ABSTRACT Background: Glioblastoma (GBM) establishes a highly immunosuppressive microenvironment through intricate molecular dialogues with tumor‐associated macrophages (TAMs), contributing to immunotherapy resistance. Methods: We integrated advanced biological network analyses with multimodal AI to identify CTSB as a key biomarker. Functional validation included GBM‐macrophage co‐culture systems, chromatin immunoprecipitation (ChIP), dual‐luciferase reporter assays, molecular docking, and co‐immunoprecipitation (Co‐IP). In vivo experiments employed orthotopic (GL261 and CT‐2A) and subcutaneous GBM models with lentivirus‐mediated CTSB knockdown and anti‐PD‐1 therapy. Tumor microenvironment dynamics were assessed via in‐house generated single‐cell RNA sequencing and multiplex immunofluorescence. Results: Cathepsin B (CTSB) was identified as a critical driver of aggressive GBM progression and poor outcomes. Mechanistically, macrophage‐derived IL‐6 activates STAT3 in tumor cells, upregulating CTSB expression. Structural and Co‐IP analyses revealed CTSB, secreted by tumor cells, binds the C‐terminus of macrophage S100A10, reinforcing IL‐6 secretion, forming a feedforward loop between CTSB+ GBM cells and S100A10+ macrophages. This loop enhances tumor growth, invasion, and immune evasion via PD‐L1 upregulation. In vivo, CTSB blockade reduced TAM activation, increased CD8+ T cell infiltration, and synergized with anti‐PD‐1 therapy. Conclusions: This study unveils a targetable GBM‐macrophage signaling axis, proposing CTSB inhibition as a strategy to enhance immunotherapy efficacy in GBM patients.
Hao Zhang, Nan Zhang, Xisong Liang et al.· Advancement of science· 0 citations
BACKGROUND
Glioblastoma (GBM) remains a lethal brain tumor with limited therapeutic options. Metabolic reprogramming, particularly lactate metabolism, plays a critical role in tumor progression and immune evasion.
METHODS
Here, we integrated single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and machine learning to investigate the heterogeneity of lactate metabolism in GBM.
RESULTS
Using scRNA-seq data (GSE138794), we classified neoplastic cells into high- and low-lactate subgroups and identified nuclear factor of activated T-cells cytoplasmic 4 (NFATc4) as a key transcription factor associated with elevated lactate metabolism. Pseudotime trajectory analysis revealed dynamic upregulation of NFATc4 during neoplastic cell differentiation, correlating with invasive phenotypes. Spatial transcriptomics (GSE194329) demonstrated colocalization of NFATc4⁺ tumor cells with SPP1⁺ macrophages, suggesting their microenvironmental crosstalk. A prognostic model constructed via 101 machine-learning algorithms (StepCox[forward] + RSF) achieved favorable performance across independent cohorts (TCGA, CGGA, GSE108474, GSE4412, and meta-cohort). Patients with different risk levels showed distinct immune infiltration, copy number alterations, and drug-sensitivity profiles. In vitro functional assays confirmed that NFATc4 knockdown in GBM cells suppressed tumor cell proliferation, migration, and cell cycle while promoting apoptosis. Besides, NFATc4 knockdown in GBM cells reduced SPP1 expression, migration, and M2-like polarization of co-cultured macrophages. Moreover, silencing SPP1 in macrophages attenuated the pro-tumorigenic effects on co-cultured GBM cells, validating the functional relevance of the NFATc4-SPP1 axis.
CONCLUSION
Our study reveals lactate metabolism-related NFATc4 as a promising therapeutic target in GBM, with implications for prognosis stratification and combination therapy.
Ruoli Wang, Wan-Tao Wu, Xuan Wu et al.· Journal of Translational Med...· 0 citations
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