Abstract 4297: OFFONOME: a new notion of genes’ on/off

Background: RNA-seq is now the most widely used technique for gene expression profiling, which generates nucleotide level genome coverage as well as summary gene expression values. In general, low-expressed genes are excluded in the data processing due to their low signal-to-noise ratio. Nonetheless, it has been shown that low-expressed genes can provide crucial information such as presence of rare cells in bulk tissue samples. To optimize signal to noise in low-expressed genes, we applied a novel approach in which we transform low-expressed genes to a robust dichotomized state of being either “on” or “off”. Methods: To determine the status of genes, we use the shape of base-level read coverage which is expected to be homogeneous across the samples if they are “on”, whereas appear to be random noise if they are “off”. We model base-resolution RNA-seq data as vectors in high dimensional data space and measure their level of shape similarity (LSS) using angles between samples with lower angles indicating higher similarity which is more likely to be “on” status. Applying this approach to 3 human cancer samples (head and neck squamous cell carcinoma (HNSC), lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC)) from the Cancer Genome Atlas (TCGA), we identified lists of genes, the OFFONOME, that were either always or sometimes “off”. Differential OFFONOME genes were queried to address supervised and unsupervised analyses. Results: Using our technique, we characterized the OFFONOME of HNSC (5851 genes), a set which would typically have been filtering for removal because of low expression. In the HNSC OFFONOME, we observed five gene clusters, each of which was strongly associated with specific gene ontology. One of the clusters identified a rare population of normal myocytes infiltrating otherwise invasive tumors. For the OFFONOME of LUAD (5435 genes) and LUSC (5292 genes), we found clusters enriched with cilia and keratinization-related genes. In the result of integrated analysis, we observed that squamous cell carcinoma (SCC) tumor types shared “on” status for keratinization-related genes known for the cause of SCC. By comparison, LUAD had “on” status genes related to microtubule-based movement related with cilia structure. Strikingly, clustering the OFFONOME with the LSS distinguished 3 tumor types with almost perfect separation, outperforming several competing gene expression measures. Conclusion: In this study, we applied a new notion of gene expression. This approach enables a robust characterization of “on” and “off” status which can be especially effective for the genes expressed at low level. The OFFONOME from 3 cancer types revealed not only the tissue-specific genes but also the genes shared in similar tumor types. Collectively, OFFONOME can provide new insights into genes expressed at vanishingly low levels, such as from minor cell populations within bulk tumor analysis. Citation Format: Wonyoung Choi, Hyo Young Choi, Daivd Neil Hayes. OFFONOME: a new notion of genes’ on/off. [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 4297.