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Cited by 820Cancer, Lipids, and MetabolismCancer, Hypoxia, and MetabolismLipid metabolism and biosynthesis

The DOI matches its Crossref record; 70 of the 73 references it cites were found in a registry or an index.

Acetyl-CoA Synthetase 2 Promotes Acetate Utilization and Maintains Cancer Cell Growth under Metabolic Stress

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Schug, Zachary T., Peck, Barrie, Jones, Dylan T., Zhang, Qifeng, Grosskurth, Shaun, Alam, Israt S., Goodwin, Louise M., Smethurst, Elizabeth, Mason, Susan, Blyth, Karen, McGarry, Lynn, James, Daniel, Shanks, Emma, Kalna, Gabriela, Saunders, Rebecca E., Jiang, Ming, Howell, Michael, Lassailly, Francois, Thin, May Zaw, Spencer-Dene, Bradley, Stamp, Gordon, van den Broek, Niels J.F., Mackay, Gillian, Bulusu, Vinay, Kamphorst, Jurre J., Tardito, Saverio, Strachan, David, Harris, Adrian L., Aboagye, Eric O., Critchlow, Susan E., Wakelam, Michael J.O., Schulze, Almut, Gottlieb, Eyal·2015·Cancer Cell
DOI 10.1016/j.ccell.2014.12.002PMC PMC4297291
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Abstract

A functional genomics study revealed that the activity of acetyl-CoA synthetase 2 (ACSS2) contributes to cancer cell growth under low-oxygen and lipid-depleted conditions. Comparative metabolomics and lipidomics demonstrated that acetate is used as a nutritional source by cancer cells in an ACSS2-dependent manner, and supplied a significant fraction of the carbon within the fatty acid and phospholipid pools. ACSS2 expression is upregulated under metabolically stressed conditions and ACSS2 silencing reduced the growth of tumor xenografts. ACSS2 exhibits copy-number gain in human breast tumors, and ACSS2 expression correlates with disease progression. These results signify a critical role for acetate consumption in the production of lipid biomass within the harsh tumor microenvironment.

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Graphical abstract CC BY-NC-ND · PubMed Central
Figure 1 In Vivo Conditions Are Most Closely Mimicked by Culturing Cells in Low Serum and Hypoxia (A) Sensitivity of breast cancer cells to C75 (2.5 μM) treatment in high (10%) and low (1%) serum concentrations. Data are presented as mean ± SEM (n = 3). (B) pIC50 (−log IC50) values for AZ22 in breast cancer cell lines cultured in full serum or lipid-reduced serum. Data are presented as mean ± SEM (n ≥ 3). (C) Lipid profiling of PC by LC-MS under normoxic (21%) and hypoxic (0.1%) conditions in MDA-MB-468 breast cancer cells grown in low serum. PC species containing highly polyunsaturated acyl chains (≥3 C = C bonds) are underlined. Data are presented as mean ± SEM (n = 3). (D) DU145, MDA-MB-468, and PC3 spheroids were grown in full medium and in the presence of AZ22 for 8–12 days to determine the dependency of spheroid growth on de novo fatty acid synthesis. Data are presented as mean ± SEM (n ≥ 3). (E) Short-term tumor xenograft growth of BT474 cells treated with vehicle or AZ62. Tumors were grown to 100 mm3 and size-matched animals were randomized to AZ62 or vehicle treatment. Animals were treated with AZ62 at 100 mg/kg (oral administration) daily for 7 days. Data are presented as mean ± SEM (n = 4 per group). (F) Steady-state levels of acetyl-CoA and CDP-choline in BT474 tumor extracts as determined by LC-MS-based metabolomics. Data are presented as mean ± SEM (n = 6 per group). See also Figure S1 and Table S1.
