Recently, increasing evidence has uncovered the roles of mRNA-miRNA-lncRNA network in multiple human cancers. However, a systematic mRNA-miRNA-lncRNA network linked to pancreatic cancer prognosis is still absent. Differentially expressed genes (DEGs) were first identified by mining GSE16515 and GSE15471 datasets. DAVID database was utilized to conduct functional enrichment analysis. Protein-protein interaction (PPI) network was built using STRING database, and hub genes were identified by Cytoscape plug-in CytoHubba. Upstream miRNAs and lncRNAs of mRNAs were predicted by miRTarBase and miRNet, respectively. Expression, survival and correlation analysis for genes, miRNAs and lncRNAs were performed via GEPIA, Kaplan-Meier plotter and starBase. 734 and 180 upregulated and downregulated significant DEGs were identified, respectively. Functional enrichment analysis revealed that they were significantly enriched in focal adhesion, pathways in cancer and metabolic pathways. According to node degree, hub genes in the PPI networks were screened, such as TGFB1 and ALB. Among the top 20 hub genes, 7 upregulated genes and 2 downregulated hub genes had significant prognostic values in pancreatic cancer. 33 miRNAs were predicted to target the 9 key genes. But only high expression of 8 miRNAs indicated favorable prognosis in pancreatic cancer. Then, 90 lncRNAs were predicted to potentially bind to the 8 miRNAs. SCAMP1, HCP5, MAL2 and LINC00511 were finally identified as key lncRNAs. By combination of results from expression, survival and correlation analysis demonstrated that MMP9/ITGB1-miR-29b-3p-HCP5 competing endogenous RNA (ceRNA) sub-network was linked to prognosis of pancreatic cancer. In a word, we established a novel mRNA-miRNA-lncRNA sub-network, among which each RNA may be utilized as a prognostic biomarker of pancreatic cancer.

Pseudogenes, abundant in the human genome, are traditionally considered as non-functional “junk genes.” However, recent studies have revealed that pseudogenes act as key regulators at DNA, RNA or protein level in diverse human disorders (including cancer), among which pseudogene-derived long non-coding RNA (lncRNA) transcripts are extensively investigated and has been reported to be frequently dysregulated in various types of human cancer. Growing evidence demonstrates that pseudogene-derived lncRNAs play important roles in cancer initiation and progression by serving as competing endogenous RNAs (ceRNAs) through competitively binding to shared microRNAs (miRNAs), thus affecting both their cognate genes and unrelated genes. Herein, we retrospect those current findings about expression, functions and potential ceRNA mechanisms of pseudogene-derived lncRNAs in human cancer, which may provide us with some crucial clues in developing potential targets for cancer therapy in the future.

Hepatitis B virus (HBV) is one of the major risk factors of hepatocellular carcinoma (HCC). Increasing evidence indicates that microRNA (miRNA)–mRNA axis is involved in HCC. However, a comprehensive miRNA–mRNA regulatory network in HBV-related HCC is still absent. This study aims to identify potential miRNA–mRNA regulatory pathways contributing to pathogenesis of HBV-related HCC. Microarray GSE69580 was downloaded from Gene Expression Omnibus (GEO) database. GEO2R and ‘R-limma’ were used to conduct differential expression analysis. The common miRNAs appeared in the two analytic sets were screened as potential differentially expressed miRNAs (DE-miRNAs). The prognostic roles of screened DE-miRNAs in HCC were further evaluated using Kaplan–Meier plotter database. Target genes of DE-miRNAs were predicted by miRNet. Then, protein–protein interaction (PPI) networks were established for these targets via the STRING database, after which hub genes in the networks were identified by Cytoscape. Functional annotation and pathway enrichment analyses for the target genes were performed through DAVID database. Three enriched pathways related to HBV-related HCC were selected for further analysis and potential target genes commonly appeared in all three pathways were screened. Cytoscape was employed to construct miRNA-hub gene network. The expression and correlation of potential miRNAs and targets were further detected in clinical HBV-related HCC samples by qRT-PCR. 7 upregulated and 9 downregulated DE-miRNAs were accessed. 5 of 7 upregulated DE-miRNAs and 5 of 7 downregulated DE-miRNAs indicated significant prognostic roles in HCC. 2312 and 1175 target genes were predicted for the upregulated and downregulated DE-miRNAs, respectively. TP53 was identified as the hub gene in the PPI networks. Pathway enrichment analysis suggested that these predicted targets were linked to hepatitis B, pathways in cancer, microRNAs in cancer and viral carcinogenesis. Further analysis of these pathways screened 20 and 16 target genes for upregulated and downregulated DE-miRNAs, respectively. By detecting the expression of 36 target genes, six candidate target genes were identified. Finally, a potential miRNA–mRNA regulatory network was established based on the results of qRT-PCR and expression correlation analysis. In the study, potential miRNA–mRNA regulatory pathways were identified, exploring the underlying pathogenesis and effective therapy strategy of HBV-related HCC.

