靶向microRNA介导的铜稳态失调以增强胶质母细胞瘤瘤内对溶瘤单纯疱疹病毒-1的易感性

Glioblastoma (GBM) is a WHO grade IV astrocytoma characterized by diffuse infiltration, rapid proliferation, and resistance to conventional therapies, resulting in dismal patient outcomes. Oncolytic virotherapy, particularly utilizing genetically engineered oncolytic herpes simplex virus-1 (oHSV), has demonstrated tumor-selective cytolysis and immunogenic cell death. Despite promising preclinical data, clinical efficacy remains limited due to poorly defined intrinsic resistance mechanisms within the tumor microenvironment (TME) of GBM. Our study identified microRNA-155 (miR-155) as a critical modulator of oHSV therapeutic resistance. We found elevated miR-155 expression in GBM compared to low-grade gliomas, which correlates with a poor prognosis and reduced response to OV therapy. These findings were further supported by The Cancer Genome Atlas (TCGA) data. Ectopic overexpression of miR-155 significantly attenuated oHSV replication and cytopathic effects. Transcriptomic profiling and pathway enrichment analyses revealed that miR-155 upregulates metallothioneins MT1E and MT1F , key regulators of intracellular copper sequestration and antiviral defense. Mechanistically, miR-155 disrupts copper homeostasis via the MT1 axis, impairing viral replication and therapeutic efficacy. Functional ablation of miR-155 via CRISPR/Cas9-mediated knockout or Locked Nucleic Acid (LNA)-based inhibition restored copper homeostasis, oHSV replication kinetics, and enhanced oncolysis in vitro and in orthotopic GBM xenograft models, resulting in prolonged survival. These data suggest that the miR-155/MT1E-MT1F/copper signaling axis represents a novel barrier to oHSV therapy. This work elucidates a previously uncharacterized antiviral resistance pathway in GBM and validates miR-155 inhibition as a rational therapeutic strategy to potentiate oHSV efficacy. Our findings provide a mechanistic framework for overcoming innate resistance and advancing the clinical translation of virotherapy in neuro-oncology. This abstract was originally written by the authors and then edited and revised with generative artificial intelligence (AI).