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Genetics and Genomics

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

British Journal of Cancer (2025)Cite this article

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Abstract

Background

Deregulated pyrimidine metabolism (PyMet) contributes to various tumorigenic features of cancer, including chemoresistance and epithelial-to-mesenchymal transition. However, cancer often encompasses complex signalling and metabolic pathway cascades for its progression and understanding of these molecular regulatory processes in PyMet is quite limited.

Methods

A comprehensive pan-cancer analysis of around 10,000 gene expression profiles of 32 cancer types was employed using a pathway-based approach utilising gene-sets of signalling and metabolic pathways. The findings were validated using in vitro inhibitor treatments, genetic perturbations and mouse-derived lung tumour organoids.

Results

Pan-cancer analysis identified several top connections with PyMet, including TERT, MTOR, DAX1, HOXA1, TP53 and TNC, implying an interdependency of regulations, which in turn was linked to the chemoresistance mechanisms. Further, these PyMet-signalling interactions were validated in vitro by inhibiting thymidylate synthase (TS) activity using knockdown approach and by brequinar (BRQ), a DHODH inhibitor. Strikingly, the BRQ treatment profile showed a strong inverse association pattern with doxorubicin chemoresistance in multiple cancer types. Indeed, BRQ synergistically sensitises cells to doxorubicin in both lung cancer cell lines and mouse-derived KrasG12D p53Δ/Δ (KP) lung tumour organoids.

Conclusions

The study highlights the PyMet-pathway interactions and its role in chemoresistance, providing a strategy for targeting PyMet in cancer.

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Fig. 1: Pathway-based activation analysis of pan-cancer transcriptome profiles has identified novel signalling pathways and metabolic processes of pyrimidine metabolism.
Fig. 2: Pathway-based activation analysis in cancer cell lines recapitulate signalling pathway associations with pyrimidine metabolic process.
Fig. 3: RNA-seq expression profiling of BRQ-treated cells validates the pyrimidine-associated pathways.
Fig. 4: Pyrimidine metabolic process and its associated signalling pathways pose chemoresistance in cancer.
Fig. 5: PYPE, a web resource for identifying the associations of pyrimidine metabolic process.

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Data availability

The RNA-seq profile of BRQ treatment produced in this study was deposited in Gene Expression Omnibus database with the accession number: GSE248686 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE248686).

Code availability

R code for the pathway-based activation analysis can be found in the Supplementary Method section.

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Acknowledgements

Sequencing was performed at the Center for Functional Genomics and Tissue Plasticity, Functional Genomics & Metabolism Research Unit, University of Southern Denmark. The authors thank Tenna P. Mortensen, Maibrith Wishoff and Ronni Nielsen for sequencing assistance.

Funding

This work was supported by the Interdisciplinary Center for Clinical Research of the University of Erlangen-Nuremberg, the German Research Foundation (DFG, CE 281/6-1), the Novo Nordisk Foundation (Hallas-Møller Ascending Investigator Grant 0066909), and by the Danish Cancer Society (A18859). Research work of MAS is supported by Lundbeck Foundation, Denmark (R380-2021-1264).

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Author notes

  1. These authors contributed equally: Vignesh Ramesh, Mert Demirdizen.

Authors and Affiliations

  1. Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark

    Vignesh Ramesh, Mert Demirdizen, Luisa Pinna, Thomas Koed Doktor, Mohammad Aarif Siddiqui & Paolo Ceppi

  2. Interdisciplinary Centre for Clinical Research, University Hospital Erlangen, FAU-Erlangen-Nuremberg, Erlangen, Germany

    Vignesh Ramesh & Paolo Ceppi

  3. Department of Molecular Biology and Genetics, Bilkent University, Ankara, Turkey

    Mert Demirdizen

  4. Department of Oncology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy

    Federica Benso

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  1. Vignesh Ramesh
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Contributions

Conceived the concept: VR and PC; Designed the experiments: VR and PC; Performed the experiments: VR, LP, FB and MAS. Performed computational and statistical analysis: VR and MD; Designed web server: MD, VR and TKD; Wrote the manuscript: VR and PC. All the authors read and approved the final manuscript.

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Correspondence to Paolo Ceppi.

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Ramesh, V., Demirdizen, M., Pinna, L. et al. Pan-cancer analysis of pyrimidine metabolism reveals signaling pathways connections with chemoresistance role. Br J Cancer (2025). https://doi.org/10.1038/s41416-025-03282-0

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