An international team led by investigators at the St. Jude Children's Research Hospital introduces a resource for interpreting variant information in children with cancer. The free, online, cloud-based platform — known as "Pediatric Cancer Variant Pathogenicity Information Exchange," or PeCanPIE — is designed for finding, annotating, and ranking potentially pathogenic variants based on variant call format files or individual variant data, the researchers explain. When they applied PeCanPIE site to germline variant data for 1,120 pediatric cancer patients, for example, the investigators tracked down more than 130 pathogenic or likely pathogenic variants in cancer predisposition genes. The resource also provided clues to secondary cancer risk in more than 3,000 pediatric cancer survivors assessed for the St. Jude Life project. The authors note that "PeCanPIE was originally developed for pediatric cancer, but can be easily extended for use for non-pediatric cancers and non-cancer genetic disease."
Researchers from Japan, France, Belgium, and the US take a look at the Escherichia coli strains that are commensal in cattle, looking at how they lined up against harmless E. coli found in humans and pathogenic Shiga toxin-producing E. coli (STEC) and enteropathogenic E. coli (EPEC) behind clinical cases in humans. Starting with almost 1,600 rectal swabs from cattle, stool samples from healthy Japanese individuals, and blood or urine samples collected in the clinic, the team sequenced almost 1,150 cattle- or human-associated E. coli strains, comparing the virulence and other genes found within and between distinct E. coli lineages. "The analyses identified two distinct lineages, in which bovine and human commensal strains are enriched, respectively," the authors report, "and revealed that STEC and EPEC strains have emerged in multiple sub-lineages of the bovine-associated lineage."
Finally, investigators at the Fred Hutchinson Cancer Research Center and the University of Wisconsin-Madison present findings from a spliceosome study, focused on the RNA components at play in this pre-messenger RNA splicing machinery. The team's quantitative PCR assays pointed to variable levels of small nuclear RNAs (snRNAs) in the splicesome, depending on the tissue type involved and the cancer status of that tissue. In a set of 144 invasive breast ductal carcinoma tumor samples, for example, they saw splice changes involving some of the same genes affected in their analyses of a breast adenocarcinoma cell line showing altered snRNA levels. "Together, our data demonstrate that the RNA components of the spliceosome are not merely basal factors," the authors write, suggesting that "non-coding RNAs constitute a previously uncharacterized layer of regulation of alternative splicing and contribute to the establishment of global splicing programs in both healthy and malignant cells."