Novel Prognostic Model for Breast Cancer Offers New Paths for Precision Medicine

Strategic Insights -

A recent study from Wuhan, People's Republic of China, has developed and validated a novel prognostic model for breast cancer based on hypoxia-related genes and lactate metabolism-related genes. The aim of the study was to identify molecular subtypes capable of predicting patient prognosis and treatment response, thereby facilitating precision medicine strategies for breast cancer. The researchers utilized bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) breast cancer cohort, identifying hypoxia-related genes (HRGs) and lactate metabolism-related genes (LMRGs) using machine learning approaches.

Key Takeaways:

  • The study developed a novel prognostic model for breast cancer, the Hypoxia and Lactate Metabolism Prognostic Score (HLMPS), which demonstrated robust prognostic discrimination, with high-risk patients exhibiting significantly inferior overall survival compared to low-risk counterparts.
  • The HLMPS model revealed that patients with a high HLMPS tended to have dysregulation of cell cycle and neurodevelopmental pathways, while those with a low HLMPS exhibited activation of immune pathways, including T-cell receptor (TCR) signaling and antigen presentation.
  • The study concluded that future work should focus on validating the HLMPS model in larger, multicenter cohorts and determining its clinical applicability in guiding personalized treatment decisions for patients with breast cancer.
  • The researchers also found that the HLMPS model demonstrated sensitivity to various drugs, including irinotecan, palbociclib, lapatinib, and sorafenib.
  • The study highlights the potential of precision medicine strategies that integrate HRGs and LMRGs based on tumor microenvironment (TME) features.

Statistics:

  • The study used 1,079 tumor samples and 99 normal samples from The Cancer Genome Atlas (TCGA) breast cancer cohort.
  • The research utilized 5 independent validation cohorts (GSE19615, GSE20685, GSE20711, GSE42568, GSE58812) retrieved from the Gene Expression Omnibus (GEO) database.
  • The Hypoxia and Lactate Metabolism Prognostic Score (HLMPS) model demonstrated high-risk patients exhibiting significantly inferior overall survival compared to low-risk counterparts (training set areas under the curve (AUCs): 0.76, 0.77, 0.74 at 1/3/5 years; validation sets AUCs: 0.61, 0.65, 0.67 at 1/3/5 years).
  • Functional enrichment analysis revealed that patients with a high HLMPS tended to have dysregulation of cell cycle and neurodevelopmental pathways, while those with a low HLMPS exhibited activation of immune pathways.

Sources:

  • Development and validation of a Hypoxia and Lactate Metabolism Prognostic Score (HLMPS) for breast cancer using machine learning. Translational Cancer Research, 2025;14(7):4399-4415.
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