The Value of Integrating Hormone Receptors into Immunohistochemistry-Based Simplified Molecular Classification in...

To explore the clinical utility of immunohistochemistry (IHC)-based molecular classification and evaluate the distribution patterns and clinical implications of hormone receptor (HR) expression across different molecular classifications in endometrial cancer (EC).

This study retrospectively conducted simplified molecular classification based on IHC analysis of mismatch repair (MMR) and p53 protein from 322 EC patients admitted to the Obstetrics and Gynecology Department of Tianjin Medical University General Hospital from March 2017 to April 2024. 121 patients underwent WHO molecular classification by gene sequencing and IHC analysis. The application value of IHC-based simplified molecular classification was evaluated. The association between HR expression and molecular classification, and their combined value in predicting survival were analyzed.

In IHC-based simplified molecular classification, 23.3% (75/322), 59.9% (193/322), and 16.8% (54/322) patients were included in the MMR deficient (MMRd) group, MMR proficient (MMRp) group, and p53-abnormal (p53abn) group, respectively. This classification correlated significantly with various clinicopathological features such as age (p=0.001), body mass index (p=0.016), FIGO stage (p=0.002), histological subtype (p<0.001), and tumor differentiation (p<0.001). Furthermore, differences in disease-free survival (DFS) among these groups were statistically significant (p=0.002). Subgroup analyses revealed that HR expressions significantly affected DFS within molecular classification groups. Patients with positive estrogen receptor (ER) or progesterone receptor (PR) expression demonstrated better DFS than those with negative expression in these groups (ER in MMRp: p<0.001, PR in MMRp: p<0.001, ER in MMRd: p<0.001, PR in MMRd: p=0.032, ER in p53abn: p=0.052, PR in p53abn: p=0.019).

IHC-based simplified molecular classification is an economically viable and clinically applicable method that effectively stratifies patients by clinicopathological features and prognosis. Moreover, this approach allows stratification into different prognostic risk groups based on HR expression in molecular classification subgroups.