Prognosis prediction and risk stratification of breast cancer patients based on a mitochondria-related gene signature

Area of Science:

• Oncology
• Genetics
• Metabolism

Background:

• Breast cancer is the most common malignancy globally, posing a significant threat to women's health.
• Mitochondrial function and metabolic reprogramming are increasingly recognized as crucial in cancer development and progression.

Purpose of the Study:

• To develop and validate a novel prognostic risk signature based on mitochondrial-related genes for breast cancer.
• To improve risk stratification and prognosis prediction in breast cancer patients.

Main Methods:

• Utilized transcriptome data and clinical features from TCGA (training) and METABRIC (validation) datasets.
• Developed a risk signature using LASSO-Cox regression, assessed prognostic efficacy with ROC curves, and created a Nomogram model.
• Conducted functional enrichment, immune infiltration, mutation landscape, and drug sensitivity analyses.

Main Results:

• Established an 8-mitochondrial-gene risk signature (ACSL1, ALDH2, MTHFD2, MRPL13, TP53AIP1, SLC1A1, ME3, BCL2A1) as an independent predictor of breast cancer survival (HR=3.028).
• The low-risk group demonstrated a more favorable prognosis, enhanced immune infiltration, distinct mutation profiles, and higher sensitivity to anti-tumor drugs.
• The high-risk group showed adverse trends in prognosis, immune infiltration, mutation landscape, and drug sensitivity.

Conclusions:

• The 8-gene mitochondrial risk signature is a novel and effective prognostic indicator for breast cancer.
• This signature facilitates patient stratification, offering valuable insights for personalized treatment strategies.
• Understanding the distinct molecular and immune characteristics of high- and low-risk groups can guide therapeutic interventions.