TELO2 induced progression of colorectal cancer by binding with RICTOR through mTORC2

Guo, Zheng; Zhang, Xiufang; Zhu, Huabin; Zhong, Nanying; Luo, Xiaoning; Tu, Fuping; Zhong, Jinghua; Wang, Xiangcai; He, Jing; Huang, Li

doi:10.3892/or.2020.7890

Cited by 53 publications

(35 citation statements)

References 37 publications

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“…Among the intersected omics features, TELO2 and ZYMND19 are the most significant DEGs. Guo et al [ 21 ] revealed that TELO2 was significantly upregulated in colorectal cancer (CRC), which was concordant with the regulatory pattern in our study. Additionally, the significant restraints of the growth, cell cycle, and metastasis of CRC cells manifest after TELO inhibition, indicating that TELO2 promotes tumor progression.…”

Section: Discussionsupporting

confidence: 92%

Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion

Wang

Lee

et al. 2021

Cancers

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This study is to identify potential multiomics biomarkers for the early detection of the prognostic recurrence of PC patients. A total of 494 prostate adenocarcinoma (PRAD) patients (60-recurrent included) from the Cancer Genome Atlas (TCGA) portal were analyzed using the autoencoder model and similarity network fusion. Then, multiomics panels were constructed according to the intersected omics biomarkers identified from the two models. Six intersected omics biomarkers, TELO2, ZMYND19, miR-143, miR-378a, cg00687383 (MED4), and cg02318866 (JMJD6; METTL23), were collected for multiomics panel construction. The difference between the Kaplan–Meier curves of high and low recurrence-risk groups generated from the multiomics panel achieved p-value = 5.33 × 10−9, which is better than the former study (p-value = 5 × 10−7). Additionally, when evaluating the selected multiomics biomarkers with clinical information (Gleason score, age, and cancer stage), a high-performance prediction model was generated with C-index = 0.713, p-value = 2.97 × 10−15, and AUC = 0.789. The risk score generated from the selected multiomics biomarkers worked as an effective indicator for the prediction of PRAD recurrence. This study helps us to understand the etiology and pathways of PRAD and further benefits both patients and physicians with potential prognostic biomarkers when making clinical decisions after surgical treatment.

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Section: Discussionsupporting

confidence: 92%

Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion

Wang

Lee

et al. 2021

Cancers

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“… 27 Referring to previous research, the cell staining intensity was classified as 4 grades, with 0 points for negative, 1 point for low positive, 2 points for median positive, and 3 points for strong positive. 28 The final results were calculated as the score of the cell staining intensity and its percentage of cells.…”

Section: Methodsmentioning

confidence: 99%

A Pyroptosis-Related Gene Signature Associated with Prognosis and Tumor Immune Microenvironment in Gliomas

Zhou¹,

Xu²,

Huang³

et al. 2022

IJGM

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Background Pyroptosis is a novel form of cell death that plays a significant role in cancer, while the prognostic values of pyroptosis-related genes in gliomas have not been revealed. Methods We analyzed the RNA-seq and clinical data of gliomas from the University of California Santa Cruz (UCSC) Xena database to determine differentially expressed pyroptosis-related genes. Based on these genes, a pyroptosis genes signature was constructed after univariate Cox analysis and Lasso Cox analyses. The sensitivity and specificity of pyroptosis genes signature were verified by the Chinese Glioma Genome Atlas (CGGA) dataset. Finally, we explored the association of risk signatures with tumor microenvironment and immune cell infiltration. Results Of 15 differentially expressed pyroptosis-related genes, three genes of BCL2 associated X (BAX), caspase 3 (CASP3), and caspase 4 (CASP4) were used to construct the risk signature. The effectiveness of risk signature for predicting survival at 1, 3, 5 years was performed by the receiver operating characteristic curve (ROC), and the area under curves (AUC) was 0.739, 0.817, and 0.800, respectively. Functional enrichment results showed signal transduction, cell adhesion, immune response, and inflammatory response were enriched. The immune analysis revealed that pyroptosis had a remarkable effect on the immune microenvironment. Conclusion In this study, we constructed a pyroptosis-related gene signature, which can serve as a potential biomarker for predicting the survival of glioma patients. Additionally, we suggested that pyroptosis may promote gliomas development by inducing chronic inflammation microenvironment.

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“…The next day, the samples were incubated with biotin-labeled secondary antibody, stained with 3,3ʹ-Diaminobenzidine (DAB) (Agilent Technologies, Santa Clara, CA, USA) and hematoxylin, and finally photographed using a confocal microscopy. Immunohistochemical scoring was performed according to a method detailed in a previous study [ 49 ].…”

Section: Methodsmentioning

confidence: 99%

MFSD4A inhibits the malignant progression of nasopharyngeal carcinoma by targeting EPHA2

et al. 2022

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DNA Methylation can lead to abnormal gene expression. In the present study, we investigated whether the expression of methylated MFSD4A (major facilitator superfamily domain containing 4 A) was downregulated in nasopharyngeal carcinoma (NPC) and whether it is associated with malignant progression and poor prognosis of NPC. Bioinformatic analysis, bisulfite pyrosequencing, quantitative real-time reverse transcription PCR, and western blotting assays were performed to explore the relationship between hypermethylation of MFSD4A and its expression in NPC. The role of MFSD4A in NPC was verified by Cell Cycle Kit 8, transwell assays and flow cytometry in vitro and by animal experiments in vivo. Mass spectrometry, co-immunoprecipitation, and immunofluorescence assays were applied to explore the mechanism by which MFSD4A inhibits NPC. The prognostic significance of MFSD4A or EPHA2 was investigated by immunohistochemical analysis of clinical specimens. Hypermethylation of the promoter region of MFSD4A led to decreased expression of MFSD4A. When MFSD4A expression was upregulated or downregulated, the proliferation, apoptosis, migration, and invasion abilities of NPC cells were altered accordingly. Mechanistically, MFSD4A could specifically bind to and degrade EPH receptor A2 (EPHA2) by recruiting ring finger protein 149 (RNF149), which led to alterations in the EPHA2-mediated PI3K-AKT-ERK1/2 pathway and epithelial-mesenchymal transition (EMT), thereby affecting NPC progression. Clinically, high MFSD4A expression or low-EPHA2 expression was associated with better prognosis for patients with NPC. In all, reduced MFSD4A expression in NPC is caused by promoter hypermethylation. MFSD4A or EPHA2 expression is associated with the malignant biological behavior and prognosis of NPC. MFSD4A is a promising potential therapeutic target for NPC.

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TELO2 induced progression of colorectal cancer by binding with RICTOR through mTORC2

Cited by 53 publications

References 37 publications

Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion

Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion

A Pyroptosis-Related Gene Signature Associated with Prognosis and Tumor Immune Microenvironment in Gliomas

MFSD4A inhibits the malignant progression of nasopharyngeal carcinoma by targeting EPHA2

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