BackgroundLong non-coding RNAs (lncRNAs) have a role in physiological and pathological processes, including cancer. The aim of this study was to investigate the expression of the long intergenic non-protein coding RNA 665 (LINC00665) gene and the cell cycle in hepatocellular carcinoma (HCC) using database analysis including The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and quantitative real-time polymerase chain reaction (qPCR).Material/MethodsExpression levels of LINC00665 were compared between human tissue samples of HCC and adjacent normal liver, clinicopathological correlations were made using TCGA and the GEO, and qPCR was performed to validate the findings. Other public databases were searched for other genes associated with LINC00665 expression, including The Atlas of Noncoding RNAs in Cancer (TANRIC), the Multi Experiment Matrix (MEM), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) networks.ResultsOverexpression of LINC00665 in patients with HCC was significantly associated with gender, tumor grade, stage, and tumor cell type. Overexpression of LINC00665 in patients with HCC was significantly associated with overall survival (OS) (HR=1.47795%; CI: 1.046–2.086). Bioinformatics analysis identified 469 related genes and further analysis supported a hypothesis that LINC00665 regulates pathways in the cell cycle to facilitate the development and progression of HCC through ten identified core genes: CDK1, BUB1B, BUB1, PLK1, CCNB2, CCNB1, CDC20, ESPL1, MAD2L1, and CCNA2.ConclusionsOverexpression of the lncRNA, LINC00665 may be involved in the regulation of cell cycle pathways in HCC through ten identified hub genes.

Esophageal carcinoma (ESCA) is one of the most common malignancies worldwide, and its pathogenesis is complex. In this study, we identified differentially expressed miRNAs (DEMs) and genes (DEGs) of ESCA from The Cancer Genome Atlas (TCGA) database. The diagnostic values of DEMs were determined by receiver operating characteristic (ROC) analyses and validated based on data from Gene Expression Omnibus (GEO). The top five DEMs with the best diagnostic values were selected, and their potential targets were predicted by various in silico methods. These target genes were then identified among the DEGs from TCGA. Furthermore, the overlapping genes were subjected to protein-protein interaction (PPI) analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The miRNA-transcription factor (TF) regulatory relations were determined using CircuitsDB and TransmiR. Finally, the regulatory networks of miRNA-TF and miRNA-gene were constructed and analyzed. A total of 136 DEMs and 3541 DEGs were identified in ESCA. The top five DEMs with the highest area under the receiver operating characteristic curve (AUC) values were miRNA-93 (0.953), miRNA-21 (0.928), miRNA-4746 (0.915), miRNA-196a-1 (0.906) and miRNA-196a-2 (0.906). The combined AUC of these five DEMs was 0.985. The KEGG analysis with 349 overlapping genes showed that the calcium signaling pathway and the neuroactive ligand-receptor interaction were the most relevant pathways. The regulatory networks of miRNA-TF and miRNA-gene, including 38 miRNA-TF and 560 miRNA-gene pairs, were successfully established. Our findings may provide new insights into the molecular mechanisms of ESCA pathogenesis. Future research will aim to explore the role of novel miRNAs in the pathogenesis and improve the early diagnosis of ESCA.

BackgroundIRAK1 has been repoted to play an essential role in the development of multiple cancers. However, the clinical significance of IRAK1 in hepatocellular carcinoma (HCC) and the underlying molecular mechanism remain unclear. Therefore, we aimed to investigate the role of IRAK1 in the pathogenesis of HCC in this study.Materials and methodsHCC tissues and para-carcinoma tissues were collected for immunohistochemistry (IHC) analysis to evaluate IRAK1 expression. Data of IRAK1 expression were downloaded from the cancer genome atlas (TCGA) for analyzing the clinical significance of IRAK1. Receiver operating characteristic (ROC) curve and survival analyses were carried out to assess the diagnostic and prognostic significance of IRAK1 in IHC and TCGA data. Additionally, we investigated the alteration of IRAK1 gene in HCC from cBioPortal to generate a network of the interaction between IRAK1 and the neighboring genes. The influence of IRAK1 gene alteration on the prognosis of HCC patients was evaluated by survival analysis.ResultsAnalysis of both IHC and TCGA data revealed a significant upregulation of IRAK1 in HCC tissues. The IHC analysis revealed there was an increasing trend in IRAK1 expression among normal liver tissues, liver cirrhosis tissues, para-carcinoma tissues and HCC tissues. The ROC curves for IHC and TCGA data demonstrated that IRAK1 exhibited a significant diagnostic value for HCC. Moreover, IRAK1 expression was observed to be associated with tumor size, metastasis and T-stage. The survival analysis indicated that the upregulation of IRAK1 predicted a worse overall survival of HCC. Additionally, data from cBioPortal confirmed that 29% of HCC tissues possessed an alteration of the IRAK1 gene.ConclusionIRAK1 may act as an oncogene in the development of HCC with its overexpression in HCC. Moreover, IRAK1 might serve as a promising diagnostic and therapeutic target for HCC.