Figure 1 In Vivo Conditions Are Most Closely Mimicked by Culturing Cells in Low Serum and Hypoxia (A) Sensitivity of breast cancer cells to C75 (2.5 μM) treatment in high (10%) and low (1%) serum concentrations. Data are presented as mean ± SEM (n = 3). (B) pIC50 (−log IC50) values for AZ22 in breast cancer cell lines cultured in full serum or lipid-reduced serum. Data are presented as mean ± SEM (n ≥ 3). (C) Lipid profiling of PC by LC-MS under normoxic (21%) and hypoxic (0.1%) conditions in MDA-MB-468 breast cancer cells grown in low serum. PC species containing highly polyunsaturated acyl chains (≥3 C = C bonds) are underlined. Data are presented as mean ± SEM (n = 3). (D) DU145, MDA-MB-468, and PC3 spheroids were grown in full medium and in the presence of AZ22 for 8–12 days to determine the dependency of spheroid growth on de novo fatty acid synthesis. Data are presented as mean ± SEM (n ≥ 3). (E) Short-term tumor xenograft growth of BT474 cells treated with vehicle or AZ62. Tumors were grown to 100 mm3 and size-matched animals were randomized to AZ62 or vehicle treatment. Animals were treated with AZ62 at 100 mg/kg (oral administration) daily for 7 days. Data are presented as mean ± SEM (n = 4 per group). (F) Steady-state levels of acetyl-CoA and CDP-choline in BT474 tumor extracts as determined by LC-MS-based metabolomics. Data are presented as mean ± SEM (n = 6 per group). See also Figure S1 and Table S1.CC BY-NC-ND · PubMed Central
Figure 2 ACSS2 Is Frequently Upregulated in Cancer and Positively Correlates with Disease Progression and Poor Survival (A) Proportional phenotypic classification of siRNA target genes. (B) Top hits from screening under metabolic stress. Growth data are presented as mean ± SD (white bars, left y axis) and mRNA expression data are presented as mean ± upper and lower limits (n = 3) (black bars, right y axis) and are normalized to a nontargeting control siRNA pool. (C) Representative immunohistochemistry images of ACSS2 expression from a tissue microarray of breast cancer samples. (D) Histograms illustrating ACSS2 expression in normal adjacent breast tissue (NAT, n = 12) and (left) IDC (p value = 0.0295; n = 78) and (right) ILC (NS = not significant; n = 75). (E) ACSS2 DNA copy-number variation comparing normal and IDC samples (p value = 1.0 × 10−4, unpaired, two-tailed t test). Boxes represent the upper and lower quartiles, the band represents the median, and the whiskers represent 5–95th percentile. (F) ACSS2 mRNA expression at different stages of IDC (asterisk, p < 0.05, Dunnet multiple comparison test). Boxes represent the upper and lower quartiles, the band represents the median, and the whiskers represent 5–95th percentile. (G) ACSS2 mRNA expression in invasive carcinoma and the patient survival status at 1 and 5 years (Mann-Whitney test, p values are as indicated). Boxes represent the upper and lower quartiles, the band represents the median, and the whiskers represent 10th–90th percentile. (H) Representative immunohistochemistry images of ACSS2 expression from a tissue microarray of prostate cancer samples. (I) Histogram illustrating ACSS2 expression in normal tissue and primary and metastatic prostate cancers. (J) The p values and fold change showing increased ACSS2 expression in metastatic prostate cancer compared with primary site tumors. Data were obtained from the Grasso (left) and Chandra (right) prostate cancer data sets available from Oncomine. Boxes represent the upper and lower quartiles, the band represents the median, and the whiskers represent minimum and maximum (p values are indicated, unpaired, two-tailed t test). See also Figure S2 and Tables S2, S3, and S4.
