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Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer
Published on: March 17, 2016
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.
Abstract:
Breast cancer encompasses molecularly distinct subtypes with divergent oncogenic dependencies, each amenable to precision therapeutic intervention. Over the past decade, clinically meaningful advances have reshaped breast cancer management: antibody-drug conjugates (ADCs) have expanded actionable HER2 expression thresholds to include HER2-low and HER2-ultralow populations; cyclin-dependent kinase (CDK) 4/6 inhibitors have become standard-of-care in hormone receptor-positive disease; and immune checkpoint blockade has established durable responses in a defined subset of triple-negative breast cancer (TNBC). Nevertheless, therapeutic resistance remains the central unresolved obstacle to durable benefit. Here, we synthesize current evidence on the signaling architecture underlying targeted therapy across breast cancer subtypes and propose a four-layer network topology model of resistance integrating: (i) canonical pathway reactivation; (ii) receptor tyrosine kinase (RTK) reprogramming; (iii) non-coding RNA (ncRNA) regulatory circuits; and (iv) epigenetic plasticity coupled with tumor microenvironment (TME) co-evolution. We explicitly stratify the discussed mechanisms into three evidence tiers-clinically actionable, plausibly translational, and exploratory-to avoid conflating preclinical observations with validated biomarkers. We critically evaluate FDA-approved and emerging agents within this framework, identify knowledge gaps, and outline future directions-including liquid biopsy-guided adaptive therapy, multi-omic resistance profiling, and biologically rational combination strategies-together with their feasibility constraints related to toxicity, sequencing, cost, and biomarker validation.
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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