The largest pan-cancer study of metastatic solid tumors genes to date is published in Nature this week. An international research team analyzed 2,520 paired tumor and normal genomes from 2,399 patients. They find that the characteristic mutations of metastatic lesions varied widely, but that the mutations reflect those of the primary tumor types and have high rates of whole-genome duplication events. Metastatic lesions also appear less heterogeneous than reported for primary tumors, with 96 percent of driver mutations being clonal and up to 80 percent of tumor-suppressor genes being inactivated biallelically by different mutational mechanisms. The scientists also note that while metastatic tumor genomes were not fundamentally different from primary tumors in terms of the mutational landscape or driver genes, they could identify characteristics that may contribute to individual patients' responsiveness or resistance to treatment. The study, its authors write, "demonstrates the importance of comprehensive genomic tumor profiling for precision medicine in cancer." GenomeWeb has more on this, here.
Common genetic variants associated with a wide range of traits such as height, body mass index, and personality are clustered by region in Great Britain, likely as a result of socioeconomic migration, according to a new study published in Nature Human Behavior. Researchers calculated polygenic scores for roughly 450,000 individuals from Great Britain using about 1.2 million genetic variants. Of 33 traits analyzed, 21 showed significant geographic clustering at the genetic level after controlling for ancestry. Alleles for educational attainment showed the greatest clustering, with educational attainment-decreasing alleles clustering in areas of lower socioeconomic status such as coal mining regions. Notably, individuals who leave coal mining areas were found to have more educational attainment-increasing alleles on average compared with those in the rest of Great Britain. "Our results are consistent with the hypothesis that social stratification leaves visible marks in geographic arrangements of common allele frequencies and gene-environment correlations," the study's authors say.
A new computational tool for quantifying ADAR adenosine-to-inosine RNA editing activity is presented in Nature Methods this week. The approach — called the Alu editing index, or AEI — is used by its developers to map global editing across a large dataset of healthy human samples and identify putative regulators of ADAR, as well as previously unknown factors affecting the observed Alu editing levels. The online tool is also applicable to non-human samples and other sets of editing-enriched genomic regions.