Figure 2 ACSS2 Is Frequently Upregulated in Cancer and Positively Correlates with Disease Progression and Poor Survival (A) Proportional phenotypic classification of siRNA target genes. (B) Top hits from screening under metabolic stress. Growth data are presented as mean ± SD (white bars, left y axis) and mRNA expression data are presented as mean ± upper and lower limits (n = 3) (black bars, right y axis) and are normalized to a nontargeting control siRNA pool. (C) Representative immunohistochemistry images of ACSS2 expression from a tissue microarray of breast cancer samples. (D) Histograms illustrating ACSS2 expression in normal adjacent breast tissue (NAT, n = 12) and (left) IDC (p value = 0.0295; n = 78) and (right) ILC (NS = not significant; n = 75). (E) ACSS2 DNA copy-number variation comparing normal and IDC samples (p value = 1.0 × 10−4, unpaired, two-tailed t test). Boxes represent the upper and lower quartiles, the band represents the median, and the whiskers represent 5–95th percentile. (F) ACSS2 mRNA expression at different stages of IDC (asterisk, p < 0.05, Dunnet multiple comparison test). Boxes represent the upper and lower quartiles, the band represents the median, and the whiskers represent 5–95th percentile. (G) ACSS2 mRNA expression in invasive carcinoma and the patient survival status at 1 and 5 years (Mann-Whitney test, p values are as indicated). Boxes represent the upper and lower quartiles, the band represents the median, and the whiskers represent 10th–90th percentile. (H) Representative immunohistochemistry images of ACSS2 expression from a tissue microarray of prostate cancer samples. (I) Histogram illustrating ACSS2 expression in normal tissue and primary and metastatic prostate cancers. (J) The p values and fold change showing increased ACSS2 expression in metastatic prostate cancer compared with primary site tumors. Data were obtained from the Grasso (left) and Chandra (right) prostate cancer data sets available from Oncomine. Boxes represent the upper and lower quartiles, the band represents the median, and the whiskers represent minimum and maximum (p values are indicated, unpaired, two-tailed t test). See also Figure S2 and Tables S2, S3, and S4.CC BY-NC-ND · PubMed Central
Figure 3 Metabolic Stress Induces Upregulation of ACSS2 and Causes Cells to Become Increasingly Sensitive to ACSS2 Depletion (A) BT474 and DU145 cell counts at 96 hr post-siRNA transfection. Dotted line represents the seeding density. Data are presented as mean ± SD (n = 3). (B) ACSS2 mRNA expression in BT474 and DU145 cells under metabolic stress (hypoxia = 0.1% O2). Error bars represent SEM (n = 2). (C) ACSS2 protein expression in BT474 and DU145 cells under metabolic stress. (D) ACSS2 mRNA expression in BT474c1 cells expressing an shRNA against ARNT. Data are normalized to expression of shNTC in normoxia + 10% serum. Error bars represent SEM (n = 3). (E) ACSS2 mRNA expression in BT474c1 cells transfected with a nontargeting control siRNA or a pool of siRNAs against SREBF1 or SREBF2. Data are normalized to expression of siNTC in 10% serum and normoxia (hypoxia = 0.1% O2). Error bars represent SEM (n = 3). See also Figure S3.
