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Cytosolic pH regulates proliferation and tumour growth by promoting expression of cyclin D1

Nature Metabolism volume 2, pages 1212–1222 (2020)Cite this article

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Abstract

Enhanced growth and proliferation of cancer cells are accompanied by profound changes in cellular metabolism. These metabolic changes are also common under physiological conditions, and include increased glucose fermentation accompanied by elevated cytosolic pH (pHc)1,2. However, how these changes contribute to enhanced cell growth and proliferation is unclear. Here, we show that elevated pHc specifically orchestrates an E2F-dependent transcriptional programme to drive cell proliferation by promoting cyclin D1 expression. pHc-dependent transcription of cyclin D1 requires the transcription factors CREB1, ATF1 and ETS1, and the histone acetyltransferases p300 and CBP. Biochemical characterization revealed that the CREB1–p300/CBP interaction acts as a pH sensor and coincidence detector, integrating different mitotic signals to regulate cyclin D1 transcription. We also show that elevated pHc contributes to increased cyclin D1 expression in malignant pleural mesotheliomas (MPMs), and renders these cells hypersensitive to pharmacological reduction of pHc. Taken together, these data demonstrate that elevated pHc is a critical cellular signal regulating G1 progression, and provide a mechanism linking elevated pHc to oncogenic activation of cyclin D1 in MPMs, and possibly other cyclin D1~dependent tumours. Thus, an increase of pHc may represent a functionally important, early event in the aetiology of cancer that is amenable to therapeutic intervention.

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Fig. 1: NHE1 activity regulates pHc and promotes cell-cycle progression through early G1.
Fig. 2: High pHc regulates cyclin D1 transcription in parallel or downstream of CREB activation.
Fig. 3: Sensing of pHc by the CREB–p300 interaction regulates cyclin D1 expression.
Fig. 4: Elevated pHc mediates oncogenic activation of cyclin D1 in MPMs.

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Data availability

Raw data and materials are available from the authors upon request. Full scans of all western blots are available in the supplementary material. Gene-expression data are accessible at GEO (https://www.ncbi.nlm.nih.gov/geo/), accession no. GSE145833. Additional data analysis for RNA-seq experiments is provided in Supplementary Tables 9–23. Raw data for targeted and untargeted metabolomics experiments are included as Supplementary Table 7 and 8, respectively. Data from the publicly available datasets used in this study can be accessed at: TCGA (https://www.cancer.gov/tcga), cBioPortal (http://www.cbioportal.org), TGCA pan cancer atlas (https://portal.gdc.cancer.gov) and Ensembl (https://www.ensembl.org/index.html) Source data are provided with this paper.

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Acknowledgements

We thank P. Kimmig, S. Gilberto, K. F. Marquart, W. Kovacs, M. Stoffel, A. Smith and members of the Peter, Curioni and Opitz laboratories for helpful discussions and comments on the manuscript; B. Vrugt, Ch. Mittmann and M. Glönkler, Department of Pathology and Molecular Pathology, University Hospital Zurich, for help with establishment of NHE1 and cyclin D1 IHC, the Functional Genomics Center Zürich (FGCZ) for support with RNA-seq and metabolomics and M. Okoniewski (Scientific IT Services ETH) for help with bioinformatic analyses. Work in the Dechant, Peter, Curioni and Opitz laboratories is funded by the SNF, ETHZ (ETH research grant 28 17-2 to RD) and the Medical University of Zurich.

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Author notes

  1. Stefania Battaglioni

    Present address: Biozentrum, University of Basel, Basel, Switzerland

Authors and Affiliations

  1. Institute of Biochemistry, Department of Biology, ETH Zurich, Zurich, Switzerland

    Lisa Maria Koch, Eivind Salmorin Birkeland, Stefania Battaglioni, Xiao Helle, Matthias Peter & Reinhard Dechant

  2. Life science Zürich, PhD program for Molecular Life Sciences, Zurich, Switzerland

    Lisa Maria Koch & Eivind Salmorin Birkeland

  3. Department of Thoracic Surgery, University Hospital Zurich, Zurich, Switzerland

    Mayura Meerang & Isabelle Opitz

  4. Department of Medical Oncology and Hematology, University Hospital Zurich, Comprehensive Cancer Center Zurich, University of Zurich, Zurich, Switzerland

    Stefanie Hiltbrunner & Alessandra Curioni-Fontecedro

  5. Core facility for Omics Research and Applied Biotechnology (ICOBA), Pontificia Universidad Católica del Perú, Lima, Peru

    Alfredo J. Ibáñez

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Contributions

R.D. conceptualized the study; performed formal analysis and visualization; wrote the manuscript with contributions of all authors. L.M.K., E.S.B., S.B., X.H. and R.D. performed experiments; L.M.K., E.S.B., M.M., S.H. and R.D. analysed data. A.J.I. performed metabolomics analysis. R.D., I.O., A.C.-F. and M.P. supervised the study.

