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

免疫组织化学 医学 肿瘤科 内科学 病理
作者
Eric Rios‐Doria,Amir Momeni Boroujeni,Claire F. Friedman,Pier Selenica,Qin Zhou,Michelle Wu,Antonio Marra,Mario M. Leitão,Alexia Iasonos,Kaled M. Alektiar,Yukio Sonoda,Vicky Makker,Elizabeth L. Jewell,Ying L. Liu,Dennis Chi,Dimitry Zamarin,Nadeem R. Abu‐Rustum,Carol Aghajanian,Jennifer J. Mueller,Lora H. Ellenson
出处
期刊:Gynecologic Oncology [Elsevier BV]
卷期号:174: 262-272 被引量:51
标识
DOI:10.1016/j.ygyno.2023.05.059
摘要

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.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.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.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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