Macrophage diversity in cancer revisited in the era of single-cell omics

TAMs have diverse functions in cancer, reflecting the heterogenous nature of these immune cells. Here, we propose a new nomenclature to identify TAM subsets.Recent single cell multi-omics technologies, which allow the clustering of TAM subsets in an unbiased manner, have significantly advanced our understanding of the molecular diversity of TAMs in mice and humans.Novel mechanisms and potential therapeutic targets have been identified that might regulate the tumor-promoting function of different TAM subsets.TAM diversity opens promising therapeutic opportunities for envisaging putative cancer treatments. Tumor-associated macrophages (TAMs) have multiple potent functions in cancer and, thus, represent important therapeutic targets. These diverse functions highlight the heterogenous nature of TAMs. Recent single cell omics technologies have significantly advanced our understanding of the molecular diversity of TAMs. However, a unifying nomenclature of TAM diversity and annotation of their molecular signatures is lacking. Here, we review recent major studies of single cell transcriptome, epigenome, metabolome, and spatial omics of cancer with a specific focus on TAMs. We also propose a consensus model of TAM diversity and present avenues for future research. Tumor-associated macrophages (TAMs) have multiple potent functions in cancer and, thus, represent important therapeutic targets. These diverse functions highlight the heterogenous nature of TAMs. Recent single cell omics technologies have significantly advanced our understanding of the molecular diversity of TAMs. However, a unifying nomenclature of TAM diversity and annotation of their molecular signatures is lacking. Here, we review recent major studies of single cell transcriptome, epigenome, metabolome, and spatial omics of cancer with a specific focus on TAMs. We also propose a consensus model of TAM diversity and present avenues for future research. TAMs represent one of the most abundant immune cell types in tumors [1.Cassetta L. Pollard J.W. Targeting macrophages: therapeutic approaches in cancer.Nat. Rev. Drug Discov. 2018; 17: 887-904Crossref PubMed Scopus (650) Google Scholar]. Since our initial review a decade ago [2.Qian B.Z. Pollard J.W. Macrophage diversity enhances tumor progression and metastasis.Cell. 2010; 141: 39-51Abstract Full Text Full Text PDF PubMed Scopus (3151) Google Scholar], the functional diversity of TAMs is now widely appreciated, with many seminal studies in the field [3.Yang M. et al.Diverse functions of macrophages in different tumor microenvironments.Cancer Res. 2018; 78: 5492-5503Crossref PubMed Scopus (202) Google Scholar, 4.DeNardo D.G. Ruffell B. 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With the wide application of single cell technologies, recent years have seen an explosion of data illustrating cellular heterogeneity in cancer, resulting in an unprecedented amount of information on the molecular diversity of TAMs, regardless of the main focus of these studies. Links between TAM molecular diversity and functional diversity are emerging. However, a consensus terminology of TAM subsets is lacking, making direct comparisons of different studies and full utilization of the data sets difficult. In this review, we summarize recent single cell studies with a focus on human data; we include traditional nomenclatures, TAM diversity at the levels of single-cell transcriptomic, epigenomic, metabolic and spatial multi-omics, therapeutic opportunities, and future directions. We also propose a new consensus model of TAM subsets. We hope that this model will serve as a