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Correspondence to Reinhard Dechant.

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Extended data

Extended Data Fig. 1 NHE1 activity regulates pHc and promotes cell cycle progression through early G1.

(a–c) FCS and glucose availability cooperatively regulate pHc. Cells were starved for 24 hours, stimulated with the indicated conditions and pHc was determined. (a) Pooled single cell data of independent experiments N=3, n=30 cells per experiment, two-sided t-Test) are shown as box plot (MATLAB) with median, 25th and 75th percentile and whiskers extending to most extreme points indicated. (b) The difference in pHc relative to the starved control (-/-) (b, c) was plotted as mean ± S.E.M. alongside the histogram of single cell measurements. In the histograms, the median pHc was indicated. For all pHc measurements data are pooled single cell data of independent experiments N=3, n=30 cells per experiment, two-sided t-Test. (d) NHE1 is the most abundant NHE localized to the plasma membrane. Relative expression levels of NHE1-9 were determined by qPCR (mean ± S.E.M. of independent experiments, N=3, two-sided t-Test). Subcellular localization of the different NHE proteins is indicated. (e–g) NHE1 activity is required for RB phosphorylation. (e) The fraction of cells with RB phosphorylation at Ser780 from the experiment shown in Fig. 1f is shown (mean ± S.E.M. of independent experiments N= 3, two-sided t-Test). (f) Cells treated as in Fig. 1f were stained for RBP-Ser807/811 and the fraction of cells with RB phosphorylation (mean ± S.E.M. of independent experiments N=3, two-sided t-Test) (f) and representative images are shown. Scale bar represents 33 µm. (g) Cells were subjected to siRNA against NHE1 and RB phosphorylation was determined after 72 hours by immunofluorescence or western blot. The fraction of RB positive cells (mean ± S.E.M. of independent experiments N=3, two-sided t-Test) and representative images are shown. Scale bar represents 100 µm. (h, i) RPE-1 cells were grown in media of different NaHCO3 concentration to adjust extracellular pH to the indicated values and relative growth by MTT (mean of independent experiments N=2) (h), the fraction of cells with RB phosphorylation (mean of independent experiments N=2) and representative images (i) are shown. Scale bar represents 100 µm.

Extended Data Fig. 2 Pharmacological inhibition of NHE activity regulates RB phosphorylation in different cell lines.

Cells treated as in Fig. 1f were stained for RBP-Ser780 and the fraction of cells with RB phosphorylation was determined in the absence or presence of DMA for the indicated cell lines (mean ± S.E.M. of independent experiments N= 3, two-sided t-Test). Scale bar represents 100 µm.

Extended Data Fig. 3 pHc does not globally affect cellular metabolism.

(a–c) RPE-1 cells were starved and the relative abundance of metabolites was determined 4 hours after stimulation with the indicated conditions as described in Materials and Methods. Selected metabolites from energy (a) and central carbon metabolism (b) are shown as mean ± S.E.M.; N=4. P-values for all pairwise comparisons between conditions are listed in the Supplementary Table S7. (c) Unsupervised clustering and (d) PCA analysis were calculated using MATLAB (The MathWorks) from metabolite datasets generated using Progenesis QI software (Nonlinear Dynamics) to demonstrate the highly similar metabolic response upon stimulation in the presence or absence of DMA.

Extended Data Fig. 4 NHE activity is required for early G1 progression.

