BET inhibition unmasks a targetable glycolytic dependency through a HIF1α stabilization and driven transcriptional

Teresa Rossi1, Egidio Iorio2, Mattea Chirico2

  • 1Laboratory of Translational Research, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy. teresa.rossi@ausl.re.it.

Insights

Triple-negative breast cancer (TNBC) cells adapt to Bromodomain and Extra-Terminal domain inhibitors (BETi) by increasing glycolysis via HIF1α. Combining BET inhibitors with glycolysis inhibitors exploits this adaptation, enhancing therapeutic vulnerability in TNBC.

Area of Science:

  • Oncology
  • Molecular Biology
  • Metabolic Reprogramming

Background:

  • Triple-negative breast cancer (TNBC) exhibits significant heterogeneity impacting treatment response.
  • The mechanisms underlying variable responses to epigenetic drugs like Bromodomain and Extra-Terminal domain inhibitors (BETi) in TNBC are poorly understood, especially concerning metabolic reprogramming.

Purpose of the Study:

  • To investigate the response of heterogeneous TNBC models to BET inhibitors (BETi).
  • To elucidate the mechanisms of BETi sensitivity and resistance, focusing on metabolic adaptation.
  • To explore combination therapies involving BETi and glycolysis inhibitors.

Main Methods:

  • Treatment of diverse TNBC models with BETi (JQ1, OTX015) and a glycolysis inhibitor (2-deoxy-D-glucose, 2-DG).
  • Analysis of BRD4 and cMYC protein levels.
  • Assessment of glycolytic gene expression and HIF1α transcriptional program induction.
  • Evaluation of apoptosis induction and combination effects.

Main Results:

  • BETi susceptibility correlates with basal BRD4 levels in cMYC-high TNBC, inducing glycolysis.
  • BETi treatment upregulates glycolytic genes via HIF1α in cMYC-high cells, an effect not seen in intrinsically glycolytic models.
  • Combination therapy of BETi and 2-DG shows additive apoptotic effects in BETi-responsive TNBC, but not in glycolysis-driven models.
  • HIF1α is functionally required for BETi-induced metabolic rewiring to glycolysis.

Conclusions:

  • TNBC cells adapt to BETi by upregulating glycolysis through the HIF1α pathway.
  • This adaptive metabolic rewiring creates a vulnerability to combined BET and glycolysis inhibition.
  • Targeting this transcriptional-metabolic axis offers a strategy to overcome BETi resistance in TNBC.

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