Combining genomic data analysis with functional experimentation, a team led by researchers from the Jackson Laboratory for Genomic Medicine has uncovered new insights into treatment responses among patients with triple-negative breast cancer (TNBC) and ovarian carcinomas (OvCas) with BRCA1 promoter methylation (BRCA1meth). Such patients are known to respond more poorly to alkylating agents, as compared to those bearing mutations in BRCA1 and BRCA2, but it is unclear why, given the biologically equivalent homologous recombination deficiency (HRD) induced by these genetic and epigenetic BRCA perturbations. To investigate, the scientists analyzed genomic data from clinical cohorts of patients with TNBC and OvCa treated using the same chemotherapeutic combinations, followed by experimentation with patient-derived xenografts and genetically engineered cell lines. As reported in Science Translational Medicine this week, they find that tumors with pathogenic mutations in either BRCA1 or BRCA2, those with BRCA1meth, and those that are proficient for both BRCA1 and BRCA2 are distinct clinical-therapeutic entities in their response to platinum chemotherapies. BRCA1meth cancers were found to be uniformly associated with poor outcomes, with data showing they are highly adaptive to genotoxin exposure and, through reversal of promoter methylation, recover BRCA1 expression and become resistant to therapy. The researchers also uncovered a specific augmented immune transcriptional signal associated with enhanced response to platinum chemotherapy, but only in patients with BRCA-proficient cancers, and showed how integrating both this cancer immune signature and the presence of BRCA mutations led to more accurate predictions of patient response when compared to either HRD status or BRCA status alone.
By analyzing published proteomic data from Escherichia coli, a pair of University of Michigan researchers have gained new insights into the phenomenon of codon usage bias (CUB). Eighteen of the 20 amino acids are encoded by more than one codon, but the synonymous codons are usually used unequally in a genome. (Synonymous codons used more often than the average are referred to as preferred codons, while the rest are called unpreferred.) One explanation for this, called the translational accuracy hypothesis (TAH), states that synonymous codons are translated with different accuracies and that CUB results in part from natural selection for translational accuracy. However there is no direct evidence supporting this hypothesis beyond case studies. In their study, which appears in this week's Science Advances, the scientists capitalize on a proteome-wide probe of mistranslation in E. coli to show that preferred codons are generally translated more accurately than unpreferred synonymous codons. They then then use the E. coli data to validate a sequence-based proxy for relative translational accuracies of synonymous codons and use the proxy to show that the TAH is supported in the vast majority of more than 1,000 diverse taxa surveyed, although the relative translational accuracies of synonymous codons vary substantially among taxa. "We find that the relative translational accuracy of a synonymous codon is strongly correlated with its cognate [transfer RNA] abundance relative to near-cognate tRNA abundance, offering a mechanistic insight into the translational accuracy variations across synonymous codons and species," the study's authors write. "These and other results suggest a model in which selections for translational efficiency and accuracy drive the CUB and its coevolution with the tRNA pool."