ArticleBreast cancer research and treatment2025
Exploring the Nottingham classification: assessing gene expression profiles in breast cancer patients and their association with outcomes.
Article in Breast cancer research and treatment, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Molecular cartography of breast cancer: decoding genomes, heterogeneity and the tumor microenvironment for personalized targeted therapeutics.Molecular biology reports · 2026Review
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15 authors.
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Abstract
backgroundBreast cancer remains a major global health concern due to its high incidence and mortality among women. Accurate prognostic stratification is essential for guiding treatment and improving outcomes. The Nottingham grading system evaluates tumor differentiation based on architectural features, nuclear atypia, and mitotic activity, serving as a key tool in assessing breast cancer prognosis.
objectivesTo investigate gene expression patterns associated with histological grades and immunohistochemical subtypes of breast cancer, and to explore their relationship with clinical outcomes, including recurrence, overall survival (OS), and disease-free survival (DFS).
methodsIn a cohort of 82 breast cancer patients, gene expression profiling was performed using the nCounter® Breast Cancer 360™ panel. Tumors were classified according to the Nottingham grading system. Differential gene expression analysis was conducted across histological grades and subtypes, with subsequent correlation to clinical outcomes.
resultsNearly half of the patients exhibited histological grade 3 tumors. Six genes-BIRC5, CDC6, FOXM1, TOP2A, MYBL2, and UBE2C-were significantly overexpressed in high-grade tumors. These genes are involved in key cell cycle regulatory pathways. Their overexpression was significantly associated with higher rates of disease recurrence and poorer OS and DFS, highlighting their prognostic value.
conclusionsThis study reinforces the prognostic utility of histological grading and reveals a set of cell cycle-related genes whose overexpression is linked to adverse outcomes in breast cancer. These findings suggest potential biomarkers for risk stratification and therapeutic targeting, offering insights for personalized management of patients beyond traditional histological assessments.
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