasion while deduced apoptosis by sponging miR-1285-3p to regulate TLN1. CircRNA_400029 was a potential onco-circRNA in CC, and might be a promised therapy target.

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“…Four of the top 10 genes were enriched in the focal adhesion pathway and were upstream regulators of FAK (PTK2), including VWF, CAV1, ITGA8 and COL1A1. The integrinactivated adhesion kinase (FAK)-mediated signaling pathway is an important pathway in tumor invasion and metastasis (22). PTK2, as an adhesion protein kinase, plays an important role in the FAK-mediated signaling pathway, which includes the transduction of signals released from integrins and growth factor receptors (23)(24)(25).…”

Section: Discussionmentioning

confidence: 99%

Identification of genes and pathways leading to poor prognosis of non-small cell lung cancer using integrated bioinformatics analysis

Cui¹,

Lou²,

Feng³

et al. 2022

Transl Cancer Res TCR

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Background: Non-small cell lung cancer (NSCLC) is a common malignancy with a high morbidity and mortality rate worldwide, but the driver genes and signaling pathways involved are largely unclear. Herein, our study aimed to identify significant genes with poor outcome and underlying mechanisms in NSCLC using bioinformatics analyses.Methods: Gene expression profiles (GSE33532, GSE19188, GSE102287, GSE27262), including 319 NSCLC and 232 adjacent lung tissues, were downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by the GEO2R online tool. Functional and pathway enrichment analyses were performed via the DAVID database. The protein-protein interactions (PPIs) of these DEGs were constructed by the STRING website and visualized by the Cytoscape software platform. The expression of hub genes in NSCLC was validated through the GEPIA database. Kaplan-Meier plotter was used to analyse the survival rate with multivariate Cox regression. The expression of protein tyrosine kinase 2 (PTK2) in NSCLC and adjacent lung tissues was evaluated on the UALCAN database platform.Results: A total of 225 significant DEGs were obtained between NSCLC and adjacent lung tissues, containing 52 upregulated genes and 173 downregulated genes. The DEGs were clustered based on functions and signaling pathways that may be closely associated with NSCLC occurrence. A total of 174 DEGs were identified from the PPI network complex. Top 10 hub genes were selected by CytoHubba plugin. As independent predictors, seven genes (COL1A1, ADAM12, VWF, OGN, EDN1, CAV1, ITGA8) were associated with poor prognosis in NSCLC via multivariate Cox regression (P<0.01). Four genes (VWF, CAV1, ITGA8, COL1A1) were found to be significantly enriched in the focal adhesion pathway (P=1.04E-04) and to be upstream regulators of PTK2. PTK2 was upregulated in NSCLC and associated with poor survival prognosis in lung squamous cell carcinoma (LUSC).Conclusions: Taken together, the important genes and pathways in NSCLC were identified by using integrated bioinformatics analysis. PTK2 could be a key gene associated with the biological process of NSCLC formation and progression and a potential therapeutic target for NSCLC treatment.

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Promotive effect of Talin‐1 protein on gastric cancer progression through PTK2‐PXN‐VCL‐E‐Cadherin‐CAPN2‐MAPK1 signaling axis

Cited by 8 publications

References 24 publications

Integrated Analysis of ceRNA Regulatory Network Associated With Tumor Stage in Cervical Cancer

Integrated Analysis of ceRNA Regulatory Network Associated With Tumor Stage in Cervical Cancer

CircRNA_400029 promotes the aggressive behaviors of cervical cancer by regulation of miR-1285-3p/TLN1 axis

Identification of genes and pathways leading to poor prognosis of non-small cell lung cancer using integrated bioinformatics analysis

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