starting point for the field that can help build a complete picture of the heterogenous and dynamic interactions between TAM subsets and the tumor, as well as with the tumor microenvironment (TME). A widely used terminology to describe macrophage diversity has been the now-obsolete M1/M2 model, proposed ~20 years ago; it separated macrophages into two distinct arms: M1 or ‘classically’ activated; and M2 or ‘alternatively’ activated, largely based on in vitro data stimulating macrophages with type 1 or 2 cytokines [8.Mills C.D. et al.M-1/M-2 Macrophages and the Th1/Th2 paradigm.J. Immunol. 2000; 164: 6166-6173Crossref PubMed Google Scholar]. The newer term ‘M1-like’ phenotype is typically described as proinflammatory and is induced by Toll-like receptor (TLR) ligands and type 1 cytokines, namely IFN-γ and TNF-α. Conversely, ‘M2-like’ macrophages are described as having anti-inflammatory characteristics, being activated by interleukin (IL)-4 or IL-13, and producing TGF-β and other profibrotic factors. This nomenclature, albeit widely used, remains oversimplified [9.Martinez F.O. Gordon S. The M1 and M2 paradigm of macrophage activation: time for reassessment.F1000Prime Rep. 2014; 6: 13Crossref PubMed Scopus (2673) Google Scholar,10.Nahrendorf M. Swirski F.K. Abandoning M1/M2 for a network model of macrophage function.Circ. Res. 2016; 119: 414-417Crossref PubMed Scopus (195) Google Scholar]. Indeed, significant diversity in morphology, function, and cell surface marker expression has been observed in resident-tissue macrophages (RTMs) from different organs [11.Bleriot C. et al.Determinants of resident tissue macrophage identity and function.Immunity. 2020; 52: 957-970Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar]; moreover, co-expression of both M1 and M2 gene signatures have been identified in macrophage subsets from almost all cancer types [12.Mulder K. et al.Cross-tissue single-cell landscape of human monocytes and macrophages in health and disease.Immunity. 2021; 54: 1883-1900Abstract Full Text Full Text PDF PubMed Google Scholar]. Therefore, a functional spectrum model of macrophage polarization that relates phenotype to function represents a more sensible approach to describing macrophage subsets [10.Nahrendorf M. Swirski F.K. Abandoning M1/M2 for a network model of macrophage function.Circ. 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Using lineage-tracing approaches in mice, studies have illustrated that human and mouse RTMs are derived from early erythromyeloid progenitors formed in either the yolk sac or the fetal liver [15.Geissmann F. et al.Blood monocytes consist of two principal subsets with distinct migratory properties.Immunity. 2003; 19: 71-82Abstract Full Text Full Text PDF PubMed Scopus (2514) Google Scholar,16.Gomez Perdiguero E. et al.Tissue-resident macrophages originate from yolk-sac-derived erythro-myeloid progenitors.Nature. 2015; 518: 547-551Crossref PubMed Scopus (1236) Google Scholar]. Additionally, adult RTMs may also derive from circulating monocytic precursors (monocytes) formed in the mouse bone marrow [17.Cox N. et al.Origins, biology, and diseases of tissue macrophages.Annu. Rev. Immunol. 2021; 39: 313-344Crossref PubMed Scopus (1) Google Scholar]. This monocyte contribution varies among different organs. For example, in steady state, microglia in the central nervous system (CNS) are derived solely from mouse yolk sac progenitors [18.Hoeffel G. et al.C-Myb(+) erythro-myeloid progenitor-derived fetal monocytes give rise to adult tissue-resident macrophages.Immunity. 