Independent prognostic miRNAs for bladder urothelial carcinoma

Screening of miRNAs as prognostic biomarkers and their associated hub targets across Hepatocellular carcinoma using survival-based bioinformatics approach

BACKGROUND

The hepatocellular carcinoma (HCC) incident rate is gradually increasing yearly despite all the research and efforts taken by scientific communities and governing bodies. Approximately 90% of all liver cancer cases belong to HCC. Usually, HCC patients approach the treatment in the late stages of this malignancy which becomes the primary cause of high mortality rate. The knowledge about molecular pathogenesis of HCC is limited and needs more attention from researchers to identify the driver genes and miRNAs, which causes to translate this information into clinical practice. Therefore, the key regulators identification of miRNA-mRNA regulatory network is essential to identify HCC-associated genes.

METHODOLOGY

We extracted microRNA (miRNA) and messenger RNA (mRNA) expression datasets of normal and tumor HCC patient samples from UCSC Xena followed by identifying differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs). Univariate and multivariate cox-proportional hazard models were utilized to identify DEMs having significant association with overall survival (OS). Kaplan-Meier (KM) plotter was used to validate the presence of prognostic DEMs. A risk-score model was used to evaluate the effectiveness of KM-plotter validated DEMs combination on risk of samples. Target DEGs of prognostic miRNAs were identified via sources such as miRTargetLink and miRWalk followed by their validation in an external microarray cohort and enrichment analysis.

RESULTS

562 DEGs and 388 DEMs were identified followed by seven prognostic miRNAs (i.e., miR-19a, miR-19b, miR-30d-5p, miR-424-5p, miR-3677-5p, miR-3913-5p, miR-7705) post univariate, multivariate, risk-score model evaluation and KM-plotter analyses. ANLN, MRO, CPEB3 were their targets and were also validated in GSE84005 dataset.

CONCLUSIONS

The findings of this study decipher that most significant miRNAs and their identified target genes have association with apoptosis, inflammation, cell cycle regulation and cancer-related pathways, which appear to contribute to HCC pathogenesis and therefore, the discovery of new targets.

Detecting plasma hsa_circ_0061276 in patients with gastric cancer by reverse transcription-digital polymerase chain reaction

Background

The role of circular RNAs (circRNAs) in the occurrence of gastric cancer is still unclear. Therefore, the diagnostic value and mechanisms underlying hsa_circ_0061276 in the occurrence of gastric cancer were explored.

Methods

Reverse transcription-droplet digital polymerase chain reaction was used to detect the copy number of hsa_circ_0061276 in plasma from healthy individuals, as well as from patients with gastric precancerous lesions or early-stage or advanced gastric cancer. Plasmids overexpressing or knocking down hsa_circ_0061276 expression were transfected into gastric cancer cells. The effects on the growth, migration, and cell cycle distribution of gastric cancer cells were then analyzed. Finally, miRanda and RNAhybrid were used to explore the binding sites between hsa_circ_0061276 and microRNAs (miRNAs). A double luciferase reporter gene assay was used to confirm the miRNA sponge effect.

Results

The results show that plasma hsa_circ_0061276 copy number showed a trend of a gradual decrease when comparing healthy controls to the early cancer group and advanced gastric cancer group. Overexpression of hsa_circ_0061276 inhibited the growth and migration of gastric cancer cells. Through bioinformatic analyses combined with cellular experiments, it was found that hsa_circ_0061276 inhibited the growth of gastric cancer by binding to hsa-miR-7705.

Conclusion

Hsa_circ_0061276 may be a new biomarker for gastric cancer. The tumor suppressor role of hsa_circ_0061276 on gastric cancer likely occurs through a sponge effect on miRNAs such as hsa-miR-7705.

Gemcitabine-Resistant Biomarkers in Bladder Cancer are Associated with Tumor-Immune Microenvironment

To identify key biomarkers in gemcitabine (GEM)-resistant bladder cancer (BCa) and investigate their associations with tumor-infiltrating immune cells in a tumor immune microenvironment, we performed the present study on the basis of large-scale sequencing data. Expression profiles from the Gene Expression Omnibus GSE77883 dataset and The Cancer Genome Atlas BLCA dataset were analyzed. Both BCa development and GEM-resistance were identified to be immune-related through evaluating tumor-infiltrating immune cells. Eighty-two DEGs were obtained to be related to GEM-resistance. Functional enrichment analysis demonstrated they were related to regulation of immune cells proliferation. Protein-protein interaction network selected six key genes (CAV1, COL6A2, FABP4, FBLN1, PCOLCE, and CSPG4). Immunohistochemistry confirmed the down-regulation of the six key genes in BCa. Survival analyses revealed the six key genes were significantly associated with BCa overall survival. Correlation analyses revealed the six key genes had high infiltration of most immune cells. Gene set enrichment analysis further detected the key genes might regulate GEM-resistance through immune response and drug metabolism of cytochrome P450. Next, microRNA-gene regulatory network identified three key microRNAs (hsa-miR-124-3p, hsa-miR-26b-5p, and hsa-miR-192-5p) involved in GEM-resistant BCa. Connectivity Map analysis identified histone deacetylase inhibitors might circumvent GEM-resistance. In conclusion, CAV1, COL6A2, FABP4, FBLN1, PCOLCE, and CSPG4 were identified to be critical biomarkers through regulating the immune cell infiltration in an immune microenvironment of GEM-resistance and could act as promising treatment targets for GEM-resistant muscle-invasive BCa.

