MYC is a potential target for many cancers but is not amenable to existing pharmacologic approaches. Inhibition of 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMG-CoA reductase) by statins has shown potential efficacy against a number of cancers. Here, we show that inhibition of HMG-CoA reductase by atorvastatin (AT) blocks both MYC phosphorylation and activation, suppressing tumor initiation and growth in vivo in a transgenic model of MYC-induced hepatocellular carcinoma (HCC) as well as in human HCC-derived cell lines. To confirm specificity, we show that the antitumor effects of AT are blocked by cotreatment with the HMG-CoA reductase product mevalonate. Moreover, by using a novel molecular imaging sensor, we confirm that inhibition of HMG-CoA reductase blocks MYC phosphorylation in vivo.

Organisms that use the standard genetic code recognize UAA, UAG, and UGA as stop codons, whereas variant code species frequently alter this pattern of stop codon recognition. We previously demonstrated that a hybrid eRF1 carrying the Euplotes octocarinatus domain 1 fused to Saccharomyces cerevisiae domains 2 and 3 (Eo/Sc eRF1) recognized UAA and UAG, but not UGA, as stop codons. In the current study, we identified mutations in Eo/Sc eRF1 that restore UGA recognition and define distinct roles for the TASNIKS and YxCxxxF motifs in eRF1 function. Mutations in or near the YxCxxxF motif support the cavity model for stop codon recognition by eRF1. Mutations in the TASNIKS motif eliminated the eRF3 requirement for peptide release at UAA and UAG codons, but not UGA codons. These results suggest that the TASNIKS motif and eRF3 function together to trigger eRF1 conformational changes that couple stop codon recognition and peptide release during eukaryotic translation termination.

Recent studies of prokaryotic ribosomes have dramatically increased our knowledge of ribosomal RNA (rRNA) structure, functional centers, and their interactions with antibiotics. However, much less is known about how rRNA function differs between prokaryotic and eukaryotic ribosomes. The core decoding sites are identical in yeast and human 18S rRNAs, suggesting that insights obtained in studies with yeast rRNA mutants can provide information about ribosome function in both species. In this study, we examined the importance of key nucleotides of the 18S rRNA decoding site on ribosome function and aminoglycoside susceptibility in Saccharomyces cerevisiae cells expressing homogeneous populations of mutant ribosomes. We found that residues G577, A1755, and A1756 (corresponding to Escherichia coli residues G530, A1492, and A1493, respectively) are essential for cell viability. We also found that residue G1645 (A1408 in E. coli ) and A1754 (G1491 in E. coli ) both make significant and distinct contributions to aminoglycoside resistance. Furthermore, we found that mutations at these residues do not alter the basal level of translational accuracy, but influence both paromomycin-induced misreading of sense codons and readthrough of stop codons. This study represents the most comprehensive mutational analysis of the eukaryotic decoding site to date, and suggests that many fundamental features of decoding site function are conserved between prokaryotes and eukaryotes.

Cancer cell lines are used extensively to study cancer biology and to test hypotheses in translational research. The relevance of cell lines is dependent on how closely they resemble the tumors being studied. Relating tumors and cell lines, and recognizing their similarities and differences are thus very important for translational research. Rapid advances in genomics have led to the generation of large volumes of genomic and transcriptomic data for a diverse set of primary cancer samples, normal tissue samples and cancer cell lines. Hepatocellular Carcinoma (HCC) is one of the most common tumors worldwide, with high occurrence in Asia and sub-Saharan regions. The current effective treatments of HCC remain limited. In this work, we compared the gene expression measurements of 200 HCC tumor samples from The Cancer Genome Atlas and over 1000 cancer cell lines including 25 HCC cancer cell lines from Cancer Cell Line Encyclopedia. We showed that the HCC tumor samples correlate closely with HCC cell lines in comparison to cell lines derived from other tumor types. We further demonstrated that the most commonly used HCC cell lines resemble HCC tumors, while we identified nearly half of the cell lines that do not resemble primary tumors. Interestingly, a substantial number of genes that are critical for disease development or drug response are either expressed at low levels or absent among highly correlated cell lines; additional attention should be paid to these genes in translational research. Our study will be used to guide the selection of HCC cell lines and pinpoint the specific genes that are differentially expressed in either tumors or cell lines.