Abstract 6588: Omics integration provides insight into esophageal cancer inhibitory mechanisms of a cranberry extract

Abstract

Abstract Our laboratory studies chemoprevention of esophageal adenocarcinoma (EAC) through utilization of the rat esophagogastroduodenal anastomosis (EGDA) surgical model of reflux-induced EAC. Specifically, we evaluated mechanisms by which cranberry proanthocyanidins (C-PAC) inhibit reflux-induced EAC by utilizing multi-omics integrative approaches employing multiple program platforms. Herein, we investigated whether pathway-based integration could be used to examine cross-talk between genes, metabolites and the microbial profiles. For this analysis, we utilized transcriptomic and untargeted metabolomic data from rat esophagi of animals that received water or C-PAC in the drinking water alone or combined with reflux inducing EGDA surgery. Additionally, we isolated DNA from fecal pellets and performed 16S rRNA sequencing to assess gut microbiome composition and functionality. Each omics dataset was analyzed for significant pathway enrichment and network generation using Metacore, DAVID and Metabolync. PICRUSt was utilized to predict microbiota functionality. Analysis of transcriptomic and metabolomic data suggest that EGDA upregulates inflammatory, NF-kB, DNA damage, cell cycle and immune function pathways as well as metabolic pathways related to eicosanoids, amino acids and primary and secondary bile acids, while C-PAC mitigates these alterations. Preliminary microbiome data analysis also suggests that bacteria related to inflammation, metabolite transport and DNA damage are increased in abundance in EGDA, with a decrease in abundance following C-PAC treatment. Analysis of omics datasets can provide insightful relationships into the cross-talk between different processes regulated by transcription, metabolism and the microbiome. Single dataset and integrative analysis showed similarities in altered pathways for vehicle and C-PAC treated animals in the context of reflux. Integration is limited by the infancy of multi-omics analysis programs, as well as the limited amount of research involving prediction of bacterial function and integration of microbiome data with other omics datasets. Further research and development of these omics programs is needed to determine accuracy of predicted results as well as continued investigation of identified pathways. Citation Format: Katherine M. Weh, Connor L. Howard, Bridget A. Tripp, Jennifer L. Clarke, Amy B. Howell, Laura A. Kresty. Omics integration provides insight into esophageal cancer inhibitory mechanisms of a cranberry extract [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6588.