Skip to main content
Premium Trial:

Request an Annual Quote

This Week in Genome Biology: Jul 15, 2015

Korean and American researchers take a look at intra-tumor heterogeneity using single-cell RNA sequencing for a study appearing online in Genome Biology. The team did single-cell messenger RNA sequencing on nearly three dozen cells isolated from a xenograft derived from tumor sample taken from an individual with lung adenocarcinoma. In the process, the investigators uncovered four lung cancer sub-clones with different gene mutations, drug resistance profiles, and prognostic gene expression patterns. "Single-cell transcriptome analysis uncovered heterogeneous behaviors of individual tumor cells," they write, "and provided new insights in drug resistance signatures that were masked in bulk tumor analyses."

Researchers from BGI-Shenzhen, Fudan University, the University of Cologne, and elsewhere compared the gene expression-based clinical predictions possible for individuals with neuroblastoma whose tumors were assessed using RNA sequencing and microarrays. Based on data for almost 500 primary neuroblastoma tumors tested with both RNA-seq and 44K microarrays, the team found that RNA-seq seems to have an edge for characterizing cancer transcriptomes. On the other hand, results of the analysis suggest that RNA-seq and microarrays provide similar clinical predictions when plugged into hundreds of different models aimed at forecasting at least half a dozen different clinical outcomes.

A team led by investigators in the UK and China describes common epigenetic alterations they identified through a pan-cancer analysis of RNA sequencing data and matched DNA methylation profiles for tumors from 10 cancer types assessed by the Cancer Genome Atlas. Using these data, combined with their causal network modeling methods, the researchers uncovered several main epigenetic shifts that tend to occur across multiple cancer types, in part due to recurrent drivers and unusual regulation of at least 11 epigenetic-related enzymes and seven tumor suppressor genes. The study's authors note that the epigenetic enzymes "are not only aberrantly expressed in specific cancers, but that they also exhibit fairly universal patterns of deregulation across different cancer types, including common patterns of correlation with global [DNA methylation] levels."