4.6 Article

Integration of clinical sequencing and immunohistochemistry for the molecular classification of endometrial carcinoma

Journal

GYNECOLOGIC ONCOLOGY
Volume 174, Issue -, Pages 262-272

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ygyno.2023.05.059

Keywords

Molecular classification; Endometrial carcinoma; Clinical sequencing; Mutation; Immunohistochemistry

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By integrating molecular data and immunohistochemistry data, an algorithmic approach was developed to molecularly classify endometrial carcinomas (ECs), resulting in more ECs being classified molecularly compared to using immunohistochemistry. The integrated approach showed prognostic value in both early-stage and advanced-stage EC.
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 clas-sify 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 muta-tions 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 molec-ularly classifying newly diagnosed EC, while overcoming issues of IHC-based genetic alteration detection.

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