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Breast-cancer-secreted miR-122 reprograms glucose metabolism in premetastatic niche to promote metastasis

Abstract

Reprogrammed glucose metabolism as a result of increased glycolysis and glucose uptake is a hallmark of cancer. Here we show that cancer cells can suppress glucose uptake by non-tumour cells in the premetastatic niche, by secreting vesicles that carry high levels of the miR-122 microRNA. High miR-122 levels in the circulation have been associated with metastasis in breast cancer patients, and we show that cancer-cell-secreted miR-122 facilitates metastasis by increasing nutrient availability in the premetastatic niche. Mechanistically, cancer-cell-derived miR-122 suppresses glucose uptake by niche cells in vitro and in vivo by downregulating the glycolytic enzyme pyruvate kinase. In vivo inhibition of miR-122 restores glucose uptake in distant organs, including brain and lungs, and decreases the incidence of metastasis. These results demonstrate that, by modifying glucose utilization by recipient premetastatic niche cells, cancer-derived extracellular miR-122 is able to reprogram systemic energy metabolism to facilitate disease progression.

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Figure 1: miR-122 is highly secreted by cancer cells.
Figure 2: miR-122 suppresses glucose metabolism by downregulating PKM.
Figure 3: Cancer-secreted miR-122 downregulates glucose uptake in lung fibroblasts.
Figure 4: Cancer-secreted miR-122 downregulates glucose uptake in astrocytes.
Figure 5: Vesicular transfer of miR-122 alters glucose uptake in niche tissues.
Figure 6: In vivo effect of miR-122 on primary tumour growth and metastasis.
Figure 7: miR-122 intervention alleviates cancer-induced glucose reallocation in vivo and reduces metastasis.

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Acknowledgements

This work was supported by the United States Army Research and Material Command grant W81-14-1-0029 (M.Y.F.), National Institutes of Health (NIH)/National Cancer Institute (NCI) grants R01CA166020 (S.E.W.) and R01CA163586 (S.E.W.), California Breast Cancer Research Program grant 20IB-0118 (S.E.W.), Breast Cancer Research Foundation-AACR grant 12-60-26-WANG (S.E.W.) and the City of Hope Women’s Cancer Program. Research reported here includes work carried out in Core Facilities supported by the NIH/NCI under grant number P30CA33572. We thank A. Riggs, E. Roberts, L. Malkas, S. Kane, S. Chen, J. Mortimer and P. Sarnow for valuable comments, as well as the Core Facilities at City of Hope for services.

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S.E.W. conceived ideas, and M.Y.F., Y.C. and X.R. contributed to project planning. M.Y.F. and S.E.W. designed and carried out the experiments. W.Zhou, L.L., A.C., S.T.F.O., S.L., A.R.C. and J.R.T. assisted with EV preparation and mouse experiments. G.Somlo and M.P. assisted with patient serum samples. Z.L. assisted with electron microscopy. A.T. assisted with mouse lung fibroblast culture. A.Y.A., M.C. and Y.C. assisted with NMR analysis. J.A. and W.Zhong assisted with AF4 analysis. G.Sun and Y.S. assisted with neuron culture. M.A.R. and M.K. assisted with medium metabolite analysis. X.W. assisted with bioinformatics analysis of miR-122 targets. P.S. assisted with anti-miR-122 and mismatch oligonucleotide synthesis. S.E.W. and M.Y.F. wrote the manuscript.

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Correspondence to Shizhen Emily Wang.

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Integrated supplementary information

Supplementary Figure 2 Characterization of the 110,000 × g medium pellet.

