Quantitative proteomic analysis of the miR‑148a‑associated mechanisms of metastasis in non‑small cell lung cancer

Chu, Dandan; Li, Jing; Lin, Hechun; Zhang, Xiao; Pan, Hongyu; Liu, Lei; Yu, Tao; Yan, Mingxia; Yao, Ming

doi:10.3892/ol.2018.8581

Cited by 6 publications

(5 citation statements)

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“…MiR-148a is a member of miR-148/152 family and its dysregulatiuon has been observed in several human cancers [15][16][17]. In this study, we found that the expression of miR-148a was significantly down-regulated in OSCC tissues and cells.…”

Section: Discussionmentioning

confidence: 48%

“…MiRNA-148a (MiR-148a) belongs to miR-148/miR-152 family which is characterized by a stem-loop structure [14]. The abnormal expression of miR-148a has been observed in several human cancers, including gastric cancer [15], esophageal squamous cell carcinoma [16], non-small cell lung cancer [17] etc. The function of miR-148a in OSCC was also reported in published articles.…”

Section: Introductionmentioning

confidence: 99%

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MiR-148a inhibits oral squamous cell carcinoma progression through ERK/MAPK pathway via targeting IGF-IR

et al. 2020

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Objective: The current study aimed to investigate the functional roles and clinical significance of microRNA-148a (miR-148a) in the progression of oral squamous cell carcinoma (OSCC). Methods: Relative expression of miR-148a in OSCC cells and tissues were detected using quantitative real-time polymerase chain reaction (qRT-PCR). Chi-square test was performed to estimate the relationship between miR-148a expression and clinical characteristics of OSCC patients. Cell transfection was carried out using Lipofectamine® 2000. Biological behaviors of tumor cells were detected using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and transwell assays. Bioinformatics analysis and luciferase reporter assay were used to identify the target genes of miR-148a. Protein expression was detected through Western blot analysis. Results: MiR-148a expression was obviously decreased in OSCC tissues and cells, and such down-regulation was closely correlated with lymph node metastasis (P=0.027) and tumor node metastasis (TNM) stage (P=0.001) of OSCC patients. miR-148a overexpression could significantly impair OSCC cell proliferation, migration and invasion in vitro (P<0.05 for all). Insulin-like growth factor-I receptor (IGF-IR) was a potential target of miR-148a. MiR-148a could inhibit ERK/MAPK signaling pathway through targeting IGF-IR. Conclusion: MiR-148a plays an anti-tumor role in OSCC and inhibits OSCC progression through suppressing ERK/MAPK pathway via targeting IGF-IR.

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Section: Discussionmentioning

confidence: 48%

Section: Introductionmentioning

confidence: 99%

MiR-148a inhibits oral squamous cell carcinoma progression through ERK/MAPK pathway via targeting IGF-IR

et al. 2020

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“…6). For example, two highlighted miRNAs, hsa-mir-7a and hsa-mir-155, play important roles in both lung cancer 27,28 and asthma, 29,30 which are involved in multiple meta-paths in Fig. 6.…”

Section: Resultsmentioning

confidence: 99%

A network-based approach to uncover microRNA-mediated disease comorbidities and potential pathobiological implications

et al. 2019

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Disease–disease relationships (e.g., disease comorbidities) play crucial roles in pathobiological manifestations of diseases and personalized approaches to managing those conditions. In this study, we develop a network-based methodology, termed meta-path-based Disease Network (mpDisNet) capturing algorithm, to infer disease–disease relationships by assembling four biological networks: disease–miRNA, miRNA–gene, disease–gene, and the human protein–protein interactome. mpDisNet is a meta-path-based random walk to reconstruct the heterogeneous neighbors of a given node. mpDisNet uses a heterogeneous skip-gram model to solve the network representation of the nodes. We find that mpDisNet reveals high performance in inferring clinically reported disease–disease relationships, outperforming that of traditional gene/miRNA-overlap approaches. In addition, mpDisNet identifies network-based comorbidities for pulmonary diseases driven by underlying miRNA-mediated pathobiological pathways (i.e., hsa-let-7a- or hsa-let-7b-mediated airway epithelial apoptosis and pro-inflammatory cytokine pathways) as derived from the human interactome network analysis. The mpDisNet offers a powerful tool for network-based identification of disease–disease relationships with miRNA-mediated pathobiological pathways.

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“…Kaplan–Meier analysis revealed that seven miRNAs (miR-148a, miR-196a, miR-1246, miR-338-3p, miR-150, miR-645 and miR-342-5p) were closely related with the prognosis of glioma patients. miR-148a has been found to be abnormally expressed in diverse malignant tumors, such as colorectal cancer ( Tsai et al, 2019 ), ovarian cancer ( Zhu et al, 2019 ), hepatocellular carcinoma ( Babu & Muckenthaler, 2019 ), breast cancer ( Lacerda et al, 2019 ), esophageal cancer ( Wang et al, 2019 ), gastric cancer ( Song et al, 2018 ), non-small cell lung cancer ( Chu et al, 2018 ) and glioma ( Cai, Zhu & Gong, 2018 ; Cui et al, 2017 ). In addition, Cai, Zhu & Gong (2018) found that miR-148a regulated STAT3 pathway activity by directly targeting CADM1 to promote glioma cell growth and metastasis.…”

Section: Discussionmentioning

confidence: 99%

Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma

Chen

Cai

et al. 2020

PeerJ

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Background Glioma is the most common form of primary malignant intracranial tumor. Methods In the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNAs and multivariate Cox regression analysis was applied to establish a miRNA signature for predicting overall survival (OS) of glioma. The signature was assessed with the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and validated by data from Gene Expression Omnibus (GEO). Results Eight miRNAs (miR-1246, miR-148a, miR-150, miR-196a, miR-338-3p, miR-342-5p, miR-548h and miR-645) were included in the miRNA signature. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. The AUC in both the CGGA and GEO datasets was similar to that based on WHO 2007 classification (0.736 and 0.799) and WHO 2016 classification (0.663 and 0.807). Additionally, Kaplan–Meier plot revealed that high-risk score patients had a poorer clinical outcome. Multivariate Cox regression analysis suggested that the miRNA signature was an independent prognosis-related factor [HR: 6.579, 95% CI [1.227−35.268], p = 0.028]. Conclusion On the whole, in the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. The results may be conducive to predict the precise prognosis of glioma and to elucidate the underlying molecular mechanisms. However, further experimental researches of miRNAs are needed to validate the findings of this study.

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Quantitative proteomic analysis of the miR‑148a‑associated mechanisms of metastasis in non‑small cell lung cancer

Cited by 6 publications

References 67 publications

MiR-148a inhibits oral squamous cell carcinoma progression through ERK/MAPK pathway via targeting IGF-IR

MiR-148a inhibits oral squamous cell carcinoma progression through ERK/MAPK pathway via targeting IGF-IR

A network-based approach to uncover microRNA-mediated disease comorbidities and potential pathobiological implications

Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma

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