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Updated: Jul 17, 2025
Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections
Published on: July 31, 2017
Noninvasive radiomics model reveals macrophage infiltration in glioma
Xiao Fan1, Jintan Li1, Bin Huang2
1Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Abstract:
Preoperative MRI is an essential diagnostic and therapeutic reference for gliomas. This study aims to evaluate the prognostic aspect of a radiomics biomarker for glioma and further investigate its relationship with tumor microenvironment and macrophage infiltration. We covered preoperative MRI of 664 glioma patients from three independent datasets: Jiangsu Province Hospital (JSPH, n = 338), The Cancer Genome Atlas dataset (TCGA, n = 252), and Repository of Molecular Brain Neoplasia Data (REMBRANDT, n = 74). Incorporating a multistep post-processing workflow, 20 radiomics features (Rads) were selected and a radiomics survival biomarker (RadSurv) was developed, proving highly efficient in risk stratification of gliomas (cut-off = 1.06), as well as lower-grade gliomas (cut-off = 0.64) and glioblastomas (cut-off = 1.80) through three fixed cut-off values. Through immune infiltration analysis, we found a positive correlation between RadSurv and macrophage infiltration (RMΦ = 0.297, p < 0.001; RM2Φ = 0.241, p < 0.001), further confirmed by immunohistochemical-staining (glioblastomas, n = 32) and single-cell sequencing (multifocal glioblastomas, n = 2). In conclusion, RadSurv acts as a strong prognostic biomarker for gliomas, exhibiting a non-negligible positive correlation with macrophage infiltration, especially with M2 macrophage, which strongly suggests the promise of radiomics-based models as a preoperative alternative to conventional genomics for predicting tumor macrophage infiltration and provides clinical guidance for immunotherapy.
Insights
A new radiomics survival biomarker (RadSurv) effectively predicts glioma patient prognosis and risk stratification. This biomarker also correlates positively with macrophage infiltration, offering insights for immunotherapy strategies.
Area of Science:
- Neuro-oncology
- Radiology
- Computational Biology
Background:
- Preoperative MRI is crucial for glioma diagnosis and treatment planning.
- Glioma prognosis and tumor microenvironment characteristics remain areas for improved predictive markers.
Purpose of the Study:
- To develop and validate a radiomics biomarker for predicting glioma prognosis.
- To investigate the association between the radiomics biomarker, tumor microenvironment, and macrophage infiltration.
Main Methods:
- Utilized preoperative MRI data from 664 glioma patients across three independent datasets (JSPH, TCGA, REMBRANDT).
- Applied a multistep workflow to extract 20 radiomics features and developed a radiomics survival biomarker (RadSurv).
- Performed immune infiltration analysis, immunohistochemical staining, and single-cell sequencing to assess macrophage infiltration.
Main Results:
- The developed RadSurv biomarker demonstrated high efficiency in risk stratification for gliomas, lower-grade gliomas, and glioblastomas.
- RadSurv showed a significant positive correlation with overall macrophage infiltration (R=0.297) and M2 macrophage infiltration (R=0.241).
- Findings were validated through immunohistochemistry and single-cell sequencing, confirming the link with macrophage infiltration.
Conclusions:
- RadSurv serves as a robust preoperative prognostic biomarker for gliomas.
- The biomarker's correlation with macrophage infiltration suggests its potential for predicting tumor immune microenvironment characteristics.
- Radiomics-based models show promise as a preoperative alternative to genomics for predicting macrophage infiltration, guiding immunotherapy.
