Precision Immunotherapeutics for Glioblastoma: Current Approaches and Emerging Strategies in 2026

Sep 23, 2026

Uploaded by James

Glioblastoma (GBM) remains a major therapeutic challenge despite extensive efforts to exploit immunotherapy. Checkpoint blockade has transformed outcomes in many cancers, yet GBM responses are limited by a profound immunosuppressive tumor microenvironment, spatial heterogeneity, and dynamic metabolic constraints. This review synthesizes systems biology insights defining how interferon competence, myeloid antigen presentation, T-cell clone status, immune spatial organization, and immune–tumor resource competition shape responsiveness. Spatial transcriptomics, single-cell profiling, and high-parameter imaging support predictive biomarker discovery and guide rational combination strategies. It further links checkpoint blockade with metabolic reprogramming, myeloid modulation, and interferon reactivation, using AI analytics and adaptive trial design.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages28

Reading Time1 h 11 min

AccessFree to download

Abstract

Introduction

The Unique Immunobiology of GBM

Immunologically Cold Tumor Hallmarks

Review Precision Immunotherapeutics for Glioblastoma: Current Approaches and Emerging Strategies in 2026 James Poe 1,†, Claire Kim 1,†, Campbell Coleman 1,‡, Hieu Nguyen 1,‡, Vaithish Velazhahan 1, Brandon Bergsneider 1, Vivek Sanker 1, Samuel Kim 1, Yijiang Chen 2, Matthew Abikenari 1, John Choi 1 and Michael Lim 1, * Academic Editor: Pablo Martín-Vasallo Received: 1 March 2026 Revised: 16 March 2026 Accepted: 18 March 2026 Published: 20 March 2026 Copyright: © 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. 1 Department of Neurosurgery, School of Medicine, Stanford University, Stanford, CA 94305, USA; [jamespoe@stanford.edu](jamespoe@stanford.edu) (J.P.); [nguyenhm@stanford.edu](nguyenhm@stanford.edu) (H.N.); [mattabi@stanford.edu](mattabi@stanford.edu) (M.A.) 2 Department of Radiation Oncology, School of Medicine, Stanford University, Stanford, CA 94305, USA * [Correspondence: mklim@stanford.edu](Correspondence: mklim@stanford.edu)[ ](Correspondence: mklim@stanford.edu)† These authors contributed equally to this work. ‡ These authors contributed equally to this work. Abstract Glioblastoma (GBM) persists as one of the greatest challenges in the treatment of human cancer, despite extensive efforts to leverage the therapeutic potential of immunotherapy. While checkpoint blockade and other forms of immunotherapy have revolutionized the treatment of various cancers, their therapeutic efficacy in GBM has been hindered by the profound immunosuppressive environment, spatial heterogeneity, and dynamic immune metabolic challenges associated with the tumor microenvironment. In this review, we will synthesize recent advances and insights to develop a next-generation framework for GBM immunotherapy based on systems biology approaches to understanding the complex interplay between GBM and the immune system, as opposed to single-axis approaches to immune activation and modulation. We will discuss how the functional competence of the interferon system, myeloid antigen presentation status, T-cell clone status, spatial organization of the immune microenvironment, and resource competition between GBMand the immune system dictate therapeutic responsiveness. Furthermore, the current paper elucidates how recent advances in spatial transcriptomics, single-cell analysis, and high-parameter imaging enable us to understand how immune phenotype status varies across GBM regions and treatment status, and how this information can be used to develop predictive and pharmacodynamic biomarkers of therapeutic efficacy and failure. We will then discuss how these advances form the basis for rational combination approaches to GBM immunotherapy, which involve the integration of checkpoint blockade with metabolic reprogramming, myeloid modulation, and interferon system reactivation, and how artificial intelligence-based analytics and adaptive clinical trial design can guide the development of biomarker-based therapeutic selection approaches. Keywords: glioblastoma; tumor microenvironment; precision immunotherapy; T cell exhaustion; metabolic reprogramming; checkpoint immunotherapy; interferon signaling; spatial immune organization 1. Introduction Glioblastoma (GBM) is the most prevalent and aggressive primary malignant brain tumor in adults, accounting for about 52.2% of all primary brain malignancies. The estimated incidence of GBM is 3.28 cases per 100,000 individuals, with a median age at diagnosis of 66 years [1] . The clinical burden of GBM extends beyond tumor location-related adverse effects, as GBM not only causes widespread metabolic derangements, but it is inherently a diffusely infiltrative disease that can disrupt synaptic function, white matter tracts, and immune function, effecting a major decline in the quality of life of patients [2] . Despite aggressive treatment strateg

FAQs

Why has immunotherapy been less effective in glioblastoma than in other cancers?

Immunotherapy outcomes in GBM are constrained by the immunosuppressive tumor microenvironment, tumor spatial heterogeneity, and dynamic immune metabolic challenges that limit effective immune activation.

Which biological factors are highlighted as determinants of therapeutic responsiveness?

The review emphasizes interferon system functional competence, myeloid antigen presentation status, T-cell clone status, spatial organization of the immune microenvironment, and resource competition between GBM and immune cells.

How can modern single-cell and spatial technologies improve GBM treatment development?

Advances in spatial transcriptomics, single-cell analysis, and high-parameter imaging help map immune phenotypes across GBM regions and treatment states, enabling predictive and pharmacodynamic biomarkers for therapy efficacy and failure.

Sep 23, 2026

Uploaded by James