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Heme catabolism by tumor-associated macrophages controls metastasis formation

Abstract

Although the pathological significance of tumor-associated macrophage (TAM) heterogeneity is still poorly understood, TAM reprogramming is viewed as a promising anticancer therapy. Here we show that a distinct subset of TAMs (F4/80hiCD115hiC3aRhiCD88hi), endowed with high rates of heme catabolism by the stress-responsive enzyme heme oxygenase-1 (HO-1), plays a critical role in shaping a prometastatic tumor microenvironment favoring immunosuppression, angiogenesis and epithelial-to-mesenchymal transition. This population originates from F4/80+HO-1+ bone marrow (BM) precursors, accumulates in the blood of tumor bearers and preferentially localizes at the invasive margin through a mechanism dependent on the activation of Nrf2 and coordinated by the NF-κB1–CSF1R–C3aR axis. Inhibition of F4/80+HO-1+ TAM recruitment or myeloid-specific deletion of HO-1 blocks metastasis formation and improves anticancer immunotherapy. Relative expression of HO-1 in peripheral monocyte subsets, as well as in tumor lesions, discriminates survival among metastatic melanoma patients. Overall, these results identify a distinct cancer-induced HO-1+ myeloid subgroup as a new antimetastatic target and prognostic blood marker.

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Fig. 1: Identification of two distinct F4/80hi and F4/80lo TAM subsets in primary and metastatic tumor lesions.
Fig. 2: Distinct effects of F4/80hi and F4/80lo TAMs on metastasis formation and tumor angiogenesis.
Fig. 3: Pathways of F4/80hi TAM accumulation and contribution to tumor development.
Fig. 4: Genomic analysis of HO-1+ TAMs.
Fig. 5: Role of myeloid-specific HO-1 in cancer development.
Fig. 6: Role of CSF1R in HO-1+ TAM differentiation.
Fig. 7: Prognostic significance of myeloid-specific HO-1.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. RNA-seq raw data are reported in Supplementary Table 1 and have been deposited at the Gene Expression Omnibus (GEO accession no. GSE167413). Datasets containing patients’ clinical parameters and flow cytometry data generated during the current study are presented in Supplementary Tables 2 and 3.

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Acknowledgements

This work was supported by Associazione Italiana per la Ricerca sul Cancro (AIRC) IG (nos. 19885 to A.S. and 15860 to R.M.); AIRC 5x1000 no. 22757; Fondazione Cariplo and Ministero Universita Ricerca (project no. 2017BA9LM5_001); AIRC fellowship ‘Pierluigi Meneghelli’ (no. 19682); Associazione “Augusto per la Vita” Novellara (RE); and Associazione “Medicine Rocks”, Milano. We thank C. Vegetti and I. Bersani (Fondazione IRCCS Istituto Nazionale dei Tumori) for excellent technical help with flow cytometry analysis of human monocyte subsets and immunohistochemistry of melanoma lesions, respectively. We also thank M. Soares for critical discussions and editing of the manuscript. M.P.S. is supported by Fundação ‘la Caixa’, Fundação para a Ciência e Tecnologia (nos. HR18-00502 and SAICT/2017/029411).

Author information

Affiliations

Authors

Contributions

F.M.C., M.G.T., A.B. and F.P. played a key role in designing and conducting most of the experiments. M. Storto provided technological support with in vivo experiments. M.F. and L.G. performed genomic analysis of myeloid populations. P.K. and A.T. provided bioinformatics analysis of genomics data. C.A. and C.P. contributed to experiments. M.E. and A.D. performed immunofluorescence analysis on murine samples. R.M., A.A., F.S., G.G. and M.M. performed flow cytometric analysis and/or immunohistochemical analysis of specimens from patients with melanoma. M. Santinami and A.M. assessed clinical condition and provided biological tissues from patients with melanoma. E.R. and V.T. performed statistical and survival analysis in the discovery and confirmation sets stratified by monocyte subset-specific HO-1. M.P.S. contributed by provision of reagents and critical discussions on the experimental results. A.A., F.M.C. and A.S. drafted the manuscript. A.S. provided the guiding hypothesis of the work and contributed to the experimental design and supervision of the study.

