Comprehensive analysis of competing endogenous RNA networks associated with cholangiocarcinoma

An immune-related microRNA signature prognostic model for pancreatic carcinoma and association with immune microenvironment

To establish a prognostic model based on immune-related microRNA (miRNA) for pancreatic carcinoma. Weighted correlation network analysis (WGCNA) was performed using the "WGCNA" package to find the key module genes involved in pancreatic carcinoma. Spearman correlation analysis was conducted to screen immune-related miRNAs. Uni- and multi-variate COX regression analyses were carried out to identify miRNAs prognostic for overall survival (OS) of pancreatic carcinoma, which were then combined to generate a prognostic model. Kaplan–Meier survival analysis, receiver operating characteristic (ROC) analysis, distribution plot of survival status in patients and regression analysis were collectively performed to study the accuracy of the model in prognosis. Target genes of the miRNAs in the model were intersected with the key module genes, and a miRNA–mRNA network was generated and visualized by Cytoscape3.8.0. TIMER analysis was conducted to study the abundance of immune infiltrates in tumor microenvironment of pancreatic carcinoma. Expression levels of immune checkpoint genes in subgroups stratified by the model were compared by Wilcoxon test. Gene Set Enrichment Analysis (GSEA) was performed to analyze the enriched signaling pathways between subgroups. Differential analysis revealed 1826 genes differentially up-regulated in pancreatic carcinoma and 1276 genes differentially down-regulated. A total of 700 immune-related miRNAs were obtained, of which 7 miRNAs were significantly associated with OS of patients and used to establish a prognostic model with accurate predictive performance. There were 99 mRNAs overlapped from the 318 target genes of the 7 miRNAs and the key modules genes analyzed by WGCNA. Patient samples were categorized as high or low risk according to the prognostic model, which were significantly associated with dendritic cell infiltration and expression of immune checkpoint genes (TNFSF9, TNFRSF9, KIR3DL1, HAVCR2, CD276 and CD80). GSEA showed remarkably enriched signaling pathways in the two subgroups. This study identified an immune-related 7-miRNA based prognostic model for pancreatic carcinoma, which could be used as a reliable tool for prognosis.

A two-microRNA signature predicts the progression of male thyroid cancer

In various cancers, microRNAs (miRNAs) are abnormally expressed, including thyroid cancer (TC). In recent years, the incidence of TC has increased annually around the world. Compared with female patients, male TC patients are more likely to have a postoperative recurrence and lymph node metastasis, and hence need second treatments. However, the molecular biological processes underlying this phenomenon are not understood. Therefore, we collected data on miRNA expression and clinical information of male TC patients from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs were identified between male TC tissues and matched normal tissues. The Kaplan–Meier method, univariate and multivariate Cox regressions, and receiver operating characteristic curve analyses were performed to assess the association between miRNAs and the disease-free survival of male TC patients. Gene Ontology (GO) and the Kyoto Encyclopaedia of Gene and Genome (KEGG) enrichment analyses were then used to explore the function of miRNA target genes. Furthermore, we evaluated the ability of the miRNA biomarker to predict survival in female TC patients. As a result, a total of 118 differentially expressed miRNAs were identified, including 25 upregulated and 93 downregulated miRNAs. Among them, miR-451a and miR-16-1-3p were confirmed to be independent prognostic factors for the disease-free survival rate. The target genes of miR-451a and miR-16-1-3p were identified, and functional analysis showed that these genes were enriched in 25 Go and KEGG accessions, including cell signal transduction, motor adhesion, phagocytosis, regulation of transcription, cell proliferation, angiogenesis, etc. Neither miR-451a and miR-16-1-3p, nor a prediction model based on both miRNAs effectively predicted survival in female TC patients. In conclusion, both miR-451a and miR-16-1-3p may play important roles in the processes of male TC. The two-miRNA signature involving miR-1258 and miR-193a may serve as a novel prognostic biomarker for male TC patients.

Identification of Prognostic Biomarkers and Correlation With Immune Infiltrates in Hepatocellular Carcinoma Based on a Competing Endogenous RNA Network

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC.

Methods

RNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve, TISIDB and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by quantitative polymerase chain reaction, Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds.

Results

The predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8⁺ T cells, CD4⁺ T cells, monocytes, macrophages, neutrophils, and dendritic cells.

Conclusion

The findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.

Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

Background

Competitive endogenous RNA (ceRNA) networks have revealed a new mechanism of interaction between RNAs, and play crucial roles in multiple biological processes and development of neoplasms. They might serve as diagnostic and prognosis markers as well as therapeutic targets.

Methods

In this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcomas by comparing the gene expression profiles between sarcoma and normal muscle samples in Gene Expression Omnibus (GEO) datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were applied to investigate the primary functions of the overlapped DEGs. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was constructed using Cytoscape software. In addition, the protein–protein interaction (PPI) network and survival analysis were performed.