2015; 42: 665-678Abstract Full Text Full Text PDF PubMed Scopus (611) Google Scholar], while subsets of dermal macrophages are of embryonic or monocyte origin [19.Kolter J. et al.A subset of skin macrophages contributes to the surveillance and regeneration of local nerves.Immunity. 2019; 50: 1482-1497Abstract Full Text Full Text PDF PubMed Scopus (69) Google Scholar]. The functional diversity of TAMs is widely appreciated and has been repeatedly reviewed [20.Pathria P. et al.Targeting tumor-associated macrophages in cancer.Trends Immunol. 2019; 40: 310-327Abstract Full Text Full Text PDF PubMed Scopus (382) Google Scholar,21.Guerriero J.L. Macrophages: the road less traveled, changing anticancer therapy.Trends Mol. Med. 2018; 24: 472-489Abstract Full Text Full Text PDF PubMed Scopus (143) Google Scholar]. Similar to their normal counterparts [11.Bleriot C. et al.Determinants of resident tissue macrophage identity and function.Immunity. 2020; 52: 957-970Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar], TAM functional diversity is regulated by not only its ontogeny, but also local cues, including cancer type, organ, and subanatomic microenvironment [1.Cassetta L. Pollard J.W. Targeting macrophages: therapeutic approaches in cancer.Nat. Rev. Drug Discov. 2018; 17: 887-904Crossref PubMed Scopus (650) Google Scholar]. Identifying the molecular basis of this functional diversity has been the focus of the field over the past decade [5.Lopez-Yrigoyen M. et al.Macrophage targeting in cancer.Ann. N. Y. Acad. Sci. 2021; 1499: 18-41Crossref PubMed Scopus (25) Google Scholar]. Recent advancements in single cell omics technologies are unveiling the multidimensional complexity of TAM diversity in an unbiased manner. This is important for not only the field of macrophage research, but also the field of immune oncology to eventually fully understand the complexity of these potent immune cells in cancer, and hopefully use this information to improve precision diagnosis and therapy. Single cell RNA sequencing (scRNA-seq) technology has revolutionized our understanding of cellular heterogeneity by providing in-depth transcriptome information at the single cell level [22.Giladi A. et al.Single-cell characterization of haematopoietic progenitors and their trajectories in homeostasis and perturbed haematopoiesis.Nat. Cell Biol. 2018; 20: 836-846Crossref PubMed Scopus (139) Google Scholar]. With substantial advances in available experimental techniques and bioinformatics pipelines in recent years, scRNA-seq has been widely used to investigate cellular heterogeneity in almost all cancer types [23.Lawson D.A. et al.Tumour heterogeneity and metastasis at single-cell resolution.Nat. Cell Biol. 2018; 20: 1349-1360Crossref PubMed Scopus (230) Google Scholar,24.Ren X. et al.Insights gained from single-cell analysis of immune cells in the tumor microenvironment.Annu. Rev. Immunol. 2021; 39: 583-609Crossref PubMed Scopus (15) Google Scholar]. These studies identified significant transcriptomic diversity in TAMs. However, a unifying nomenclature of TAM diversity and annotation of their molecular signatures remain lacking. Two recent large-scale pan-cancer scRNA-seq studies provided valuable information regarding TAM diversity. One study analyzed scRNA-seq data of myeloid cells in 380 samples across 15 cancer types from 210 patients through the combination of newly collected data with eight published data sets [25.Cheng S. et al.A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells.Cell. 2021; 184: 792-809Abstract Full Text Full Text PDF PubMed Scopus (111) Google Scholar]. Comparison of the monocytes and macrophages across multiple cancer types identified the consistent presence of two subsets of CD14+ and CD16+ tumor-infiltrating monocytes (TIMs), a subset of LYVE1+ interstitial