Pan-cancer analysis of pyrimidine metabolism reveals signaling pathways connections with chemoresistance role

Abstract

AbstractDeregulated nucleotide metabolism, and in particular increased pyrimidine metabolism (PyMet), has been shown to contribute to various pathological features of cancer including chemoresistance and epithelial-to-mesenchymal transition. However, cancer often encompasses complex signaling and metabolic pathway cascades for its progression, and understanding of these molecular regulatory processes in pyrimidine metabolism is quite limited. Therefore, a comprehensive pan-cancer analysis in around 10,000 gene expression profiles of 32 cancer types was employed using a pathway-based approach utilizing gene-sets representing various signaling and metabolic pathways. The analysis identified several top connections with PyMet including TERT, MTOR, DAX1, HOXA1, TP53 and TNC implying an inter-dependency of regulations which in turn was linked to the chemoresistance mechanisms. PyMet-signaling interactions were validated within vitroderived gene-sets from endogenous thymidylate synthase (TYMS)-promoter activity reporter, fromTYMSknockdown and from brequinar treatment, and further at single cell transcriptome level. Strikingly, brequinar treatment profile showed a strong inverse association pattern with doxorubicin chemoresistance in multiple cancer types. The study highlights the PyMet-pathway interactions and its role in chemoresistance, thereby providing an effective tool for improving PyMet targeting strategy in cancer. The analysis as an accessible resource is available at:www.pype.compbio.sdu.dkHighlightsPan-cancer analysis showed pyrimidine metabolism connections with signaling pathways Top pathway interactors of pyrimidine metabolism were TERT, HOXA1, TP53 and TNC In vitro derived pyrimidine gene-sets recapitulate cancer patients’ pathway analysis Pyrimidine associated pathways confer chemoresistance in multiple cancer types Pyrimidine metabolic inhibitor brequinar reversed doxorubicin chemoresistance feature