Results

A total of 1296 DEGs were identified in sarcoma samples by combining the GO and KEGG enrichment analyses, 338 DELs were discovered after the probes were reannotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, through target gene prediction, a lncRNA–miRNA–mRNA ceRNA network that contained 113 mRNAs, 69 lncRNAs and 29 miRNAs was constructed. The PPI network identified the six most significant hub proteins. Survival analysis revealed that seven mRNAs, four miRNAs and one lncRNA were associated with overall survival of sarcoma patients.

Conclusions

Overall, we constructed a ceRNA network in sarcomas, which might provide insights for further research on the molecular mechanism and potential prognosis biomarkers.

Exosomal noncoding RNAs in cholangiocarcinoma: Laboratory noise or hope?

Currently, extracellular vesicles and particularly exosomes have gained a lot of research interest due to their unique roles in several biological processes. Noncoding RNAs (microRNAs, long noncoding RNAs and circular RNAs) represent a class of functional RNA with distinct regulatory roles in tumorigenesis and cancer progression. Cholangiocarcinoma is a rare but highly aggressive type of malignancy that is very challenging to diagnose, especially in early stages; surgical resection still represents the sole potentially curative treatment option. Hence, there is an urgent need for the discovery of novel diagnostic and prognostic biomarkers. Hereby, we provide a comprehensive review of the most recent discoveries that focus on exosomal noncoding RNAs in cholangio-carcinoma with the aim to identify new molecular players that could be used as biomarkers and therapeutic targets.

Long noncoding RNA OSER1‑AS1 promotes the malignant properties of non‑small cell lung cancer by sponging microRNA‑433‑3p and thereby increasing Smad2 expression

OSER1 antisense RNA 1 (OSER1-AS1), a long noncoding RNA, has been well studied in the context of hepatocellular carcinoma. However, its expression status, specific functions, and tumorigenic mechanism in non-small cell lung cancer (NSCLC) remain uninvestigated. Hence, this study aimed to assess OSER1-AS1 expression, test the malignancy-related biological functions of OSER1-AS1, and illustrate how they affect NSCLC progression. OSER1-AS1 expression in NSCLC was measured by reverse transcription-quantitative polymerase chain reaction. Cell Counting Kit-8 assay, flow cytometry, cell migration and invasion assay, and tumor xenograft assay were performed to analyze the effects of OSER1-AS1 on the malignant phenotypes of NSCLC cells. Bioinformatics prediction with luciferase reporter and RNA immunoprecipitation assays were performed to determine the interaction between OSER1-AS1 and microRNA-433-3p (miR-433-3p). OSER1-AS1 was strongly expressed in NSCLC tissues and cell lines. Enhanced OSER1-AS1 expression was significantly correlated with tumor size, TNM stage, and lymph node metastasis in patients with NSCLC. Patients with NSCLC exhibiting high OSER1-AS1 expression had shorter overall survival than those exhibiting low OSER1-AS1 expression. Functionally, a reduction in OSER1-AS1 expression led to significant decreases in NSCLC cell proliferation, migration, and invasion as well as an increase in cell apoptosis in vivo. OSER1-AS1 knockdown suppressed the tumorigenic ability of NSCLC cells in vivo. Mechanistically, OSER1-AS1 acts as a competing endogenous RNA (ceRNA) in NSCLC cells by sponging miR-433-3p and thereby increasing the expression of mothers against decapentaplegic homolog 2 (Smad2). Finally, restoration experiments revealed that the suppression of miR-433-3p and restoration of Smad2 both counteracted the suppressive effects of OSER1-AS1 depletion in NSCLC cells. Our findings illustrate the biological importance of the OSER1-AS1/miR-433-3p/Smad2 pathway in NSCLC progression and offer a novel perspective regarding the identification of effective therapeutic and diagnostic targets.

Multifaceted Aspects of Metabolic Plasticity in Human Cholangiocarcinoma: An Overview of Current Perspectives

Cholangiocarcinoma (CCA) is a deadly tumor without an effective therapy. Unique metabolic and bioenergetics features are important hallmarks of tumor cells. Metabolic plasticity allows cancer cells to survive in poor nutrient environments and maximize cell growth by sustaining survival, proliferation, and metastasis. In recent years, an increasing number of studies have shown that specific signaling networks contribute to malignant tumor onset by reprogramming metabolic traits. Several evidences demonstrate that numerous metabolic mediators represent key-players of CCA progression by regulating many signaling pathways. Besides the well-known Warburg effect, several other different pathways involving carbohydrates, proteins, lipids, and nucleic acids metabolism are altered in CCA. The goal of this review is to highlight the main metabolic processes involved in the cholangio-carcinogeneis that might be considered as potential novel druggable candidates for this disease.