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Oncogenic mTOR signalling recruits myeloid-derived suppressor cells to promote tumour initiation

An Erratum to this article was published on 28 June 2016

This article has been updated

Abstract

Myeloid-derived suppressor cells (MDSCs) play critical roles in primary and metastatic cancer progression. MDSC regulation is widely variable even among patients harbouring the same type of malignancy, and the mechanisms governing such heterogeneity are largely unknown. Here, integrating human tumour genomics and syngeneic mammary tumour models, we demonstrate that mTOR signalling in cancer cells dictates a mammary tumour’s ability to stimulate MDSC accumulation through regulating G-CSF. Inhibiting this pathway or its activators (for example, FGFR) impairs tumour progression, which is partially rescued by restoring MDSCs or G-CSF. Tumour-initiating cells (TICs) exhibit elevated G-CSF. MDSCs reciprocally increase TIC frequency through activating Notch in tumour cells, forming a feedforward loop. Analyses of primary breast cancers and patient-derived xenografts corroborate these mechanisms in patients. These findings establish a non-canonical oncogenic role of mTOR signalling in recruiting pro-tumorigenic MDSCs and show how defined cancer subsets may evolve to promote and depend on a distinct immune microenvironment.

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Figure 1: Inter-tumoral heterogeneity of MDSC infiltration.
Figure 2: The mTOR pathway drives tumour-induced MDSC accumulation.
Figure 3: The oncogenic mTOR pathway drives MDSC accumulation through G-CSF.
Figure 4: FGFR, an upstream activator of the mTOR pathway, can be targeted to reduce G-CSF production.
Figure 5: A G-CSF-responsive gene signature (G-CSF-sig) links the mTOR pathway to MDSC infiltration and immunosuppression in human breast cancer.
Figure 6: G-CSFhigh cells enrich for TICs.
Figure 7: MDSCs promote breast cancer TIC features.
Figure 8: The mTOR–MDSC cascade increases TIC frequency in vivo.

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Change history

  • 20 May 2016

    In the version of this Article originally published, in the fourth affiliation, 'Los Angeles' should have read 'Louisiana'. This has been corrected in all online versions of the Article.

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Acknowledgements

We would like to thank Novartis for providing BGJ-398, and H. C. Lo and D. Weiss for helpful input. We also thank the Antibody-Based Proteomics Shared Resource of the Dan L. Duncan Cancer Center supported by Cancer Center Support grant NCI P30CA125123, and A. Welm, Huntsman Cancer Institute, USA for generously providing some of the PDX models. X.H.-F.Z. is supported by NCI CA183878, the Breast Cancer Research Foundation, US Department of Defense DAMD W81XWH-13-1-0195, Susan G. Komen CCR14298445, and McNair Medical Institute. T.Welte is supported by the Helis Foundation. H.W. is supported by US Department of Defense DAMD W81XWH-13-1-0296. Studies with the p53-null tumours were supported by NIH grant CA148761 to J.M.R. and with the WNT1–iFGFR tumours by NIH grant CA16303 to J.M.R. RRPA experiments were supported by Cancer Prevention and Research Institute of Texas (CPRIT) Core Facilities Support Award RP120092 to D.P.E. The authors acknowledge the joint participation by Diana Helis Henry Medical Research Foundation through its direct engagement in the continuous active conduct of medical research in conjunction with Baylor College of Medicine.

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Contributions

Conception and design: X.H.-F.Z., J.M.R. and T.Welte. Development of methodology: T.Welte, I.S.K., L.T., X.G., S.H., J.X., T.Wang and Q.M. Acquisition of data: T.Welte, I.S.K., L.T., X.G., H.W., J.L., X.B.H., J.I.H., A.P., G.X., S.K., T.N., L.L., D.P.E., S.H., J.X., Y.L., M.T.L., T.Wang, T.F.W. and L.X. Analysis and interpretation of data: T.Welte, X.H.-F.Z., J.M.R., T.Wang, I.S.K. and Q.M. Writing and review of manuscript: X.H.-F.Z., T.Welte, T.Wang and J.M.R. Study supervision: X.H.-F.Z. and J.M.R.

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Correspondence to Jeffrey M. Rosen or Xiang H.-F. Zhang.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Inter-tumoral heterogeneity of MDSC accumulation in mammary tumour models.

