Mining featured micro ribonucleic acids associated with lung cancer based on bioinformatics

Emerging roles of MiR-133a in human cancers

MicroRNAs (miRNAs) can post-transcriptionally regulate the expression of cancer-relevant genes via binding to the 3'-untranslated region (3'-UTR) of the target mRNAs. MiR-133a, as a miRNA, participate in tumorigenesis, progression, autophagy and drug-resistance in various malignancies. Based on the recent insights, we discuss the functions of miR-133a in physiological and pathological processes and its potential effects on cancer diagnosis, prognosis and therapy.

Licochalcone A reverses NNK-induced ectopic miRNA expression to elicit in vitro and in vivo chemopreventive effects

BACKGROUND

Chemoprevention is the best cost-effective way regarding cancers. MicroRNAs (miRNAs) have been reported to be differentially expressed during the development of lung cancer. However, if lung cancer prevention can be achieved through modulating miRNAs expression so far remains unknown.

PURPOSE

To discover ectopically expressed miRNAs in NNK-induced lung cancer and clarify whether Licochalcone A (lico A) can prevent NNK-induced lung cancer by modulating miRNA expression.

STUDY DESIGN AND METHODS

A/J mice were used to construct a lung cancer model by intraperitoneal injection with physiological saline NNK (100 mg/kg). Chemopreventive effects of lico A against lung cancer at 2 mg/kg and 20 mg/kg doses were evaluated in vivo. MicroRNA array and RT-qPCR were used to assess the expression levels of miRNAs. MLE-12 cells were treated with 0.1 mg/ml NNK, stimulating the ectopic expression pattern of miR-144-3p, miR-20a-5p, miR-29c-3p, let-7d-3p, and miR-328-3p. miR-144-3p mimics and inhibitors were used to manipulate miR-144-3p levels. The effects of lico A (10 μM) on cell cycle distribution, apoptosis, and the expression of CK19, RASA1, miR-144-3p, miR-20a-5p, miR-29c-3p, let-7d-3p, and miR-328-3p in NNK-treated MLE-12 cells were studied.

RESULTS

The expression levels of miR-144-3p, miR-20a-5p, and miR-29c-3p increased, while those of let-7d-3p and miR-328-3p decreased in both NNK-induced A/J mice and MLE-12 cells. Lico A could reverse the NNK-induced ectopic miRNA (miR-144-3p, miR-20a-5p, miR-29c-3p, let-7d-3p, and miR-328-3p) expression both in vivo and in vitro and elicit in vivo lung cancer chemopreventive effect against NNK. In MLE-12 cells, the overexpression of miR-144-3p elicited the same effect as NNK regarding the expression of lung cancer biomarker CK19; the silencing of miR-144-3p reversed the effect of NNK on cell cycle distribution and apoptosis. Lico A could reverse the effect of NNK on the expression of miR-144-3p, CK19, and RASA1 (predicted target of miR-144-3p).

CONCLUSION

The present study suggests that miR-144-3p, miR-20a-5p, miR-29c-3p, let-7d-3p, and miR-328-3p were involved in the in vivo pathogenesis of NNK-induced lung cancer, and lico A could reverse the effect of NNK both in vivo and in vitro to elicit lung cancer chemopreventive effects through, at least partially, these five ectopically expressed miRNAs, especially miR-144-3p.

IRGS: an immune-related gene classifier for lung adenocarcinoma prognosis

Background

Tumour cells interfere with normal immune functions by affecting the expression of some immune-related genes, which play roles in the prognosis of cancer patients. In recent years, immunotherapy for tumours has been widely studied, but a practical prognostic model based on immune-related genes in lung adenocarcinoma comparable to existing model has not been established and reported.

Methods

We first obtained publicly accessible lung adenocarcinoma RNA expression data from The Cancer Genome Atlas (TCGA) for differential gene expression analysis and then filtered immune-related genes based on the ImmPort database. By using the lasso algorithm and multivariate Cox Proportional-Hazards (CoxPH) regression analysis, we identified candidate genes for model development and validation. The robustness of the model was further examined by comparing the model with three established gene models.

Results

Gene expression data from a total of 524 lung adenocarcinoma patients from TCGA were used for model development. We identified four biomarkers (MAP3K8, CCL20, VEGFC, and ANGPTL4) that could predict overall survival in lung adenocarcinoma (HR = 1.98, 95% CI 1.48 to 2.64, P = 4.19e−06) and this model could be used as a classifier for the evaluation of low-risk and high-risk groups. This model was validated with independent microarray data and was highly comparable with previously reported gene expression signatures for lung adenocarcinoma prognosis.

Conclusions

In this study, we identified a practical and robust four-gene prognostic model based on an immune gene dataset with cross-platform compatibility. This model has potential value in improving TNM staging for survival predictions in patients with lung adenocarcinoma.

Impact

The study provides a method of immune relevant gene prognosis model and the identification of immune gene classifier for the prediction of lung adenocarcinoma prognosis with RNA sequencing and microarray compatibility.

A combined panel of circulating microRNA as a diagnostic tool for detection of the non-small cell lung cancer

BACKGROUND

Recently, much attention has been paid to use circulating microRNAs (miRs) as a non-invasive tumor marker. The present study for the first time was designed to evaluate concurrent use of miR-21, miR-638, miR148 and miR-152 as putative diagnostic tool for detection of non-small cell lung carcinoma (NSCLC).

METHODS

Forty-three patients diagnosed as primary NSCLC was included in this study. The level of selected miRs was measured in whole blood specimens of patients and controls. The corresponding values were also obtained in stages I-IV. We also assessed possible correlation between selected miRs and the clinicopathological findings of studied individuals.

RESULTS

miR-21 was increased in patients compared to controls (P = 0.004). In contrast, circulating miR-638, miR-148 and miR-152 was observed to be down-regulated in NSCLC patients than controls (P = 0.001, 0.003, 0.053, respectively). Rise in miR-21-5p expression and decreased blood level of miR-148a-3p was associated with higher stage of NSCLC. The highest sensitivity (90%) was observed for miR-21 while miR-148 had the highest specificity (71%). The corresponding sensitivity and specificity for combined-miRs-panel was 96.4% and 86.67%, respectively.

CONCLUSION

In summary, our data suggested the diagnostic importance of combined-miR-panel including miR-21, miR-638, miR148 and miR-152 for effective discrimination of NSCLC from non-cancerous subjects.

A survey on database resources for microRNA-disease relationships

The relationships between microRNAs (miRNAs) and diseases are garnering greater interest in the biological research fields. Recently, miRNA-disease databases have emerged as powerful tools for bioinformatics studies of these relationships. However, guidelines for comparing the features of this type of database have not yet been established. In this article, the details of popular miRNA-disease databases are analyzed, and their features are compared from several different aspects, including database scale, disease classification, miRNA targets, miRNA detection technique, miRNA regulation, quantitative scores, study design and tissue/cell lines. Then, guidelines for choosing a suitable database for specific research interests are provided. This survey will guide computational biology or biological researchers as well as medical and clinical researchers in making better use of miRNA-disease data resources.