Gastric cancer (GC) threatens human health worldwide and we performed this meta-analysis to evaluate the clinical value of Ki-67/MKI67 in patients with GC. The combined hazard ratio (HR), odds ratio (OR) and 95% confidence interval (95% CI) were calculated to assess the relationships of Ki-67/MKI67 expression with prognoses and clinicopathological characteristics. Genes co-expressed with MKI67 were collected for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analyses. In total, 53 studies with 7078 patients were included in this study. The pooled HRs indicated that an elevated expression of Ki-67/MKI67 predicted an unfavorable overall survival (HR: 1.54, 95% CI: 1.33-1.78, P<0.0001) and disease-free survival (HR: 2.28, 95% CI: 1.43-3.64, P<0.0001) in GC patients. Additionally, in patients with advanced GC, a high Ki-67/MKI67 expression was also significantly connected with OS (HR: 1.37, 95% CI: 1.18-1.60, P<0.0001). The combined ORs showed that Ki-67/MKI67 expression was related to TNM stage (stage III/IV versus stage I/II: OR=1.93, 95% CI=1.34-2.78, P<0.0001), tumor differentiation (poor versus well/moderate: OR=1.94, 95% CI=1.32-2.85, P=0.001), lymph node metastasis (yes versus no: OR=1.67, 95% CI=1.23-2.25, P=0.001), distant metastasis (yes versus no: OR=1.67, 95% CI=1.24-2.26, P=0.001) and tumor invasion depth (T3/T4 versus Tis/T1/T2: OR=1.98, 95% CI=1.60-2.44, P<0.0001). The results of GO, KEGG pathway and PPI network analyses indicated that Ki-67/MKI67 may be involved in the development of GC via influencing P53 signaling pathway. Ki-67/MKI67 could be a potential indicator to predict the prognosis of patients with GC and identify high-risk cases. Detecting Ki-67/MKI67 expression in clinic may be helpful in optimizing individual treatment and further improving the survival expectancy of patients with GC.

The clinical significance of microRNA (miR)-136-5p in hepatocellular carcinoma (HCC) has not been verified. Therefore, in the current study, the authors aimed to explore miR-136-5p expression and its clinical significance in HCC, as well as to investigate its potential target genes function. The authors detected the levels of miR-136-5p in 101 pairs of HCC and para-cancer tissues via reverse transcription-quantitative polymerase chain reaction. Gene Expression Omnibus database and the Cancer Genome Atlas (TCGA) database were used to further verify the clinical significance of miR-136-5p expression in HCC. The target genes prediction analysis of miR-136-5p, natural language processing (NLP) analysis of HCC in PubMed and gene functional enrichment analysis were conducted. The miR-136-5p level was markedly downregulated in HCC tissue, compared to para-non-tumor tissue. MiR-136-5p expression decreased in HCC patients with metastasis (P=0.004), advance TNM stage (P<0.001), portal vein tumor embolus (P=0.007) and vaso-invasion (P=0.003), compared with those HCC patients with non-metastasis, early TNM stage, non-portal vein tumor embolus and non-vaso-invasion, respectively. In the TCGA database, downregulated miR-136-5p was also observed in HCC tissue compared to normal liver tissue (P<0.001). There were 178 genes obtained from the overlap between predicted targets and NLP analysis. GO and KEGG pathway analyses revealed some significant pathways related to cancers. Downregulation of miR-136-5p may be responsible for the carcinogenesis and aggressiveness of HCC. miR-136-5p may act as an anti-carcinoma miRNA, which is essential for HCC progression through the regulation of various signaling pathways. Thus, miR-136-5p interaction may provide a novel strategy for HCC treatment.

ABSTRACT. The purpose of this study was to examine the hypothesis that a transcriptome network can be developed through a set of transcription factors regulated by the expression of various genes induced by dilated cardiomyopathy can be identified and modulated to respond to heart failure. We searched for significant pathways related to dilated cardiomyopathy using the GSE4172 microarray data to identify potential genes related to heart failure. We mapped differentially expressed genes to pathways and constructed a regulation network to investigate the regulatory relationships between transcription factors and pathways. Some transcription factors and target genes in the networks have been clearly linked to heart failure in previous studies. We also found new transcription factors and target genes, such as CCAAT/ enhancer-binding protein delta and JunB, responsible for inflammatory cardiomyopathy. Transcriptome network analysis was useful in the identification of candidate genes in heart failure. This method is well suited for microarray data and therefore is proposed as a powerful tool in the search for new pathways related to disease.

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