Corresponding author

Correspondence to Antonio Sica.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Immunology thanks Daniele Gilkes, Hozumi Motohashi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Zoltan Fehervari was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Role of NF-κB1 in macrophage migration.

a, FACS analysis of C5aR1, and C3aR in WT and p50–/– PECs (∆=variation compared to isotype control), n = 4 mice per genotype; shown are data representative of two independent experiments. b, Boyden-chamber migration assay of WT and p50–/– PECs in response to C3a or C5a; shown are pooled data from n = 2 experiments with n = 3 animals per group. c, Bell-shaped curve migration of WT and p50–/– PECs in response to C3a and C5a, for each condition, cells pooled from n = 3 mice were used; one experiment was performed. d, Phospho-ERK1/2 levels in WT and p50–/– PECs treated with C3a, C5a or LPS, for each condition, cells pooled from n = 3 mice were used; one experiment was performed. e, Chemotactic activity of WT PECs: untreated (M/M); LPS-activated: 20 h medium plus 4 h LPS (M/L); LPS-tolerant: 20 h LPS plus 4 h restimulation with LPS (L/L); medium and C5a: shown are pooled data from n = 2 experiments with n = 3 animals per group, C3a: n = 3 mice were used, one experiment was performed. f, immunoblot analysis of phospho-ERK1/2 in M/M, M/L and L/L PECs in response to C3a or C5a treatment, for each condition, cells pooled from n = 3 mice were used; one experiment was performed. g, Boyden-chamber migration assay of TAMs (CD45+F4/80+CD11b+) FACS-sorted from WT or p50–/– MN/MCA1 tumor-bearing mice. For each condition, cells pooled from n = 3 mice were used; one experiment was performed. Data are mean ± SEM. *P < 0.05 **P < 0.01 ***P < 0.001, ****P < 0.0001 between selected relevant comparisons. In a-g, two-way ANOVA with Sidak’s multiple comparisons test.

Source data

Extended Data Fig. 2 Impact of F4/80hi TAMs accumulation on metastasis formation and tumor angiogenesis.

a, area of metastatic burden quantified from H&E stained lung sections from WT MN-MCA1-bearing mice treated with vehicle or anti-CSF1R is expressed as a percentage of total lung surface area. Representative images are shown. Scale bars, 1 mm. n = 4 (Vehicle) and n = 5 (anti-CSF1R), one experiment was performed. b, FACS quantification of CD31+ cells in lung metastasis of WT MN-MCA1-bearing mice treated with vehicle or anti-CSF1R; n = 5 (Vehicle) and n = 4 (anti-CSF1R), shown are data representative of two independent experiments. c, Representative H&E stained lung sections from WT and C3–/– MN-MCA1-bearing mice and quantification of area of metastatic burden expressed as a percentage of total lung surface area. Scale bars, 1 mm. n = 3 (Vehicle) and n = 5 (C3–/–), one experiment was performed. d, FACS quantification of CD31+ cells in lung metastasis of WT and C3–/– MN-MCA1-bearing mice; n = 5 (Vehicle) and n = 4 (C3–/–), shown are data representative of two independent experiments. e, Representative images of MN/MCA1 tumor sections from WT, C3–/– and anti-CSF1R treated mice injected with FITC-Dextran. Sections were co-stained for FITC-Dextran (green) and CD31 (red) (top left); quantification of vascular permeability expressed as percentage of colocalization rate between extracted signal of CD31+ and FITC+ pixels (bottom left). Representative images of MN/MCA1 tumor sections from WT, C3–/– and anti-CSF1R treated mice costained for collagen IV (green), CD31 (red) and α-SMA (white) (top right); quantification of vessel stability was assessed as colocalization rate of Collagen IV+ or α-SMA+ with CD31+ vessels (bottom right); scale bars, 10 μm; n = 3 mice per genotype, one experiment was performed. Data are mean ± SEM. *P < 0.05 **P < 0.01 ***P < 0.001, ****P < 0.0001 between selected relevant comparisons. In a-d, two-tailed unpaired Student’s t-test. In e, one-way ANOVA and Kruskal-Wallis test with Dunn’s multiple comparisons test.

