Recent advances in spatial omics and single-cell omics have significantly reshaped biomarker discovery in tumor immunotherapy by addressing critical challenges posed such as tumor heterogeneity, immune evasion, and variability within the tumor microenvironment (TME).

While immunotherapeutic strategies—such as immune checkpoint inhibitors and adoptive T-cell transfer—have demonstrated promising clinical outcomes, their effectiveness is hindered by low response rates and immune-related adverse events (irAEs). Thus, identifying reliable biomarkers is essential for predicting treatment efficacy, minimizing irAEs, and facilitating patient stratification. Spatial omics integrates molecular profiling with spatial localization, providing comprehensive insights into the cellular organization and functional states of the TME. By revealing spatial patterns of immune cell infiltration and tumor heterogeneity, this approach enhances our predictive capacity for therapeutic response. Similarly, single-cell omics yields high-resolution analysis of cellular heterogeneity, capturing transcriptomic, epigenomic, and metabolic signatures at the single-cell level. The combined application of spatial and single-cell omics has led to the identification of previously undetected biomarkers, including rare immune cell subsets implicated in resistance mechanisms. Beyond spatial transcriptomics (ST), this technological landscape also includes spatial proteomics and metabolomics, which further facilitate the study of dynamic tumor–immune interactions. Multi-omics integration offers a comprehensive overview of biomarker landscapes, while the rapid evolution artificial intelligence approaches enhances the analysis of complex, multidimensional datasets—ultimately enhancing predictive power and clinical utility. Despite substantial progress, challenges remain in standardization, data integration, and real-time monitoring. Nevertheless, incorporating spatial omics and single-cell omics into biomarker research holds transformative potential for personalized cancer immunotherapy. These emerging strategies pave the way for innovative diagnostic and therapeutic interventions, enabling precision oncology and elevating treatment outcomes for patients a wide range of tumor profiles.

This review aims to provide a comprehensive summary of the integration of spatial omics and single-cell omics in tumor immunotherapy biomarker discovery. Specifically, it focuses on how these emerging technologies address challenges related to tumor heterogeneity, immune evasion, and the dynamic TME. By elaborating on the principles, applications, and clinical potential of these technologies, the review will also critically evaluate their limitations, challenges, and the current gaps in their translational applications.

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