A new strategy in molecular typing: the accuracy of an NGS panel for the molecular classification of endometrial cancers

BACKGROUND: Multiplatform molecular subtyping has been put into clinical practice as an alternative for The Cancer Genome Atlas (TCGA)-based classification for endometrial cancer (EC), which proved a tool for predicting prognosis and guiding treatment. The traditional methods for the molecular classification of EC only based on pathological indicators are not accurate. The present study aimed to classify EC on a molecular level and explored the possibility of a one-time solution to guide clinical treatment and prognosis determination by utilizing data from a next-generation sequencing (NGS) panel. The ultimate aim was to utilize multiplatform testing to overcome disadvantages of long detection periods and limitations in the information regarding genetic variation. METHODS: An NGS-panel was produced using FFPE samples isolated from 86 patients pathologically diagnosed with EC, and molecular subtyping was performed according to the recommended criteria. In addition, 45 matched samples from 86 patients were randomly selected for immunohistochemical (IHC) staining of P53, MLH1, MSH2, PMS2, and MSH6. Another 41 samples were not analyzed due to incomplete IHC staining results. SPSS (V26.0; IBM Corp., Armonk, NY, USA) was used for receiver operating characteristic (ROC) curve analysis. RESULTS: The molecular typing ratio of the 86 cases of endometrial carcinoma was calculated to be 16.28% for POLE type, 17.44% for MSI-H type, 47.67% for CN-L type, 12.79% for CN-H type, 5.81% for unclassified case. A comparison between IHC ProMisE-based subtyping and NGS-based subtyping of the 45 cases revealed that 3 cases were classified as MSI-H by IHC but as MSS by NGS. Among these cases, 1 case was deficient in MLH1 expression and PMS2 protein expression but had wild-type P53 protein, and the P53 sequencing data of this sample showed a missense mutation. Good overall consistency between the 2 determination methods was shown. Receiver operating characteristic (ROC) analysis showed that NGS had particularly high specificity and sensitivity for detecting the MSI and CN subtypes [area under the curve (AUC) =0.893>0.5, P=0.000029<0.01]. CONCLUSIONS: The present study suggested that NGS-based subtyping could serve as an effective approach for the molecular typing of EC. Both NGS and IHC bear their own unique advantages and challenges in clinical practice.