The CXCL9/SPP1 polarity axis in tumor-associated macrophages: immunoregulatory and prognostic significance in non-small cell lung cancer

This study addresses the limitations of the traditional M1/M2 binary classification for tumor-associated macrophages (TAMs) in non-small cell lung cancer (NSCLC) by introducing a NSCLC-specific functional framework based on the CXCL9/SPP1 (CS) expression ratio. Through the integration of single-cell and bulk transcriptomic data, the research identified four distinct TAM subpopulations. Among these, the CXCL9 + SPP1 − subpopulation exhibited macrophages with anti-tumor features, whereas the CXCL9 − SPP1 + subpopulation showed macrophages with pro-tumor features. A robust CS-polarity-associated tumor microenvironment (TME) six-gene signature was constructed and validated using extensive machine-learning optimization. This model effectively stratified NSCLC patients into high-risk and low-risk groups, with high-risk patients displaying an immunosuppressive TME enriched in M0/M2 macrophages. The study further demonstrated the dynamic plasticity of TAM polarity through pseudotime trajectory analysis and validated key gene expression. For the first time, this study introduces the CXCL9/SPP1 polarity axis into the field of non-small cell lung cancer (NSCLC). By integrating single-cell trajectory analysis, we reveal the dynamic differentiation patterns of TAM polarity in NSCLC. Furthermore, utilizing a combination of 101 machine learning algorithms, we constructed the first six-gene prognostic model based on this polarity axis, achieving precise risk stratification for NSCLC patients and enabling correlative analysis of the immune status within the tumor microenvironment.