CASC3 promotes transcriptome-wide activation of nonsense-mediated decay by the exon junction complex

The exon junction complex (EJC) is an essential constituent and regulator of spliced messenger ribonucleoprotein particles (mRNPs) in metazoans. As a core component of the EJC, CASC3 was described to be pivotal for EJC-dependent nuclear and cytoplasmic processes. However, recent evidence suggests that CASC3 functions differently from other EJC core proteins. Here, we have established human CASC3 knockout cell lines to elucidate the cellular role of CASC3. In the knockout cells, overall EJC composition and EJC-dependent splicing are unchanged. A transcriptome-wide analysis reveals that hundreds of mRNA isoforms targeted by nonsense-mediated decay (NMD) are upregulated. Mechanistically, recruiting CASC3 to reporter mRNAs by direct tethering or via binding to the EJC stimulates mRNA decay and endonucleolytic cleavage at the termination codon. Building on existing EJC-NMD models, we propose that CASC3 equips the EJC with the persisting ability to communicate with the NMD machinery in the cytoplasm. Collectively, our results characterize CASC3 as a peripheral EJC protein that tailors the transcriptome by promoting the degradation of EJC-dependent NMD substrates

<em>De novo</em> discovery of phenotypic intra-tumor heterogeneity using imaging mass spectrometry.

An essential and so far unresolved factor influencing the evolution of cancer and the clinical management of patients is intra-tumor clonal and phenotypic heterogeneity. However, the de novo identification of tumor subpopulations is a so far challenging, if not an unresolved, task. Here we present the first systematic approach for the de novo discovery of clinically detrimental molecular tumor subpopulations. In this proof-of-principle study, spatially-resolved, tumor-specific mass spectra were acquired using matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry from tissues of 63 gastric carcinoma and 32 breast carcinoma patients. The mass spectra, representing the proteomic heterogeneity within tumor areas, were grouped by a corroborated statistical clustering algorithm in order to obtain segmentation maps of molecularly distinct regions. These regions were presumed to represent different phenotypic tumor subpopulations. This was confirmed by linking the presence of these tumor subpopulations to the patients&#39; clinical data. This revealed several of the detected tumor subpopulations to be associated with a different overall survival of the gastric cancer patients (P&thinsp;=&thinsp;0.025) and the presence of locoregional metastases in patients with breast cancer (P&thinsp;=&thinsp;0.036). The procedure presented is generic and opens novel options in cancer research as it reveals microscopically indistinct tumor subpopulations that have an adverse impact on clinical outcome. This enables their further molecular characterization for deeper insights into the biological processes of cancer which may finally lead to new targeted therapies