(a) Quantification of S100A8 + cells identified by immunofluorescence staining. Six fields were randomly picked from each tumour, and three tumours were included. (b) Relative expression of the S100A8 gene in the bulk of tumour and in CD11b+Gr1+ cells purified from the tumour by FACS. n = 2 and 5 tumours for the bulk tumour and purified CD11b + Gr1 + cells, respectively. (c) In vitro CD3- and IL-2 stimulated T-cell proliferation, measured by CFSE decrease assay, is inhibited by MDSCs. The percentage of proliferating T-cells in conditioned medium (bottom) under indicated conditions. CD11b+Ly6G+ cells and T cells were admixed at 3:1. Two experiments each with technical triplicates were performed with similar results; results of one representative experiment are shown.

Supplementary Figure 2 Genetic knockdown of Raptor in 4T1 cells as gauged by Western blotting against the indicated proteins.

Supplementary Figure 3 G-CSF inhibition reduces primary tumour growth and lung metastasis, an effect that is partially overcome by exogenous MDSCs.

(a) P53N tumour bearing mice were treated with G-CSF neutralizing antibody. Relative G-CSF levels in blood after treatment were measured by ELISA. n = 5 and 3 animals in IgG and anti-G-CSF groups, respectively. Two experiments were performed with consistent results, one representative experiment is shown. (b) 4T1 tumour cells were lentivirus-transduced with G-CSF shRNA (Control: GIPZ vector transduced). Efficiency in reducing G-CSF levels in vivo (left panel) and in vitro (right panel) was evaluated by G-CSF ELISA. Left: n = 10 and 17 animals for Control and shG-CSF groups, respectively. Right: cells cultured in 3 different wells were used as technical replicates. Two independent experiments were conducted with representative results shown. (c) MDSC numbers in blood of P53N-C tumour bearing mice after G-CSF-neutralizing antibody regimen compared to IgG control antibody-treated tumour-bearing mice. n = 3, 4, and 7 animals for the three groups, respectively P value is determined by non-parametric Wilcoxon test. (d) 4T1 cells transduced with vector control lentivirus (GIPZ, control) or with G-CSF shRNA expressing lentivirus (shG-CSF) were orthotopically injected to mammary gland. MDSC numbers in blood were quantified. n = 9 and 7 animals for the two groups, respectively. (e) No direct role of G-CSF in 4T1 tumour cell survival. Cell viability was assessed by WST-1 assay in presence of G-CSF neutralizing antibody or G-CSF shRNA compared to controls ‘n.s.’: no significant difference. One experiment was performed in which cells of different groups were cultured in 5 wells each. Error bars indicate s.e.m., and P values are calculated by two-tailed Student’s t tests unless otherwise noted. Statistics source data of Supplementary Fig. 3b–d are provided in Supplementary Table 4.

Supplementary Figure 4 A G-CSF responsive gene signature (G-CSF-sig) links the mTOR activity to MDSC infiltration in human breast cancer.

(a) Heat maps show the expression of G-CSF signature as a single score (top), and TCR pathway components (bottom) in the EMC-MSK dataset. The red sticks above the heat maps indicate tumour samples whose gene expression level exceeds the mean of all tumours by more than 2 × s.d. n = 615 patients. (bd). Three human datasets were analysed for the relationship between expression of G-CSF signature and T-cell activation signature in tumour biopsies. n = 615, 409, and 1992 patients for (b), (c), (d), respectively. (e) As a negative control, the analysis was applied to a panel of tumour cell lines (n = 51, available from GSE12777), showing no correlation as expected. For (be), P values were determined based on two-side Student’s t tests for Pearson correlation coefficients. (f) Multivariate (MV) analysis of METABRIC and EMC-MSK datasets using the Cox Proportional-Hazards model to estimate the hazard ratios (HR) of G-CSF-sig. The P values were computed based on the Multivariate Cox Proportional-Hazards model. (g) MDSC quantity in P53N-C tumour-bearing hosts that are either wild type (WT) Balb/c mice or athymic nude (Nu) mice. TF (−) controls are shown for comparison. ‘n.s.’: no significant difference. n = 5 animals per group. Error bars indicate s.e.m., and P values are calculated by two-tailed Student’s t tests. (h) Representative Western blotting of pS6K(T389) and quantitative PCR assay of G-CSF in PDX tumours. Dotted lines indicate the matching between the two types of data across different PDX lines. Error bars indicate s.e.m.

Supplementary Figure 5 Correlation between high G-CSF expression and TIC features.

