Molecular Classification of Endometrial Cancer of Chinese Population

Background: Endometrial cancer (EC) is one of the most prevalent gynecologic tumors. Current diagnosis and treatment of EC no longer rely solely on traditional histopathological classification. Nevertheless, molecular classification of EC demonstrated clear prognostic value and may guide clinical decision-making. Methods: : In this study, archived formalin-fixed paraffin-embedded (FFPE) tissue from 229 EC patients were employed for further research. Four subtypes [ POLE ultramutated ( POLE mut), MMR-deficient (MMR-D), p53 abnormal (p53abn), and no specific molecular profile (NSMP)] were stratified by next-generation sequencing (NGS) panel (Amoy Diagnostics, Xiamen, China) targeting POLE , TP53 , BRCA1 , and BRCA2 genes and microsatellite instability (MSI) status. Immunohistochemistry (IHC) was applied to detect the expression of P53, MMR and other related proteins. Results: : Distributions of the EC subtype in 229 patients were 12 (5.24%) of POLE mut, 35 (15.28%) of MMR-D, 36 (15.72%) of p53abn, and 146 (63.76%) of NSMP. Compared to published results of EC subtypes in Caucasian including TCGA, ProMisE as well as TransPORTEC, real-world data on Chinese EC displayed a significantly larger proportion of NSMP/CNL (copy number low). In addition, it was found that BRCA2 appeared to be more prevalent in EC than BRCA1 . Further analysis revealed that the overall consistency for NGS-based and IHC-based P53 abnormalities detection and MSI/MMR status assessment were as high as 89.08% and 96.94%, respectively, and about half of truncating mutations can result in detectable (but nonfunctional) p53 protein yielding a normal wild-type staining pattern . Conclusions: : Chinese ECs have unique molecular characteristics. In order to perform accurate molecular typing of Chinese ECs, more molecular indicators that match the characteristics of the Chinese population should be added to the existing classifiers. Further analysis revealed a high consistency between NGS and IHC in P53 detection and MSI evaluation.