Circular 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). A 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. Six 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. Our study provides a novel insight into the pathogenesis and therapy of HCC from the circRNA–miRNA–mRNA network view.

Matrix metalloproteinases (MMPs) are regarded to be relevant to the prognosis of breast cancer. Numerous studies have confirmed the association between MMPs and tumor growth, invasion and metastasis in breast cancer. However, their prognostic values for survival in patients with breast cancer remain controversial. Hence, a meta-analysis was performed to clarify a more accurate estimation of the role of MMPs on prognosis of breast cancer patients. A systemic electronic search was conducted in PubMed, Embase and Web of science databases to identify eligible studies, which were associated with the relationship between MMPs and prognosis of breast cancer. The correlation in random-effect model was evaluated by using the hazard ratios (HRs) and 95% confidence intervals (CIs). A total of 28 studies covering 4944 patients were included for meta-analysis. A summary hazard ratio (HR) of all studies was calculated, as well as the sub-group HRs. The combined HRs calculated by either univariate or multivariate analysis both suggested that overexpression of MMPs had an unfavorable impact on overall survival (OS) (HR = 1.694, 95%CI: 1.347–2.129, P < 0.001; HR = 1.611, 95%CI: 1.419–1.830, P < 0.001, respectively). And the univariate analysis showed that patients with overexpression of MMPs had worse relapse-free survival (RFS) (HR = 1.969, 95%CI: 1.460–2.655, P < 0.001) in all eligible studies. In the sub-group analyses, HRs of MMP-9 positivity with poor OS were 1.794 (95%CI: 1.330–2.420, P < 0.001) and 1.709 (95%CI: 1.157–2.526, P = 0.007) which were separately evaluated by univariate and multivariate analysis. A small number of articles demonstrated that MMP-2 overexpression was not related with shorter OS (HR = 1.400, 95%CI: 0.610–3.029, P = 0.427). Four studies included in the OS analysis of MMPs expression in serum suggested that positive expression of serum MMPs may be an unfavorable factor (HR = 1.630, 95%CI: 1.065–2.494) for breast cancer patients. No publication bias was observed in the current meta-analysis. Our findings suggested that MMPs overexpression (especially MMP-9, MMP-2, MMPs overexpression in serum) might indicate a higher risk of poor prognosis in breast cancer. Larger prospective studies are further needed to estimate the prognostic values of MMPs overexpression.

Ki-67 is a Valuable Prognostic Factor in Gliomas: Evidence from a Systematic Review and Meta-analysis Ki-67;glioma;meta-analysis;immunohistochemistry;prognosis;survival; Ki-67 has been widely used as an indicator of cell proliferation in gliomas. However, the role of Ki-67 as a prognostic marker is still undefined. Thus, we conducted a meta-analysis of the published literatures in order to clarify the impact of Ki-67 on survival in glioma cases. Eligible studies were identified in PubMed, EMBASE, ISI Web of Science, Cochrane Central Register of Controlled Trials, Science Direct and Wiley Online Library with the last search updated on August 31, 2014. The clinical characteristics, overall survival (OS) and progression-free survival (PFS) together with Ki-67 expression at different time points were extracted. A total of 51 studies, covering 4,307 patients, were included in the current meta-analysis. The results showed that overexpression of Ki-67 can predict poor OS (HR=1.66, 95%CI: 1.53-1.80; Z=11.87; p=0.000) and poor PFS (HR=1.67, 95%CI: 1.47-1.91; Z=7.67; p=0.000) in gliomas. Moreover, subgroup analyses also indicated that high level of Ki-67 expression was related to poor OS and PFS in glioma patients regardless of region, pathology type, cut-off value and statistical method. In conclusion, the current meta-analysis revealed that Ki-67 expression might be a predicative factor for poor prognosis of glioma patients, emphasizing its importance as a predictor.

Aberrant expression of microRNA-34a (miR-34a) has been reported to be involved in the tumorigenesis and progression of various classes of malignancies. However, its role in hepatocellular carcinoma (HCC) has not been completely clarified. In the current study, we have investigated the clinical significance and the in vitro contribution of miR-34a on biological functions of human HCCs. miR-34a expression in eighty-three cases of HCC formalin-fixed paraffin-embedded (FFPE) tissues decreased significantly compared to that in the adjacent liver tissues (P<0.01), as detected by real-time quantitative RT-PCR (RT-qPCR). miR-34a expression in the groups of TNM stage I and II, without metastasis and without portal vein tumor embolus, was significantly higher than that of their corresponding groups (P<0.05). In functional experiments, miR-34a mimic suppressed cell growth, migration and invasion, meanwhile it increased cellular apoptosis and caspase activity in HCC cells. miR-34a mimic also reduced phospho-ERK1/2 and phospho-stat5 signaling. In addition, miR-34a mimic enhanced the effect of cell proliferation inhibition and caspase activity induction of agents targeting c-MET (siRNAs and small molecular inhibitor su11274). In conclusion, miR-34a may act as a tumor suppressor miRNA of HCC. The strategies to increase miR-34a level might be a critical targeted therapy for HCC in future.

MiR-221 is over-expressed in human hepatocellular carcinoma (HCC), but its clinical significance and function in HCC remains uncertain. The aim of the study was to investigate the relationship between miR-221 overexpression and clinicopathological parameters in HCC formalin-fixed paraffin-embedded (FFPE) tissues, and the effect of miR-221 inhibitor and mimic on different HCC cell lines in vitro.

Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, and inflammation relates significantly to its initiation and prognosis. Systematic exploration of the immunogenomic landscape therein to assist in PTC prognosis is therefore urgent. The Cancer Genome Atlas (TCGA) project provides a large number of genetic PTC samples that enable a comprehensive and reliable immunogenomic study. We integrated the expression profiles of immune-related genes (IRGs) and progression-free intervals (PFIs) in survival in 493 PTC patients based on the TCGA dataset. Differentially-expressed and survival-associated IRGs in PTC patients were estimated a computational difference algorithm and COX regression analysis. The potential molecular mechanisms and properties of these PTC-specific IRGs were also explored with the help of computational biology. A new prognostic index based on immune-related genes was developed by using multivariable COX analysis. A total of 46 differentially expressed immune-related genes were significantly correlated with clinical outcome of PTC patients. Functional enrichment analysis revealed that these genes were actively involved in a cytokine-cytokine receptor interaction KEGG pathway. A prognostic signature based on RGs (AGTR1, CTGF, FAM3B, IL11, IL17C, PTH2R and SPAG11A) performed moderately in prognostic predictions and correlated with age, tumor stage, metastasis, number of lesions, and tumor burden. Intriguingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells. Together, our results screened several IRGs of clinical significance, revealed drivers of the immune repertoire, and demonstrated the importance of a personalized, IRG-based immune signature in the recognition, surveillance, and prognosis of PTC.