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Updated: Jul 19, 2026
Isolation and Flow Cytometric Analysis of Glioma-infiltrating Peripheral Blood Mononuclear Cells
Published on: November 28, 2015
Cross-Disease myeloid remodeling along the GMP-TAM axis predicts immunotherapy response in glioma
Yuanyuan Zhang1, Xin Liu1, Shi Hua2
1Department of General Practice, Peking University People's Hospital, No.11 Xizhimen South Street, Beijing 100044, China.
Backgrounds:
Immune checkpoint inhibitor-induced colitis (CICs) represents a state of systemic immune activation and is paradoxically associated with superior anti-tumor responses. This study has been designed to explore gene signatures derived from CICs that could identify the key immunological drivers, and predict sensitivity of immunotherapy in immunologically cold tumors e.g. glioma.
Methods:
We integrated bulk, single-cell, and spatial transcriptomic data from CICs and glioma cohorts. Cross-disease analysis have been performed to identify an immunotherapy-responsive granulocyte-monocyte progenitor (IR-GMP) signature. Risk score (RS) model has been constructed through LASSO regression, and have been validated for its potential prognostic as well as predictive values.
Results:
We have identified 112 IR-GMP genes enriched in pathways that may cause myeloid immunosuppression. A four-gene RS model (RAC2, LAPTM5, HCLS1, CD74) has been developed, and glioma patients have been divided into high- and low-risk groups based on the model. RS is an independent prognostic factor, and demonstrated to exhibit superior accuracy for predicting survival when combining with clinical variables. High-RS tumors exhibited immunosuppressive TME characterized by M2 macrophage enrichment, SPP1-signaling hyperactivation, and an immune-tolerant genomic landscape (C4 subtype). Crucially, the high-RS group showed significantly higher immunophenoscores under PD-1 and combined PD-1/CTLA-4 blockade, indicating potential sensitivity to immunotherapy, and distinct chemotherapy susceptibility. Single-cell and spatial transcriptomic results confirmed the lineage specificity and regional colocalization of RS genes with M2 macrophages.
Conclusions:
Our cross-disease analysis unveils a conserved GMP-TAM myeloid remodeling axis in glioma. The derived RS model may serve as a powerful marker for predicting prognosis, and also for predicting the benefits derived from immunotherapy, offering a novel tool for precision immunotherapy in glioma.
Insights
Immune checkpoint inhibitor-induced colitis (CICs) reveals a myeloid remodeling axis. A four-gene risk score model predicts glioma prognosis and immunotherapy sensitivity.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Immune checkpoint inhibitor-induced colitis (CICs) is linked to enhanced anti-tumor immunity.
- Understanding CICs may reveal drivers of immunotherapy response in cold tumors like glioma.
Purpose of the Study:
- Identify gene signatures in CICs to predict immunotherapy sensitivity in glioma.
- Develop a prognostic and predictive model for glioma patients.
Main Methods:
- Integrated bulk, single-cell, and spatial transcriptomics from CICs and glioma.
- Identified an immunotherapy-responsive granulocyte-monocyte progenitor (IR-GMP) signature.
- Constructed and validated a four-gene risk score (RS) model using LASSO regression.
Main Results:
- Discovered 112 IR-GMP genes linked to myeloid immunosuppression.
- Developed a four-gene RS model (RAC2, LAPTM5, HCLS1, CD74) classifying glioma patients into high- and low-risk groups.
- High-RS tumors showed immunosuppressive microenvironments and potential sensitivity to immunotherapy.
Conclusions:
- Unveiled a conserved granulocyte-monocyte progenitor-tumor-associated myeloid (GMP-TAM) axis in glioma.
- The RS model predicts prognosis and immunotherapy benefits in glioma.
- Offers a novel tool for precision immunotherapy in glioma.
