Computer gaming habits have a tendency to evolve with technology, the best being ones that immerse both our imagination and intellect. Here, we describe a new game platform, an Augmented Reality Rubik's cube. The cube acts simultaneously as both the controller and the game board. Gameplay is controlled by the cube, and game assets are rendered on top of it. Shuffling and tilting operations on the cube are mapped to game interaction. We discuss the game design decisions involved in developing a game for this platform, as well as the technological challenges in implementing it. Ultimately, we describe two games and discuss the conclusions of an informal user study based on those games.

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The advancement of sequencing technologies made unbiased whole genome and transcriptome studies ubiquitous in the cancer research field. However, these omics analysis methods do not describe post-transcriptional and post-translational levels. With the recent availability of large scale multi-omics datasets, we set out to study the correlation between phosphorylations, protein expression and gene expression. The goal of this analysis is to highlight the cases in which systematic characterization of the whole proteome and phosphoproteome can uncover insights that are undetected with RNA sequencing. The analysis described below applies RNA-protein-phosphorylation comparisons based on clinical cancer datasets. We make use of the large amount of data generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), which generates unique phosphorylations, protein and mRNA expression data from the exact same samples. Correlation analysis between the phosphorylation-protein-RNA profiles highlights multiple differences among cancer types and functional pathways. We specifically focus on the various DNA damage response pathways which are mediated by kinase activity, and as expected, show modest mRNA-protein correlations. The protein-RNA discordance is further demonstrated when using an unsupervised clustering of the data based on protein or RNA. This analysis showed substantial differences in tumor classification and the cellular processes that differentiate between clusters. Altogether, this study demonstrates the opportunity presented by applying proteomics and phosphoproteomics techniques to study multiple systems that are at play in cancer biology, highlighting DNA damage response as a striking example. Citation Format: Gali Arad, Kirill Pevzner, Eran Seger, Tamar Geiger. What can we learn from phosphoproteomics compared to transcriptomics in DNA damage and other processes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2022.

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