Figure 3 Metabolic Stress Induces Upregulation of ACSS2 and Causes Cells to Become Increasingly Sensitive to ACSS2 Depletion (A) BT474 and DU145 cell counts at 96 hr post-siRNA transfection. Dotted line represents the seeding density. Data are presented as mean ± SD (n = 3). (B) ACSS2 mRNA expression in BT474 and DU145 cells under metabolic stress (hypoxia = 0.1% O2). Error bars represent SEM (n = 2). (C) ACSS2 protein expression in BT474 and DU145 cells under metabolic stress. (D) ACSS2 mRNA expression in BT474c1 cells expressing an shRNA against ARNT. Data are normalized to expression of shNTC in normoxia + 10% serum. Error bars represent SEM (n = 3). (E) ACSS2 mRNA expression in BT474c1 cells transfected with a nontargeting control siRNA or a pool of siRNAs against SREBF1 or SREBF2. Data are normalized to expression of siNTC in 10% serum and normoxia (hypoxia = 0.1% O2). Error bars represent SEM (n = 3). See also Figure S3.CC BY-NC-ND · PubMed Central
Figure 4 Metabolic Stress Increases Acetate Uptake and Supports Biosynthesis of Membrane Phospholipids (A) Schematic for the ACSS2 reaction and destinations for nucleocytosolic acetyl-CoA. (B) 14C2-acetate uptake under metabolic stress. Data are presented as mean ± SEM (n = 3). (C) 14C2-acetate-dependent lipid synthesis over a 12 hr period under metabolic stress. Data are presented as mean ± SEM (n = 3). (D) Steady-state acetyl-CoA levels in a panel of breast cancer cell lines. Data are presented as mean ± SD (n ≥ 3). (E) Enrichment of 0.20 mM 13C2-acetate in the acetyl-CoA pool in BT474c1 cells cultured in normoxia and SMEM + 10% serum or hypoxia and SMEM + 1% serum over a 12 hr period. Data are presented as mean ± SEM (n ≥ 3). (F) Abundance of PC(34:1) isotopologs in BT474 cells cultured in SMEM + 1% serum supplemented with 0.50 mM 13C2-acetate. Area under the curve is shown to highlight the shift in the isotopolog-labeling pattern induced by metabolic stress. Data are presented as mean ± SEM (n ≥ 2).
Figure 4 Metabolic Stress Increases Acetate Uptake and Supports Biosynthesis of Membrane Phospholipids (A) Schematic for the ACSS2 reaction and destinations for nucleocytosolic acetyl-CoA. (B) 14C2-acetate uptake under metabolic stress. Data are presented as mean ± SEM (n = 3). (C) 14C2-acetate-dependent lipid synthesis over a 12 hr period under metabolic stress. Data are presented as mean ± SEM (n = 3). (D) Steady-state acetyl-CoA levels in a panel of breast cancer cell lines. Data are presented as mean ± SD (n ≥ 3). (E) Enrichment of 0.20 mM 13C2-acetate in the acetyl-CoA pool in BT474c1 cells cultured in normoxia and SMEM + 10% serum or hypoxia and SMEM + 1% serum over a 12 hr period. Data are presented as mean ± SEM (n ≥ 3). (F) Abundance of PC(34:1) isotopologs in BT474 cells cultured in SMEM + 1% serum supplemented with 0.50 mM 13C2-acetate. Area under the curve is shown to highlight the shift in the isotopolog-labeling pattern induced by metabolic stress. Data are presented as mean ± SEM (n ≥ 2).CC BY-NC-ND · PubMed Central
Figure 5 Acetate Is the Major Contributor to Palmitate Synthesis during Metabolic Stress (A) Immunoblot of BT474c1 and DU145 protein extracts 72 hr postdoxycycline administration. (B) Uptake of [3H]-acetate in BT474c1 and DU145 cells after doxycycline induced silencing of ACSS2. Cells were cultured in 10% serum and normoxia. Data are presented as mean ± SEM in triplicate (n = 2). (C) Schematic representation of the final reaction in the synthesis of PC and PE. (D) Change in the steady-state intracellular levels of CDP-choline and CDP-ethanolamine following transfection of the indicated siRNAs in BT474c1 cells cultured in SMEM + 1% serum and hypoxia (0.1% O2). Data are presented as mean ± SEM (n = 3). (E) BT474c1 cells were transfected with indicated siRNAs for 24 hr prior to the addition of 1% serum, 10% serum, or 10% LPDS and transferred to hypoxia (0.1% O2). Cell counts were performed 72 hr later. Data are normalized to a nontargeting siRNA control for each condition and represent the mean ± SEM in triplicate (n = 1). (F) Immunoblot for ACSS2 expression in cell lysates from the experiment in (E). (G) 13C2-acetate-dependent labeling of palmitate in indicated growth conditions after 24 hr. Data are presented as mean ± SEM (n = 3). (H) 13C6-glucose-, 13C5-glutamine-, and 13C2-acetate-dependent labeling of palmitate in indicated growth conditions after 24 hr. The relative concentrations of glucose, glutamine, and acetate were equal in all three conditions. Data are presented as mean ± SEM (n = 3). See also Figure S4.
