HIF-2α expression and metabolic signaling require ACSS2 in clear cell renal cell carcinoma
Zachary A. Bacigalupa, Emily N. Arner, Logan M. Vlach, Melissa M. Wolf, Whitney A. Brown, Evan S. Krystofiak, Xiang Ye, Rachel A. Hongo, Madelyn Landis, Edith K. Amason, Kathryn E. Beckermann, W. Kimryn Rathmell, Jeffrey C. Rathmell
Zachary A. Bacigalupa, Emily N. Arner, Logan M. Vlach, Melissa M. Wolf, Whitney A. Brown, Evan S. Krystofiak, Xiang Ye, Rachel A. Hongo, Madelyn Landis, Edith K. Amason, Kathryn E. Beckermann, W. Kimryn Rathmell, Jeffrey C. Rathmell
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Research Article Cell biology Metabolism

HIF-2α expression and metabolic signaling require ACSS2 in clear cell renal cell carcinoma

Abstract

Clear cell renal cell carcinoma (ccRCC) is an aggressive cancer driven by VHL loss and aberrant HIF-2α signaling. Identifying means to regulate HIF-2α thus has potential therapeutic benefit. Acetyl-CoA synthetase 2 (ACSS2) converts acetate to acetyl-CoA and is associated with poor patient prognosis in ccRCC. Here we tested the effects of ACSS2 on HIF-2α and cancer cell metabolism and growth in ccRCC models and clinical samples. ACSS2 inhibition reduced HIF-2α levels and suppressed ccRCC cell line growth in vitro, in vivo, and in cultures of primary ccRCC patient tumors. This treatment reduced glycolytic signaling, cholesterol metabolism, and mitochondrial integrity, all of which are consistent with loss of HIF-2α. Mechanistically, ACSS2 inhibition decreased chromatin accessibility and HIF-2α expression and stability. While HIF-2α protein levels are widely regulated through pVHL-dependent proteolytic degradation, we identify a potential pVHL-independent pathway of degradation via the E3 ligase MUL1. We show that MUL1 can directly interact with HIF-2α and that overexpression of MUL1 decreased HIF-2α levels in a manner partially dependent on ACSS2. These findings identify multiple mechanisms to regulate HIF-2α stability and ACSS2 inhibition as a strategy to complement HIF-2α–targeted therapies and deplete pathogenically stabilized HIF-2α.

Authors

Zachary A. Bacigalupa, Emily N. Arner, Logan M. Vlach, Melissa M. Wolf, Whitney A. Brown, Evan S. Krystofiak, Xiang Ye, Rachel A. Hongo, Madelyn Landis, Edith K. Amason, Kathryn E. Beckermann, W. Kimryn Rathmell, Jeffrey C. Rathmell

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Figure 6

ACSS2 activity supports cholesterol biosynthesis and glucose uptake.

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ACSS2 activity supports cholesterol biosynthesis and glucose uptake. (A)...
(A) Heatmap showing gene distance from the transcription start site as a measure of accessibility (red, no coverage; blue, maximum coverage). (B) Left: Heatmap showing differential gene expression expressed as fold change (downregulated or upregulated at least 1.1-fold, adjusted P value ≤ 0.05) between groups with 24-hour treatment of 786-O cells with DMSO (blue; n = 3) versus 5 μM ACSS2i (red; n = 3). Gene expression clustering on the y axis depicts genes that are upregulated (purple) and downregulated (green) in the DMSO group. Middle and right: Bar graphs showing transcript counts for genes involved in the cholesterol biosynthesis pathway and glycolysis. Statistical significance was determined by multiple unpaired, 2-tailed t tests (*P < 0.05; **P < 0.005; ***P < 0.0005). (C) Western blot analysis assessing expression of GLUT1 (n = 2), HKII (n = 2), SREBP1 (n = 2), SREBP2 (n = 2), and actin (n = 3) in 786-O cells treated with DMSO or 5 μM or 10 μM ACSS2i for 24 hours. (D) Bar graph showing total cholesterol levels in 786-O cells treated with DMSO (blue; n = 3) or 5 μM ACSS2i (red; n = 3) for 24 hours. Statistical significance was determined using an unpaired, 2-tailed Student’s t test (*P < 0.05). (E) Bar graph showing measured glucose concentrations in the medium of 786-O cells treated with DMSO or 5 μM ACSS2i for 0, 24, and 48 hours (n = 3 for all conditions). Statistical significance was determined using a 2-way ANOVA and Tukey’s multiple-comparison test (***P < 0.0005). Data are represented as mean ± SD.