macrophages in non-cancer tissues, and seven subsets of TAM clusters: INHBA+ TAMs, C1QC+ TAMs, ISG15+ TAMs, LNRP3+ TAMs, LYVE1+ TAMs, and SPP1+ TAMs. Another study compiled human mononuclear phagocytes (MNPs) isolated from 41 data sets from 13 tissue types, including TAMs of six cancer types, into a common universe, termed the MNP-VERSE. Monocyte and macrophage clusters were then extracted and reintegrated to generate a MoMac-VERSEi. Using single cell regulatory network inference and clustering (SCENIC) analysis [26.Aibar S. et al.SCENIC: single-cell regulatory network inference and clustering.Nat. Methods. 2017; 14: 1083-1086Crossref PubMed Scopus (1003) Google Scholar], the authors identified the presence of classical monocytes, nonclassical monocytes, and five TAM subsets (HES1 TAM, C1Qhi TAM, TREM2 TAM, IL4I1 TAM, and proliferating TAMs) across multiple cancer types [12.Mulder K. et al.Cross-tissue single-cell landscape of human monocytes and macrophages in health and disease.Immunity. 2021; 54: 1883-1900Abstract Full Text Full Text PDF PubMed Google Scholar]. Although different nomenclatures were used in these two studies, and many others, a consensus pattern of TAM transcriptomics diversity is emerging. By reviewing recent scRNA-seq cancer studies from major journals, we found that seven TAM subsets were preserved in almost all cancer types (Table 1). Based on their signature genes, enriched pathways, and predicated function, we propose naming these TAM subsets as interferon-primed TAMs (IFN-TAMs), immune regulatory TAMs (Reg-TAMs), inflammatory cytokine-enriched TAMs (Inflam-TAMs), lipid-associated TAMs (LA-TAMs), pro-angiogenic TAMs (Angio-TAMs), RTM-like TAMs (RTM-TAMs), and proliferating TAMs (Prolif-TAMs) (Table 1 and Figure 1, Key figure). Furthermore, three subsets of TIMs were observed in multiple cancer types (Table 1 and Box 1).Table 1Mouse and human macrophage and monocyte subsets in various TMEsaBlack font: signature genes of TAM clusters; blue font: protein markers of TAM clusters; Underline: protein markers by CITE-seq; Bold: key genes reported in more than one paper., bAbbreviations: BRCA, breast cancer; CAF, cancer-associated macrophage; CITE-seq, cellular indexing of transcriptomes and epitopes by sequencing; CRC, colorectal cancer; CyTOF, Mass cytometry time of flight; ECM, extracellular matrix; ESCA, esophageal carcinoma; GC, gastric cancer; HCC, hepatocellular carcinoma; HNC, head and neck cancer; i.v., intravenous; IF, immunofluorescent staining; INs-seq, intracellular staining and sequencing; LCM, laser capture microdissection; LYM, lymphoma; MEL, melanoma; Mets, metastasis; mIHC, multiplex immunochemistry staining; MMY, multiple myeloma; N/A, not available; NPC, nasopharyngeal carcinoma; NSCLC, nonsmall cell lung cancer; OS, osteosarcoma; OVC, ovarian cancer; PDAC, pancreatic ductal adenocarcinoma; PRAC, prostate cancer; RCC, renal cancer; Reg-TAMs, immune regulatory TAMs; SARC, sarcoma; sc-MS, single-cell mass spectrometry; SEPN, spinal ependymomas; SKC, skin cancer; ST, spatial transcriptomics; s.c., subcutaneous; TAMs, tumor-associated macrophages; THCA, thyroid carcinoma; UCEC, uterine corpus endometrial carcinoma.AnnotationSpeciesSignatureTFCancer typeFunction/enriched pathwayAssayRefsIFN-TAMsHumanCASP1, CASP4, CCL2/3/4/7/8, CD274hi, CD40, CXCL2/3/9/10/11, IDO1, IFI6, IFIT1/2/3, IFITM1/3, IRF1, IRF7, ISG15, LAMP3, PDCD1LG2hi, TNFSF10, C1QA/C, CD38, IL4I1, ISG15, TNFSF10, IFI44LSTAT1 IRF1/7BRCACRCCRC liver metsGBMHCCHNCLYMMELMMYNPCNSCLCOSPDACSEPNTHCAUCECApoptosis regulatorsEnhance tumor proliferationInflammatory responsesPromote Treg entry into tumorT cell exhaustionImmunosuppressionColocalization with exhausted T cells (ST, IF)Decreased antigen presentation (CyTOF)Suppressed T cell activation (in vitro)IFN-α/γ-IFN response signature; IL2/STAT5; IL6/JAK/STAT3scRNA-seqCITE-seqmIHCSTNanoString GeoMx[12.Mulder K. et al.Cross-tissue single-cell landscape of human monocytes and macrophages in health and disease.Immunity. 