(a) For each cell line, RNA were extracted from the 110,000 × g medium pellet and concentrated supernatant obtained from equivalent volume of CM and analysed for miR-122 and miR-16 by RT-qPCR. Absolute miRNA levels are calculated based on standard curves (n = 6 extracts). (b) Representative EM images of vesicles in the AF4 fraction eluted at 18–25 min. The measured diameter of vesicles was shown as mean ± s.d. (n = 126 for MCF10A/vec-derived vesicles; n = 222 for MCF10A/miR-122-derived vesicles; n = 41 for MDA-MB-231-derived vesicles). Bars equal 100 nm. (c) RT-qPCR-determined levels of miRNAs in MCF10A/vec- and MCF10A/miR-122-derived protein and vesicle fractions separated by AF4. Absolute miRNA levels are shown (n = 6 extracts). ND: not detected. (d) Absolute miRNA levels in each gradient fraction after sucrose gradient centrifugation of MCF10A/miR-122-derived 110,000 × g medium pellet were determined by RT-qPCR (n = 6 extracts). (e) A representative EM image of MCF10A/miR-122-derived vesicles in sucrose fraction 6 (F6) (n = 362 vesicles). Bar equals 100 nm. P < 0.05 for all panels derived from Kruskal–Wallis test. Data are represented as mean ± s.d. in all panels except (b,e).

Supplementary Figure 3 Examples of peak assignment based on NMR spectra.

For all spectrum snapshots, black represents MCF10A/vec, red represents MCF10A/miR-122, and blue represents library entry. In general, each metabolite produces multiple resonances in different regions of the spectrum. We only analysed those with some of the resonances that can be resolved unambiguously. An example is given by glucose as shown in (a). One of the glucose resonances overlaps with that of O-acetylcholine, lactose, glutathione, homoserine and ethanolamine at around 3.8 ppm, but another glucose resonance is well resolved at around 3.4 ppm. Another example is given by lactate that has peaks in two regions of the spectrum that do not overlap with other resonances (b). The unique patterns of NMR resonances, due to J-coupling, are used for de-convolution of overlapping resonances. An example is given in (c), which shows that one set of peaks of isocitrate overlaps with that of glutathione, but the patterns of the peaks from the two metabolites are different, and at least one peak of the isocitrate resonance can be well resolved for de-convolution to extract the concentrations. Similarly, the pyruvate peak can be well resolved from those of glutamate (d). Examples of assignments of some other resolved peaks are given in (e).

Supplementary Figure 4 Characterization of cell lines with modified miR-122 levels used for in vivo studies.

(a) Cell number counts of MCFDCIS/miR-122 and MCFDCIS/vec cells at indicated time points (n = 6 biological replicates). (b) Medium metabolite analysis after 48 h of culture (n = 6 biological replicates). (c) RT-qPCR analysis showing the relative expression of indicated genes in MCFDCIS/miR-122 and MCFDCIS/vec cells (n = 6 extracts). (d) Western blot analysis in MCFDCIS/miR-122 and MCFDCIS/vec cells. Size of markers (in kDa) are indicated. (e) RT-qPCR-determined levels of intracellular and secreted miR-122 as well as PKM expression in MDA-MB-231 cells with stable knockdown of miR-122 (MDA-MB-231/122KD) compared to the control cells (n = 6 extracts).P < 0.05 for all panels derived from Kruskal–Wallis test. Data are represented as mean ± s.d. in all panels except (d). Uncropped, unprocessed images of blots are shown in Supplementary Fig. 5.

Supplementary Figure 5 BLI of the primary tumours established with MDA-MB-231-HM and treated with anti-miR-122 oligos.

(a) BLI images at week 3. (b) Quantification of (a) using Living Image Software (n = 8 mice per group). No significant difference (P > 0.05) between groups based on Kruskal–Wallis test.

Supplementary Figure 6 Uncropped, unprocessed images of blots and gels.

Supplementary Table 1 RT-qPCR primer sequences for human and mouse genes.

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Fong, M., Zhou, W., Liu, L. et al. Breast-cancer-secreted miR-122 reprograms glucose metabolism in premetastatic niche to promote metastasis. Nat Cell Biol 17, 183–194 (2015). https://doi.org/10.1038/ncb3094

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