Unveiling Macrophage Content as a Predictive Biomarker for Intraoperative ICG Imaging Efficacy in Lung Cancer

Due to the phenotypic and genotypic heterogeneity of tumors, the efficacy of intraoperative indocyanine green (ICG) imaging in lung cancer exhibits significant inter-patient variability. This study identifies macrophage content as a critical predictive biomarker for ICG imaging outcomes, offering both mechanistic, and clinical insights into this variability. Mechanistically, macrophages are demonstrated to serve as the principal ICG reservoirs in tumor tissues, exhibiting seven-fold higher uptake capacity compared to cancer cells. This critical role is confirmed by significantly diminished ICG accumulation following macrophage depletion in patient-derived xenograft (PDX) models. Clinically, a strong correlation is observed between imaging quality and macrophage content, with solid nodules exhibiting superior ICG uptake compared to ground-glass nodules due to higher macrophage infiltration. Furthermore, the strong tumor-to-normal ratio (TNR) association with preoperative maximum Standardized Uptake Value (SUVmax) on PET-CT suggests the feasibility of predicting ICG-guided surgery outcomes through routine imaging. The substantial contribution of macrophages to this predictive capability is a significant discovery, offering a novel biomarker for patient stratification in ICG-guided surgery. These insights not only deepen our comprehension of the intricate interplay between ICG and the lung cancer microenvironment but also open new avenues for the development of more personalized and precise surgical strategies.

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Publication Details

Journal
Advanced Science
Published
2025-08-04
DOI
https://doi.org/10.1002/advs.202504498
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Unveiling Macrophage Content as a Predictive Biomarker for Intraoperative ICG Imaging Efficacy in Lung Cancer

Yiguang Wang, Hui Zhao, Xing Yang, Jian Zhou et al.
Advanced Science
Lung Cancer Diagnosis and Treatment
article

Unveiling Macrophage Content as a Predictive Biomarker for Intraoperative ICG Imaging Efficacy in Lung Cancer

Yiguang Wang, Hui Zhao, Xing Yang, Jian Zhou, Guanchao Jiang, Jun Wang, Jianfeng Li, Yun Li, Yimeng Zhang, Kezhong Chen, Yanguo Liu, Jiahui Mi, Yue Yan, Fan Yang
article en

Abstract

Due to the phenotypic and genotypic heterogeneity of tumors, the efficacy of intraoperative indocyanine green (ICG) imaging in lung cancer exhibits significant inter-patient variability. This study identifies macrophage content as a critical predictive biomarker for ICG imaging outcomes, offering both mechanistic, and clinical insights into this variability. Mechanistically, macrophages are demonstrated to serve as the principal ICG reservoirs in tumor tissues, exhibiting seven-fold higher uptake capacity compared to cancer cells. This critical role is confirmed by significantly diminished ICG accumulation following macrophage depletion in patient-derived xenograft (PDX) models. Clinically, a strong correlation is observed between imaging quality and macrophage content, with solid nodules exhibiting superior ICG uptake compared to ground-glass nodules due to higher macrophage infiltration. Furthermore, the strong tumor-to-normal ratio (TNR) association with preoperative maximum Standardized Uptake Value (SUVmax) on PET-CT suggests the feasibility of predicting ICG-guided surgery outcomes through routine imaging. The substantial contribution of macrophages to this predictive capability is a significant discovery, offering a novel biomarker for patient stratification in ICG-guided surgery. These insights not only deepen our comprehension of the intricate interplay between ICG and the lung cancer microenvironment but also open new avenues for the development of more personalized and precise surgical strategies.

Advanced ScienceVol. 12(39)
Peking University (CN), Peking University People's Hospital (CN), Peking University First Hospital (CN)
National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality, Chinese Academy of Medical Sciences, Fundamental Research Funds for the Central Universities
Good health and well-being
Openalex Percentile: Top 70%
Lung Cancer Diagnosis and Treatment
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