(a) 4T1 control cells and 4T1 cells expressing G-CSF shRNA were subjected to intracellular G-CSF FACS staining procedure. Overlay-graph demonstrates changes in G-CSF levels. The experiment was performed twice with similar results. Results of a representative experiment are shown. (b) Staining specificity control for pS6K antibody: PS6K levels were measured by intracellular FACS staining in 4T1 cells cultured in medium without serum (starved) or with 10% FBS. (c) Cells with highest G-CSF expression (top 5.3%, expression >2 times mean of total population) were compared to whole 4T1 cell population in the expression of CD24/CD29. Representative plots of gating strategy and identification of CD24highCD29high cells. (d). Same analysis as in (c), for P53N-C model. In (c) and (d): representative of three FACS staining experiments with 2–3 stained samples per experiment. (e) 4T1 cells were stained for G-CSF, CD24 and CD29. Expression of G-CSF in CD24highCD29high cells and in the total population was compared. (f) Same analysis as in (e), for P53N-C cells. (g,h). Correlation between G-CSF and Epcam+CD49f+ cells; analysis was done as described for CD24highCD29high cells in (e). In (h), EpCAMhighCD49fmed and EpCAMmedCD49fhigh denote specific cell population in P53N-C model as described in Fig. 6c. (eh) n = 3 independent experiments each with technical replicates. Mean values of all three experiments are used to generate the plot and calculate P values. (i) Under TIC enriched conditions 4T1 tumour cells produce increased levels of soluble factors to enhance MDSC differentiation from naïve bone marrow cells. Treatment of primary mouse bone marrow cells with conditioned medium (CM) from either 4T1 cells cultured in TIC-enriching condition (as 3D suspension mammospheres) or 2D conditions favouring differentiation. To eliminate effects of media-composition, all treatment conditions contained the same percentage of 2D and 3D media by supplementing with non-conditioned media as needed. αG-CSF: Five times ED50 dose of G-CSF-neutralizing antibody. G-CSF: 40 ng ml−1 recombinant human G-CSF. (j) Treatment of primary human bone marrow cells with CM from either MC1 cells cultured in 3D TIC-enriching condition or 2D conditions favouring differentiation. Left: FACS analysis showing MDSC-like cells in treated bone marrow. Right: quantification of MDSC-like cells under indicated conditions. Data are from two independent experiments. Error bars indicate s.e.m., and P values are calculated by two-tailed Student’s t tests. Statistics source data of Supplementary Fig. 5e–h are provided in Supplementary Table 4.

Supplementary Figure 6 The mTOR-G-CSF-MDSC axis does not affect tumour angiogenesis.

Immunofluorescence staining of CD31 was performed to quantitate angiogenesis in 4T1 tumours with indicated treatments. The CD31 + area was assessed using ImageJ software and displayed in the right panel. n = 8, 7, 6, and 5 fields randomly picked from 4 different tumours for the four groups, respectively. n.s.: no significance. Scale bar 100 μm.

Supplementary Figure 7 MDSCs promote tumour-initiating capacity.

(a) Counts of mammosphere numbers with or without co-cultures of MDSCs. In each group, cells were cultured in four wells. Results shown are from one representative experiment among four independent experiments. Consistent trends were observed in all experiments. Scale bar, 100 μm. (b) Fold changes induced in 4T1 cells by co-culture with MDSCs are shown for total tumour cell numbers (GFP marker), and sub-populations of CD24highCD29high, CD49f+CD29high and Sca1+c-Kit+. n = 3 independent experiments per group, each experiment with technical triplicates. Combined results of all three experiments are shown. (c). Mammary gland tumours formed by 4T1 cells that had been transduced with vector control (GIPZ) or with G-CSF shRNA lentivirus, were evaluated for mammosphere formation. For each tumour, cells were cultured in four technical replicates. Results (mammosphere numbers per equal tumour cell input) of two individual GIPZ control tumours and four G-CSF shRNA tumours are shown. (d,e) Experimental design as shown in Fig. 8a. P53N-C tumour bearing mice were transiently treated with rapamycin or rapamcin plus MDSCs or left untreated. Tumor cells were extracted and tested for tumour initiation potential on injection to mammary fat pads of untreated mice. Tumor size was measured on day 17 post tumour cell transfer from indicated groups (1,000 cell-injection per mouse). n = 5 animals per group. Error bars, s.d. Kaplan Meier curve of TF survival. (200 cell injection per mouse). n = 5 animals per group. P values were determined by log-rank test. Number of mice with tumours at end of observation time and total numbers of mice are also indicated for each condition. Error bars indicate s.e.m., and P values are calculated by two-tailed Student’s t tests unless otherwise noted. Statistical source data of Supplementary Fig. 7b is provided in Supplementary Table 4.

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Welte, T., Kim, I., Tian, L. et al. Oncogenic mTOR signalling recruits myeloid-derived suppressor cells to promote tumour initiation. Nat Cell Biol 18, 632–644 (2016). https://doi.org/10.1038/ncb3355

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