A precision medicine approach to metabolic therapy for breast cancer in mice

Ngozi D Akingbesote1,2, Aaron Norman1,2, Wanling Zhu1,2

  • 1Department of Celullar and Molecular Physiology, Yale University School of Medicine, New Haven, CT, USA.

Insights

Sodium-glucose transport protein 2 (SGLT2) inhibitors like dapagliflozin enhance paclitaxel chemotherapy for breast cancer. This metabolic approach shows promise for patients with specific genetic mutations, improving survival rates.

Area of Science:

  • Oncology
  • Metabolic pathways
  • Pharmacology

Background:

  • Metabolic targeting is a promising adjuvant strategy for cancer therapy.
  • Sodium-glucose transport protein 2 (SGLT2) inhibitors are a novel class of antihyperglycemic agents.
  • The neoadjuvant application of SGLT2 inhibitors in precision cancer medicine remains unexplored.

Purpose of the Study:

  • To investigate the efficacy of the SGLT2 inhibitor dapagliflozin as a neoadjuvant therapy for breast cancer, both as monotherapy and in combination with paclitaxel.
  • To identify predictive biomarkers for response to SGLT2 inhibitor-based neoadjuvant therapy.

Main Methods:

  • Lean breast tumor-bearing mice were treated with dapagliflozin monotherapy and in combination with paclitaxel.
  • Tumor glucose uptake, survival rates, and circulating insulin levels were assessed.
  • Genetic analysis was performed to identify response signatures.

Main Results:

  • Dapagliflozin significantly enhanced the efficacy of paclitaxel chemotherapy, reducing tumor glucose uptake and prolonging survival.
  • The therapeutic enhancement correlated with reduced circulating insulin in a subset of tumors.
  • Tumors with driver mutations upstream of canonical insulin signaling pathways showed a positive response, unlike those with downstream mutations.

Conclusions:

  • Dapagliflozin demonstrates potential as an effective neoadjuvant therapy to enhance chemotherapy response in breast cancer.
  • A genetic signature, specifically mutations upstream of insulin signaling, may predict patient response to this combined neoadjuvant approach.