Skip to main content
Premium Trial:

Request an Annual Quote

This Week in Cell: Dec 13, 2017

Researchers from the Netherlands and Switzerland introduce a breast cancer organoid line collection established from 155 primary or metastatic breast tumor samples. When they characterized 95 of the breast cancer organoid lines with whole-genome sequencing, RNA sequencing, drug response profiling, and histology, the investigators found that the set represented all of the main breast cancer subtypes, spanning a range of tumor grades, histological features, hormone receptor patterns, expression subgroups, and drug response profiles. "DNA copy number variations as well as sequence changes were consistent within tumor-organoid pairs and largely retained even after extended passaging," the authors write, noting that the collection may aid in everything from basic cancer research to drug development. 

An international team led by investigators in Germany and the US presents findings from a genome sequencing study of Candidatus Stammera capleta, an obligate bacterial symbiont found in the tortoise leaf beetle Cassida rubiginosa that helps the beetle break down pectin in the plants it consumes. After identifying the symbiont by 16S ribosomal RNA gene sequencing, combined with PCR analyses on beetle representatives from several countries, the researchers sequenced the 271,175-base Stammera genome, which contained an estimated 251 predicted protein-coding genes and appeared particularly apt to produce the pectinase enzyme. "[O]ur findings highlight symbiosis as a strategy for an herbivore to metabolize one of nature's most complex polysaccharides and a  universal component of plant tissues," the authors write.

Researchers from the Broad Institute, the Dana-Farber Cancer Institute, and elsewhere provide information on a high-throughput, reduced representation expression profiling approach dubbed L1000 that they used to flesh out the National Institutes of Health "Library of Integrated Network-Based Cellular Signatures" consortium's Connectivity Map, or CMap. The L1000 method extrapolates broader expression profiles from fluorescence signals produced by barcoded 'landmark' transcripts that are captured, amplified, and reverse-transcribed in 384-well plates, the team says, using expression relationships informed by expression arrays, the Gene Expression Omnibus, and other resources. From there, the investigators generated more than 1.3 million L1000 profiles for dozens of cell lines exposed to genetic or small molecule treatments.