{
  "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.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "name": "Yuchen Li"
    },
    {
      "name": "Shaochao Zhan"
    },
    {
      "name": "Ting Li"
    },
    {
      "name": "Chengjian Xie"
    },
    {
      "name": "Tao Yang"
    },
    {
      "name": "Yi Yu"
    },
    {
      "name": "Zhaohui Guo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2g1gkx5kp3fa2.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-74323-8",
  "fulltext_url": null,
  "id": "2g1gkx5kp3fa2",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-74323-8",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1306|Breast Cancer Treatment Studies"
    ]
  ],
  "openalex": "W7219749529",
  "pdf_url": "https://www.nature.com/articles/s41598-026-74323-8_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-04",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/2g1gkx5kp3fa2.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.1038/s41598-026-74323-8",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-74323-8"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:1306|Breast Cancer Treatment Studies",
      "subfield": "oncology"
    }
  ],
  "title": "Immune–metabolic heterogeneity and prognostic associations in breast cancer: development of an eight-gene risk model and preliminary functional characterization of NAT2",
  "title_text": "Immune–metabolic heterogeneity and prognostic associations in breast cancer: development of an eight-gene risk model and preliminary functional characterization of NAT2",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/2g1gkx5kp3fa2",
  "venue": "Scientific Reports",
  "versions": []
}