Molecular mechanisms of targeted therapy in breast cancer: An integrated signaling network perspective

Yadong Wang1, Maona Zhang2, Xuefang Zhang2

  • 1Emergency Department, Wuhan Hospital of Traditional Chinese Medicine, Wuhan, Hubei 430000, China.

Insights

Therapeutic resistance in breast cancer is a major challenge. This study proposes a four-layer network model of resistance mechanisms and evaluates targeted therapies, aiming to guide future adaptive treatment strategies.

Area of Science:

  • Oncology
  • Molecular Biology
  • Cancer Therapeutics

Background:

  • Breast cancer comprises distinct molecular subtypes requiring tailored therapies.
  • Recent advances include antibody-drug conjugates (ADCs), CDK4/6 inhibitors, and immune checkpoint blockade.
  • Therapeutic resistance remains a significant hurdle in achieving durable patient benefit.

Purpose of the Study:

  • To synthesize evidence on signaling pathways driving targeted therapy resistance in breast cancer.
  • To propose a four-layer network topology model for understanding resistance mechanisms.
  • To critically evaluate current and emerging therapeutic agents within this framework.

Main Methods:

  • Literature synthesis of current evidence on breast cancer targeted therapy resistance.
  • Development of a four-layer network topology model integrating various resistance mechanisms.
  • Stratification of resistance mechanisms into evidence tiers: clinically actionable, plausibly translational, and exploratory.

Main Results:

  • Identified four key layers of resistance: canonical pathway reactivation, RTK reprogramming, ncRNA regulatory circuits, and epigenetic/TME co-evolution.
  • Stratified resistance mechanisms based on clinical evidence to differentiate validated biomarkers from preclinical observations.
  • Evaluated FDA-approved and emerging agents against the proposed resistance framework.

Conclusions:

  • Understanding the multi-layered network of resistance is crucial for advancing breast cancer treatment.
  • Future directions include liquid biopsy-guided adaptive therapy, multi-omic profiling, and rational combination strategies.
  • Addressing feasibility constraints like toxicity, cost, and biomarker validation is essential for clinical implementation.

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