Document Type : Original Article
Authors
1
M. S. Ramaiah Memorial Hospital, Bengaluru, Karnataka, India.
2
The Gujarat Cancer and Research Institute, Ahmedabad, Gujarat, India.
3
Consultant Pathologist, Apollo, Chennai, Tamil Nadu, India.
4
All India Institute of Medical Sciences, Mangalagiri, Andhra Pradesh, India.
10.21608/eajbsd.2024.390659
Abstract
Background: High grade Endometrial carcinomas (ECs) include type II and grade 3 endometrioid carcinoma. Challenges include risk stratification on diagnostic biopsy and predictive biomarker assessment post- surgery for adjuvant treatment. Distinguishing grade 3 endometrioid carcinoma and type II EC is a challenge. We analyzed ER, PR, p53, Her2 expression in histotypes of EC and their utility to distinguish type I and II tumors. Materials and methods: A prospective study involving 106 cases of EC, categorized into low and high-grade ECs was conducted to analyze clinicopathological parameters and expression of several biomarkers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2) and p53, using immunohistochemistry (IHC). The study specifically focused on differentiating grade 3 endometrioid carcinomas from non-endometrioid tumors. Results: ER was found to be sensitive and specific (90.42% & 80% respectively) in differentiating endometrioid carcinoma from serous carcinoma. PR was identified as specific in differentiating high-grade endometrioid carcinoma from serous carcinoma. p53 exhibited high sensitivity (100%) in differentiating high-grade endometrioid carcinoma from serous carcinoma and highly specific in differentiating endometrioid carcinoma from serous carcinoma, further emphasizing its importance as a diagnostic marker in distinguishing between these subtypes. Conclusion: The use of ER, PR, and p53 as a panel offers high sensitivity and specificity in EC diagnosis and classification, particularly in high-grade cases. Additionally, HER2 detection in type II ECs provides valuable information for targeted therapy selection, highlighting the importance of molecular profiling in guiding personalized treatment approaches for endometrial cancer.
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