Predictive and Prognostic Values of Glycoprotein 96, Androgen Receptors, and Extranodal Extension in Sentinel Lymph Node-Positive Breast Cancer: An Immunohistochemical Retrospective Study
2024

Predictive and Prognostic Values of Glycoprotein 96 and Androgen Receptors in Breast Cancer

Sample size: 107 publication 10 minutes Evidence: moderate

Author Information

Author(s): Klarica Gembić, Grebić Damir, Gulić Tamara, Golemac Mijo, Avirović Manuela, Kumar Ashish

Primary Institution: Clinical Hospital Center Rijeka, Croatia

Hypothesis

This study investigates the association of glycoprotein 96 (GP96) and androgen receptor (AR) expression with clinicopathological factors and their potential role in predicting survival in breast cancer patients with sentinel lymph node involvement.

Conclusion

ENE in sentinel lymph nodes is the strongest predictor of non-sentinel lymph node involvement and could have prognostic significance, while GP96 expression does not influence survival outcomes.

Supporting Evidence

  • ENE in SLN was present in 35.51% of cases and was associated with a higher risk of non-SLN metastases.
  • High GP96 expression was linked to a greater relative risk for locoregional recurrence.
  • Negative AR expression correlated with higher rates of locoregional and distant recurrence.

Takeaway

The study found that a specific marker in lymph nodes can help predict if breast cancer has spread, which is important for treatment decisions.

Methodology

The study retrospectively enrolled 107 female patients with invasive breast cancer and positive sentinel lymph node biopsy, evaluating GP96 and AR expression through immunohistochemistry.

Limitations

The study is limited by its single-center, retrospective design and relatively small sample size.

Participant Demographics

All participants were female patients diagnosed with cT1-T2 invasive breast cancer.

Statistical Information

P-Value

p = 0.001 for ENE in SLN

Confidence Interval

95% CI 1.051–6.914 for ENE in SLN

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.3390/jcm13247665

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