Single-cell technologies have revolutionized cancer studies by enabling high-resolution granular exploration of individual cells in cancer cell populations. Here, we explored how single-cell sequencing of genomics, epigenomics, transcriptomics, and multi-omics provides deep insight into cancer biology, interactions in tumor microenvironment, dynamics of immune response, and evolution of cancer. We describe the central platforms and computational approaches used in single-cell research, along with data sparsity, integration, and challenges in clinical translation. Key applications are illustrated in early diagnosis of cancer, identification of distinct biomarkers, monitoring of minimal residual disease, and classification of rare cell types. We further explored the identification of resistance mechanism to drugs, blockade of immune checkpoints, and strategies for adaptive immune therapy through single-cell technologies. Finally, we assess the drawbacks and future directions which is shifting toward precision oncology assisted by advanced computational analytics and initiatives taken globally. Overall, this chapter underlines the potential of single-cell technology to transform cancer diagnosis and therapeutics, which paves the way for precision medicine.