Rabbit Anti-E2F2 monoclonal antibody, clone TO312-15

RB+/- individuals develop retinoblastoma and, subsequently, many other tumors. The Rb relatives p107 and p130 protect the tumor-resistant Rb-/- mouse retina. Determining the mechanism underlying this tumor suppressor function may expose novel strategies to block Rb pathway cancers. p107/p130 are best known as E2f inhibitors, but here we implicate E2f-independent Cdk2 inhibition as the critical p107 tumor suppressor function in vivo. Like p107 loss, deleting p27 or inactivating its Cdk inhibitor (CKI) function (p27(CK-)) cooperated with Rb loss to induce retinoblastoma. Genetically, p107 behaved like a CKI because inactivating Rb and one allele each of p27 and p107 was tumorigenic. Although Rb loss induced canonical E2f targets, unexpectedly p107 loss did not further induce these genes, but instead caused post-transcriptional Skp2 induction and Cdk2 activation. Strikingly, Cdk2 activity correlated with tumor penetrance across all the retinoblastoma models. Therefore, Rb restrains E2f, but p107 inhibits cross talk to Cdk. While removing either E2f2 or E2f3 genes had little effect, removing only one E2f1 allele blocked tumorigenesis. More importantly, exposing retinoblastoma-prone fetuses to small molecule inhibitors of E2f (HLM006474) or Cdk (R547) for merely 1 week dramatically inhibited subsequent tumorigenesis in adult mice. Protection was achieved without disrupting normal proliferation. Thus, exquisite sensitivity of the cell-of-origin to E2f and Cdk activity can be exploited to prevent Rb pathway-induced cancer in vivo without perturbing normal cell division. These data suggest that E2f inhibitors, never before tested in vivo, or CKIs, largely disappointing as therapeutics, may be effective preventive agents. Oncogene (2012) 31, 5019-5028; doi:10.1038/onc.2011.654; published online 30 January 2012

Background. Long non-coding RNAs (lncRNAs) play crucial roles in the initiation and progression of renal cell carcinoma (RCC) by competing in binding to miRNAs, and related competitive endogenous RNA (ceRNA) networks have been constructed in several cancers. However, the coexpression network has been poorly explored in RCC. Methods. We collected RCC RNA expression profile data and relevant clinical features from The Cancer Genome Atlas (TCGA). A cluster analysis was explored to show different lncRNA expression patterns. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and gene set enrichment analysis (GSEA) were performed to analyze the functions of the intersecting mRNAs. Targetscan and miRanda bioinformatics algorithms were used to predict potential relationships among RNAs. Univariate Cox proportional hazards regression was conducted to determine the RNA expression levels and survival times. Results. Bioinformatics analysis revealed that the expression profiles of hundreds of aberrantly expressed lncRNAs, miRNAs, and mRNAs were significantly changed between different stages of tumors and non-tumor groups. By combining the data predicted by databases with intersection RNAs, a ceRNA network consisting of 106 lncRNAs, 26 miRNAs and 69 mRNAs was established. Additionally, a protein interaction network revealed the main hub nodes (VEGFA, NTRK2, DLG2, E2F2, MYB and RUNX1). Furthermore, 63 lncRNAs, four miRNAs and 31 mRNAs were significantly associated with overall survival. Conclusion. Our results identified cancer-specific lncRNAs and constructed a ceRNA network for RCC. A survival analysis related to the RNAs revealed candidate biomarkers for further study in RCC.