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Updated: Dec 27, 2025
Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer
Published on: March 17, 2016
Targeting Metabolic Deregulation Landscapes in Breast Cancer Subtypes
Erandi A Serrano-Carbajal1, Jesús Espinal-Enríquez1,2, Enrique Hernández-Lemus1,2
1Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico.
Abstract:
Metabolic deregulation is an emergent hallmark of cancer. Altered patterns of metabolic pathways result in exacerbated synthesis of macromolecules, increased proliferation, and resistance to treatment via alteration of drug processing. In addition, molecular heterogeneity creates a barrier to therapeutic options. In breast cancer, this broad variation in molecular metabolism constitutes, simultaneously, a source of prognostic and therapeutic challenges and a doorway to novel interventions. In this work, we investigated the metabolic deregulation landscapes in breast cancer molecular subtypes. Such landscapes are the regulatory signatures behind subtype-specific metabolic features. n = 735 breast cancer samples of the Luminal A, Luminal B, Her2+, and Basal subtypes, as well as n = 113 healthy breast tissue samples were analyzed. By means of a single-sample-based algorithm, deregulation for all metabolic pathways in every sample was determined. Deregulation levels match almost perfectly with the molecular classification, indicating that metabolic anomalies are closely associated with gene-expression signatures. Luminal B tumors are the most deregulated but are also the ones with higher within-subtype variance. We argued that this variation may underlie the fact that Luminal B tumors usually present the worst prognosis, a high rate of recurrence, and the lowest response to treatment in the long term. Finally, we designed a therapeutic scheme to regulate purine metabolism in breast cancer, independently of the molecular subtype. This scheme is founded on a computational tool that provides a set of FDA-approved drugs to target pathway-specific differentially expressed genes. By providing metabolic deregulation patterns at the single-sample level in breast cancer subtypes, we have been able to further characterize tumor behavior. This approach, together with targeted therapy, may open novel avenues for the design of personalized diagnostic, prognostic, and therapeutic strategies.
Insights
Metabolic deregulation in breast cancer subtypes is linked to gene expression. Luminal B tumors show the most variation, potentially explaining their poor prognosis and treatment resistance. A new therapeutic strategy targets purine metabolism.
Area of Science:
- Oncology
- Metabolomics
- Genomics
Background:
- Metabolic deregulation is a key feature of cancer, impacting tumor growth, proliferation, and treatment response.
- Breast cancer exhibits significant molecular and metabolic heterogeneity, posing challenges for diagnosis and therapy.
- Understanding subtype-specific metabolic landscapes is crucial for developing targeted interventions.
Purpose of the Study:
- To investigate metabolic deregulation landscapes across different breast cancer molecular subtypes.
- To correlate metabolic anomalies with gene-expression signatures and subtype classification.
- To develop a subtype-independent therapeutic strategy targeting metabolic pathways.
Main Methods:
- Analysis of metabolic deregulation in 735 breast cancer samples (Luminal A, Luminal B, Her2+, Basal) and 113 healthy controls.
- Application of a single-sample-based algorithm to quantify metabolic pathway deregulation.
- Development of a computational tool using FDA-approved drugs for targeted purine metabolism regulation.
Main Results:
- Metabolic deregulation patterns closely align with molecular subtypes and gene-expression signatures.
- Luminal B tumors exhibit the highest deregulation and within-subtype variance, correlating with poorer outcomes.
- A therapeutic scheme targeting purine metabolism was designed, applicable across subtypes.
Conclusions:
- Metabolic deregulation is a fundamental characteristic of breast cancer subtypes.
- Subtype-specific metabolic profiles, particularly in Luminal B, influence tumor behavior and treatment efficacy.
- Personalized diagnostic, prognostic, and therapeutic strategies can be advanced by integrating metabolic deregulation analysis with targeted therapies.
