@article{10.1172/jci.insight.142980, author = {Vassilis Genoud AND Felipe I. Espinoza AND Eliana Marinari AND Viviane Rochemont AND Pierre-Yves Dietrich AND Paul McSheehy AND Felix Bachmann AND Heidi A. Lane AND Paul R. Walker}, journal = {JCI Insight}, publisher = {The American Society for Clinical Investigation}, title = {Treating ICB-resistant glioma with anti-CD40 and mitotic spindle checkpoint controller BAL101553 (lisavanbulin)}, year = {2021}, month = {11}, volume = {6}, url = {https://insight.jci.org/articles/view/142980}, abstract = {Glioblastoma is a highly malignant brain tumor with no curative treatment options, and immune checkpoint blockade has not yet shown major impact. We hypothesized that drugs targeting mitosis might affect the tumor microenvironment and sensitize cancer cells to immunotherapy. We used 2 glioblastoma mouse models with different immunogenicity profiles, GL261 and SB28, to test the efficacy of antineoplastic and immunotherapy combinations. The spindle assembly checkpoint activator BAL101553 (lisavanbulin), agonistic anti-CD40 antibody, and double immune checkpoint blockade (anti–programmed cell death 1 and anti–cytotoxic T lymphocyte–associated protein 4; anti–PD-1 and anti–CTLA-4) were evaluated individually or in combination for treating orthotopic GL261 and SB28 tumors. Genomic and immunological analyses were used to predict and interpret therapy responsiveness. BAL101553 monotherapy increased survival in immune checkpoint blockade–resistant SB28 glioblastoma tumors and synergized with anti-CD40 antibody, in a T cell–independent manner. In contrast, the more immunogenic and highly mutated GL261 model responded best to anti–PD-1 and anti–CTLA-4 therapy and more modestly to BAL101553 and anti-CD40 combination. Our results show that BAL101553 is a promising therapeutic agent for glioblastoma and could synergize with innate immune stimulation. Overall, these data strongly support immune profiling of glioblastoma patients and preclinical testing of combination therapies with appropriate models for particular patient groups.}, number = {18}, doi = {10.1172/jci.insight.142980}, url = {https://doi.org/10.1172/jci.insight.142980}, }