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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Cancer Immunity and Immunotherapy

Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1564463

This article is part of the Research Topic Current Insights in Melanoma Immunology, Immune Escape and Immunotherapy Advances View all 4 articles

Exhaled breath analysis with the use of an electronic nose to predict response to immune checkpoint inhibitors in patients with metastatic melanoma: melaNose trial

Provisionally accepted
Brigit Van Dijk Brigit Van Dijk 1Ivonne J. H. Schoenaker Ivonne J. H. Schoenaker 2Astrid AM Van Der Veldt Astrid AM Van Der Veldt 3Jan Willem B. de Groot Jan Willem B. de Groot 2*
  • 1 Medical Oncology, Erasmus Medical Center, Rotterdam, Netherlands
  • 2 Isala Oncology Center, Zwolle, Netherlands
  • 3 Medical Oncology and Radiology & Nuclear Medicine, Erasmus Medical Center, Rotterdam, Netherlands

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

    Introduction: Immune checkpoint inhibitors (ICIs) have significantly improved the overall survival for patients with different solid tumors. However, there is an urgent need for predictive biomarkers to identify patients with metastatic melanoma who do not benefit from treatment with ICIs, to prevent unnecessary immune related adverse events (irAEs). Electronic noses (eNoses) showed promising results in the detection of cancer as well as the prediction of response outcome in patients with cancer. In this feasibility study, we aimed to investigate whether the breath pattern measured using eNose can be used as a simple biomarker to predict clinical benefit to first-line treatment with ICIs in patients with metastatic melanoma.In this prospective, observational single-center feasibility study, patients with metastatic melanoma performed a breath test using Aeonoseā„¢ before start of first-line treatment with ICIs. The detected exhaled breath pattern of volatile organic compounds (VOC) was used for machine learning in a training set to develop a model to identify patients who do not benefit from treatment with ICIs. Lack of clinical benefit was defined as progressive disease according to best tumor response using RECIST v1.1.Primary outcome measures were sensitivity, specificity and accuracy.The eNose showed a distinct breath pattern between patients with and without clinical benefit from ICIs. To identify patients who do not benefit from first-line ICIs treatment, breath pattern analysis using the eNose resulted in a sensitivity of 88%, specificity of 79%, and accuracy of 85%.Exhaled breath analysis using eNose can identify patients with metastatic melanoma who will not benefit from first-line treatment with ICIs and guide treatment strategies. When validated in an external cohort, eNose could be a useful tool to select these patients for alternative treatment strategies in clinical practice.

    Keywords: Melanoma, Immune checkpoint inhibitor (ICI), eNose, clinical benefit prediction, Exhaled breath analysis, Volatile organic compound (VOC)

    Received: 21 Jan 2025; Accepted: 19 Mar 2025.

    Copyright: Ā© 2025 Van Dijk, Schoenaker, Van Der Veldt and de Groot. 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: Jan Willem B. de Groot, Isala Oncology Center, Zwolle, Netherlands

    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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