An eight-mRNA signature predicts the prognosis of patients with bladder urothelial carcinoma

Background

Bladder cancer is one of the most common cancers, and its histopathological type is mainly bladder urothelial carcinoma, accounting for about 90%. The prognostic biomarkers of bladder cancer are classified into clinical features biomarkers and molecular biomarkers. Nevertheless, due to the existence of individual specificity, patients with similar pathological characteristics still have great differences in the risk of disease recurrence. Therefore, it is often inaccurate to predict the survival status of patients based on clinical characteristic biomarkers, and a prognostic molecular biomarker that can grade the risk of bladder cancer patients is needed.

Methods

A total of three bladder urothelial carcinoma datasets were used in this study from the Cancer Genome Atlas database and Gene Expression Omnibus database. In order to avoid overfitting, all samples were randomly divided into one training set and three validation sets, which were used to construct and test the prognostic biomarker model of bladder urothelial carcinoma. Univariate and multivariate Cox regression were used to screen candidate mRNAs and construct prognostic biomarkers model. Kaplan-Meier survival analysis and the receiver operating characteristic (ROC) curve were used to evaluate the predictive performance of the model.

Results

A prognostic biomarker model of bladder urothelial carcinoma combining with eight mRNA was constructed. Kaplan-Meier analyses indicated that a significant difference in the survival time of patients between the high-risk and the low-risk group. The area under the ROC curve were 0.632 (95% confidence interval (CI) [0.541-0.723]), 0.693 (95% CI [0.601-0.784]) and 0.686 (95% CI [0.540-0.831]) when the model was used to predict the patient's survival time in three validation datasets. The model showed high accuracy and applicability.

Identification of miRNA profiling in prediction of tumor recurrence and progress and bioinformatics analysis for patients with primary esophageal cancer: Study based on TCGA database

OBJECT

This study focused on the identification of prognostic miRNAs for the prediction of tumor recurrence and progress in esophageal cancer.

METHODS

MiRNA profiling and clinical characteristics of esophageal cancer patients was downloaded from the TCGA database. Univariate analysis was performed to select potential prognostic miRNAs and covariates. LASSO based logistic regression was conducted to identify the prognostic miRNAs given covariates. Bioinformatics analysis including gene ontology, disease ontology and pathway enrichment analysis were performed. A nomogram was generated based on multivariate logistic regression to illustrate the association between the identified miRNAs and the risk of tumor recurrence and progress.

RESULTS

A total of 1881 miRNAs and 10 clinical characteristics were obtained from TCGA database. 18 miRNAs were finally identified in which 6 miRNAs were identified for the first time to be associated with the tumor recurrence and progress of esophageal cancer given covariates. Bioinformatics analysis suggested that the identified miRNAs were associated with the tumor recurrence and progress of esophageal cancer. The association between identified miRNAs and risk of tumor recurrence and progress were presented in a nomogram.

CONCLUSION

The 6 newly identified miRNAs may be potential biomarkers for the prediction of tumor recurrence and progress of esophageal cancer.

Tumor-suppressing effects of microRNA-612 in bladder cancer cells by targeting malic enzyme 1 expression

The present study investigated the possible tumor-suppressing function of microRNA (miR)-612 and the underlying molecular mechanism of its action in bladder cancer in vitro and in vivo. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to quantify the expression levels of miR-612 in bladder cancer tissues and cell lines. The data demonstrated that the level of miR-612 expression was significantly reduced in bladder cancer tissues and cell lines, as compared with that in non-cancerous tissues and cells. Reduced miR-612 expression was associated with advanced tumor, lymph node and metastasis stages, and with distant metastasis of bladder cancer. A functional study revealed that transfection of cells with an miR-612 mimic suppressed bladder cancer cell growth, colony formation, migration, invasion and epithelial-mesenchymal transition. Bioinformatics analysis identified that miR-612 targeted the expression of malic enzyme 1 (ME1), and this was confirmed by western blot and luciferase reporter assay results. Furthermore, the ME1 expression levels were inversely associated with miR-612 expression in bladder cancer tissue specimens. In addition, knockdown of ME1 expression using ME1 siRNA mimicked the effect of ectopic miR-612 overexpression in bladder cancer cells in terms of tumor cell growth, migration and invasion. By contrast, ME1 overexpression weakened the inhibitory effect of the miR-612 mimic in bladder cancer cells. In conclusion, the present study demonstrated that miR-612 may function as a tumor suppressor in bladder cancer by targeting ME1 expression.