2021; 54: 1883-1900Abstract Full Text Full Text PDF PubMed Google Scholar,29.Gubin M.M. et al.High-dimensional analysis delineates myeloid and lymphoid compartment remodeling during successful immune-checkpoint cancer therapy.Cell. 2018; 175: 1014-1030Abstract Full Text Full Text PDF PubMed Scopus (165) Google Scholar,32.Zavidij O. et al.Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma.Nat. 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CRCCT26 intrasplenic liver mets modelT3 SARC (s.c.)Orthotopic GL261 GBMIFN response signaturescRNA-seqCITE-seqmIHC[29.Gubin M.M. et al.High-dimensional analysis delineates myeloid and lymphoid compartment remodeling during successful immune-checkpoint cancer therapy.Cell. 2018; 175: 1014-1030Abstract Full Text Full Text PDF PubMed Scopus (165) Google Scholar,45.Wu Y. et al.Spatiotemporal immune landscape of colorectal cancer liver metastasis at single-cell level.Cancer Discov. 2021; 12: 134-153Crossref PubMed Scopus (10) Google Scholar,52.Pombo Antunes A.R. et al.Single-cell profiling of myeloid cells in glioblastoma across species and disease stage reveals macrophage competition and specialization.Nat. Neurosci. 2021; 24: 595-610Crossref PubMed Scopus (78) Google Scholar]Inflam-TAMsHumanCCL2/3/4/5/20, CCL3L1, CCL3L3, CCL4L2, CCL4L4, CXCL1/2/3/5/8, G0S2, IL1B, IL1RN, IL6, INHBA, KLF2/6, NEDD9, PMAIP1, S100A8/A9, SPP1EGR3 IKZF1 NFKB1 NFE2L2 RELCRCCRC liver metsOSSEPNGCRecruiting and regulating immune cellsCNS inflammation-associated chemokinesPromotes inflammationNeutrophil recruitment in tumor lumenT cell interaction (IHC)TNF signaling; WNTImmune check pointsscRNA-seqmIHCNanoString GeoMx[31.Che L.-H. et al.A single-cell atlas of liver metastases of colorectal cancer reveals reprogramming of the tumor microenvironment in response to preoperative chemotherapy.Cell Discovery. 2021; 7: 80Crossref PubMed Scopus (4) Google Scholar,33.Zhou Y. et al.Single-cell RNA landscape of intratumoral heterogeneity and immunosuppressive microenvironment in advanced osteosarcoma.Nat. 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Neurosci. 2021; 24: 595-610Crossref PubMed Scopus (78) Google Scholar]Angio-TAMsHumanADAM8, AREG, BNIP3, CCL2/4/20, CD163, CD300E, CD44, CD55, CEBPB, CLEC5A, CTSB, EREG, FCN1, FLT1, FN1, HES1, IL1B, IL1RN, IL8, MAF, MIF, NR1H3, OLR1, PPARG, S100A8/9/12, SERPINB2, SLC2A1, SPIC, SPP1, THBS1, TIMP1, VCAN, VEGFABACH1 CEBPB FOSL2 HIFA KLF5 MAF NFKB1 NR1H3 RUNX1 SPIC TEAD1 ZEB2BRCACRCCRCCRC liver metsESCAGBMGCHCCMELNPCNPCNSCLCOVCPDACPDAC liver metsRCCSEPNTHCAUCECAngiogenesisCAF interactionECM proteolysis; ECM receptor interactionPromotion of tumor cell EMTHIF pathway; NF-kB signaling; Notch signaling; VEGF signalingJuxtaposed to PLVAP+/DLL4+ endothelial cells (IF)scRNA-seqSMART-seq2CITE-seqNanoString GeoMx[25.Cheng S. et al.A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells.Cell. 2021; 184: 792-809Abstract Full Text Full Text PDF PubMed Scopus (111) Google Scholar,27.Zilionis R. et al.Single-cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species.Immunity. 2019; 50: 1317-1334Abstract Full Text Full Text PDF PubMed Scopus (424) Google Scholar,28.Yang Q. et al.Single-cell RNA sequencing reveals the heterogeneity of tumor-associated macrophage in non-small cell lung cancer and differences between sexes.Front. 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