Virtual clinical trial reveals significant clinical potential of targeting tumour-associated macrophages and microglia to treat glioblastoma

Glioblastoma is the most aggressive primary brain tumour, with a median survival of just fifteen months with treatment. Standard-of-care (SOC) for glioblastoma consists of resection followed by radio- and chemotherapy. Clinical trials involving PD-1 inhibition with nivolumab in combination with SOC failed to increase overall survival. A quantitative understanding of the interactions between the tumour and its immune environment driving treatment outcomes is currently lacking. As such, we developed a mathematical model of tumour growth that considers cytotoxic CD8+ T cells, pro- and antitumoral tumour-associated macrophages and microglia (TAMs), SOC, and nivolumab. Our results show that PD-1 inhibition fails due to a lack of CD8+ T cell recruitment during treatment explained by TAM-driven immunosuppressive mechanisms. Using our model, we studied five TAM-targeting strategies currently under investigation for solid tumours. Our model predicts that while reducing TAM numbers does not improve prognosis, altering their functions to counter their protumoral properties has the potential to considerably reduce post-treatment tumour burden. In particular, restoring antitumoral TAM phagocytic activity through anti-CD47 treatment in combination with SOC was predicted to nearly eradicate the tumour. By studying time-varying efficacy with the same half-life as the anti-CD47 antibody Hu5F9-G4, our model predicts that repeated dosing of anti-CD47 provides sustained control of tumour growth. Thus, we propose that targeting TAMs by enhancing their antitumoral properties is a highly promising avenue to treat glioblastoma and warrants future clinical development. Together, our results provide proof-of-concept that mechanistic mathematical modelling can uncover the mechanisms driving treatment outcomes and explore the potential of novel treatment strategies for hard-to-treat tumours like glioblastoma.