Peng Lin

Diagnostic value of strand‐specific miRNA‐101‐3p and miRNA‐101‐5p for hepatocellular carcinoma and a bioinformatic analysis of their possible mechanism of action

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.

In silico analysis of the potential mechanism of telocinobufagin on breast cancer MCF-7 cells

BACKGROUNDS AND AIMSnThe extractives from a ChanSu, traditional Chinese medicine, have been discovered to possess anti-inflammatory and tumor-suppressing abilities. However, the molecular mechanism of telocinobufagin, a compound extracted from ChanSu, on breast cancer cells has not been clarified. The aim of this study is to investigate the underlying mechanism of telocinobufagin on breast cancer cells.nnnMETHODS AND MATERIALSnThe differentially expressed genes after telocinobufagin treatment on breast cancer cells were searched and downloaded from Gene Expression Omnibus (GEO), ArrayExpress and literatures. Bioinformatics tools were applied to further explore the potential mechanism of telocinobufagin in breast cancer using the Kyoto Encyclopedia of genes and genomes (KEGG) pathway, Gene ontology (GO) enrichment, panther, and protein-protein interaction analyses. To better comprehend the role of telocinobufagin in breast cancer, we also queried the Connectivity Map using the gene expression profiles of telocinobufagin treatment.nnnRESULTSnOne GEO accession (GSE85871) provided 1251 differentially expressed genes after telocinobufagin treatment on MCF-7 cells. The pathway of neuroactive ligand-receptor interaction, cell adhesion molecules (CAMs), intestinal immune network for IgA production, hematopoietic cell lineage and calcium signaling pathway were the key pathways from KEGG analysis. IGF1 and KSR1, owning to higher protein levels in breast cancer tissues, IGF1 and KSR1 could be the hub genes related to telocinobufagin treatment. It was indicated that the molecular mechanism of telocinobufagin resembled that of fenspiride.nnnCONCLUSIONSnTelocinobufagin might regulate neuroactive ligand-receptor interaction pathway to exert its influences in breast cancer MCF-7 cells, and its molecular mechanism might share some similarities with fenspiride. This study only presented a comprehensive picture of the role of telocinobufagin in breast cancer MCF-7 cells using big data. However, more thorough and deeper researches are required to add to the validity of this study.

The anticipating value of PLK1 for diagnosis, progress and prognosis and its prospective mechanism in gastric cancer: a comprehensive investigation based on high-throughput data and immunohistochemical validation

Polo-like kinase 1 (PLK1) is a multi-functional protein and its aberrant expression is a driver of cancerous transformation and progression. To increase our understanding of the clinical value and potential molecular mechanism of PLK1 in gastric cancer (GC), we performed this comprehensive investigation. A total of 25 datasets and 12 publications were finally incorporated. Additional immunohistochemistry was conducted to validate the expression pattern of PLK1 in GC. The pooled standard mean deviation (SMD) indicated that PLK1 mRNA was up-regulated in GC (SMD=1.21, 95% CI: 0.65-1.77, P< 0.001). Similarly, the pooled odds ratio (OR) revealed that PLK1 protein was overexpressed in GC compared with normal gastric tissue (OR=12.12, 95% CI: 5.41-27.16, P<0.001). The area under the curve (AUC) of the summary receiver operating characteristic (SROC) curve was 0.86. Furthermore, our results demonstrated that GC patients with PLK1 overexpression were significantly associated with unfavorable overall survival (HR =1.54, 95% CI: 1.30–1.83, P<0.001), lymph node metastasis (OR = 1.78, 95% CI: 1.13–2.80, P=0.013) and advanced TNM stage (OR=1.48, 95% CI: 1.02-2.15, P=0.038). Altogether, 100 similar genes were identified by Gene Expression Profiling Interactive Analysis (GEPIA) and further with gene-set enrichment analysis. These genes were related to gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways relevant to the cell cycle. Gene set enrichment analysis (GSEA) indicated that PLK1 is associated with various cancer-related pathways. Collectively, this study suggests that PLK1 overexpression could play vital roles in the carcinogenesis and deterioration of GC via regulating tumor-related pathways.

