Single-cell technologies have transformed cancer research by enabling high-resolution characterization of tumor heterogeneity and the microenvironment. These approaches uncover rare malignant cell states, clonal dynamics, and immunosuppressive subsets that shape tumor progression and therapeutic resistance. They have also advanced biomarker discovery, minimal residual disease monitoring, and prediction of immunotherapy response, opening new avenues for patient stratification and precision oncology. Yet, key challenges remain, including scalability, protocol standardization, and data privacy. Emerging innovations, such as spatial multi-omics, organoid-based systems, and artificial intelligence, promise to bridge these gaps and accelerate clinical translation. Collectively, single-cell technologies represent a paradigm shift in oncology, with profound implications for diagnosis, prognosis, and therapy.