A longer time to relapse is associated with a larger increase in differences between paired primary and recurrent IDH wild-type glioblastomas at both the transcriptomic and genomic levels.

Glioblastoma (GBM) is the most common malignant brain tumor in adults, which remains incurable and often recurs rapidly after initial therapy. While large efforts have been dedicated to uncover genomic/transcriptomic alternations associated with the recurrence of GBMs, the evolutionary trajectories of matched pairs of primary and recurrent (P-R) GBMs remain largely elusive. It remains challenging to identify genes associated with time to relapse (TTR) and construct a stable and effective prognostic model for predicting TTR of primary GBM patients. By integrating RNA-sequencing and genomic data from multiple datasets of patient-matched longitudinal GBMs of isocitrate dehydrogenase wild-type (IDH-wt), here we examined the associations of TTR with heterogeneities between paired P-R GBMs in gene expression profiles, tumor mutation burden (TMB), and microenvironment. Our results revealed a positive correlation between TTR and transcriptomic/genomic differences between paired P-R GBMs, higher percentages of non-mesenchymal-to-mesenchymal transition and mesenchymal subtype for patients with a short TTR than for those with a long TTR, a high correlation between paired P-R GBMs in gene expression profiles and TMB, and a negative correlation between the fitting level of such a paired P-R GBM correlation and TTR. According to these observations, we identified 55 TTR-associated genes and thereby constructed a seven-gene (ZSCAN10, SIGLEC14, GHRHR, TBX15, TAS2R1, CDKL1, and CD101) prognostic model for predicting TTR of primary IDH-wt GBM patients using univariate/multivariate Cox regression analyses. The risk scores estimated by the model were significantly negatively correlated with TTR in the training set and two independent testing sets. The model also segregated IDH-wt GBM patients into two groups with significantly divergent progression-free survival outcomes and showed promising performance for predicting 1-, 2-, and 3-year progression-free survival rates in all training and testing sets. Our findings provide new insights into the molecular understanding of GBM progression at recurrence and potential targets for therapeutic treatments.

Detecting intragenic trans-splicing events from non-co-linearly spliced junctions by hybrid sequencing.

Trans-spliced RNAs (ts-RNAs) are a type of non-co-linear (NCL) transcripts that consist of exons in an order topologically inconsistent with the corresponding DNA template. Detecting ts-RNAs is often interfered by experimental artifacts, circular RNAs (circRNAs) and genetic rearrangements. Particularly, intragenic ts-RNAs, which are derived from separate precursor mRNA molecules of the same gene, are often mistaken for circRNAs through analyses of RNA-seq data. Here we developed a bioinformatics pipeline (NCLscan-hybrid), which integrated short and long RNA-seq reads to minimize false positives and proposed out-of-circle and rolling-circle long reads to distinguish between intragenic ts-RNAs and circRNAs. Combining NCLscan-hybrid screening and multiple experimental validation steps successfully confirmed that four NCL events, which were previously regarded as circRNAs in databases, originated from trans-splicing. CRISPR-based endogenous genome modification experiments further showed that flanking intronic complementary sequences can significantly contribute to ts-RNA formation, providing an efficient/specific method to deplete ts-RNAs. We also experimentally validated that one ts-RNA (ts-ARFGEF1) played an important role for p53-mediated apoptosis through affecting the PERK/eIF2a/ATF4/CHOP signaling pathway in breast cancer cells. This study thus described both bioinformatics procedures and experimental validation steps for rigorous characterization of ts-RNAs, expanding future studies for identification, biogenesis, and function of these important but understudied transcripts.

An Evolutionary Landscape of A-to-I RNA Editome across Metazoan Species.

Adenosine-to-inosine (A-to-I) editing is widespread across the kingdom Metazoa. However, for the lack of comprehensive analysis in nonmodel animals, the evolutionary history of A-to-I editing remains largely unexplored. Here, we detect high-confidence editing sites using clustering and conservation strategies based on RNA sequencing data alone, without using single-nucleotide polymorphism information or genome sequencing data from the same sample. We thereby unveil the first evolutionary landscape of A-to-I editing maps across 20 metazoan species (from worm to human), providing unprecedented evidence on how the editing mechanism gradually expands its territory and increases its influence along the history of evolution. Our result revealed that highly clustered and conserved editing sites tended to have a higher editing level and a higher magnitude of the ADAR motif. The ratio of the frequencies of nonsynonymous editing to that of synonymous editing remarkably increased with increasing the conservation level of A-to-I editing. These results thus suggest potentially functional benefit of highly clustered and conserved editing sites. In addition, spatiotemporal dynamics analyses reveal a conserved enrichment of editing and ADAR expression in the central nervous system throughout more than 300 Myr of divergent evolution in complex animals and the comparability of editing patterns between invertebrates and between vertebrates during development. This study provides evolutionary and dynamic aspects of A-to-I editome across metazoan species, expanding this important but understudied class of nongenomically encoded events for comprehensive characterization.

Lipopolysaccharide increases resistin gene expression in vivo and in vitro.

Although resistin has been thought to be an important link between obesity and diabetes, recent results do not support this hypothesis. We speculated that resistin may be involved in inflammatory processes and be induced by inflammatory stimuli. In this study, we tested whether lipopolysaccharide (LPS) induced resistin expression in rats. The results show that resistin mRNA levels in white adipose tissue and white blood cells were increased by LPS treatment. LPS also increased resistin mRNA levels in 3T3-L1 adipocytes and human peripheral blood monocytes. The results suggest that resistin is involved in insulin resistance and probably in other inflammatory responses.