MicroRNA-147b promotes lung adenocarcinoma cell aggressiveness through negatively regulating microfibril-associated glycoprotein 4 (MFAP4) and affects prognosis of lung adenocarcinoma patients

Feng, Yuyu; Liu, Conghui; Yang, Xue; Chen, Yuanyuan; Wang, Yuli; Wu, Xiaoqing

doi:10.1016/j.gene.2019.144316

Cited by 29 publications

(20 citation statements)

References 27 publications

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“…In vitro experiments revealed that miR-147b could promote cell proliferation, colony formation, invasion and migration. Mechanism analysis showed microfibril-associated glycoprotein 4 may be the putative target gene of miR-147b (Feng et al, 2020). In this study, we predicted a new possible target (WDR82) to explain the pro-metastatic mechanisms for miR-147b in LUAD.…”

Section: Discussionmentioning

confidence: 81%

“…Although Meng et al (2013) and Cui et al (2015) also identified miR-147b as a lymph node metastasis-related DEM, they did not explore its function mechanisms. The association of miR-147b with metastasis in lung cancer was also rarely investigated except for a recent study performed by Feng et al (2020). Feng et al observed miR-147b was up-regulated in LUAD tissues and cell lines, which induced poor prognosis outcomes.…”

Section: Discussionmentioning

confidence: 99%

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miR-224, miR-147b and miR-31 associated with lymph node metastasis and prognosis for lung adenocarcinoma by regulating PRPF4B, WDR82 or NR3C2

Wang

Shang

et al. 2020

PeerJ

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Background The present study is to screen lymph node metastasis-related microRNAs (miRNAs) in lung adenocarcinoma (LUAD) and uncover their underlying mechanisms. Methods The miRNA microarray dataset was collected from the Gene Expression Omnibus database under accession number GSE64859. The differentially expressed miRNAs (DEMs) were identified using a t-test. Target genes of DEMs were predicted through the miRWalk2.0 database. The function of these target genes was annotated with the clusterProfiler and the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools. Protein-protein interaction network was established using the STRING database to extract hub target genes. The expressions and associations with survival and lymph node metastasis of miRNAs and target genes were validated by analysis of The Cancer Genome Atlas (TCGA) dataset. Results Eight DEMs were identified between lymph node metastasis and non-metastasis samples of GSE64859 dataset. miRNA-target gene pairs were predicted between six DEMs and 251 target genes (i.e. hsa-miR-224-PRPF4B, hsa-miR-147b-WDR82 and hsa-miR-31-NR3C2). The clusterProfiler analysis showed WDR82 was involved in the mRNA surveillance pathway, while the GO enrichment analysis using the DAVID database indicated PRPF4B participated in the protein phosphorylation and NR3C2 was related with the transcription, DNA-templated. WDR82 and PRPF4B may be hub genes because they could interact with others. Two DEMs (miR-31-5p and miR-31-3p) and 45 target genes (including PRPF4B and NR3C2) were significantly associated with overall survival. The expressions of miR-224 and miR-147b were validated to be upregulated, while WDR82, PRPF4B and NR3C2 were downregulated in lymph node metastasis samples of TCGA datasets compared with non-metastasis samples. Also, there were significantly negative expression correlations between miR-147b and WDR82, between miR-224 and PRPF4B, as well as between miR-31 and NR3C2 in LUAD samples. Conclusions The present study identified several crucial miRNA-mRNA interaction pairs, which may provide novel explanations for the lymph node metastasis and poor prognosis for LUAD patients.

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Section: Discussionmentioning

confidence: 81%

Section: Discussionmentioning

confidence: 99%

miR-224, miR-147b and miR-31 associated with lymph node metastasis and prognosis for lung adenocarcinoma by regulating PRPF4B, WDR82 or NR3C2

Wang

Shang

et al. 2020

PeerJ

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“…CDO1 is a metabolic liability for NSCLC [ 34 ], and the functional identification of cancer-specific methylation of CDO1 could be applied for the diagnosis of lung cancer [ 35 ]. The expression of MFAP4 is negatively regulated by miR-147b in LUAD cells [ 36 ]. The deubiquitinase USP10 moderates KLF4 stability and suppresses lung tumorigenesis [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

Potential Prognostic Biomarkers of Lung Adenocarcinoma Based on Bioinformatic Analysis

