Upregulation of Long Noncoding RNA_GAS5 Suppresses Cell Proliferation and Metastasis in Laryngeal Cancer via Regulating PI3K/AKT/mTOR Signaling Pathway

Liu, Wenlin; Zhan, Jiandong; Zhong, Rong; Li, Rui; Sheng, Xiaoli; Xu, Mimi; Lu, Zhongming; Zhang, Siyi

doi:10.1177/1533033821990074

Cited by 16 publications

(12 citation statements)

References 27 publications

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“…For example, CDKN2B-AS1 regulates the cell cycle of laryngeal neoplasms (F. Liu et al, 2020 ), PVT1 regulates miR-519d-3p to promote the development of laryngeal neoplasms ( Zheng et al, 2019 ), and CCAT1 regulates the progression of laryngeal neoplasms ( Zhang and Hu, 2017 ) through different ways. Notably, the model predicts that lncRNA GAS5, which scored second, inhibits proliferation and metastasis of laryngeal neoplasms by regulating the PI3K/AKT/mTOR signaling pathway, according to a recent study in 2020 ( Liu et al, 2021 ).…”

Section: Resultsmentioning

confidence: 99%

Prediction of lncRNA–Disease Associations via Closest Node Weight Graphs of the Spatial Neighborhood Based on the Edge Attention Graph Convolutional Network

Kong

Wang

et al. 2022

Front. Genet.

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Accumulated evidence of biological clinical trials has shown that long non-coding RNAs (lncRNAs) are closely related to the occurrence and development of various complex human diseases. Research works on lncRNA–disease relations will benefit to further understand the pathogenesis of human complex diseases at the molecular level, but only a small proportion of lncRNA–disease associations has been confirmed. Considering the high cost of biological experiments, exploring potential lncRNA–disease associations with computational approaches has become very urgent. In this study, a model based on closest node weight graph of the spatial neighborhood (CNWGSN) and edge attention graph convolutional network (EAGCN), LDA-EAGCN, was developed to uncover potential lncRNA–disease associations by integrating disease semantic similarity, lncRNA functional similarity, and known lncRNA–disease associations. Inspired by the great success of the EAGCN method on the chemical molecule property recognition problem, the prediction of lncRNA–disease associations could be regarded as a component recognition problem of lncRNA–disease characteristic graphs. The CNWGSN features of lncRNA–disease associations combined with known lncRNA–disease associations were introduced to train EAGCN, and correlation scores of input data were predicted with EAGCN for judging whether the input lncRNAs would be associated with the input diseases. LDA-EAGCN achieved a reliable AUC value of 0.9853 in the ten-fold cross-over experiments, which was the highest among five state-of-the-art models. Furthermore, case studies of renal cancer, laryngeal carcinoma, and liver cancer were implemented, and most of the top-ranking lncRNA–disease associations have been proven by recently published experimental literature works. It can be seen that LDA-EAGCN is an effective model for predicting potential lncRNA–disease associations. Its source code and experimental data are available at https://github.com/HGDKMF/LDA-EAGCN.

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Section: Resultsmentioning

confidence: 99%

Prediction of lncRNA–Disease Associations via Closest Node Weight Graphs of the Spatial Neighborhood Based on the Edge Attention Graph Convolutional Network

Kong

Wang

et al. 2022

Front. Genet.

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“…STAD is one of the most common digestive tract malignancies and has high morbidity and mortality. Several recent studies have shown that lncRNAs are involved in the progression of various cancers (12)(13)(14). For example, lncRNA GAS5 was shown to be downregulated in laryngeal carcinoma tissues.…”

Section: Discussionmentioning

confidence: 99%

“…GAS5 overexpression inhibited laryngeal cancer cell proliferation, G2/M phase arrest, migration, and invasion, accompanied by cell apoptosis rate. GAS5 overexpression regulated the PI3K/AKT/mTOR signaling pathway to participate in cancer progression (12). ASB16-AS1 is an under-studied novel lncRNA highly expressed in colorectal cancer (CRC) cells.…”

Section: Discussionmentioning

confidence: 99%

Inhibition of ITGB1-DT expression delays the growth and migration of stomach adenocarcinoma and improves the prognosis of cancer patients using the bioinformatics and cell model analysis