Extended Data Fig. 3 Impact of F4/80hi HO-1+ TAMs accumulation at the invasive tumor margin on metastasis formation and tumor angiogenesis.

a, (top) Representative confocal microscopy of WT MN/MCA1 tumor sections (a-b: peripheral marginal zone; c: inner area). F4/80 (red), HO-1 (green), nuclei (DAPI, blue). Representative images are shown, scale bars are 10 μm, n = 5 mice, one experiment was performed. (bottom) Expression of HO-1 in WT MN/MCA1 tumor sections (top: inner area; bottom: periphery). Consecutive sections from the same formalin-fixed paraffin-embedded (FFPE) lesion were stained for F4/80 and HO-1. Scale bars are 200 μm, n = 4 mice, one experiment was performed. b, Expression of HO-1 in the neoplastic tissue of a lymph node metastasis from a melanoma patient. The analysis is representative of n = 5 patients, one experiment was performed. Left panels, Consecutive sections from the same FFPE lesion were stained for CD68, CD163 and HO-1. Middle panels, Low magnification images showing cell staining for the three markers. Right panels, Higher magnification images of the indicated areas. Two bottom panels, quantitative analysis of the spatial distribution of HO-1+ cells by QuPath software (HO-1+ cells: red, HO-1 cells: blue). c, area of metastatic burden quantified from H&E stained lung sections from Hmox1fl/fl and Hmox1fl/flLyz2-Cre- bearing mice expressed as a percentage of total lung surface area. Representative images are shown. Scale bars, 1 mm. n = 6 (Hmox1fl/fl) and n = 7 (Hmox1fl/flLyz2-Cre), one experiment was performed. d, FACS quantification of CD31+ cells in lung metastasis of n = 6 Hmox1fl/fl and n = 6 Hmox1fl/flLyz2-Cre MN/MCA1-bearing mice; one experiment was performed. e (top, left), Representative images of MN/MCA1 tumor sections from Hmox1fl/fl and Hmox1fl/flLyz2-Cre mice injected with FITC-Dextran. Sections were co-stained for FITC-Dextran (green) and CD31 (red); (top, right) quantification of vascular permeability; (bottom) Representative images of MN/MCA1 tumor sections from Hmox1fl/fl and Hmox1fl/flLyz2-Cre mice co-stained for collagen IV (green), CD31 (red) and α-SMA (white) and quantification of vessel stability, n = 3 mice per genotype, one experiment was performed. f, FACS quantification of VEGF, HIFα in TAMs subsets and VEGFR in CD31+ cells in tumors (top) and lung metastasis (bottom) of Hmox1fl/fl and Hmox1fl/flLyz2-Cre MN/MCA1-bearing mice; n = 5 mice per genotype (tumor), n = 4 mice per genotype (metastasis), one experiment was performed. Data are mean ± SEM. *P < 0.05 **P < 0.01 ***P < 0.001, ****P < 0.0001 between selected relevant comparisons. In c-d-e(top)-f, two-tailed unpaired Student’s t-test. In e (bottom), two-way ANOVA with Sidak’s multiple comparisons test.

