Radiotherapy and immunotherapy in cancer treatment: mechanisms of clinical synergy
TL;DR
A spatial interaction–centric perspective is adopted to synthesize current knowledge on how RT governs the DC/CD8+ T cell interaction axis across the tumor microenvironment and tumor-draining lymph nodes, aiming to chart a rational course from empirical combination toward personalized, precision radioimmunotherapy.
Abstract
Synergizing radiotherapy (RT) with immune checkpoint inhibitors has emerged as a promising strategy for solid tumors. RT acts as a potent immunomodulator, capable of functioning as an in situ vaccine through the induction of immunogenic cell death and activation of innate immune sensing, thereby promoting DC maturation and CD8+ T cell responses. However, RT also triggers counter-regulatory immunosuppression, including PD-L1 upregulation and the recruitment of suppressive cells, providing the biological rationale for synergy. Here, we systematically review advances in radioimmunotherapy, covering immunomodulatory mechanisms, clinical optimization of dose and sequencing, and the emerging role of artificial intelligence (AI) in guiding treatment paradigms. We adopt a spatial interaction–centric perspective to synthesize current knowledge on how RT governs the DC/CD8+ T cell interaction axis across the tumor microenvironment and tumor-draining lymph nodes, aiming to chart a rational course from empirical combination toward personalized, precision radioimmunotherapy. Furthermore, we explore how AI-driven analysis of radiomics and multiomics data is being applied to predict responders and personalize treatment planning.