LAUSR

Early detection of cancer is an important driver of increased survival, quality of life and reduced healthcare costs. Earli is developing a highly sensitive, orthogonal approach that uses a genetic construct that usurps dysregulated pathways and actively forces cancer cells to drive the expression of a detectable ‘synthetic’ biomarker. Identification of abnormally elevated transcription factors (TF) in cancer is crucial when developing a cancer-activated expression platform. Evaluating TF function in a genome wide fashion is a challenge, especially since TF activity is not solely reflected by just its RNA expression or even by protein abundance, but also its post-translational modification including phosphorylation. In this study, we use the publicly available multiomics dataset from Clinical Proteomic Tumor Analysis Consortium (CPTAC) which includes RNA-seq based transcriptional profiling, MS based protein abundance and phosphorylation from 211 paired tumor and normal adjacent samples derived from NSCLC patients. Performing Multiomics Factor Analysis (MOFA) analysis, we identified a short list of 34 dysregulated TFs in NSCLC that displayed high expression levels in at least two of the three omics platforms relative to normal tissues, six of which scored highly across all three. A subset of candidate TF binding sequences were subcloned as multimers into expression constructs with a basal promoter and empirically evaluated in multiple cancer cell lines, including patient-derived xenograft (PDX) cell lines and normal cell lines.Transfection experiments demonstrated that these novel chimeric synthetic promoters could produce robust levels of expression in PDX-derived cell lines that was 10-20x higher than expression mediated by known cancer-activated promoters such as the endogenous survivin (BIRC5) promoter. Furthermore, levels achieved were only 3-4 fold lower than a control EF-1a promoter, one of the strongest promoters, typically used to drive constitutive expression in mammalian cells. Currently, a small subset of these chimeric constructs is being tested in murine tumor models and in large animal cancer models such as oncopigs. These experiments will further drive the development of this approach for use in early cancer detection. Citation Format: Yue Wendy Zhang, Shireen Rudina, Dariusz Wodziak, Chloe Xia, Maggie Louie, Albert Park, David Suhy. Using multiomics analysis to identify dysregulated transcription factors in non-small cell lung cancer (NSCLC) to drive the expression of a cancer-activated synthetic biomarker. [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 4311.