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

Quantitative Proteomics Reveal the Mechanism of MiR-138-5p Suppressing Cervical Cancer via Targeting ZNF385A

MicroRNAs are short, noncoding RNA molecules that exert pivotal roles in cancer development and progression by modulating various target genes. There is growing evidence that miR-138-5p is significantly involved in cervical cancer (CC). However, its precise molecular mechanism has yet to be fully understood. In the current investigation, a quantitative proteomics approach was utilized to detect possible miR-138-5p targets in HeLa cells systematically. In total, 364 proteins were downregulated, and 150 were upregulated after miR-138-5p overexpression. Bioinformatic analysis of these differentially expressed proteins (DEPs) revealed significant enrichment in several cancer-related pathways. Zinc finger protein 385A (ZNF385A) was determined as a novel direct target of miR-138-5p and discovered to facilitate the proliferation, migration, and cell cycle progression of HeLa cells. SFN and Fas cell surface death receptor(FAS) were then identified as functional downstream effectors of ZNF385A and miR-138-5p. Moreover, a tumor xenograft experiment was conducted to validate the association of miR-138-5p-ZNF385A-SFN/FAS axis with the development of CC in vivo. Our findings have collectively established a catalog of proteins mediated by miR-138-5p and have provided an in-depth comprehension of the molecular mechanisms responsible for the inhibitory effect of miR-138-5p on CC. The miR-138-5p-ZNF385A-SFN/FAS axis could also be beneficial to the identification of new therapeutic targets.

Epigenome-wide DNA methylation in leukocytes and toenail metals: The normative aging study

BACKGROUND

Environmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window.

OBJECTIVES

This study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort.

METHODS

We repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data.

RESULTS

We included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease.

CONCLUSIONS

This study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.

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

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.

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

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.

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

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.