Abstract
BACKGROUND: Colorectal cancer (CRC) represents the third most prevalent malignancy worldwide and accounts for the second-highest cancer-related mortality rate. Accumulating evidence over the past decade has established the pivotal role of tumor-associated macrophages (TAMs) in CRC tumorigenesis and disease progression. This study employs bibliometric analysis to delineate the research landscape and emerging frontiers in CRC TAMs investigation. METHODS: We systematically retrieved publications indexed in the Web of Science Core Collection from database inception through 14 April 2025, applying predefined inclusion and exclusion criteria. Using VOSviewer and CiteSpace, we conducted comprehensive visual analyses of the CRC TAMs research domain, including country contributions, institutional productivity, annual publication trends, and journal distributions. RESULTS: Our bibliometric analysis identified 2861 publications on CRC TAMs worldwide, with a consistent upward publication trend since 2018. Geospatial analysis revealed that China and the United States are the predominant contributing nations, with Sun Yat-sen University being the most productive institution. Keyword co-occurrence mapping identified five predominant research clusters: CRC biology, TAMs characterization, patient survival outcomes, disease progression mechanisms, and metastatic processes. Four key research directions emerged: (1) single-cell RNA sequencing for TAMs heterogeneity analysis, (2) PD-1/PD-L1 checkpoint interactions with TAMs, (3) molecular mechanisms underlying macrophage polarization, and (4) chemotherapeutic modulation of TAMs functionality (particularly irinotecan). These advances provide mechanistic insights into CRC TAMs biology and may facilitate (1) the discovery of novel diagnostic biomarkers, (2) precision therapeutic strategies, and (3) personalized prognostic frameworks. CONCLUSION: Bibliometric analysis has highlighted the global landscape of research on CRC TAMs. Future research directions in CRC TAMs are likely to center on the integration of multi-omics, in-depth investigation of the tumor microenvironment, targeting TAMs, application of machine learning and artificial intelligence, and the development of personalized treatment strategies for CRC.