Figure 5 Acetate Is the Major Contributor to Palmitate Synthesis during Metabolic Stress (A) Immunoblot of BT474c1 and DU145 protein extracts 72 hr postdoxycycline administration. (B) Uptake of [3H]-acetate in BT474c1 and DU145 cells after doxycycline induced silencing of ACSS2. Cells were cultured in 10% serum and normoxia. Data are presented as mean ± SEM in triplicate (n = 2). (C) Schematic representation of the final reaction in the synthesis of PC and PE. (D) Change in the steady-state intracellular levels of CDP-choline and CDP-ethanolamine following transfection of the indicated siRNAs in BT474c1 cells cultured in SMEM + 1% serum and hypoxia (0.1% O2). Data are presented as mean ± SEM (n = 3). (E) BT474c1 cells were transfected with indicated siRNAs for 24 hr prior to the addition of 1% serum, 10% serum, or 10% LPDS and transferred to hypoxia (0.1% O2). Cell counts were performed 72 hr later. Data are normalized to a nontargeting siRNA control for each condition and represent the mean ± SEM in triplicate (n = 1). (F) Immunoblot for ACSS2 expression in cell lysates from the experiment in (E). (G) 13C2-acetate-dependent labeling of palmitate in indicated growth conditions after 24 hr. Data are presented as mean ± SEM (n = 3). (H) 13C6-glucose-, 13C5-glutamine-, and 13C2-acetate-dependent labeling of palmitate in indicated growth conditions after 24 hr. The relative concentrations of glucose, glutamine, and acetate were equal in all three conditions. Data are presented as mean ± SEM (n = 3). See also Figure S4.CC BY-NC-ND · PubMed Central
Figure 6 Silencing of ACSS2 Expression Inhibited Tumor Xenograft Growth (A) Spheroid growth was monitored following doxycycline-induced ACSS2 silencing in DU145 + shNTC and DU145 + shACSS2#64 cells in indicated growth conditions. Data are presented as mean ± SEM (n ≥ 4). (B and C) Nude mice (nu/nu) were injected subcutaneously with DU145 (B) or BT474c1 (C) cells. Silencing of ACSS2 was initiated by providing doxycycline at the indicated time. Each group is presented mean tumor volume ± SEM. (D) Immunohistochemistry for ACSS2 at day 22 in BT474c1 tumors. (E) Kaplan-Meier plot of survival of BT474c1 tumor-xenografted mice (n = total number of mice injected subcutaneously for each condition). (F) Immunohistochemical staining of serial sections from a BT474c1 + shACSS2#20 tumors (no DOX) with antipimonidazole (hypoxia marker) and anti-ACSS2 antibodies. Hypoxic regions are outlined in black. (G) Mean intensity of ACSS2 staining per pixel in normoxic (pimonidazole-negative) versus hypoxic (pimonidazole-positive) regions of three individual tumor sections. Data are presented as mean ± SEM (n = 3; p value = 0.031, paired, two-tailed t test). See also Figure S5.
