Abstract
The introduction of immune checkpoint inhibitors (ICIs) targeting cytotoxic T-lymphocyte–associated protein 4 (CTLA-4) and later programmed cell death protein 1 (PD-1) or its ligand (PD-L1) marked a turning point in cancer therapy. These agents validated the principle that durable tumor control can be achieved by releasing inhibitory pathways that restrain antitumor T cell responses. Long-term survival benefits in melanoma, non-small cell lung cancer, and other malignancies have established immunotherapy as a defining development in oncology. However, long-term clinical benefits remain confined to a minority of patients, and resistance or relapse is common in the remaining patients. The mechanisms underlying this limited efficacy include inadequate T cell infiltration, tumor-intrinsic defects in antigen presentation, compensatory upregulation of alternative checkpoints, and an immunosuppressive tumor microenvironment (TME). In addition, immune-related toxicities, particularly those associated with CTLA-4 blockade, restrict the broader use of these agents. To overcome these barriers, attention has shifted toward next-generation checkpoint pathways in cancer therapy. Inhibitory receptors, such as LAG-3, TIGIT, TIM-3, and VISTA, along with innate checkpoints, including CD47-SIRPα, NKG2A, and Siglec-15, are emerging as promising targets. Simultaneously, strategies to enhance co-stimulatory signaling through OX40, 4-1BB, ICOS, GITR, and CD40 aim to overcome T cell exhaustion and broaden immune activation have been developed. The approval of relatlimab, an anti-LAG-3 antibody, in combination with nivolumab, provides clinical proof-of-concept, while many agents directed at additional pathways remain in early- and late-phase trials. This review summarizes the current knowledge of next-generation checkpoint biology and development, highlights resistance mechanisms and biomarker-driven patient selection, and considers future approaches, including multispecific antibodies, engineered cytokines, and precision immunotherapy strategies.
Keywords
Artificial intelligence, Biomarkers, Cancer immunotherapy, Immune checkpoint inhibitors, Resistance mechanisms