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Features of metabolism associated molecular patterns in pancreatic ductal adenocarcinoma

Cancer Gene Therapy volume 30, pages 1296–1307 (2023)Cite this article

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Abstract

Exploring pancreatic ductal adenocarcinoma (PDAC) metabolic landscape would contribute to further understand PDAC from the metabolic perspective and provide more details for precise treatment design. This study aims to describe metabolic landscape of PDAC. Bioinformatics analysis was used to investigate the differences of genome, transcriptome, and proteome levels of metabolic patterns. Three subtypes (MC1, MC2, and MC3) were identified and characterized as distinct metabolic patterns. MC1, enriched in lipid metabolism and amino acid metabolism signatures, was associated with lower abundance of immune cells and stromal cells, and non-response to immunotherapy. MC2 displayed immune-activated characteristics, minor genome alterations and good response to immunotherapy. MC3 was characterized by high glucose metabolism, high pathological grade, immune-suppressed features, poor prognosis, and epithelial-mesenchymal transition phenotype. A ninety-three gene classifier preformed robust prediction and high accuracy (training set: 93.7%; validation set 1: 85.0%; validation set 2: 83.9%). Using random forest classifier, probabilities of three patterns could be predicted on pancreatic cancer cell lines, which could be used to find vulnerable targets in response to both genetic and drug perturbation. Our study revealed features of PDAC metabolic landscape, which could be expected to provide a reference for prognosis prediction and precise treatment design.

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Fig. 1: Overview of systemic design.
Fig. 2: Metabolic and clinical characteristics of distinct PDAC subclasses.
Fig. 3: Immune features of distinct subclasses.
Fig. 4: Prediction of responses to immunotherapy and drug therapies.
Fig. 5: Molecular characteristics of distinct PDAC subclasses.
Fig. 6: Cluster probabilities for drug response and discovery of novel drug targets.

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Data availability

All data in our study are available upon request.

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Acknowledgements

This work was supported by the Supporting Programs of the National Natural Science Foundation of China (Nos. 82073358 and 81871918).

Funding

This work was supported by the Supporting Programs of the National Natural Science Foundation of China (Nos. 82073358 and 81871918).

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Author notes

  1. These authors contributed equally: Junfei Chen, Yongjie Wang.

Authors and Affiliations

  1. State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 200032, Shanghai, China

    Junfei Chen & Hua Jiang

  2. Department of Clinical Laboratory, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Yongjie Wang

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JC and YW contributed to the conception and design, acquisition of data, analysis and interpretation of data, and writing, review, and revision of the manuscript. HJ contributed to conceptualization, resources, supervision, funding acquisition, investigation, project administration, writing, review, and editing. All authors read and approved the final manuscript.

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Correspondence to Hua Jiang.

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Chen, J., Wang, Y. & Jiang, H. Features of metabolism associated molecular patterns in pancreatic ductal adenocarcinoma. Cancer Gene Ther 30, 1296–1307 (2023). https://doi.org/10.1038/s41417-023-00639-6

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