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Virus-Based Immunotherapy of Glioblastoma.

ABSTRACT: Glioblastoma (GBM) is the most common type of primary brain tumor in adults. Despite recent advances in cancer therapy, including the breakthrough of immunotherapy, the prognosis of GBM patients remains dismal. One of the new promising ways to therapeutically tackle the immunosuppressive GBM microenvironment is the use of engineered viruses that kill tumor cells via direct oncolysis and via stimulation of antitumor immune responses. In this review, we focus on recently published results of phase I/II clinical trials with different oncolytic viruses and the new interesting findings in preclinical models. From syngeneic preclinical GBM models, it seems evident that oncolytic virus-mediated destruction of GBM tissue coupled with strong adjuvant effect, provided by the robust stimulation of innate antiviral immune responses and adaptive anti-tumor T cell responses, can be harnessed as potent immunotherapy against GBM. Although clinical testing of oncolytic viruses against GBM is at an early stage, the promising results from these trials give hope for the effective treatment of GBM in the near future.

SUBMITTER: Martikainen M

PROVIDER: S-EPMC6407011 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Virus-Based Immunotherapy of Glioblastoma.

Martikainen Miika M Essand Magnus M

Cancers 20190205 2

Glioblastoma (GBM) is the most common type of primary brain tumor in adults. Despite recent advances in cancer therapy, including the breakthrough of immunotherapy, the prognosis of GBM patients remains dismal. One of the new promising ways to therapeutically tackle the immunosuppressive GBM microenvironment is the use of engineered viruses that kill tumor cells via direct oncolysis and via stimulation of antitumor immune responses. In this review, we focus on recently published results of phase ...[more]

PMID: 30764570

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Project description:IntroductionAs a malignant brain tumor, glioblastoma (GBM) is characterized by intratumor heterogeneity, a worse prognosis, and highly invasive, lethal, and refractory natures. Immunotherapy has been becoming a promising strategy to treat diverse cancers. It has been known that there are highly heterogeneous immunosuppressive microenvironments among different GBM molecular subtypes that mainly include classical (CL), mesenchymal (MES), and proneural (PN), respectively. Therefore, an in-depth understanding of immune landscapes among them is essential for identifying novel immune markers of GBM.Methods and resultsIn the present study, based on collecting the largest number of 109 immune signatures, we aim to achieve a precise diagnosis, prognosis, and immunotherapy prediction for GBM by performing a comprehensive immunogenomic analysis. Firstly, machine-learning (ML) methods were proposed to evaluate the diagnostic values of these immune signatures, and the optimal classifier was constructed for accurate recognition of three GBM subtypes with robust and promising performance. The prognostic values of these signatures were then confirmed, and a risk score was established to divide all GBM patients into high-, medium-, and low-risk groups with a high predictive accuracy for overall survival (OS). Therefore, complete differential analysis across GBM subtypes was performed in terms of the immune characteristics along with clinicopathological and molecular features, which indicates that MES shows much higher immune heterogeneity compared to CL and PN but has significantly better immunotherapy responses, although MES patients may have an immunosuppressive microenvironment and be more proinflammatory and invasive. Finally, the MES subtype is proved to be more sensitive to 17-AAG, docetaxel, and erlotinib using drug sensitivity analysis and three compounds of AS-703026, PD-0325901, and MEK1-2-inhibitor might be potential therapeutic agents.ConclusionOverall, the findings of this research could help enhance our understanding of the tumor immune microenvironment and provide new insights for improving the prognosis and immunotherapy of GBM patients.

Dataset Information

Virus-Based Immunotherapy of Glioblastoma.

Publications

Virus-Based Immunotherapy of Glioblastoma.

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