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Author Spotlight: Advancing Reproductive Immunology with a Protocol for the Quantitative Evaluation of Endometrial Immune Cells
Published on: October 13, 2023
Integration of clinical sequencing and immunohistochemistry for the molecular classification of endometrial carcinoma
Eric Rios-Doria1, Amir Momeni-Boroujeni2, Claire F Friedman3
1Gynecology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Purpose:
Using next generation sequencing (NGS), The Cancer Genome Atlas (TCGA) found that endometrial carcinomas (ECs) fall under one of four molecular subtypes, and a POLE mutation status, mismatch repair (MMR) and p53 immunohistochemistry (IHC)-based surrogate has been developed. We sought to retrospectively classify and characterize a large series of unselected ECs that were prospectively subjected to clinical sequencing by utilizing clinical molecular and IHC data.
Experimental Design:
All patients with EC with clinical tumor-normal MSK-IMPACT NGS from 2014 to 2020 (n = 2115) were classified by integrating molecular data (i.e., POLE mutation, TP53 mutation, MSIsensor score) and MMR and p53 IHC results. Survival analysis was performed for primary EC patients with upfront surgery at our institution.
Results:
Utilizing our integrated approach, significantly more ECs were molecularly classified (1834/2115, 87%) as compared to the surrogate (1387/2115, 66%, p < 0.001), with an almost perfect agreement for classifiable cases (Kappa 0.962, 95% CI 0.949-0.975). Discrepancies were primarily due to TP53 mutations in p53-IHC-normal ECs. Of the 1834 ECs, most were of copy number (CN)-high molecular subtype (40%), followed by CN-low (32%), MSI-high (23%) and POLE (5%). Histologic and genomic variability was present amongst all molecular subtypes. Molecular classification was prognostic in early- and advanced-stage disease, including early-stage endometrioid EC.
Conclusions:
The integration of clinical NGS and IHC data allows for an algorithmic approach to molecularly classifying newly diagnosed EC, while overcoming issues of IHC-based genetic alteration detection. Such integrated approach will be important moving forward given the prognostic and potentially predictive information afforded by this classification.
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