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Background <p>Breast 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.</p> Objectives <p>To 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).</p> Methods <p>In 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.</p> Results <p>Nearly 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.</p> Conclusions <p>This 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.</p>

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Exploring the Nottingham classification: assessing gene expression profiles in breast cancer patients and their association with outcomes

  • 期刊论文

  • 发表日期：

    2025年5月28日

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  • Ana Julia Aguiar de Freitas,
  • Rhafaela Lima Causin,
  • Stéphanie Calfa,
  • Iara Viana Vidigal Santana,
  • Mariana Balie,
  • Welinton Hirai,
  • Ana Carolina Laus,
  • Hadson Silva Araujo,
  • Cassio Murilo Hidalgo Filho,
  • Fernanda de Oliveira Bombarda,
  • Vinicius Duval da Silva,
  • Adriane Feijó Evangelista,
  • Cristiano de Pádua Souza,
  • Rui Manuel Reis,
  • Márcia Maria Chiquitelli Marques

摘要

Background

Breast 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.

Objectives

To 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).

Methods

In 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.

Results

Nearly 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.

Conclusions

This 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.