Estimating tumour immune infiltration: methodological convergence across histology and spatial technologies.

Abstract

Estimating tumour immune infiltration is critical for understanding cancer biology and predicting patient response to surgery and immunotherapy. A wide array of experimental platforms supports various computational approaches for quantifying tumour-infiltrating lymphocytes and immune infiltration level within the tumour microenvironment, including traditional histopathology, immunohistochemistry, AI-based digital pathology, bulk RNA sequencing, and spatial omics now. Although numerous technologies are available to quantify immune infiltration, important questions remain about which approaches are most suitable and how best to guide platform and methodological choices. In this review, we provide a comprehensive overview of how each platform estimates tumour immune profile coupled with their corresponding computational approaches, followed by a comparative discussion on technological resolution, cell-type specificity, spatial context, and clinical interpretability. We also discuss emerging trends in multimodal data integration, including mapping-based and fusion-based strategies. Together, our review underscores both the methodological opportunities and the translational potential of diverse immune infiltration estimation strategies, guiding the design of more actionable immune profiling strategies.