Ni¹,

Guo²,

Luo³

2022

J Gastrointest Oncol

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Background: The long non-coding RNA, integrin subunit beta 1 (ITGB1) divergent transcript (ITGB1-DT), is known to be involved in cancer progression and associated with the poor prognosis of cancer patients. At present, the role of ITGB1-DT in stomach adenocarcinoma (STAD) has not been reported. Methods:The expression level of ITGB1-DT was detected in normal gastric and STAD tissues from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. A receiver operating characteristic (ROC) analysis was used to evaluate the role of ITGB1-DT in diagnosing STAD. The relationship between ITGB1-DT overexpression and clinicopathological features, prognosis, and immuneinfiltrated cells in STAD were explored using correlation, survival, and Cox regression analyses. A cell model of ITGB1-DT interference was constructed to explore the roles of ITGB1-DT on STAD cell proliferation and migration, and the signaling mechanism was investigated using Gene Set Enrichment Analysis (GSEA).Results: ITGB1-DT was expressed up-regulated in STAD tissues. ITGB1-DT overexpression was associated with the T stage, therapeutic effect, overall survival, progression-free interval status, and poor prognosis in STAD patients. ITGB1-DT overexpression was valuable in diagnosing STAD and a negative factor affecting the prognosis of STAD patients. Interference with ITGB1-DT expression inhibited STAD cell proliferation, invasion, and migration. GSEA results showed that ITGB1-DT may be involved in STAD progression through the insulin, p53, mechanistic target of rapamycin kinase (MTOR), and other signaling pathways. Overexpression of ITGB1-DT was significantly correlated with the levels of STAD B cells, T cells, T helper cells, CD8 T cells, cytotoxic cells, and other immune cells.Conclusions: ITGB1-DT was overexpressed and associated with poor prognosis in STAD. Interference with ITGB1-DT expression may delay the progression of STAD to improve the prognosis of STAD patients.

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“…In non-small cell lung cancer, miR-133b has the potential to be involved in the progression by regulating its target-mediated PI3K/AKT and p53 signaling pathways ( 35 ). In laryngeal cancer, lncRNA growth arrest-specific transcript 5 inhibits cancer cell invasion and proliferation via the PI3K/AKT/mTOR signaling pathway ( 36 ). Downregulation of sterol regulatory element binding transcription factor 1 inhibits the invasion by regulation of Bcl-2 and Bax and inhibition of the PI3K/AKT pathway in non-small-cell lung cancer ( 37 ).…”

Section: Discussionmentioning

confidence: 99%

Long non‑coding RNA HCG18 facilitates the progression of laryngeal and hypopharyngeal squamous cell carcinoma by upregulating FGFR1 via miR‑133b

Peng

2021

Mol Med Rep

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It has been reported that long non-coding RNA HLA complex group 18 (HCG18) is involved in the progression of cancer, acting as an oncogenic gene. The aim of the present study was to investigate the mechanism underlying the action of HCG18 in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC). The expression levels of HCG18, microRNA (miR)-133b and fibroblast growth factor receptor 1 (FGFR1) in LHSCC tissues and transfected LHSCC cells were evaluated by reverse transcription-quantitative PCR or immunohistochemistry. The viability, migration and invasion of transfected LHSCC cells were detected by Cell Counting Kit-8, wound healing and Transwell assays, respectively. The targeting relationships of HCG18, miR-133b and FGFR1 were predicted by bioinformatics analysis and confirmed using a dual-luciferase reporter assay. Moreover, the expression levels of FGFR1, phosphorylated (p)-PI3K, PI3K, p-AKT, AKT, p53, Bax and Bcl-2 in transfected LHSCC cells were measured by western blotting. It was found that the expression levels of HCG18 and FGFR1 were upregulated, but those of miR-133b were downregulated in LHSCC tissues. Short hairpin RNA (sh) HCG18 and miR-133b mimic inhibited LHSCC cell viability, while enhancing miR-133b expression. HCG18 could competitively bind with miR-133b. Moreover, the miR-133b inhibitor promoted cell viability, migration, invasion and the expression levels of Bcl-2, p-PI3K and p-AKT, but inhibited the expression levels of p53 and Bax, which were abrogated by shHCG18. miR-133b could competitively bind with FGFR1, and the miR-133b mimic decreased the expression level of FGFR1 in transfected LHSCC cells. shFGFR1 promoted the expression levels of p53 and Bax, while inhibiting viability, migration, invasion and Bcl-2, p-PI3K and p-AKT expression in LHSCC cells. In conclusion, the current results indicated that HCG18 facilitated the progression of LHSCC by upregulating FGFR1 via miR-133b. The present study evaluated the mechanism with regards to the action of HCG18 in LHSCC, and these experimental results may provide novel evidence for targeted therapy of LHSCC.

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Upregulation of Long Noncoding RNA_GAS5 Suppresses Cell Proliferation and Metastasis in Laryngeal Cancer via Regulating PI3K/AKT/mTOR Signaling Pathway

Cited by 16 publications

References 27 publications

Prediction of lncRNA–Disease Associations via Closest Node Weight Graphs of the Spatial Neighborhood Based on the Edge Attention Graph Convolutional Network

Prediction of lncRNA–Disease Associations via Closest Node Weight Graphs of the Spatial Neighborhood Based on the Edge Attention Graph Convolutional Network

Inhibition of ITGB1-DT expression delays the growth and migration of stomach adenocarcinoma and improves the prognosis of cancer patients using the bioinformatics and cell model analysis

Long non‑coding RNA HCG18 facilitates the progression of laryngeal and hypopharyngeal squamous cell carcinoma by upregulating FGFR1 via miR‑133b

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