(a, b) Elevated pHc is required within the first 8 hours of the cell-cycle. Extracts of cells as in Fig. 1g were blotted for RB phosphorylation and cyclin A expression as markers for cell-cycle progression. Blots representative of three independent experiments are shown. (b) Elevated pHc is required to drive cell-cycle progression before initiation of S phase. Cells were starved (-/-) and treated with FCS glucose for the indicated time points and BrdU incorporation was measured to follow DNA synthesis. Results of a representative experiment from three independent experiments with percentage of cells in G1, S and G2/M phase are shown. (c, d) pHc regulates a subset of FCS and glucose dependent genes required for G1 progression. Cells were starved for 24 hours, treated with FCS glucose in the presence or absence of DMA for 5 hours and analyzed by RNAseq. (c) Venn diagram indicating the overlap of starvation and DMA-regulated genes. P-value demonstrating statistical significance of co-regulated genes based on a hypergeometric distribution is shown. (d) Genes repressed upon starvation and DMA treatment and co-regulated genes in both conditions were analyzed by GO-term enrichment using ShinyGO (http://bioinformatics.sdstate.edu/go/). Significantly enriched GO-terms were identified for the individual groups and plotted as -log10(FDR).

Source data

Extended Data Fig. 5 Regulation of cyclin D1 transcription requires CREB1/ATF1 and ETS1 transcription factors.

(a–c) An elevated pHc is required for cyclin D1 expression. (a) HFF-1 cells were starved and cyclin D1 expression was determined by western blotting 6 hours after stimulation with the indicated conditions. (b) RPE-1 cells were grown and cyclin D1 and phosphorylated RB was determined by western blotting upon treatment with DMA at the indicated time points. (c) RPE-1 cells were subjected to siRNA against NHE1 and cyclin D1 abundance was determined after 72 hours by western blot (d and e) CDK4cyclin D1 activity is required for G1/S progression. Cells were treated as in Fig. 1f and cell-cycle progression was determined by (d) western blotting and (e) FACS analysis and upon treatment with the CDK4cyclin D1 inhibitor Ribociclib at the indicated times. (f) pHc regulates cyclin D1 transcription rather than mRNA stability. Cells were treated with the indicated inhibitors for 4 hours and relative mRNA levels of cyclin D1 were determined (mean ± S.E.M. of independent experiments N=4, two-sided t-Test) (g) CREB1, ATF1 and ETS1 are required for cyclin D1 expression. Cells were transduced with Lentiviral particles expressing shRNA constructs against the indicated genes and expression of transcription factors and cyclin D1 protein levels were determined by western blotting. For all western blots in this figure, blots representative of three independent experiments are shown.

Source data

Extended Data Fig. 6 Regulation of cyclin D1 transcription requires p300/CBP.

(a, b) Reduced activity of p300/CBP decreases cyclin D1 expression and acetylation of histone H3 at K27. (a) Cells were subjected to shRNA against the indicated transcription factors or co-activators and histone acetylation at H3-K27 was determined by western blotting. (b) Cells were grown as in Fig. 3b and cyclin D1 mRNA levels were determined by 4 hours after stimulation with the indicated conditions by qPCR (mean ± S.E.M. of 3 independent experiments, two-sided t-Test). (c) Cells were grown as in Fig. 3a and the efficiency of shRNA mediated knock-down of p300 and CBP and cyclin D1 protein levels were determined by western blotting. (d) DMA treatment and p300/CBP inhibition does not generally affect histone acetylation. Cells were grown as in Fig. 3c and acetylation of histone H3 at K9 was determined by western blotting. (e–g) Starvation, inhibition of NHE activity and p300/CBP activity trigger a similar gene expression program. Cells were grown as in Fig. 1h and gene expression was determined by RNAseq. Volcano plots of differentially expressed genes upon stimulation with FCS glucose relative to (e) starvation, (f) DMA treatment and (g) C646 treatment is shown. Co-regulated genes under all conditions are indicated in red. (h) Venn diagram showing number of significantly higher expressed genes under the indicated conditions. For all western blots in this figure, blots representative of three independent experiments are shown.

Source data

Extended Data Fig. 7 pHc is regulated by Akt activity and active glucose metabolism.

