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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Cancer Metabolism
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1510018
This article is part of the Research Topic Synthetic Biology and Metabolomics: Novel Insight in Oncology Research View all 3 articles

Discrimination of superficial lymph nodes using ultrasonography and tissue metabolomics coupled with machine learning

Provisionally accepted
Lu Li Lu Li 1*Xinyue Wang Xinyue Wang 2*Hongyan Deng Hongyan Deng 2*Wenjuan Lu Wenjuan Lu 2*Yasu Zhou Yasu Zhou 2*Xinhua Ye Xinhua Ye 2Yong Li Yong Li 3*Jie Wang Jie Wang 2*
  • 1 First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu Province, China
  • 2 Department of Ultrasound, First Affiliated Hospital, Nanjing Medical University, Nanjing, Liaoning Province, China
  • 3 Jiangsu Academy of Agricultural Sciences (JAAS), Nanjing, China

The final, formatted version of the article will be published soon.

    Diagnosing the types of malignant lymphoma could help determine the most suitable treatment, anticipate the probability of recurrence and guide long-term monitoring and follow-up care. We evaluated the differences in benign, lymphoma and metastasis superficial lymph nodes using ultrasonography and tissue metabolomics. Our findings indicated that three ultrasonographic features, blood supply pattern, cortical echo, and cortex elasticity, hold potential in differentiating malignant lymph nodes from benign ones, and the shape and corticomedullary boundary emerged as significant indicators for distinguishing between metastatic and lymphoma groups. Metabolomics revealed the difference in metabolic profiles among lymph nodes. We observed significant increases in many amino acids, organic acids, lipids, and nucleosides in both lymphoma and metastasis groups, compared to the benign group. Specifically, the lymphoma group exhibited higher levels of nucleotides (inosine monophosphate and adenosine diphosphate) as well as glutamic acid, and the metastasis group was characterized by higher levels of carbohydrates, acylcarnitines, glycerophospholipids, and uric acid.Linear discriminant analysis coupled with these metabolites could be used for differentiating lymph nodes, achieving recognition rates ranging from 87.4% to 89.3%, outperforming ultrasonography (63.1% to 75.4%). Our findings could contribute to a better understanding of malignant lymph node development and provide novel targets for therapeutic interventions.

    Keywords: Lymph Nodes, Lymphoma, metastasis, Ultrasonography, Metabolomics

    Received: 12 Oct 2024; Accepted: 07 Jan 2025.

    Copyright: © 2025 Li, Wang, Deng, Lu, Zhou, Ye, Li and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Lu Li, First Affiliated Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu Province, China
    Xinyue Wang, Department of Ultrasound, First Affiliated Hospital, Nanjing Medical University, Nanjing, 211166, Liaoning Province, China
    Hongyan Deng, Department of Ultrasound, First Affiliated Hospital, Nanjing Medical University, Nanjing, 211166, Liaoning Province, China
    Wenjuan Lu, Department of Ultrasound, First Affiliated Hospital, Nanjing Medical University, Nanjing, 211166, Liaoning Province, China
    Yasu Zhou, Department of Ultrasound, First Affiliated Hospital, Nanjing Medical University, Nanjing, 211166, Liaoning Province, China
    Yong Li, Jiangsu Academy of Agricultural Sciences (JAAS), Nanjing, China
    Jie Wang, Department of Ultrasound, First Affiliated Hospital, Nanjing Medical University, Nanjing, 211166, Liaoning Province, China

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