Extended Data Fig. 4 Impact of HO-1 on tumor growth, EMT and LPS-treated macrophages.

a, Expression of EMT-related genes in MN/MCA1 tumor cells FACS-sorted from Hmox1fl/fl and Hmox1fl/flLyz2-Cre mice, shown are pooled data from n = 3 animals per genotype. b, (left) Growth of B16 melanoma in Hmox1fl/fl and Hmox1fl/flLyz2-Cre mice; shown are pooled data from n = 2 independent experiments with n = 5 Hmox1fl/fl and n = 4 Hmox1fl/flLyz2-Cre animals per group; (right) macroscopic appearances of lung metastasis are shown; n = 3 mice per genotype. c, Frequency of TNF+ and CD206+ in TAMs subsets and CD31+ cells; n = 5 (Hmox1fl/fl) and n = 4 (Hmox1fl/flLyz2-Cre) mice. d, Quantification of IFNγ+CD8+ T cells and CD8 : Treg ratio in B16 melanoma grown in Hmox1fl/fl and Hmox1fl/flLyz2-Cre mice, n = 6 (Hmox1fl/fl) and n = 4 (Hmox1fl/flLyz2-Cre) mice. e, Expression of EMT-related genes in B16 tumor cells FACS-sorted from Hmox1fl/fl and Hmox1fl/flLyz2-Cre mice; shown are pooled data from n = 3 animals per genotype. f, WT PECs pre-treated or not with ZnPPIX were analyzed by RT-PCR for the expression of representative M1 and M2 cytokine genes; for each condition, cells pooled from n = 3 mice were used. g-h, PECs from WT or p50–/– mice (g) or Hmox1fl/fl and Hmox1fl/flLyz2-Cre mice (h) pre-treated or not with CORM-2 were analyzed by RT-PCR for the expression of representative M1 and M2 cytokine genes. Results are given as mRNA fold increase over untreated cells (M/M); for each condition, cells pooled from n = 3 mice were used. i, Frequency of F480+Ly6Clow/negSiglecF blood monocytes and relative C5aR1, C3aR and HO-1 expression in LPS-treated WT and p50–/– mice; n = 5 (WT: 0h and 6h), n = 5 (WT: 24h, p50–/–: 0h), n = 4 (p50–/–: 6h and 24h). Data are mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, between selected relevant comparisons. In a, d, e, f, g, h, i, two-tailed unpaired Student’s t-test. In b, c, two-way ANOVA with Sidak’s multiple comparisons test. The data in b (left), c, d, are representative of two independent experiment; in a, b (right), e, f-i one experiment was performed.

Extended Data Fig. 5 Role of p50 NF-κB, CSF1R and C3aR in the generation of HO-1+ myeloid cells.

a, FACS quantification of Nrf2 expression by F4/80hi and F4/80lo TAMs in WT MN/MCA1 tumors (left), n = 4 mice; Nrf2 and HO-1 expression by F4/80hi in WT, C3–/–, p50–/– and anti-CSF1R treated MN/MCA1-bearing mice (middle, right), n = 4 (WT, p50–/–) and n = 3 (C3–/–, anti-CSF1R) mice per group. b, CD115 expression of TAMs subsets in WT, C3–/– and p50–/– MN/MCA1-bearing mice, n = 4 (WT, p50–/–) and n = 3 (C3–/–, anti-CSF1R) mice. c, FACS analysis of Nrf2, HO-1 and CD115 expression in WT and p50–/– PECs stimulated or not with C3 (∆=variation compared to isotype control), for each condition, cells were pooled from n = 4 mice. d, FACS analysis of Nrf2, HO-1 and C3aR expression in WT, p50–/– and C3–/– PECs stimulated or not with M-CSF, for each condition, cells pooled from n = 4 mice were used. e, FACS analysis of Nrf2 and HO-1 expression in WT and Nfe2l2–/– BM-DMs stimulated or not with M-CSF and C3; for each condition, cells were pooled from n = 4 mice. f, (top) macroscopic lung metastasis quantification in WT, anti-CSF1R, C3–/, p50–/– (left) and in Hmox1fl/fl and Hmox1fl/flLyz2-Cre MN/MCA1 tumor-bearing mice (right), treated or not with Brusatol. (bottom) area of metastatic burden was quantified in H&E stained lung sections from WT MN-MCA1-bearing mice treated with vehicle or Brusatol and is expressed as a percentage of total lung surface area. Representative images are shown. Scale bars, 1 mm. g, (top) FACS quantification of F4/80hi and F4/80lo TAMs and relative HO-1 expression levels in WT, anti-CSF1R, C3–/–, p50–/– MN/MCA1 tumor bearing mice, treated with brusatol; (bottom) percentage of LSK, LK, CMPs, MEPs and GMPs and relative HO-1 expression in the BM of untreated and brusatol-treated MN-MCA1-bearing WT mice. Data are mean ± SEM. *P < 0.05 **P < 0.01 ***P < 0.001, between selected relevant comparisons. In a one-way ANOVA or two-tailed unpaired Student’s t-test. In b–g, two-way ANOVA with Sidak’s multiple comparisons test. In a-g, one experiment was performed.

