Immune checkpoint inhibitors for glioblastoma: emerging science, clinical advances, and future directions

胶质母细胞瘤的免疫检查点抑制剂:新兴科学、临床进展和未来方向

阅读:3

Abstract

Glioblastoma (GBM), the most common and aggressive primary central nervous system (CNS) tumor in adults, continues to have a dismal prognosis. Across hundreds of clinical trials, few novel approaches have translated to clinical practice while survival has improved by only a few months over the past three decades. Randomized controlled trials of immune checkpoint inhibitors (ICIs), which have seen impressive success for advanced or metastatic extracranial solid tumors, have so far failed to demonstrate a clinical benefit for patients with GBM. This has been secondary to GBM heterogeneity, the unique immunosuppressive CNS microenvironment, immune-evasive strategies by cancer cells, and the rapid evolution of tumor on therapy. This review aims to summarize findings from major clinical trials of ICIs for GBM, review historic failures, and describe currently promising avenues of investigation. We explore the biological mechanisms driving ICI responses, focusing on the role of the tumor microenvironment, immune evasion, and molecular biomarkers. Beyond conventional monotherapy approaches targeting PD-1, PD-L1, CTLA-4, we describe emerging approaches for GBM, such as dual-agent ICIs, and combination of ICIs with oncolytic virotherapy, antigenic peptide vaccines, chimeric antigenic receptor (CAR) T-cell therapy, along with nanoparticle-based delivery systems to enhance ICI efficacy. We highlight potential strategies for improving patient selection and treatment personalization, along with real-time, longitudinal monitoring of therapeutic responses through advanced imaging and liquid biopsy techniques. Integrated radiomics, tissue, and plasma-based analyses, may potentially uncover immunotherapeutic response signatures, enabling early, adaptive therapeutic adjustments. By specifically targeting current therapeutic challenges, outcomes for GBM patients may potentially be improved.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。