Figure 6 Silencing of ACSS2 Expression Inhibited Tumor Xenograft Growth (A) Spheroid growth was monitored following doxycycline-induced ACSS2 silencing in DU145 + shNTC and DU145 + shACSS2#64 cells in indicated growth conditions. Data are presented as mean ± SEM (n ≥ 4). (B and C) Nude mice (nu/nu) were injected subcutaneously with DU145 (B) or BT474c1 (C) cells. Silencing of ACSS2 was initiated by providing doxycycline at the indicated time. Each group is presented mean tumor volume ± SEM. (D) Immunohistochemistry for ACSS2 at day 22 in BT474c1 tumors. (E) Kaplan-Meier plot of survival of BT474c1 tumor-xenografted mice (n = total number of mice injected subcutaneously for each condition). (F) Immunohistochemical staining of serial sections from a BT474c1 + shACSS2#20 tumors (no DOX) with antipimonidazole (hypoxia marker) and anti-ACSS2 antibodies. Hypoxic regions are outlined in black. (G) Mean intensity of ACSS2 staining per pixel in normoxic (pimonidazole-negative) versus hypoxic (pimonidazole-positive) regions of three individual tumor sections. Data are presented as mean ± SEM (n = 3; p value = 0.031, paired, two-tailed t test). See also Figure S5.CC BY-NC-ND · PubMed Central

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Authors
Schug, Z. T., Peck, B., Jones, D. T., Zhang, Q., Grosskurth, S., Alam, I. S., Goodwin, L. M., Smethurst, E., Mason, S., Blyth, K., McGarry, L., James, D., Shanks, E., Kalna, G., Saunders, R. E., Jiang, M., Howell, M., Lassailly, F., Thin, M. Z., Spencer-Dene, B., Stamp, G., van den Broek, N. J. F., Mackay, G., Bulusu, V., Kamphorst, J. J., Tardito, S., Strachan, D., Harris, A. L., Aboagye, E. O., Critchlow, S. E., Wakelam, M. J. O., Schulze, A., & Gottlieb, E.
Affiliations
  • Cancer Research UK Scotland Institute (GB)
  • Cancer Research UK (GB)
  • John Radcliffe Hospital (GB)
  • Babraham Institute (GB)
  • AstraZeneca (United Kingdom) (GB)
  • Hammersmith Hospital (GB)
  • University of Glasgow (GB)
Corresponding author
Gottlieb, Eyal
ORCID
Venue
Cancer Cell
Publisher
Elsevier BV
Published
2015-01
Volume
27
Issue
1
Pages
57-71
ISSN
1535-6108 (ISSN-L)
DOI
10.1016/j.ccell.2014.12.002
PMC
PMC4297291
OpenAlex
W2044515618
Cited by
820
References
73
Citations by year
2026: 64 · 2025: 76 · 2024: 96 · 2023: 72 · 2022: 88 · 2021: 75 · 2020: 63 · 2019: 67 · 2018: 68 · 2017: 57 · 2016: 63 · 2015: 28
FWCI
23.79
Type
journal article
Language
en
Open access
Licence
Locations
  • Cancer Cell (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
Funders
  • AstraZeneca
  • Francis Crick Institute (10009, 10008)
  • Cancer Research UK (11359, 18278, 12011, 10337, 16466, 16584, 22311, 18974)
  • National Institute for Health and Care Research (NIHR/CS/009/009, NF-SI-0611-10163, EME/13/122/01)
  • Directorate for Biological Sciences
  • Medical Research Council (MR/J007986/1)
  • Biotechnology and Biological Sciences Research Council (BBS/E/B/000C0415, BBS/E/B/000C0413)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Lipids, and Metabolism
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Lipid metabolism and biosynthesis
Keywords
acetyl-CoA synthetase 2, ACSS2, acetate utilization, cancer cell growth, metabolic stress, hypoxia, lipid depletion, tumor xenografts, fatty acid synthesis, phospholipid synthesis, tumor microenvironment, breast cancer, copy number gain, tumor progression
MeSH terms
Acetate-CoA Ligase, Animals, Hypoxia, Fatty Acids, Humans, Mice, Nude, Neoplasm Transplantation, Neoplasms, Stress, Physiological, Gene Expression Regulation, Neoplastic, Disease Progression, Gene Dosage, Cell Line, Tumor, Cell Proliferation, Mice, MCF-7 Cells

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