Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Nov 22;16(1):87.
doi: 10.1186/s12964-018-0297-z.

SOX2 as a novel contributor of oxidative metabolism in melanoma cells

Affiliations

SOX2 as a novel contributor of oxidative metabolism in melanoma cells

Elena Andreucci et al. Cell Commun Signal. .

Abstract

Background: Deregulated metabolism is a hallmark of cancer and recent evidence underlines that targeting tumor energetics may improve therapy response and patient outcome. Despite the general attitude of cancer cells to exploit the glycolytic pathway even in the presence of oxygen (aerobic glycolysis or "Warburg effect"), tumor metabolism is extremely plastic, and such ability to switch from glycolysis to oxidative phosphorylation (OxPhos) allows cancer cells to survive under hostile microenvironments. Recently, OxPhos has been related with malignant progression, chemo-resistance and metastasis. OxPhos is induced under extracellular acidosis, a well-known characteristic of most solid tumors, included melanoma.

Methods: To evaluate whether SOX2 modulation is correlated with metabolic changes under standard or acidic conditions, SOX2 was silenced and overexpressed in several melanoma cell lines. To demonstrate that SOX2 directly represses HIF1A expression we used chromatin immunoprecipitation (ChIP) and luciferase assay.

Results: In A375-M6 melanoma cells, extracellular acidosis increases SOX2 expression, that sustains the oxidative cancer metabolism exploited under acidic conditions. By studying non-acidic SSM2c and 501-Mel melanoma cells (high- and very low-SOX2 expressing cells, respectively), we confirmed the metabolic role of SOX2, attributing SOX2-driven OxPhos reprogramming to HIF1α pathway disruption.

Conclusions: SOX2 contributes to the acquisition of an aggressive oxidative tumor phenotype, endowed with enhanced drug resistance and metastatic ability.

Keywords: HIF1α; Melanoma; Oxidative metabolism; SOX2; Tumor extracellular acidosis.

PubMed Disclaimer

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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

