# Expression of PTEN and p53 and Their Clinicopathological Correlation in Breast Cancer

## TL;DR

This study examines how PTEN and p53 expression relates to breast cancer severity and patient outcomes.

## Contribution

The study identifies clinicopathological correlations of PTEN and p53 in breast cancer.

## Key findings

- PTEN loss was linked to higher tumor grade and lymph node metastasis.
- p53 overexpression was associated with aggressive tumor features and premenopausal status.
- An inverse relationship was observed between PTEN loss and p53 positivity.

## Abstract

Background: Breast cancer is one of the most common malignancies in women and is a major cause of cancer-related mortality. Alterations in the expression of tumor suppressor genes such as PTEN and p53 may influence tumor behavior and prognosis. This study aimed to evaluate the immunohistochemical expression of PTEN and p53 in breast carcinoma and analyze their association with clinicopathological parameters.

Methods: A cross-sectional study was conducted on 50 histologically confirmed female breast carcinoma cases. Immunohistochemistry (IHC) for PTEN and p53 was performed using standard protocols. PTEN expression was assessed based on cytoplasmic and nuclear staining intensity and categorized as positive or negative. p53 expression was evaluated as nuclear positivity and categorized similarly. Statistical analysis was done using standard significance tests.

Results: The mean patient age was 49.8 years. The most common histologic subtype was infiltrating ductal carcinoma (IDC). Loss of PTEN expression was found in most of the cases and was associated with higher tumor grade and lymph node metastasis. Most cases exhibited p53 overexpression, which showed trends toward an association with higher tumor grade, premenopausal status, and lymph node positivity. An inverse relationship was noted between PTEN loss and p53 positivity.

Conclusions: PTEN loss and p53 overexpression were frequent in breast carcinoma and correlated with aggressive tumor features. Combined assessment of these biomarkers may provide prognostic value and support therapeutic decision-making in breast cancer.