Taken together, our data demonstrate that JAK2/STAT3 signaling is essential for EGFRvIII-driven migration and invasion by promoting focal adhesion and stabilizing the EGFRvIII/JAK2/STAT3 axis. Targeting JAK2/STAT3 therapy, such as AG490, may have potential clinical implications for the tailored treatment of GBM patients bearing EGFRvIII-positive tumors.

Alterations of polycomb group (PcG) genes directly modulate the trimethylation of histone H3 lysine 27 (H3K27me3) and may thus affect the epigenome of hepatocellular carcinoma (HCC), which is crucial for controlling the HCC cell phenotype. However, the extent of downstream regulation by PcGs in HCC is not well defined. Using cDNA microarray analysis, we found that the target gene network of PcGs contains well-established genes, such as cyclin-dependent kinase inhibitors (CDKN2A), and genes that were previously undescribed for their regulation by PcG, including E2F1, NOTCH2, and TP53. Using chromatin immunoprecipitation assays, we demonstrated that EZH2 occupancy coincides with H3K27me3 at E2F1 and NOTCH2 promoters. Interestingly, PcG repress the expression of the typical tumor suppressor TP53 in human HCC cells, and an increased level of PcG was correlated with the downregulation of TP53 in certain HCC specimens. Unexpectedly, we did not find obvious H3K27me3 modification or an EZH2 binding signal at the TP53 promoters, suggesting that PcG regulates TP53 expression in an H3K27me3-independent manner. Finally, the reduced expression of PcGs effectively blocked the aggressive signature of liver cancer cells in vitro and in vivo.Implications: Taken together, our results establish the functional and mechanistic significance of certain gene regulatory networks that are regulated by PcGs in HCC.

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The identification of human cancer-related microRNAs (miRNAs) is important for cancer biology research. Although several identification methods have achieved remarkable success, they have overlooked the functional information associated with miRNAs. We present a computational framework that can be used to prioritize human cancer miRNAs by measuring the association between cancer and miRNAs based on the functional consistency score (FCS) of the miRNA target genes and the cancer-related genes. This approach proved successful in identifying the validated cancer miRNAs for 11 common human cancers with area under ROC curve (AUC) ranging from 71.15% to 96.36%. The FCS method had a significant advantage over miRNA differential expression analysis when identifying cancer-related miRNAs with a fine regulatory mechanism, such as miR-27a in colorectal cancer. Furthermore, a case study examining thyroid cancer showed that the FCS method can uncover novel cancer-related miRNAs such as miR-27a/b, which were showed significantly upregulated in thyroid cancer samples by qRT-PCR analysis. Our method can be used on a web-based server, CMP (cancer miRNA prioritization) and is freely accessible at http://bioinfo.hrbmu.edu.cn/CMP. This time- and cost-effective computational framework can be a valuable complement to experimental studies and can assist with future studies of miRNA involvement in the pathogenesis of cancers.