Biological function of UCA1 in hepatocellular carcinoma and its clinical significance: Investigation with in vitro and meta-analysis

Urothelial cancer associated 1 (UCA1) was upregulated in hepatocellular carcinoma (HCC) tissues and cell lines, and the expression of UCA1 was associated with several clinical features and malignant behaviours in HCC. However, none of these findings completely interpreted the role of UCA1 in HCC. We conducted this investigation to validate the expression of UCA1 and its relationship with Tumor Node Metastasis (TNM) stage in 41 HCC tissues and their paired noncancerous adjacent tissues by real-time qPCR. Furthermore, we also explored the biological functions of UCA1 in vitro with HCC cell lines. Most importantly, we conducted a comprehensive meta-analysis and bioinformatics investigation based on peer-reviewed literature and in silico approaches to further summarise the clinical value and functions of UCA1 in HCC. UCA1 expression was remarkably upregulated in HCC tissues, and its expression was profoundly higher in advanced stages than in early stages. Reducing the expression levels of UCA1 suppressed the proliferation and induced apoptosis of HCC cells. Furthermore, the present meta-analysis validated that up-regulated UCA1 was closely related to larger tumour size and advanced TNM stages, and the overexpression of UCA1 was significantly correlated with a shorter OS. Additionally, according to GO analysis, the target genes were found concentrated in the following biological processes: extracellular matrix organisation, cilium assembly and cilium morphogenesis. KEGG pathway analysis showed that the UCA1-related genes were significantly enriched in the following pathways: hippo signalling pathway, bile secretion and gastric acid secretion. This evidence hinted that UCA1 could play an indispensable proliferation-related key role in HCC via the hippo signalling pathway. However, the exact molecular mechanism needs to be verified with future functional experiments.

An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients

Prognostic signatures have been proposed as clinical tools to estimate prognosis in hepatocellular carcinoma (HCC), which is the second most common contributor to cancer-related death at present globally. Autophagy-related genes play a dynamic and fundamental role in HCC, but knowledge of their utility as prognostic markers is limited. Here, we facilitated univariate and multivariate Cox proportional hazards regression analyses to reveal that 3 autophagy-related genes (BIRC5, FOXO1 and SQSTM1) were closely related to the survival of HCC. Then, we generated a prognosis index (PI) for predicting overall survival (OS) based on the three genes, which was an independent prognostic indicator for the OS of HCC (HR = 1.930, 95% CI: 1.200–3.104, P = 0.007). The PI showed moderate performance for predicting the survival of HCC patients and its efficacy was validated by data from three microarrays (GSE10143, GSE10186 and GSE17856). Furthermore, we deeply mined the integrated large-scale datasets from public microarrays and immunohistochemistry to validate the overexpression of BIRC5 and SQSTM1 while down-regulated FOXO1 expression in HCC. Bioinformatic analysis offered the hypothesis that proliferative signals in high-risk HCC patients were disturbing and thereby facilitated inferior clinical outcomes. Collectively, the prognostic signature we proposed is a promising biomarker for monitoring outcome of HCC. Nevertheless, prospective experimental studies are needed to validate the clinical utility.

Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma

Cholangiocarcinoma (CCA) is one of the most common epithelial cell malignancies worldwide. However, its prognosis is poor. The aim of the present study was to examine the prognostic landscape and potential therapeutic targets for CCA. RNA sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) dataset and processed. A total of 172 genes that were significantly associated with overall survival of patients with CCA were identified using the univariate Cox regression method. Bioinformatics tools were applied using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO). It was identified that ‘Wnt signaling pathway’, ‘cytoplasm’ and ‘AT DNA binding’ were the three most significant GO categories of CCA survival-associated genes. ‘Transcriptional misregulation in cancer’ was the most significant pathway identified in the KEGG analysis. Using the Drug-Gene Interaction database, a drug-gene interaction network was constructed, and 31 identified genes were involved in it. The most meaningful potential therapeutic targets were selected via protein-protein and gene-drug interactions. Among these genes, polo-like kinase 1 (PLK1) was identified to be a potential target due to its significant upregulation in CCA. To rapidly find molecules that may affect these genes, the Connectivity Map was queried. A series of molecules were selected for their potential anti-CCA functions. 0297417-0002B and tribenoside exhibited the highest connection scores with PLK1 via molecular docking. These findings may offer novel insights into treatment and perspectives on the future innovative treatment of CCA.

Genomic analysis of small nucleolar RNAs identifies distinct molecular and prognostic signature in hepatocellular carcinoma

As one of the most lethal malignancies worldwide, hepatocellular carcinoma (HCC) has a high mortality rate, which is mainly due to the complex and multi‑step aberrations in gene expression associated with it. Small nucleolar RNAs (snoRNAs), non‑coding RNAs that are 60‑300xa0nucleotides in length, have been proposed to be closely associated with numerous human diseases, including HCC. However, the current knowledge regarding their clinical significance and mechanistic roles in HCC is limited. The present study comprehensively analyzed the snoRNA expression profiles in HCC and identified several ones that were dysregulated. The potential regulatory mechanisms of these snoRNAs were assessed via gene functional enrichment analyses. Univariate and multivariate Cox regression analyses were performed to identify snoRNAs that are independently associated with the risk of mortality. Subsequently, a prognostic index (PI) for survival prediction was established, which may serve as a prognostic biomarker for patients with HCC (hazard ratio, 3.023; 95% confidence interval: 1.785‑5.119; P<0.001). In addition, a series of bioinformatics analyses were performed to identify potential differences in the perturbation of pathways between high‑xa0and low‑risk groups. The PI developed in the present study was determined to have a moderate predictive value regarding the clinical outcome for HCC patients.

