Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory study

Abstract Immune checkpoint inhibitors (ICIs) show limited efficacy in non-small cell lung cancer (NSCLC), highlighting the need for predictive biomarkers. Here we prospectively analysed serial plasma samples from 34 ICI-treated advanced NSCLC patients (plus 30 validation samples) using the Olink Imm...

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Main Authors: Yuan Gao, Fei Qi, Wenhao Zhou, Peng Jiang, Mingming Hu, Ying Wang, Congcong Song, Yi Han, Dongdong Li, Na Qin, Hongmei Zhang, Haitao Luo, Tongmei Zhang, Hongxia Li
Format: Article
Language:English
Published: Springer 2025-07-01
Series:Molecular Biomedicine
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Online Access:https://doi.org/10.1186/s43556-025-00291-6
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author Yuan Gao
Fei Qi
Wenhao Zhou
Peng Jiang
Mingming Hu
Ying Wang
Congcong Song
Yi Han
Dongdong Li
Na Qin
Hongmei Zhang
Haitao Luo
Tongmei Zhang
Hongxia Li
author_facet Yuan Gao
Fei Qi
Wenhao Zhou
Peng Jiang
Mingming Hu
Ying Wang
Congcong Song
Yi Han
Dongdong Li
Na Qin
Hongmei Zhang
Haitao Luo
Tongmei Zhang
Hongxia Li
author_sort Yuan Gao
collection DOAJ
description Abstract Immune checkpoint inhibitors (ICIs) show limited efficacy in non-small cell lung cancer (NSCLC), highlighting the need for predictive biomarkers. Here we prospectively analysed serial plasma samples from 34 ICI-treated advanced NSCLC patients (plus 30 validation samples) using the Olink Immuno-Oncology panel. We assessed dynamic proteomic changes associated with ICI efficacy and immune-related adverse events (irAEs), and developed a prognostic model. Following ICIs, 42/92 proteins significantly elevated upon ICI treatment (p < 0.05). Baseline levels of CD28, CXCL10, and TNFSF14, and increased CD40L post-treatment, correlated with inferior response. Baseline IL-4, IL-13 and increased GZMA post-treatment were associated with irAE occurrence. Using LASSO-Cox regression, we established an Immunosuppressive Signature of Combined Resistance Elements (I-SCORE) model based on eight plasma proteins (CCL23, ARG1, CD83, ADA, CXCL10, TNFSF14, CD28, GZMA). I-SCORE demonstrated strong predictive power for overall survival (12-month AUC = 0.94), progression-free survival (12-month AUC = 0.75), and treatment response (AUC = 0.62). Furthermore, a high I-SCORE was demonstrated to reflect an inflammatory and immunosuppressive phenotype, showing positive linear relationships with plasma IL-6, IL-8, IL-10, and monocyte count, and negative relationships with IL-33 and active T-cell proportion. Our study identifies I-SCORE, derived from plasma proteomics, as a promising integrated biomarker for predicting ICI outcomes in NSCLC. It suggests targeting specific proteins or the associated immunosuppressive microenvironment might enhance immunotherapy efficacy.
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spelling doaj-art-2df8224098c0406494a68dce38e315fa2025-08-20T03:42:39ZengSpringerMolecular Biomedicine2662-86512025-07-016111610.1186/s43556-025-00291-6Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory studyYuan Gao0Fei Qi1Wenhao Zhou2Peng Jiang3Mingming Hu4Ying Wang5Congcong Song6Yi Han7Dongdong Li8Na Qin9Hongmei Zhang10Haitao Luo11Tongmei Zhang12Hongxia Li13General Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteGeneral Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteShenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology CoGeneral Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteGeneral Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteGeneral Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteShenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology CoCardiothoracic Surgery Department, Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi University of Chinese MedicineSchool of Life Sciences, Anhui Medical UniversityOutpatient Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteGeneral Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteShenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology CoGeneral Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteGeneral Department, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research InstituteAbstract Immune checkpoint inhibitors (ICIs) show limited efficacy in non-small cell lung cancer (NSCLC), highlighting the need for predictive biomarkers. Here we prospectively analysed serial plasma samples from 34 ICI-treated advanced NSCLC patients (plus 30 validation samples) using the Olink Immuno-Oncology panel. We assessed dynamic proteomic changes associated with ICI efficacy and immune-related adverse events (irAEs), and developed a prognostic model. Following ICIs, 42/92 proteins significantly elevated upon ICI treatment (p < 0.05). Baseline levels of CD28, CXCL10, and TNFSF14, and increased CD40L post-treatment, correlated with inferior response. Baseline IL-4, IL-13 and increased GZMA post-treatment were associated with irAE occurrence. Using LASSO-Cox regression, we established an Immunosuppressive Signature of Combined Resistance Elements (I-SCORE) model based on eight plasma proteins (CCL23, ARG1, CD83, ADA, CXCL10, TNFSF14, CD28, GZMA). I-SCORE demonstrated strong predictive power for overall survival (12-month AUC = 0.94), progression-free survival (12-month AUC = 0.75), and treatment response (AUC = 0.62). Furthermore, a high I-SCORE was demonstrated to reflect an inflammatory and immunosuppressive phenotype, showing positive linear relationships with plasma IL-6, IL-8, IL-10, and monocyte count, and negative relationships with IL-33 and active T-cell proportion. Our study identifies I-SCORE, derived from plasma proteomics, as a promising integrated biomarker for predicting ICI outcomes in NSCLC. It suggests targeting specific proteins or the associated immunosuppressive microenvironment might enhance immunotherapy efficacy.https://doi.org/10.1186/s43556-025-00291-6Non-small cell lung cancerImmune checkpoint inhibitorPlasma proteomicsEfficacyRisk score
spellingShingle Yuan Gao
Fei Qi
Wenhao Zhou
Peng Jiang
Mingming Hu
Ying Wang
Congcong Song
Yi Han
Dongdong Li
Na Qin
Hongmei Zhang
Haitao Luo
Tongmei Zhang
Hongxia Li
Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory study
Molecular Biomedicine
Non-small cell lung cancer
Immune checkpoint inhibitor
Plasma proteomics
Efficacy
Risk score
title Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory study
title_full Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory study
title_fullStr Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory study
title_full_unstemmed Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory study
title_short Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory study
title_sort liquid biopsy using plasma proteomics in predicting efficacy and tolerance of pd 1 pd l1 blockades in nsclc a prospective exploratory study
topic Non-small cell lung cancer
Immune checkpoint inhibitor
Plasma proteomics
Efficacy
Risk score
url https://doi.org/10.1186/s43556-025-00291-6
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