Figures

Fig. 1
Fig. 1
SOX2 is up-regulated by extracellular acidosis and its inhibition increases the glycolytic metabolism in A375-M6 melanoma cells. a, b) Representative flow cytometry plot (left) and relative quantification chart (right) (a) and Western blot (b) of SOX2 in A375-M6 cells exposed for 24 h to standard pH 7.4 and acidic pH 6.7. p < 0.05, T-test. N = 3. HDAC2 was used as loading control of nuclear protein fraction. Quantification of SOX2 protein expression in shown in italic. c) Representative flow cytometry plot (left) and relative quantification chart (right) of SOX2 level variation along with pH values. p < 0.01, T-test, N = 3. d) Quantification of lactate production by A375-M6 cells exposed for 24 h to standard (pH 7.4) or acidic (pH 6.7) conditions. p < 0.01, T-test, N = 3. e) Representative flow cytometry plot (left) and quantification of glucose uptake (right) in A375-M6 cells exposed for 24 h to standard (pH 7.4) or acidic (pH 6.7) conditions. p < 0.05, T-test, N = 3. f, g) Quantitative Real Time PCR (qPCR) (f) and Western blot (g) of SOX2 in A375-M6 silenced for SOX2 (siSOX2) compared to control (siCTRL). Quantification of SOX2 protein is shown in italic. β-actin used as loading control. p < 0.01, T-test. N = 3. h) Quantification chart of lactate production by A375-M6 siSOX2 compared to siCTRL in standard condition (pH 7.4) p < 0.01, T-test, N = 3. i) qPCR of a panel of glycolysis- and OxPhos-related genes of A375-M6 in standard condition (pH 7.4) silenced for SOX2 (siSOX2) compared to control (siCTRL). *p < 0.05, **p < 0.01; ***p < 0.001, T-test, N = 3. j) Quantification chart of lactate production by acidosis-exposed (pH 6.7) siSOX2 A375-M6 compared siCTRL. p < 0.01, T-test, N = 3. k) qPCR analysis of a panel of glycolysis- and OxPhos-related genes of acidosis-exposed (pH 6.7) A375-M6 siSOX2 compared siCTRL. *p < 0.05, **p < 0.01, ***p < 0.001, T-test. N = 3
Fig. 2
Fig. 2
SOX2 silencing in A375-M6 melanoma cells alters the efficacy of the metabolic drugs 2-DG and Metformin. a) Quantification chart (upper panel) and representative pictures (lower panel) of Annexin V/PI analysis of A375-M6 treated for 24 h with the anti-glycolytic drug 2-DG (50 mM) under standard (pH 7.4) or acidic (pH 6.7) conditions. b) Quantification chart (upper panel) and representative pictures (lower panel) of Annexin V/PI analysis of A375-M6 treated for 24 h with the anti-OxPhos drug Metformin (10 mM) under standard (pH 7.4) or acidic (pH 6.7) conditions. *p < 0.05, **p < 0.01, ***p < 0.001, Two-way ANOVA (statistical analysis compares for each phase- early apoptosis, late apoptosis, and necrosis- siSOX2 versus the respective untreated or treated siCTRL). N = 3
Fig. 3
Fig. 3
Modulation of SOX2 expression induces metabolic changes in SSM2c and in 501-Mel melanoma cells. a) Western blot analysis of SOX2 expression in SK-MEL-2, SK-MEL-5, SK-MEL-28, A375-M6, 501-Mel and SSM2c melanoma cells. β-actin was used as loading control. b, c) qPCR (b) and Western blot (c) of SOX2 in SSM2c silenced for SOX2 (LV-shSOX2) compared to control (LV-c). Quantification of SOX2 protein is shown in italic. p < 0.05, T-test. N = 3. d) Quantification chart of lactate production of SSM2c LV-shSOX2 compared to LV-c. p < 0.05, T-test, N = 3. e) qPCR of a panel of glycolysis- and OxPhos-related genes in SSM2c LV-shSOX2 compared to LV-c. *p < 0.05, **p < 0.01, ***p < 0.001, T-test. N = 3. f, g) qPCR (f) and Western blot (g) of SOX2 in 501-Mel with SOX2 overexpression (pBABE-SOX2) compared to control (pBABE-c). Quantification of SOX2 protein is shown in italic. p < 0.01, T-test. N = 3. h) Quantification chart of lactate production of 501-Mel pBABE-SOX2 compared to pBABE-c. p < 0.01, T-test, N = 3. i) qPCR of a panel of glycolysis- and OxPhos-related genes in 501-Mel pBABE-SOX2 compared to pBABE-c. *p < 0.05, **p < 0.01, ***p < 0.001, T-test. N = 3
Fig. 4
Fig. 4
SOX2 regulates HIF1α expression in SSM2c, A375-M6 and 501-Mel melanoma cells. a) (Left) Representative image of HIF1A promoter showing the sequence and the position of the putative SOX2-binding sites (BS) relative to the transcriptional start site (TSS). (Right) Chromatin Immunoprecipitation (ChIP) assay showing SOX2 binding at HIF1A promoter; Actin promoter was used as negative control and set to 1. p < 0.01, Two-way ANOVA. b) Quantification of dual-luciferase reporter assay in SSM2c cells. Relative luciferase activities were Firefly/Renilla ratios, with the level induced by control equated to 1. Data represent mean ± s.e.m. p < 0.001 vs control, One-way ANOVA. N = 4. c, d) qPCR (c) and Western blot (d) of HIF1α in SSM2c LV-shSOX2 compared to LV-c. Quantification of SOX2 and HIF1α protein is shown in italic. p < 0.01, T-test. N = 4. e, f) qPCR (e) and Western blot (f) of HIF1α in A375-M6 LV-shSOX2 compared to LV-c. Quantification of SOX2 and HIF1α protein is shown in italic. p < 0.05, T-test. N = 4. g, h) qPCR (g) and Western blot (h) of HIF1α in 501-Mel pBABE-SOX2 compared to pBABE-c. Quantification of SOX2 and HIF1α protein is shown in italic. p < 0.01, T-test. N = 4. HSP90 was used as loading control

References

    1. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646–674. doi: 10.1016/j.cell.2011.02.013. - DOI - PubMed
    1. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009;324(5930):1029–1033. doi: 10.1126/science.1160809. - DOI - PMC - PubMed
    1. Peppicelli S, Andreucci E, Ruzzolini J, Margheri F, Laurenzana A, Bianchini F, et al. Acidity of microenvironment as a further driver of tumor metabolic reprogramming. J Clin Cell Immunol. 2017;8:485. doi: 10.4172/2155-9899.1000485. - DOI
    1. Koukourakis MI, Giatromanolaki A, Harris AL, Sivridis E. Comparison of metabolic pathways between cancer cells and stromal cells in colorectal carcinomas: a metabolic survival role for tumor-associated stroma. Cancer Res. 2006;66(2):632–637. doi: 10.1158/0008-5472.CAN-05-3260. - DOI - PubMed
    1. Webb BA, Chimenti M, Jacobson MP, Barber DL. Dysregulated pH: a perfect storm for cancer progression. Nat Rev Cancer. 2011;11(9):671–677. doi: 10.1038/nrc3110. - DOI - PubMed

Publication types

MeSH terms

Substances