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Circulating cytokine signatures as a soluble biomarker of immune checkpoint inhibitor therapy in non-small-cell lung cancer

Genes & Immunity volume 25, pages 89–91 (2024)Cite this article

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Lung cancer, largely represented by non-small-cell lung cancer (NSCLC), remains the leading cause of cancer-related death on a global scale [1]. In recent years, immune checkpoint inhibitors (ICIs) have been increasingly utilized in the treatment of NSCLC with acceptable safety and effectiveness. However, ICIs yield diverse response rates, with less than 40% of individuals showing a positive response when chosen based on programmed death-ligand 1 (PD-L1) expression. Therefore, predictive biomarkers are urgently needed. Analyzing tumor tissue samples is frequently a requirement for most clinically approved biomarkers, which might not effectively predict therapeutic outcomes and patient survival in response to ICI therapy for NSCLC. Soluble biomarkers offer the benefits of real-time monitoring, repeatability, and easy feasibility at each stage of lung cancer—from diagnosis to disease progression—in a minimally invasive manner. Hence, there is a pressing demand to discover precise soluble biomarkers for predicting the responsiveness to ICI therapy in NSCLC [2]. Cytokines, acting as soluble mediators in the host’s immune system, play critical roles in cancer immunotherapy. They facilitate tumor infiltration and reactivate effector lymphocytes within the tumor microenvironment. Until recently, only a limited number of cytokines were individually assessed for predicting ICI therapy responsiveness in small samples of patients with NSCLC. Therefore, we employed a non-linear machine learning approach on a high-dimensional dataset encompassing 93 circulating cytokines from patients undergoing ICI therapy. The goal was to identify circulating cytokine signatures with predictive value, serving as a biomarker associated with overall survival (OS) in NSCLC [3].

Our investigation not only suggests the potential of circulating cytokine signatures as an effective biomarker for predicting ICI prognosis, but also contributes novel insights in the exploration of tumor immune mechanisms. By calculating the importance of each cytokine in the prediction model, machine learning quantified the extent of association between the 93 cytokines and the outcomes of ICI treatment. At both pre and edt time points, plasma osteopontin (encoded by SPP1) exhibits a more significant correlation with OS compared to the remaining 92 cytokines. Recent reports underscore the growing interest from cancer researchers regarding the significance of SPP1 in cancer progression as well as immunotherapeutic outcomes. Bill et al. discovered that macrophage polarity, defined by CXCL9 and SPP1 expression rather than conventional M1 and M2 markers, exhibited a notably robust prognostic association in variety of human cancers [4]. Liu et al. identified a tumor immune barrier structure, a spatial niche consisting of SPP1+ macrophages and cancer-associated fibroblasts near the tumor boundary, correlated with the effectiveness of ICI treatment [5]. The significance of plasma osteopontin in CIRI models observed in our study may arise from its representation of the immune infiltration as well as the broader network of cellular states within the tumor microenvironment, which are directly linked to the effectiveness of tumor immunity. Beyond osteopontin, the signature encompasses many factors with unknown functions and interaction mechanisms, which play a substantial role in their association with immunotherapeutic outcomes. This provides a valuable starting point for elucidating the mechanisms underlying the action of ICIs and identifying additional factors that contribute to ICI activation.

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Fig. 1: Circulating cytokine signatures as a soluble biomarker of immune checkpoint inhibitor (ICI) therapy in non-small-cell lung cancer (NSCLC).

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Funding

The original work was supported by Japan Society for the Promotion of Science Grant to FW: Grant-in-Aid for Scientific Research (C): 22K08724; AMED Grant to TS: JP19ae0101076.

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Authors and Affiliations

  1. Division of Cancer Immunotherapy, Kanagawa Cancer Center Research Institute, Yokohama, Japan

    Feifei Wei & Tetsuro Sasada

  2. Cancer Vaccine and Immunotherapy Center, Kanagawa Cancer Center, Yokohama, Japan

    Feifei Wei & Tetsuro Sasada

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  1. Feifei Wei
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  2. Tetsuro Sasada
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Contributions

Conceptualization, FW and TS; original draft preparation, FW; reviewing, editing and supervision, TS. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Feifei Wei or Tetsuro Sasada.

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Competing interests

TS received honoraria from Chugai and Bristol Myers Squibb, and research funds from Taiho and BrightPath Biotherapeutics.

Ethics approval

Participants in the original study provided informed consent, and the study design was approved by Institutional Review Boards of Kurume University Hospital (approval numbers: 15210 and 19240) and Kanagawa Cancer Center (approval number: 2019-131).

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Wei, F., Sasada, T. Circulating cytokine signatures as a soluble biomarker of immune checkpoint inhibitor therapy in non-small-cell lung cancer. Genes Immun 25, 89–91 (2024). https://doi.org/10.1038/s41435-023-00236-5

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  • DOI: https://doi.org/10.1038/s41435-023-00236-5

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