Nexus between PI3K/AKT and Estrogen Receptor Signaling in Breast Cancer

Aditi S Khatpe1,2, Adedeji K Adebayo1,2, Christopher A Herodotou1

  • 1Department of Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, USA.

Cancers
|January 27, 2021
PubMed

Insights

Estrogen receptor alpha (ERα) signaling drives many breast cancers. Understanding resistance mechanisms to anti-estrogen therapy, like ERα pathway crosstalk, is key to developing effective combination treatments for recurrent disease.

Area of Science:

  • Oncology
  • Endocrinology
  • Molecular Biology

Background:

  • Estrogen receptor alpha (ERα) and estradiol (E2) signaling are crucial for approximately 70% of breast cancers.
  • Anti-estrogen therapies are standard treatments, but resistance leads to recurrence in about 30% of ERα-positive breast cancers, even years after diagnosis.

Purpose of the Study:

  • To review the mechanisms of resistance to anti-estrogen therapy in ERα-positive breast cancer.
  • To explore the interplay between ERα signaling and other pathways, such as PI3K/AKT/mTOR and cell cycle machinery.
  • To highlight how understanding these interactions informs the development of combination therapies.

Main Methods:

  • Literature review focusing on ERα signaling, resistance mechanisms, and targeted therapies.
  • Analysis of studies investigating ESR1 mutations and pathway crosstalk.
  • Examination of clinical data on combination therapies for recurrent breast cancer.

Main Results:

  • Resistance to anti-estrogens can arise from ESR1 mutations or crosstalk with growth factor and cell cycle pathways, leading to ligand-independent ERα activation.
  • Combination therapies targeting both ERα and these crosstalk pathways (e.g., PI3K/AKT/mTOR or CDK4/6 inhibitors) are clinically utilized for recurrent ERα-positive breast cancer.

Conclusions:

  • Understanding the ERα-PI3K/AKT/mTOR pathway nexus is vital for overcoming anti-estrogen resistance.
  • Combination strategies targeting ERα and associated signaling networks represent a promising approach for managing recurrent ERα-positive breast cancer.

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