(a) Cells as in Fig. 3g were grown and relative biomass accumulation was scored by MTT 72 hours after DMA treatment. (mean ± S.E.M. of independent experiments N=6, two-sided t-Test). (b) Cells as in Fig. 3g were grown and RB phosphorylation was scored 24 hours after DMA treatment. (mean ± S.E.M. of independent experiments N=3, two-sided t-Test). (c) CREB1 peptides interact with the KIX domain of CBP. A result of a pull-down of the KIX domain of CBP with biotinylated peptides representative for 6 independent experiments is shown. (d) RPE-1 cells were starved, stimulated with the indicated conditions and changes in cytosolic pH (mean ± S.E.M. of pooled single cell data from independent experiments, N=3, was plotted alongside the histogram of single cell measurements, n=30 cells per experiment) was determined. (e) RPE-1 cells were starved, stimulated with FCS and glucose in the presence of DMA and C646 and Akt-dependent phosphorylation of TSC2 was determined by western blotting. Blots representative of three independent experiments are shown. (f) Elevated pHc requires active glucose metabolism. pHc as determined in Fig. 3j is plotted from pooled single cell data of independent experiments N=3, n=30 cells per experiment are shown as box plot (MATLAB) with median, 25th and 75th percentile and whiskers extending to most extreme points not considered outliers, and outliers (+) indicated, two-sided t-Test.

Source data

Extended Data Fig. 8 NHE1 activity is critical for cell-cycle progression in PDAC cell lines.

(a) Cells of the indicated genotype expressing pHluorin were starved for 24 hours and pHc was determined 30 min following stimulation with the indicated conditions. For all pHc measurements data are pooled single cell data of independent experiments N=3 for PANC-1, N=3 for MIA Paca-2), n=30 cells per experiment, two-sided t-Test. Box plot (MATLAB) with median, 25th and 75th percentile, whiskers extending to most extreme points not considered outliers, and outliers (+) indicated. (b) Cells as in (a) were starved, treated with DMA for 6 hours and cyclin D1 and RB phosphorylation were determined by western blotting. (c) Cells were subjected to siRNA against NHE1 and cyclin D1, RB phosphorylation and NHE1 abundance were determined by western blotting. (d) Cyclin D1, but not NHE1 expression correlates with survival in PDAC cell lines. Data obtained from TCGA were independently analyzed for a correlation of cyclin D1 and NHE1 mRNA and survival and Kaplan Meier analysis was performed using log-rank test (N=85 patients with high expression of NHE1 or cyclin D1, respectively, N=96 patient with low expression of these markers). Hazard Ratio for NHE1 (with confidence interval) HR = 1.08 (0.72 - 1.62); for cyclin D1 HR = 2.05 (1.36 - 3.10).

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Extended Data Fig. 9 MPMs may be caused by hyperactivation of the NHE1/cyclin D1 axis.

(a) MPMs are associated with high CDK4cyclin D activity. Percentage of patients with the indicated mutations was determined from 2 patient cohorts as described in Materials and Methods. Only mutations in genes linked to the cyclin D/RB pathway are shown. (b) Cells were grown and treated as in Fig. 4c and cyclin D1 protein abundance was analyzed by western blot. Blots representative of three independent experiments are shown. (c) Cells were grown and phosphorylation of RB was analyzed upon DMA treatment (mean ± SEM of independent experiments, N=4). Scale bar represents 100 µm. (d) Cells subjected to siRNA mediated knockdown of NHE1 and cyclin D1 and NHE1 protein levels were analyzed by western blot (mean ± S.E.M. of 3 independent experiments). (e) NHE1 is the most abundant NHE isoform in MPM cell lines. Steady state mRNA levels of the indicated genes relative to NHE1 were determined by qPCR (mean ± SEM of independent experiments, N=3).

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Extended Data Fig. 10 NHE1 expression correlates with cyclin D1 expression and survival in MPM patients.

(a) Representative images of histological sections stained as in Fig. 4f with high (N=45 patients) and low NHE1 (N=51 patients) expression with the corresponding cyclin D1 stainings. Scale bar represents 100 µm. (b) Kaplan Meier analysis of survival data based on high (N=49 patients) or low (N=37 patients) NHE1 expression from the TCGA-Meso cohort using log-rank test. Hazard Ratio for (with confidence interval) HR = 1.95 (1.16 - 3.30) (c) Cyclin D1 expression for patient cohorts with high and low NHE1 expression as determined in (b) Box plot (MATLAB) with median, 25th and 75th percentile, whiskers extending to most extreme points not considered outliers, and outliers (+) indicated.

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Koch, L.M., Birkeland, E.S., Battaglioni, S. et al. Cytosolic pH regulates proliferation and tumour growth by promoting expression of cyclin D1. Nat Metab 2, 1212–1222 (2020). https://doi.org/10.1038/s42255-020-00297-0

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