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The identification of reliable indicators in the tumor microenvironment (TME) is critical for tumor prognosis. Tumor associated macrophages (TAMs) are the major component of non-tumor stromal cells in TME and have increasingly been recognized as a predictive biomarker for lung adenocarcinoma (LUAD) prognosis. Here, we report the development of a prognosis model for LUAD using three immune-related genes (IRGs) detected in The Cancer Genome Atlas (TCGA) which potentially regulate TAMs in TME. In 497 LUAD patients, higher immune scores conferred better overall survival (OS). We identified 93 hub IRGs out of 234 for further prognostic significance. Among them, three IRGs (BTK, Cd1c, and S100P) were proved to be closely correlated to the prognosis of patients with LUAD. Moreover, the immune risk score (IRS) based on the gene expression level of the three IRGs was an independent prognostic factor for OS. Higher IRS predicted lower OS, higher mortality and worse tumor stage. With a good predictive ability [area under the ROC curve (AUC) in TCGA = 0.701, AUC in GEO = 0.722], the IRS contributed to a good risk stratification ability of the nomogram. Immunologically, the three IRGs were related to M1 macrophages and NK cell subsets in TME. Interestingly, by characterizing these immune components  in situ  we found that S100P is a driver for tumor cells to induce TAM migration and M2 polarization in the immunosuppressive tumor niche. We identified the key genes driving TAM migration and transformation and elucidated the immune landscape of LUAD. The data suggest that IRGs from TME have the potential to become indicators for estimating cancer prognosis and guiding individualized treatment.

Identification of Key Genes Driving Tumor Associated Macrophage Migration and Polarization Based on Immune Fingerprints of Lung Adenocarcinoma