Abstract
Reprogramming of cellular metabolism is a hallmark of cancer, particularly ovarian cancer (OC), that contributes to rapid cancer growth and survival. However, studies using clinical specimens are limited. To identify metabolic alterations specific to OC, we performed metabolomic analysis of OC and benign ovarian tumors. The relationship between metabolomics and transcriptomics was investigated by transcriptome analysis. Fifty-one patients with OC and three with benign ovarian tumors, diagnosed between 2011 and 2014 using available frozen tissue and plasma specimens, were enrolled at the National Cancer Center Hospital. To identify metabolic alterations, plasma samples from 51 patients with OC and three with benign tumors, along with both cancerous and non-cancerous tissue samples from 44 of the 51 patients with OC, were analyzed using gas chromatography-mass spectrometry. In addition, we performed transcriptomic analysis of cancerous tissues obtained from 39 of the 44 patients with OC. It was not possible to classify patients based on plasma metabolite levels; therefore, the 44 patients with OC were classified into two groups based on metabolite levels: high and low, based on tissue analysis. The group with high metabolite levels had more advanced-stage tumors (P = 0.02). Transcriptome pathway analysis revealed suppression of pathways related to natural killer (NK) cells and immune responses in the group with high metabolite levels. NK cell percentages were lower in the group with high metabolite levels than in the group with low metabolite levels (P = 0.04). Thus, the group with high metabolite levels was associated with advanced stages and a reduced fraction of NK cells, suggesting that high metabolite levels may play a direct or indirect role in immune activity or in the malignant progression of OC.
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Data availability
Raw RNA sequencing and whole-exome sequencing data have been deposited in the NBDC Human Database under project accession number hum0524 (https://humandbs.dbcls.jp/en/hum0524-v1).
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Acknowledgements
The authors thank Hitoshi Ichikawa, Maiko Matsuda, Yoko Shimada, Sachiyo Mitani, Miyu Narita, and other physicians and staff members at the National Cancer Center Hospital for assistance and support. We also thank Bioedit Ltd. for assisting with English language editing.
Funding
This work was supported by Japan Agency for Medical Research and Development (AMED) (23ama221520h0001 to K.S.), a Grant-in-Aid for Scientific Research (B) 20H03668, BRIDGE (programs for bridging the gap between R&D and the ideal society (Society 5.0 to RH and KS) and generating economic and social value to K.S.), the National Cancer Center Research and Development Fund (2022-A-20, 2023-J-2, NCC Biobank, and NCC Core Facility to K.S.), and the Yamagata Prefectural Government and City of Tsuruoka (HM).
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Conceptualization, D. H., E. F., M. K-Kato, K. H., Y. A., M. K., R. H., K. M., A. S., Y. T., A. I., K. T., K. T., H. Y., and M. I.; methodology, M. Y. and K.S.; validation, M. Y. and K.S.; formal analysis, H. M. and H. O.; investigation, M. Y. and H. M.; resources, T.K, H. T, and M. I; data curation, H. O.; writing—original draft preparation, M. Y. and K. S.; writing—review and editing, K. S.; visualization, M. Y.; project administration, D. H., E. F., M. K-Kato, K. H., Y. A., M. K., R. H., K. M., A. S., Y. T., A. I., K. T., K. T., H. Y., and M. I.; funding acquisition K. S. All authors have read and agreed to the published version of the manuscript.
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Yamaguchi, M., Higuchi, D., Yoshida, H. et al. Metabolomic and transcriptomic analyses identify metabolic alterations and immune suppression in ovarian cancer. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38014-8
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DOI: https://doi.org/10.1038/s41598-026-38014-8
