The Immune Rheostat: A Shared Regulatory Axis Linking Cancer Immune Evasion and Autoimmune Activation

Cancer and autoimmune diseases are traditionally regarded as distinct clinical entities, yet growing evidence indicates that both arise from dysregulation of shared immune-regulatory pathways coordinating immune activation, peripheral tolerance and tissue homeostasis. Rather than acting as independent processes, immune checkpoint signalling, T-cell functional integrity, regulatory T-cell (Treg) stability, cytokine and myeloid-cell polarization, and spatial immune organization form interconnected circuits that determine the quality, magnitude, and persistence of immune responses. The direction and extent of perturbation within these pathways, rather than simple activation or inhibition, determines whether immune responses promote tumour evasion or autoimmunity. Clinical experience with immune checkpoint inhibitors provides compelling evidence for this shared biology: blockade of PD-1 or CTLA-4 restores antitumor immunity but frequently disrupts peripheral tolerance, producing immune-related adverse events that closely resemble spontaneous autoimmune disease, showing checkpoints function within a broader network balancing protective immunity with self-tolerance. In this review, we propose the immune rheostat as an integrative framework unifying these shared mechanisms across cancer and autoimmune disease. We examine checkpoint co-signalling, T-cell exhaustion, Treg epigenetic stability, cytokine/myeloid networks, spatial architecture, and biomarker signatures across the disease spectrum, illustrated through a lupus nephritis model in which restoring follicular regulatory (Tfr)-helper (Tfh) T-cell balance demonstrates how coordinated pathway rewiring restores homeostasis. This review offers a unified framework for shared immune regulation, proposes layer-specific therapeutic strategies and a matched, non-checkpoint-restricted biomarker panel for tracking patients along the rheostat, and situates this framework against related single-disease and checkpoint-centric models.