Glycogen phosphorylase B promotes ovarian cancer progression via Wnt/β-catenin signaling and is regulated by miR-133a-3p

Zhou, Yang; Jin, Zhendong; Wang, Chengcai

doi:10.1016/j.biopha.2019.109449

Cited by 58 publications

(62 citation statements)

References 34 publications

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“…High expression of ADH1B was correlated with markedly higher risk of residual disease in OSC [20], which played a significant role in accelerating ovarian cancer cell infiltration and may enhance the possibility of postoperative residual lesions [21]. PYGB obviously promoted ovarian cancer cell proliferation, invasion and migration via wnt pathway [22]. Therefore, previous studies just provided limited information on the mechanism of 8 MRGs in OSC patient survival.…”

Section: Discussionmentioning

confidence: 98%

“…ENPP1, FH, CYP2E1, HPGDS, ADCY9, NDUFA5, ADH1B and PYGB it characterized in this network. Given the potential molecular mechanisms of the eight MRG, reports on the functions and mechanisms of HPGDS, ADCY9 and NDUFA5 have not been published on OSC [13][14][15][16][17]. However, five of these eight hub MRGs have been studied, namely, ENPP1, FH, CYP2E1, ADH1B and PYGB.…”

Section: Discussionmentioning

confidence: 99%

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Identification and validation of a prognostic index based on a metabolic-genomic landscape analysis of ovarian cancer

Wang¹,

Li²,

Luo³

et al. 2019

Preprint

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Purpose: Tumor metabolism has been a novel driver of personalized cancer medicine, with aggressive efforts to regulate the metabolic system to prolong their life. The aim of this study is to explore the prognostic value of metabolism in ovarian serous cystadenocarcinoma (OSC), which is the most common subtype of ovarian cancer, accounts for 75-80% of reported cases. Patients and methods: we integrated the expression profiles of metabolism-related genes (MRGs) in survival in 379 OSC patients based on The Cancer Genome Atlas (TCGA) database. Then, several biomedical computational algorithms were employed to identify eight key prognostic MRGs, which were related with overall survival (OS) significantly in OSC. The eight genes represented important clinical significance and prognostic value in OSC. Then a prognostic index was constructed. Results: A total of 701 differentially expressed metabolism-related genes (MRGs) were identified in OSC patients based on TCGA database. Functional enrichment analyses hinted that metabolism may act in a significant role in the development and progression of OSC. Random walking with restart (RWR) algorithm, Univariate cox and lasso regression analysis indicated a prognostic signature based on MRGs (ENPP1, FH, CYP2E1, HPGDS, ADCY9, NDUFA5, ADH1B and PYGB), which performed moderately in prognostic predictions. Conclusion: This study provides a latent prognostic feature for predicting the prognosis of OSC patients and the molecular mechanism of OSC metabolism.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Identification and validation of a prognostic index based on a metabolic-genomic landscape analysis of ovarian cancer

Wang¹,

Li²,

Luo³

et al. 2019

Preprint

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“…PYGB is an enzyme that metabolizes glycogen and can in uence the growth and apoptosis of the cancer cell by regulating the NF-κB/Nrf2 signaling pathway [17]. In addition, PYGB was associated with the poor prognosis of cancer and can promote the proliferation and invasion of cancer cells by activating Wnt/β-catenin signaling [18][19]. AKR1B1, a member of the aldo/keto reductase superfamily, was associated with the poor survival outcomes of cancer and can promote the occurrence and metastasis of cancer by activating epithelialmesenchymal transition [20].…”

Section: Discussionmentioning

confidence: 99%

Identification of Metabolism-associated Genes and Construction of a Prognostic Signature in Bladder Cancer