Extended Data Fig. 6 Effects of HO-1 antagonist (ZnPPIX) on immune infiltrate and tumor growth.

a, Mean ±- SEM tumor volume of B16 implants in WT mice treated with vehicle or ZnPPIX; n = 5 mice per group. b, FACS quantification of TNF and CD206 expression in F4/80hi and F4/80lo TAMs subsets; n = 6 mice per group. c, Quantification of IFNγ expression in B16 tumor-infiltrating CD8+ T lymphocytes and CD8 : Treg ratio in vehicle- and ZnPPIX-treated mice; n = 5 mice per group. d, TAMs purified from MN/MCA1 tumors growing in WT mice treated or not with ZnPPIX were analyzed by RT-PCR for the expression of representative M1 and M2 cytokine genes; shown are pooled data from n = 2 technical replicates from n = 4 mice. e, FACS quantification of HO-1 expression in F4/80hi and F4/80lo TAMs subsets and in MN/MCA1 (left, n = 5 mice) or B16 tumor cells (right, n = 3 mice) in WT mice. f, (left) Mean ± SEM tumor volume of subcutaneous B16 implants in n = 5 Hmox1fl/fl and n = 5 Hmox1fl/flLyz2-Cre treated with vehicle or ZnPPIX; (right) proliferation rates of B16 and MN/MCA1 cells in primary tumors and lung metastasis of mice treated with vehicle or ZnPPIX; B16: n = 5 (vehicle), n = 4 (ZnPPIX); MN/MCA1: n = 4 (tumor) and n = 3 (metastasis). g, Representative images of K1735-M2 lung metastasis and quantification of K1735M2 melanoma cells in C3HN mice treated or not with ZnPPIX; n = 7 (Vehicle) and n = 6 (ZnPPIX). h TAMs purified from MN/MCA1 tumors growing in WT mice treated or not with CORM-2 were analyzed by FACS for pSTAT1, pSTAT3, pSTAT6 expression (top, n = 3 mice) and by RT-PCR for the expression of representative M1 and M2 cytokine genes (bottom, n = 4 mice), i, FACS quantification of CD31+ cells, E-cadherin+, N-cadherin+ and Vimentin+ mCherry+ MN/MCA1 cells in primary tumors of T lymphocyte-depleted MN-MCA1-bearing WT mice, treated or not with ZnPPIX, n = 5 (Vehicle and ZnPPIX) and n = 4 (anti-CD4/CD8+ZnPPIX). j, Mean ± SEM tumor volume and size of B16 tumors growing in WT mice treated with Vehicle, anti-PD-1 antibody, ZnPPIX, or anti-PD-1 antibody plus ZnPPIX are shown, n = 2 (Vehicle), n = 3 (anti-PD-1 and ZnPPIX) and n = 4 (anti-PD-1+ZnPPIX). Data are mean ± SEM. *P < 0.05 **P < 0.01 ***P < 0.001, between selected relevant comparisons. In a, b, f, j, two-way ANOVA with Sidak’s multiple comparisons test. In c, d, f, g, h, two-tailed unpaired Student’s t-test or Mann–Whitney U-test. In e, i one-way ANOVA and Kruskal-Wallis test with Dunn’s multiple comparisons test. The data in a–c, are representative of two independent experiment; in dj one experiment was performed.

