Co-localization analysis of spatial transcriptomics in ligand-receptor pairs from tumor microenvironment

Ligand-receptor pair analysis, a key aspect of cell-to-cell interactions, is vital for understanding physiological and pathological processes in organisms. However, most analytical tools fail to incorporate spatial in situ information, resulting in false positive predictions. Spatial transcriptomics, which integrates gene expression data with cellular localization, has emerged as a powerful method for inferring cell-cell interactions. Co-localization analysis using spatial transcriptomic data enables the identification of cell candidates with potential interactions, significantly enhancing ligand-receptor pair analysis and improving predictive accuracy. This review explores the data types and computational approaches for co-localization analysis, along with its specific applications in identifying ligand-receptor pairs within the tumor microenvironment, based on a systematic literature search. Additionally, it examines the future prospects of co-localization analysis in the discovery of therapeutic targets and its role in advancing precision medicine. In summary, co-localization analysis aids in uncovering novel ligand-receptor pairs, supports the identification of new disease targets, and contributes to the development of clinical precision medicine, with the integration of artificial intelligence further enhancing analysis accuracy.