Shen

Liu

Wang

et al. 2020

Preprint

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Background Bladder cancer (BC) is a commonly diagnosed malignant tumor in the urinary system, with a high morbidity and recurrence rate. Current studies indicated that metabolism-associated genes (MAGs) having critical roles in the etiology of BC. The present study aims to identify differentially expressed MAGs and construct a MAGs prognostic risk signature in BC by using The Cancer Genome Atlas (TCGA) database and proteomics data. Methods RNA-sequence data from the TCGA database and proteomics were used to identify differentially expressed MAGs and construct a prognostic MAGs signature in BC. Subsequently, survival analysis and nomogram were used to evaluate the prognostic and predictive value of the MAGs model in BC. RNA isolation and reverse transcription‑quantitative PCR (RT-qPCR) was further performed to investigate the expression levels of MAGs in BC cell lines and explore the relationship between MAGs and M2 tumor associated macrophages (TAMs) secreted TGF-beta 1 in BC. Results A total of 23 differentially expressed MAGs were identified and five MAGs were finally used to construct a MAGs based signature. Survival analysis revealed that the MAGs based signature was closely correlated with the survival outcomes of patients with BC. A nomogram with the MAGs based signature risk score and clinical features also constructed to facilitate the individualized prediction of BC patients. RT-qPCR showed that four MAGs were significantly elevated and the expression levels of three MAGs were positively correlated with M2 TAM secreted TGF-β1 in T24 cells. Conclusions Our study identified novel prognostic MAGs and constructed a MAGs based signature, which can be used as an independent signature in evaluating the prognosis of patients with BC. Furthermore, M2 TAMs may promote the expression of three MAGs via TGF-β1 signaling pathway. Further clinical trials and experimental exploration are needed to validate our observations in BC.

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“…Cell growth was assessed using CCK-8 assay, EdU staining assay and colony formation assays as previously described. 20…”

Section: Cell Growth Assaysmentioning

confidence: 99%

<p>B3GNT3, a Direct Target of miR-149-5p, Promotes Lung Cancer Development and Indicates Poor Prognosis of Lung Cancer</p>

Sun¹,

Liu²,

Lu³

et al. 2020

CMAR

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These authors contributed equally to this work Background: B3GNT3 (β1, 3-N-acetylglucosaminyltransferase-3) belongs to the β3GlcNAcT family and is essential to form extended core 1 oligosaccharides. Previous studies revealed that B3GNT3 expression was dysregulated in multiple cancers. Here, we aimed to understand the expression profile and function of B3GNT3 in lung cancer. Materials and Methods: The expression of B3GNT3 was measured by immunohistochemistry and public database analysis. B3GNT3 was knocked down to evaluate the lung cancer cell proliferation, migration and invasion in in vitro and in vivo tumor formation experiments. miR-149-5p targeting B3GNT3 was identified with TargetScan analysis and confirmed with reporter assay. Overexpression of miR-149-5p was achieved using microRNA mimics and function of microRNA-149-5p/B3GNT3 axis was tested in vitro. Results: B3GNT3 was upregulated in lung cancer, and B3GNT3 overexpression was associated with poor prognosis of lung cancer patients. High expression of B3GNT3 was associated with advanced TNM stages, larger tumor size, tumor metastasis and recurrence. Functionally, we demonstrated that knockdown of B3GNT3 suppressed lung cancer cell growth and invasion in vitro. Knockdown of B3GNT3 suppressed lung cancer development in a xenograft tumor model. Moreover, miR-149-5p was validated to negatively regulate B3GNT3 expression through directly targeting B3GNT3 3ʹ-UTR. Overexpression of miR-149-5p could antagonize the tumorigenesis effect of B3GNT3 in vitro. Conclusion: In summary, our study demonstrated that B3GNT3 overexpression was correlated with poor prognosis of lung cancer patient, indicating that B3GNT3 could be a promising prognostic biomarker for lung cancer. miR-149-5p negatively regulated B3GNT3 expression, which might be utilized for therapeutic target in lung cancer.

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Glycogen phosphorylase B promotes ovarian cancer progression via Wnt/β-catenin signaling and is regulated by miR-133a-3p

Cited by 58 publications

References 34 publications

Identification and validation of a prognostic index based on a metabolic-genomic landscape analysis of ovarian cancer

Identification and validation of a prognostic index based on a metabolic-genomic landscape analysis of ovarian cancer

Identification of Metabolism-associated Genes and Construction of a Prognostic Signature in Bladder Cancer

<p>B3GNT3, a Direct Target of miR-149-5p, Promotes Lung Cancer Development and Indicates Poor Prognosis of Lung Cancer</p>

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