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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Cancer Immunity and Immunotherapy

Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1539653

This article is part of the Research Topic Microbiota-Immune Interactions: A New Frontier in Cancer Treatment Optimization View all 3 articles

Revealing gut microbiota biomarkers associated with melanoma immunotherapy response and key bacteria-fungi interaction relationships: Evidence from metagenomics, machine learning, and SHAP methodology

Provisionally accepted
  • 1 Department of Pharmacology, Liaoning Cancer Hospital, China Medical University, Shenyang, China
  • 2 Department of Breast Medicine 1, Liaoning Cancer Hospital ,China Medical University, Shenyang, Liaoning Province, China
  • 3 Department of Bioinformatics, Kanghui Biotechnology Co., Ltd., Shenyang, China
  • 4 Department of Breast Medicine, Liaoning Cancer Hospital,Dalian University of Technology, Shenyang, Liaoning Province, China

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

    The gut microbiota is associated with the response to immunotherapy in cutaneous melanoma (CM). However, gut fungal biomarkers and bacterial-fungal interactions have yet to be determined.Metagenomic sequencing data of stool samples collected before immunotherapy from three independent groups of European ancestry CM patients were collected. After characterizing the relative abundances of bacteria and fungi, Linear Discriminant Analysis Effect Size (LEfSe) analysis, Random Forest (RF) model construction, and SHapley Additive exPlanations (SHAP) methodology were applied to identify biomarkers and key bacterial-fungal interactions associated with immunotherapy responders in CM. Results: Diversity analysis revealed significant differences in the bacterial and fungal composition between CM immunotherapy responders and non-responders. LEfSe analysis identified 45 bacterial and 4 fungal taxa as potential biomarkers. After constructing the RF model, the AUC of models built using bacterial and fungal data separately were 0.64 and 0.65, respectively. However, when bacterial and fungal data were combined, the AUC of the merged model increased to 0.71. In the merged model, the following taxa were identified as important biomarkers: Romboutsia, Endomicrobium, Aggregatilinea, Candidatus Moduliflexus, Colwellia, Akkermansia, Mucispirillum, and Rutstroemia, which were associated with responders, whereas Zancudomyces was associated with non-responders.Moreover, the positive correlation interaction between Akkermansia and Rutstroemia is considered a key bacterial-fungal interaction associated with CM immunotherapy response.Our results provide valuable insights for the enrichment of responders to immunotherapy in CM patients. Moreover, this study highlights the critical role of bacterial-fungal interactions in CM immunotherapy.

    Keywords: gut microbiota1, melanoma2, immunotherapy3, Biomarker4, metagenomics5, machine learning6, SHAP methodology7

    Received: 04 Dec 2024; Accepted: 28 Feb 2025.

    Copyright: © 2025 Zhou, Han, Feng, Wang, Liu, Sun and Xu. 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:
    Tao Sun, Department of Breast Medicine 1, Liaoning Cancer Hospital ,China Medical University, Shenyang, Liaoning Province, China
    Junnan Xu, Department of Breast Medicine 1, Liaoning Cancer Hospital ,China Medical University, Shenyang, Liaoning Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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