Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics.

Cancer is driven by genomic alterations, but the processes causing this disease are largely performed by proteins. However, proteins are harder and more expensive to measure than genes and transcripts. To catalyze developments of methods to infer protein levels from other omics measurements, we leveraged crowdsourcing via the NCI-CPTAC DREAM proteogenomic challenge. We asked for methods to predict protein and phosphorylation levels from genomic and transcriptomic data in cancer patients. The best performance was achieved by an ensemble of models, including as predictors transcript level of the corresponding genes, interaction between genes, conservation across tumor types, and phosphosite proximity for phosphorylation prediction. Proteins from metabolic pathways and complexes were the best and worst predicted, respectively. The performance of even the best-performing model was modest, suggesting that many proteins are strongly regulated through translational control and degradation. Our results set a reference for the limitations of computational inference in proteogenomics. A record of this paper's transparent peer review process is included in the Supplemental Information.

Super-resolution fluorescence microscopy of the cardiac connexome reveals plakophilin-2 inside the connexin43 plaque.

AIMS: Cell function requires formation of molecular clusters localized to discrete subdomains. The composition of these interactomes, and their spatial organization, cannot be discerned by conventional microscopy given the resolution constraints imposed by the diffraction limit of light (∼200-300 nm). Our aims were (i) Implement single-molecule imaging and analysis tools to resolve the nano-scale architecture of cardiac myocytes. (ii) Using these tools, to map two molecules classically defined as components 'of the desmosome' and 'of the gap junction', and defined their spatial organization. METHODS AND RESULTS: We built a set-up on a conventional inverted microscope using commercially available optics. Laser illumination, reducing, and oxygen scavenging conditions were used to manipulate the blinking behaviour of individual fluorescent reporters. Movies of blinking fluorophores were reconstructed to generate subdiffraction images at ∼20 nm resolution. With this method, we characterized clusters of connexin43 (Cx43) and of 'the desmosomal protein' plakophilin-2 (PKP2). In about half of Cx43 clusters, we observed overlay of Cx43 and PKP2 at the Cx43 plaque edge. SiRNA-mediated loss of Ankyrin-G expression yielded larger Cx43 clusters, of less regular shape, and larger Cx43-PKP2 subdomains. The Cx43-PKP2 subdomain was validated by a proximity ligation assay (PLA) and by Monte-Carlo simulations indicating an attraction between PKP2 and Cx43. CONCLUSIONS: (i) Super-resolution fluorescence microscopy, complemented with Monte-Carlo simulations and PLAs, allows the study of the nanoscale organization of an interactome in cardiomyocytes. (ii) PKP2 and Cx43 share a common hub that permits direct physical interaction. Its relevance to excitability, electrical coupling, and arrhythmogenic right ventricular cardiomyopathy, is discussed.