Immune checkpoint inhibitors (ICIs) have transformed oncological practice by generating durable antitumour responses across a broad spectrum of malignancies. However, meaningful clinical benefit accrues to only a fraction of patients, and resistance remains a persistent challenge. This review examines the evolution of ICI-based therapy from single-agent checkpoint blockade through multimodal combination regimens to biomarker-directed, personalised strategies. Combination approaches pairing ICIs with cytotoxic chemotherapy, radiotherapy, molecularly targeted agents, and emerging platforms such as oncolytic viruses and therapeutic vaccines exploit mechanistic synergies and have demonstrated improved immunological and clinical endpoints. The expanding repertoire of predictive biomarkers encompassing PD-L1 expression, tumour mutational burden (TMB), microsatellite instability (MSI) status, and transcriptomic immune signatures has refined patient stratification. The tumour immune microenvironment and the gut microbiome are increasingly recognised as modulable determinants of treatment response, offering avenues aligned with integrative oncology. Artificial intelligence and machine learning applied to multi-omics datasets are advancing response prediction and resistance identification. Key challenges include immune-related adverse events (irAEs), treatment costs, and biomarker standardisation. Future priorities encompass next-generation checkpoint targets, bispecific antibodies, liquid biopsy-guided surveillance, and microbiome-directed interventions. The convergence of immunological precision, integrative patient-centred care, and computational decision-making defines the next chapter of cancer immunotherapy.
