Abstract
Mass cytometry (CyTOF) and Imaging Mass Cytometry (IMC) provide single-cell resolution for over 50 protein markers, enabling unprecedented exploration of tumour and immune heterogeneity. We conducted a scoping review of 61 original studies (inception-2025), spanning 17 cancer types, to map current applications, analytical strategies, and emerging biological insights. 46 studies used CyTOF alone, 12 employed IMC exclusively, and 3 combined both platforms. Median panel sizes were 33.5 markers for CyTOF and 33 for IMC. While lineage and immune checkpoint markers were universal, phospho-epitopes, metabolic enzymes, and stromal proteins appeared in more focused subsets. Most studies followed a three-step analytical workflow: (i) segmentation or gating, (ii) unsupervised clustering, and (iii) downstream spatial or functional analyses. CyTOF investigations frequently identified exhausted CD8(+) T-cell subsets (e.g., PD-1(+)TIM-3(+)CD39(+)), suppressive myeloid populations (e.g., CD163(+)HLA-DR(-) macrophages), and metabolically reprogrammed Tregs. IMC studies uncovered spatial patterns predictive of outcome, such as tertiary lymphoid structures (TLSs) and macrophage-T cell exclusion zones. Several studies proposed predictive immune signatures or integrated CyTOF with transcriptomic or spatial datasets. We identified five recurrent immunobiological motifs, CD8(+) T-cell bifurcation, CD38(+) TAM barriers, TLS maturity, CTLA-4(+) NK-cell signatures and metabolically defined niches, highlighting convergent axes of resistance and response. Bioinformatic pipelines converged around FlowSOM or PhenoGraph clustering, CITRUS or elastic-net feature selection, and increasingly, machine learning and agent-based spatial modelling. Collectively, CyTOF and IMC are redefining biomarker discovery, therapeutic stratification, and virtual trial design in oncology, establishing high-dimensional CyTOF as a cornerstone of next-generation precision cancer medicine.