It has been discovered that miR-133a-3p acts as a tumor suppressor in bladder cancer (BC). Nevertheless, the function of miR-133a-3p in BC remains unclarified. Thus, we carried out this study to validate the expression of miR-133a-3p in BC and provide insights into the molecular mechanism underlying it. To assess the expression of miR-133a-3p in BC, we searched eligible studies from literature and Gene expression Omnibus (GEO) to perform a meta-analysis. We also plotted the summary receiver operating characteristic (SROC) curve to evaluate the diagnostic ability of miR-133a-3p in BC. Additionally, the potential target genes of miR-133a-3p were acquired from 14 online software programs and GEO database. Protein-protein interaction (PPI) network was created to identify the hub genes. Then, Gene Ontology (GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out to investigate the regulatory network of the target genes. From the meta-analysis, miR-133a-3p was remarkably downregulated in BC tissues compared with that in non-cancer tissues (standard mean difference =−3.84, 95% confidence interval =−6.99–0.29). Moreover, results from SROC suggested that miR-133a-3p exhibited the ability to diagnose BC (area under curve =0.8418). As for the bioinformatics study, 488 genes were chosen as the potential targets of miR-133a-3p in BC, among which 10 genes were defined as hub genes (all degrees >5). Further GO and KEGG pathway analysis indicated that the target genes of miR-133a-3p aggregated in specific biological process and pathways. In conclusion, miR-133a-3p possessed great diagnostic potential with its downregulation in BC, and miR-133a-3p might serve as a novel biomarker for BC.

Increasing evidence has demonstrated that microRNA (miR)-133a-3p is an important regulator of hepatocellular carcinoma (HCC). In the present study, the diagnostic role of miR-133a-3p in HCC, and the potential functional pathways, were both explored based on publicly available data. Eligible microarray datasets were collected from NCBI Gene Expression Omnibus (GEO) database and ArrayExpress database. The data related to HCC and matched adjacent normal tissues were also downloaded from The Cancer Genome Atlas (TCGA). Published studies reporting the association between miR-133a-3p expression and HCC were reviewed from multiple databases. By combining the data derived from three sources (GEO, TCGA and published studies), the authors analyzed the comprehensive relationship between miR-133a-3p expression and clinicopathological features of HCC. Eventually, putative targets of miR-133a-3p in HCC were selected for further bioinformatics prediction. A total of eight published microarray datasets were gathered, and the pooled results demonstrated that the expression of miR-133a-3p in the tumor group was lower than that in normal groups [standardized mean difference (SMD)=−0.54; 95% confidence interval (CI), −0.74 to −0.35; P<0.001]. Consistently, the level of miR-133a-1 in HCC was reduced markedly compared to normal tissues (P<0.001) based on TCGA data, and the AUC value of low miR-133a-1 expression for HCC diagnosis was 0.670 (P<0.001). Furthermore, the combined SMD of all datasets (GEO, TCGA and literature) suggested that significant difference was observed between the HCC group and the normal control group, and lower miR-133a-3p expression in HCC group was noted (SMD=−0.69; 95% CI, −1.10 to −0.29; P=0.001). In addition, the authors discovered five key genes of the calcium signaling pathway (NOS1, ADRA1A, ADRA1B, ADRA1D and TBXA2R) that may probably be targeted by miR-133a-3p in HCC. The study reveals that miR-133a-3p may function as a tumor suppressor in HCC. The prospective novel pathways and key genes of miR-133a-3p could offer potential biomarkers for HCC; however, the predictions require further confirmation.