Downregulation of miR‑486‑5p in papillary thyroid carcinoma tissue: A study based on microarray and miRNA sequencing

Abnormal expression of microRNA (miR) is associated with the occurrence and progression of various types of cancers, including papillary thyroid carcinoma (PTC). In the present study, the aim was to explore miR-486-5p expression and its role in PTC, as well as to investigate the biological function of its potential target genes. The expression levels of miR-486-5p and its clinicopathological significance were examined in 507 PTC and 59 normal thyroid samples via The Cancer Genome Atlas (TCGA). Subsequently, the results were validated using data from Gene Expression Omnibus (GEO) and ArrayExpress. Receiver operating characteristic and summary receiver operating characteristic curves were used to assess the ability of miR-486-5p in distinguishing PTC from normal tissue. Furthermore, potential miR-486-5p mRNA targets were identified using 12 prediction tools and enrichment analysis was performed on the encoding genes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. The expression levels of miR-486-5p were consistently downregulated in PTC compared with in normal tissue across datasets from TCGA, GEO (GSE40807, GSE62054 and GSE73182) and ArrayExpress (E-MTAB-736). The results also demonstrated that miR-486-5p expression was associated with cancer stage (P=0.003), pathologic lymph node (P=0.047), metastasis (P=0.042), neoplasm (P=0.012) and recurrence (P=0.016) in patients with PTC. In addition, low expression of miR-486-5p in patients with PTC was associated with a worse overall survival. A total of 80 miR-486-5p-related genes were observed from at least 9 of 12 prediction platforms, and these were involved in ‘hsa05200: Pathways in cancer’ and ‘hsa05206: MicroRNAs in cancer’. Finally, three hub genes, CRK like proto-oncogene, phosphatase and tensin homolog and tropomyosin 3, were identified as important candidates in tumorigenesis and progression of PTC. In conclusion, it may be hypothesized that miR-486-5p contributes towards PTC onset and progression, and may act as a clinical target. However, in vitro and in vivo experiments are required to validate the findings of the present study.

Expression of the Long Intergenic Non-Protein Coding RNA 665 (LINC00665) Gene and the Cell Cycle in Hepatocellular Carcinoma Using The Cancer Genome Atlas, the Gene Expression Omnibus, and Quantitative Real-Time Polymerase Chain Reaction

Background Long 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/Methods Expression 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. Results Overexpression 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. Conclusions Overexpression of the lncRNA, LINC00665 may be involved in the regulation of cell cycle pathways in HCC through ten identified hub genes.

A circRNA–miRNA–mRNA network identification for exploring underlying pathogenesis and therapy strategy of hepatocellular carcinoma

BackgroundCircular RNAs (circRNAs) have received increasing attention in human tumor research. However, there are still a large number of unknown circRNAs that need to be deciphered. The aim of this study is to unearth novel circRNAs as well as their action mechanisms in hepatocellular carcinoma (HCC).MethodsA combinative strategy of big data mining, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and computational biology was employed to dig HCC-related circRNAs and to explore their potential action mechanisms. A connectivity map (CMap) analysis was conducted to identify potential therapeutic agents for HCC.ResultsSix differently expressed circRNAs were obtained from three Gene Expression Omnibus microarray datasets (GSE78520, GSE94508 and GSE97332) using the RobustRankAggreg method. Following the RT-qPCR corroboration, three circRNAs (hsa_circRNA_102166, hsa_circRNA_100291 and hsa_circRNA_104515) were selected for further analysis. miRNA response elements of the three circRNAs were predicted. Five circRNA–miRNA interactions including two circRNAs (hsa_circRNA_104515 and hsa_circRNA_100291) and five miRNAs (hsa-miR-1303, hsa-miR-142-5p, hsa-miR-877-5p, hsa-miR-583 and hsa-miR-1276) were identified. Then, 1424 target genes of the above five miRNAs and 3278 differently expressed genes (DEGs) on HCC were collected. By intersecting the miRNA target genes and the DEGs, we acquired 172 overlapped genes. A protein–protein interaction network based on the 172 genes was established, with seven hubgenes (JUN, MYCN, AR, ESR1, FOXO1, IGF1 and CD34) determined from the network. The Gene Oncology, Kyoto Encyclopedia of Genes and Genomes and Reactome enrichment analyses revealed that the seven hubgenes were linked with some cancer-related biological functions and pathways. Additionally, three bioactive chemicals (decitabine, BW-B70C and gefitinib) based on the seven hubgenes were identified as therapeutic options for HCC by the CMap analysis.ConclusionsOur study provides a novel insight into the pathogenesis and therapy of HCC from the circRNA–miRNA–mRNA network view.