Work

Immune–metabolic heterogeneity and prognostic associations in breast cancer: development of an eight-gene risk model and preliminary functional characterization of NAT2

Year: 2026

Type: article

Abstract: Breast cancer is highly heterogeneous, and immune–metabolic interactions within the tumor microenvironment may contribute to differences in clinical outcome. In this study, transcriptomic, clinical, and somatic mutation data from TCGA-BRCA were analyzed, and the prognostic model was evaluated in GSE199633, a retrospective external transcriptomic cohort. Immune- and metabolism-related genes were integrated to define molecular subtypes and construct a prognostic model. Tumor microenvironment features, tumor mutational burden (TMB), and NAT2-related findings were further examined. Two molecular subtypes derived from the integrated immune- and metabolism-related candidate pool were identified. The 15-gene subtype panel was predominantly immune-related, with a smaller metabolism-related component. An eight-gene signature stratified patients into high- and low-risk groups across the training, internal testing, and retrospective external transcriptomic cohorts. Low-risk tumors showed an immune-hot-like phenotype, with higher immune and stromal scores, higher estimated cytotoxic lymphocyte abundance, increased immune checkpoint expression, and higher immunophenoscores, whereas high-risk tumors showed proliferation-related programs and relatively lower estimated immune-cell abundance. Additional correlation, network, and enrichment analyses showed reproducible correlation patterns and associations with immune, proliferative, and metabolic features rather than evidence of a single mechanistic pathway. The association between TMB and overall survival varied across risk-score groups. NAT2 was consistently upregulated in breast cancer, and its silencing reduced colony formation, migration, and invasion in vitro. Overall, the signature showed retrospective cross-cohort prognostic reproducibility, and NAT2 emerged as a risk-associated candidate gene with preliminary functional support; however, the generalisability of the model to prospectively recruited populations and routine clinical settings remains uncertain.

Source: Scientific Reports

DOI: 10.1038/s41598-026-74323-8