Heterogeneity and potential therapeutic insights for triple-negative breast cancer based on metabolic-associated molecular subtypes and genomic mutations

Area of Science:

• Oncology
• Metabolic Reprogramming
• Cancer Heterogeneity

Background:

• Triple-negative breast cancer (TNBC) presents a significant therapeutic challenge due to its poor prognosis and lack of effective treatments.
• Metabolic reprogramming is a key hallmark of cancer, influencing tumorigenesis, diagnosis, prognosis, and treatment response.
• Understanding TNBC's metabolic heterogeneity is crucial for developing targeted therapies.

Purpose of the Study:

• To categorize metabolic patterns within TNBC to address its heterogeneity.
• To identify distinct TNBC subtypes based on metabolic characteristics.
• To provide a foundation for targeted therapeutic strategies in TNBC.

Main Methods:

• Utilized The Cancer Genome Atlas (TCGA) data from 115 TNBC patients to form a virtual cohort.
• Identified differentially expressed genes (DEGs) and applied analyses to five independent datasets for subtype verification.
• Evaluated subtypes based on prognosis, metabolic features, immune infiltration, clinical characteristics, somatic mutations, and drug sensitivity.

Main Results:

• Identified two distinct metabolic subtypes of TNBC: C1 and C2.
• C1 exhibited high immune checkpoint gene expression and sensitivity to PD-1 inhibitors.
• C2 showed significant metabolic pathway variations, lacked immune signatures, had a late pathological stage, low immune infiltration, poor prognosis, and activated PI3K/angiogenesis pathways with specific mutations (PIK3CA, KMT2D, KMT2C).
• Developed a 100-gene classifier and identified AKR1B10 as a potential biomarker for C2 subtypes.

Conclusions:

• Two TNBC subtypes with distinct metabolic phenotypes were identified, offering new insights into TNBC heterogeneity.
• The findings provide a theoretical basis for developing novel therapeutic strategies.
• AKR1B10 may serve as a predictive biomarker for the C2 subtype.