Hepatocellular carcinoma (HCC) has been one of the most highly lethal cancers. The acquisition of drug resistance accounts for the majority of poor effects of chemotherapy in HCC. Non-coding RNAs (ncRNAs) including miRNAs, long ncRNAs (lncRNAs), and circular RNA (circRNA) have been well-documented to participate in cancer occurrence and progression. Recently, multiple studies have highlighted the key roles of ncRNAs in chemoresistance of HCC. In addition, accumulating evidence has demonstrated that they can serve as biomarkers in diagnosis, treatment, and prognosis of HCC. In this review, we first overviewed up-to-date findings regarding miRNA and lncRNA in drug resistance of HCC, then summarized specific mechanisms that they modulate chemoresistance of HCC, and finally discussed their potential clinical application in overcoming the obstacle of HCC chemoresistance in the future.

Circular RNAs (circRNAs), a novel class of non-coding RNAs, have been found to act as microRNA (miRNA) sponges and thus play key roles in biological processes and pathogenesis. However, studies regarding circRNAs in colorectal cancer (CRC) remain inadequate. By differential expression analysis, 10 candidate circRNAs (6 upregulated and 4 downregulated circRNAs) were chosen. 9 of 10 circRNAs were available on CSCD and their structure showed the binding potential of miRNA. Intersection analysis revealed that miR-145-5p, miR-3127-5p, miR-761, miR-4766-3p, miR-135a-5p, miR-135b-5p, miR-374a-3p and miR-330-3p were 8 miRNAs with the most potential in binding circRNAs. Further expression validation and correlation analysis demonstrated hsa_circ_0001955/miR-145-5p and hsa_circ_0000977/miR-135b-5p axes as key pathways in CRC. Subsequently, target gene prediction, differential expression analysis, intersection analysis and correlation analysis showed that CDK6, MMP12 and RAB3IP were the three potential downstream targets of hsa_circ_0001955/miR-145-5p axis and FOXO1, MBNL1, MEF2C, RECK, PPM1E, TTLL7 and PCP4L1 were the seven potential downstream targets of hsa_circ_0000977/miR-135b-5p axis in CRC. Finally, we also confirmed that expression of hsa_circ_0001955 or hsa_circ_0000977 was significantly positively correlated with their individual targets in CRC. In the present work, we constructed a potential hsa_circ_0001955/hsa_circ_0000977-mediated circRNA-miRNA-mRNA regulatory network in CRC by a series of in silico analysis and experimental validation. Whole-transcriptome microarrays from CRC and matched normal samples were obtained from GEO. The structure of circRNA was identified by CSCD. starBase and miRNet were successively used to predict miRNA of circRNA and target gene of miRNA. Expression correlation between RNA-RNA interactions was assessed using GEO and TCGA data. Finally, a potential circRNA-miRNA-mRNA network was established based on competing endogenous RNA (ceRNA) hypothesis.

Roles of Piezo-type mechanosensitive ion channel component 2 (PIEZO2) in cancer remain largely unknown. Herein, we explored PIEZO2 expression, prognosis and underlying mechanisms in cancer. Breast was selected as the candidate as its relatively higher expression level of PIEZO2 than other human tissues. Next, we identified a decreased expression of PIEZO2 in breast cancer compared with normal controls, and found that PIEZO2 expression positively correlated with estrogen receptor (ER) and progesterone receptor (PR) status but negatively correlated with human epidermal growth factor receptor 2 (HER2) status, Nottingham Prognostic Index (NPI) score, Scarff-Bloom-Richardson (SBR) grade, basal-like and triple-negative status. Subsequent analysis revealed that high expression of PIEZO2 had a favorable prognosis in breast cancer. 182 miRNAs were predicted to target PIEZO2. Among these miRNAs, five miRNAs (miR-130b-3p, miR-196a-5p, miR-301a-3p, miR-421 and miR-454-3p) possess the greatest potential in targeting PIEZO2. 109 co-expressed genes of PIEZO2 were identified. Pathway enrichment analysis showed that these genes were enriched in Hedgehog signaling pathway, including Cell adhesion molecule-related/downregulated by oncogenes (CDON). CDON expression was decreased in breast cancer and downregulation of CDON indicated a poor prognosis. Altogether, these findings suggest that decreased expression of PIEZO2 may be utilized as a prognostic biomarker of breast cancer.