Extended Data Fig. 7 Gating strategy for the assessment of HO-1 in peripheral blood monocyte subsets.

a, Monocytes from peripheral blood samples were identified as CD45+ CD3 CD19 CD56 cells after doublet exclusion, live cell selection and FS-A vs. SS-A gating (upper set of dot plots). Intracellular HO-1 expression (geometric mean fluorescence intensity, gMFI) detected in permeabilized cells was then recorded in 15 monocyte subsets (R1 to R3 and R1R5 to R3R8) defined by differential expression of CD14, CD16, CD88 and Tie-2. b, Median HO-1 gMFI values for each of the 15 monocyte subsets observed in peripheral blood samples from the discovery, confirmation and combined sets (discovery + confirmation). c, Expression of HO-1 (gMFI) in main monocyte subsets in peripheral blood samples from the discovery (n = 47) and confirmation (n = 45) sets of AJCC stage IIIC and IV melanoma patients. Statistical analysis of the combined set (discovery+confirmation cohorts) gMFI HO-1 values by Kruskal Wallis test followed by Dunn’s multiple comparisons test. ns= not significant; *: P < 0.05; **: P < 0.01; ****: P < 0.0001.

Extended Data Fig. 8 Stratification of melanoma patients’ survival based on the subset-specific median HO-1.

a, Schematic of the gating strategy to identify twelve monocyte subsets (R1R5 to R3R8) in the peripheral blood of melanoma patients, based on differential expression of CD14, CD16, CD88 and Tie-2. b, Kaplan Meyer survival analysis in discovery and confirmation sets stratified by HO-1 gMFI higher or lower than the combined set median value observed in each monocyte subset.

Extended Data Fig. 9 Prognostic significance of myeloid-specific HO-1.

a, expression of CD163 and HO-1 in metastatic lesions of AJCC Stage III melanoma patients. Consecutive sections from lesions (LN=lymph node; s.c.: subcutaneous) of 10 patients were stained for CD163 and HO-1. Wide field images and higher magnification insets are shown centered on the same area of the tumor tissue for both markers. Lesions from patients #1 to #8 (short survival) show expression of both CD163 and HO-1 in the same areas of the tumor tissue. Lesions from patients #11 to #15 (long survival) show lack of both CD163 and HO-1 expression. For each patient, survival was computed from the date of surgery for removal of metastatic lesions. Status: DOD: dead of disease, NED: no evidence of disease. b, results of multivariable Cox proportional hazard model on TCGA skin cutaneous melanoma dataset (n = 471) were obtained through the outcome module of TIMER2.0 web server, by testing the relevance of tumor infiltrating macrophages, as identified by the M2_TIDE macrophage signature52, and of the expression of macrophage-related genes CD163, HO-1 and CD68. Tumor stage was included as clinical covariate.

Supplementary information

Supplementary Information

Supplementary Fig. 1 and Tables 2 and 3.

Reporting Summary

Supplementary Table 1

Differential gene expression analysis between F4/80hi and F4/80lo TAMs and PECs. A probe was considered significantly differentially expressed if it had an absolute fold change ≥1.5 and adjusted P ≤ 0.05. Expression profiling data are available at Gene Expression Omnibus (GEO) with accession no. GSE167413.

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Unprocessed western blots.

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Consonni, F.M., Bleve, A., Totaro, M.G. et al. Heme catabolism by tumor-associated macrophages controls metastasis formation. Nat Immunol 22, 595–606 (2021). https://doi.org/10.1038/s41590-021-00921-5

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