Redefining Tumor-Associated Macrophage Subpopulations and Functions in the Tumor Microenvironment

Abstract

The immunosuppressive status of the tumor microenvironment (TME) remains poorly defined due to a lack of understanding regarding the function of tumor-associated macrophages (TAMs), which are abundant in the TME. TAMs are crucial drivers of tumor progression, metastasis, and resistance to therapy. Intra- and inter-tumoral spatial heterogeneities are potential keys to understanding the relationships between subpopulations of TAMs and their functions. Antitumor M1-like and pro-tumor M2-like TAMs coexist within tumors, and the opposing effects of these M1/M2 subpopulations on tumors directly impact current strategies to improve antitumor immune responses. Recent studies have found significant differences among monocytes or macrophages from distinct tumors, and other investigations have explored the existence of diverse TAM subsets at the molecular level. In this review, we discuss emerging evidence highlighting the redefinition of TAM subpopulations and functions in the TME and the possibility of separating macrophage subsets with distinct functions into antitumor M1-like and pro-tumor M2-like TAMs during the development of tumors. Such redefinition may relate to the differential cellular origin and monocyte and macrophage plasticity or heterogeneity of TAMs, which all potentially impact macrophage biomarkers and our understanding of how the phenotypes of TAMs are dictated by their ontogeny, activation status, and localization. Therefore, the detailed landscape of TAMs must be deciphered with the integration of new technologies, such as multiplexed immunohistochemistry (mIHC), mass cytometry by time-of-flight (CyTOF), single-cell RNA-seq (scRNA-seq), spatial transcriptomics, and systems biology approaches, for analyses of the TME.

Keywords: multiplexed immunohistochemical staining; single-cell sequencing; spatial transcriptomics; tumor microenvironment; tumor-associated macrophages.

Figure 1

The polarization of TAMs and their characteristics. The figure displays a general principle of polarized M1-like and M2-like phenotypes. M1-like and M2-like phenotypes represent two extremes of TAM polarization and display distinct functions. In response to different stimuli in the TME, TAMs undergo M1-like, or M2-like activation. M1-like TAMs are stimulated by IFN-γ, TGF-α, or GM-CSF, express CD68, CD80, and CD86, secrete IL-1β, IL-6, IL-12, IL-23, CXCL9, and CXCL10, and exert anti-tumor effects. In contrast, M2-like TAMs are activated by IL-10 or TGF-β, express CD163, CD204, and CD206, secrete IL-10, TNF, CCL17, CCL18, CCL22, and CCL24 and promote tumor progression.

Figure 2

Integrated strategies to redefine the classification of TAMs. High-dimensional analysis of TAMs supported by CyTOF and scRNA-seq, along with bioinformatic approaches (including dimension reduction tools and cluster analysis), provides an overview of surface protein and gene expression, thus contributing to the identification of TAM subsets at the proteomic and transcriptomic levels. Clusters of interest can then be selected depending on either different compositions or distinct functions among identified TAM subpopulations, which are associated with their histopathological characteristics in tissue samples and clinical significance confirmed by survival analysis. By combining bulk RNA-seq data obtained from TCGA and tumor-specific transcriptomic programme, the heterogeneity of TAMs can be further analyzed to provide evidence for the selection of suitable TAM markers. Based on these markers, the spatial distribution in the TME obtained by mIHC and spatial transcriptomics facilitate subsequent generation of the complete landscape in tumor tissues and deconvolution of cell-state relationships, benefiting a deeper understanding of the associations between the functions and phenotypes of TAMs. The integrated use of these technologies strongly reveals the inter- and intra-tumoral heterogeneity of TAMs, potentially redefining TAMs with valuable biomarkers.