Article Text
Abstract
Introduction/Background The Proactive Molecular Risk Classifier for Endometrial Cancer (ProMise) study identified four distinct prognostic endometrial cancer subgroups: POLEmut tumors with an excellent prognosis, p53-abnormal (p53abn) tumors with a poor prognosis and mismatch repair deficient (MMR-d), or non-specific molecular profile (NSMP) tumors with an intermediate prognosis. The aim of our prospective study was to evaluate the concordance between immunohistochemical and molecular classification in the diagnostic biopsy with the definitive histologic after total hysterectomy.
Methodology A prospective observational study of patients diagnosed with EC was conducted between January-2023 to September-2023. Sequencing of tumors for pathological exons in POLE and immunohistochemistry (IHC) for MMR proteins and p53 were applied to both endometrial biopsy and hysterectomy specimens after staging surgery from 37 individuals to identify molecular subgroups: MMR-d, POLEmut, and p53abn. The level of concordance for immunohistochemical and molecular profiles in both specimens was established with Cohen's kappa (k) estimates.
Results Preliminary data of concordance about molecular and IHC categorization between diagnostic biopsy and hysterectomy specimen was achieved in 37 cases. Concordance for the expression of MMR-d, p53abn, and POLEmut was respectively 92%, 92%, and 100%. Overall concordance showed an optimal level of agreement (k=0,81; 95%,0,67–0,95) with a good level for p53abn and MMR-d (k=0.77 and 0.77, respectively).
Conclusion Our results showed a high concordance between immunohistochemical and molecular alterations in diagnostic biopsy and definitive hysterectomy specimens. Considering the role attributed to diagnostic biopsy in the latest FIGO staging, these preliminary data are going to validate for the first time, in a prospective setting, the immunohistochemical and molecular analysis in the diagnostic biopsy. In the future, the analysis of oncogenic pathway status on diagnostic biopsy could be applied as pre-operative information to propose personalized surgery.
Disclosures None.