Hou

Cheng

2021

BioMed Research International

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Lung adenocarcinoma (LUAD), which accounts for 60% of non-small-cell lung cancers, is poorly diagnosed and has a low average 5-year survival rate (approximately 20%). It remains the leading cause of cancer-related deaths worldwide. Studies on long noncoding RNAs (lncRNAs) in LUAD-related competing endogenous RNA (ceRNA) networks are limited. We aimed to identify novel prognostic biomarkers for LUAD using bioinformatic tools and data analysis. We systemically integrated differentially expressed genes and clinically significant modules using weighted correlation network analysis. We performed a functional analysis of the collected candidate genes and explored three LUAD-related genes (VWF, PECAM1, and COL1A1) associated with the overall survival rates of patients with LUAD. Based on Cox proportional hazards analysis of candidate mRNAs and lncRNAs together with differentially expressed microRNAs, we constructed ceRNA networks, obtained 12 lncRNAs in the ceRNA networks, and revealed seven novel lncRNAs AC021016.2, AC079630.1, AC116407.1, AC125807.2, AF131215.5, LINC01936, and RHOXF1-AS1. These lncRNAs were found to be associated with overall survival rates and are suitable for the prediction of prognosis by Kaplan-Meier survival and receiver operating characteristic curve analyses. In particular, three lncRNAs—AF131215.5, AC125807.2, and LINC01936—showed an independent prognostic value of overall survival for patients with LUAD. We evaluated the diagnostic capabilities of seven lncRNAs for patients with LUAD using principal component analysis and the Gene Set Variation Analysis index. lncRNAs and crucial genes could be effectively used for distinguishing LUAD tumors from normal tissues in the Gene Expression Omnibus profile. In particular, AC021016.2 showed a significant prognostic value in the validation dataset. Our findings reveal the significance of exploring lncRNAs in cancer-related ceRNAs using bioinformatic strategies.

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“…MFAP4 has been associated with immune response ( Niu et al, 2011 ), liver fibrosis ( Madsen et al, 2020 ), renal fibrosis ( Pan et al, 2020 ), atherosclerosis ( Wulf-Johansson et al, 2013 ), pulmonary airspace enlargement ( Holm et al, 2015 ), and abdominal aortic aneurysms ( Lindholt et al, 2020 ). MFAP4 was also found to be involved in human cancers, such as pancreatic adenocarcinoma ( Guerrero et al, 2021 ), serous OC ( Zhao et al, 2019 ), breast cancer ( Yang et al, 2019 ), and lung cancer ( Feng et al, 2020 ). Yang et al (2019) found that MFAP4 was down-regulated and may function as a tumor suppressor in breast cancer.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Prognostic Nomogram Based on DNA Methylation-Driven Genes for Patients With Ovarian Cancer

Zhou

Hong

et al. 2021

Front. Genet.

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Background: DNA methylation affects the development, progression, and prognosis of various cancers. This study aimed to identify DNA methylated-differentially expressed genes (DEGs) and develop a methylation-driven gene model to evaluate the prognosis of ovarian cancer (OC).Methods: DNA methylation and mRNA expression profiles of OC patients were downloaded from The Cancer Genome Atlas, Genotype-Tissue Expression, and Gene Expression Omnibus databases. We used the R package MethylMix to identify DNA methylation-regulated DEGs and built a prognostic signature using LASSO Cox regression. A quantitative nomogram was then drawn based on the risk score and clinicopathological features.Results: We identified 56 methylation-related DEGs and constructed a prognostic risk signature with four genes according to the LASSO Cox regression algorithm. A higher risk score not only predicted poor prognosis, but also was an independent poor prognostic indicator, which was validated by receiver operating characteristic (ROC) curves and the validation cohort. A nomogram consisting of the risk score, age, FIGO stage, and tumor status was generated to predict 3- and 5-year overall survival (OS) in the training cohort. The joint survival analysis of DNA methylation and mRNA expression demonstrated that the two genes may serve as independent prognostic biomarkers for OS in OC.Conclusion: The established qualitative risk score model was found to be robust for evaluating individualized prognosis of OC and in guiding therapy.

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MicroRNA-147b promotes lung adenocarcinoma cell aggressiveness through negatively regulating microfibril-associated glycoprotein 4 (MFAP4) and affects prognosis of lung adenocarcinoma patients

Cited by 29 publications

References 27 publications

miR-224, miR-147b and miR-31 associated with lymph node metastasis and prognosis for lung adenocarcinoma by regulating PRPF4B, WDR82 or NR3C2

miR-224, miR-147b and miR-31 associated with lymph node metastasis and prognosis for lung adenocarcinoma by regulating PRPF4B, WDR82 or NR3C2

Potential Prognostic Biomarkers of Lung Adenocarcinoma Based on Bioinformatic Analysis

Development and Validation of a Prognostic Nomogram Based on DNA Methylation-Driven Genes for Patients With Ovarian Cancer

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