ArticleBioMed research international2021
Tumor Microenvironment Subtypes and Immune-Related Signatures for the Prognosis of Breast Cancer.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Subtype-Stratified Consensus Gene Signatures: Bridging Tumor Cell Biology, Immune Microenvironment, and Clinical Prognosis in Breast Cancer.International journal of molecular sciences · 2026Article
- A Histone Deacetylase Activity Model for the Discovery and Validation of Sepsis Biomarkers.Endocrine, metabolic & immune disorders drug targets · 2026Article
- Impact of Molecular Profiling on Therapy Management in Breast Cancer.Journal of clinical medicine · 2024Review
- Circ_BBS9 as an early diagnostic biomarker for lung adenocarcinoma: direct interaction with IFIT3 in the modulation of tumor immune microenvironment.Frontiers in immunology · 2024Article
- Construction of an immune-related gene signature for the prognosis and diagnosis of glioblastoma multiforme.Frontiers in oncology · 2022Article
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Authors and funding
3 authors.
Funding
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Abstract
objectiveTo better understand the immune-related heterogeneity of tumor microenvironment (TME) and establish a prognostic model for breast cancer in clinical practice.
methodsFor the 2620 breast cancer cases obtained from The Cancer Genome Atlas and the Molecular Taxonomy of Breast Cancer International Consortium, the CIBERSORT algorithm was performed to identify the immunological pattern, which underwent consensus clustering to curate TME subtypes, and biological profiles were explored by enrichment analysis. Random forest analysis, least absolute shrinkage, and selection operator analysis, in addition to uni- and multivariate COX regression analyses, were successively employed to precisely select the significant genes with prediction values for the introduction of the prognostic model.
resultsThree TME subtypes with distinct molecular and clinical features were identified by an unsupervised clustering approach, of which the molecular heterogeneity could be the result of cell cycle dysfunction and the variation of cytotoxic T lymphocyte activity. A total of 15 significant genes were proposed to construct the prognostic immune-related score system, and a predictive model was established in combination with clinicopathological characteristics for the survival of breast cancer patients. For immunological signatures, proactivity of CD8 T lymphocytes and hyperangiogenesis could be attributed to heterogeneous survival profiles.
conclusionsWe developed and validated a prognostic model based on immune-related signatures for breast cancer. This promising model is justified for validation and optimized in future clinical practice.
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