In order to determine the diagnostic efficacy of microRNA (miR)-122-5p and to identify the potential molecular signaling pathways underlying the function of miR-122-5p in hepatocellular carcinoma (HCC), the expression profiles of data collected from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and literature databases were analyzed, along with any associations between clinicopathological characteristics and the diagnostic value of miR-122-5p in HCC. The intersection of 12 online prediction databases and differentially expressed genes from TCGA and GEO were utilized in order to select the prospective target genes of miR-122-5p in HCC. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction network (PPI) analyses were subsequently performed based on the selected target genes. The average expression level of miR-122-5p was decreased in HCC patients compared with controls from TCGA database (P<0.001), and the downregulation of miR-122-5p was significantly associated with HCC tissues (P<0.001), tumor vascular invasion (P<0.001), metastasis (P=0.001), sex (P=0.006), virus infection status (P=0.001) and tissue (compared with serum; P<0.001) in cases from the GEO database. The pooled sensitivity and specificity for miR-122-5p to diagnose HCC were 0.60 [95% confidence interval (CI), 0.48–0.71] and 0.81 (95% CI, 0.70–0.89), respectively. The area under the curve (AUC) value was 0.76 (95% CI, 0.72–0.80), while in Meta-DiSc 1.4, the AUC was 0.76 (Q*=0.70). The pooled sensitivity and specificity were 0.60 (95% CI, 0.57–0.62) and 0.79 (95% CI, 0.76–0.81), respectively. A total of 198 overlapping genes were selected as the potential target genes of miR-122-5p, and 7 genes were defined as the hub genes from the PPI network. Cell division cycle 6 (CDC6), minichromosome maintenance complex component 4 (MCM4) and MCM8, which serve pivotal functions in the occurrence and development of HCC, were the most significant hub genes. The regulation of cell proliferation for cellular adhesion and the biosynthesis of amino acids was highlighted in the GO and KEGG pathway analyses. The downregulation of miR-122-5p in HCC demonstrated diagnostic value, worthy of further attention. Therefore, miR-122-5p may function as a tumor suppressor by modulating genome replication.

Background Hepatocellular carcinoma (HCC) remains one of the most common cancers worldwide and tends to be detected at an advanced stage. More effective biomarkers for HCC screening and prognosis assessment are needed and the mechanisms of HCC require further exploration. The role of MAOA in HCC has not been intensively investigated. Methods In‐house tissue microarrays, genechips, and RNAsequencing datasets were integrated to explore the expression status and the clinical value of MAOA in HCC. Immunohistochemical staining was utilized to determine MAOA protein expression. Intersection genes of MAOA related co‐expressed genes and differentially expressed genes were obtained to perform functional enrichment analyses. In vivo experiment was conducted to study the impact of traditional Chinese medicine nitidine chloride (NC) on MAOA in HCC. Results MAOA was downregulated and possessed an excellent discriminatory capability in HCC patients. Decreased MAOA correlated with poor prognosis in HCC patients. Downregulated MAOA protein was relevant to an advanced TNM stage in HCC patients. Co‐expressed genes that positively related to MAOA were clustered in chemical carcinogenesis, where CYP2E1 was identified as the hub gene. In vivo experiment showed that nitidine chloride significantly upregulated MAOA in a nude mouse HCC model. Conclusions A decreased MAOA level is not only correlated with aggressive behaviors in males but also serves as a promising biomarker for the diagnosis and prognosis of HCC patients. Moreover, MAOA may play a role in AFB1 toxic transformation through its synergistic action with co‐expressed genes, especially CYP3A4. MAOA also serves as a potential therapy target of NC in HCC patients.

There is accumulating evidence that miRNA might serve as potential diagnostic and prognostic markers for various types of cancer. Hepatocellular carcinoma (HCC) is the most common type of malignant lesion but the significance of miRNAs in HCC remains largely unknown. The present study aimed to establish the diagnostic value of miR‐101‐3p/5p in HCC and then further investigate the prospective molecular mechanism via a bioinformatic analysis. First, the miR‐101 expression profiles and parallel clinical parameters from 362 HCC patients and 50 adjacent non‐HCC tissue samples were downloaded from The Cancer Genome Atlas (TCGA). Second, we aggregated all miR‐101‐3p/5p expression profiles collected from published literature and the Gene Expression Omnibus and TCGA databases. Subsequently, target genes of miR‐101‐3p and miR‐101‐5p were predicted by using the miRWalk database and then overlapped with the differentially expressed genes of HCC identified by natural language processing. Finally, bioinformatic analyses were conducted with the overlapping genes. The level of miR‐101 was significantly lower in HCC tissues compared with adjacent non‐HCC tissues (P < 0.001), and the area under the curve of the low miR‐101 level for HCC diagnosis was 0.925 (P < 0.001). The pooled summary receiver operator characteristic (SROC) of miR‐101‐3p was 0.86, and the combined SROC curve of miR‐101‐5p was 0.80. Bioinformatic analysis showed that the target genes of both miR‐101‐3p and miR‐101‐5p are involved in several pathways that are associated with HCC. The hub genes for miR‐101‐3p and miR‐101‐5p were also found. Our results suggested that both miR‐101‐3p and miR‐101‐5p might be potential diagnostic markers in HCC, and that they exert their functions via targeting various prospective genes in the same pathways.