ArticleBiology of the cell2026
Integrated 2D-3D Proteomic Profiling Identifies MLK4 as a Microenvironment-Responsive Regulator of Chemotherapeutic Resistance in Human Glioblastoma Cells.
Article in Biology of the cell, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundTherapeutic resistance is a major cause of treatment failure in glioblastoma (GBM), highlighting the need for physiologically relevant models to identify actionable resistance mechanisms. While two-dimensional (2D) cultures are widely used for target discovery, they poorly represent the tumor microenvironment. In contrast, three-dimensional (3D) spheroid cultures better recapitulate spatial heterogeneity, hypoxic gradients, and stress-adaptive signaling observed in tumors.
methodsWe applied an integrated 2D-3D quantitative proteomic approach to identify microenvironment-dependent regulators of chemoresistance in GBM. Proteomic profiling was performed in U87MG and U251MG cells grown as 2D monolayers or 3D spheroids. Differentially expressed proteins were validated by quantitative RT-PCR, and functional studies were conducted using genetic depletion followed by assessment of temozolomide (TMZ) sensitivity.
resultsComparative analysis identified 13 proteins consistently differentially expressed between 2D and 3D cultures: NDUFB5, RNGTT, MLK4, SYN1, DDX5, EIF2AK2, ITGA1, ZNF33B, ZNF343, WDR19, JPH3, CCT8L2, and FNDC3A. Among these, Mixed Lineage Kinase 4 (MLK4) showed strong and reproducible upregulation in 3D spheroids in both GBM cell lines. Genetic depletion of MLK4 significantly increased TMZ sensitivity without affecting basal cell viability, suggesting a specific role in therapy response. Notably, MLK4 expression was induced only under 3D conditions.
conclusionMLK4 functions as a microenvironment-responsive regulator of chemoresistance in GBM. These findings demonstrate that 3D culture systems reveal clinically relevant resistance pathways not detectable in conventional 2D models and highlight 3D proteomic profiling as a powerful strategy for identifying therapeutically actionable targets.
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