Uterine Inflammatory Myofibroblastic Tumors

病理 危险分层 转录组 医学 生物 肿瘤科 内科学 基因 基因表达 生物化学
作者
Nicholas R. Ladwig,Gregory R. Bean,Melike Pekmezci,John Boscardin,Nancy M. Joseph,Nicole L. Therrien,Ankur R. Sangoi,Brian Piening,Venkatesh Rajamanickam,Matthew Galvin,Brady Bernard,Charles Zaloudek,Joseph T. Rabban,Karuna Garg,Sarah E. Umetsu
出处
期刊:The American Journal of Surgical Pathology [Lippincott Williams & Wilkins]
卷期号:47 (2): 157-171 被引量:31
标识
DOI:10.1097/pas.0000000000001987
摘要

Inflammatory myofibroblastic tumor (IMT) of the uterus is a rare mesenchymal tumor with largely benign behavior; however, a small subset demonstrate aggressive behavior. While clinicopathologic features have been previously associated with aggressive behavior, these reports are based on small series, and these features are imperfect predictors of clinical behavior. IMTs are most commonly driven by ALK fusions, with additional pathogenic molecular alterations being reported only in rare examples of extrauterine IMTs. In this study, a series of 11 uterine IMTs, 5 of which demonstrated aggressive behavior, were evaluated for clinicopathologic variables and additionally subjected to capture-based next-generation sequencing with or without whole-transcriptome RNA sequencing. In the 6 IMTs without aggressive behavior, ALK fusions were the sole pathogenic alteration. In contrast, all 5 aggressive IMTs harbored pathogenic molecular alterations and numerous copy number changes in addition to ALK fusions, with the majority of the additional alterations present in the primary tumors. We combined our series with cases previously reported in the literature and performed statistical analyses to propose a novel clinicopathologic risk stratification score assigning 1 point each for: age above 45 years, size≥5 cm,≥4 mitotic figures per 10 high-power field, and infiltrative borders. No tumors with 0 points had an aggressive outcome, while 21% of tumors with 1 to 2 points and all tumors with ≥3 points had aggressive outcomes. We propose a 2-step classification model that first uses the clinicopathologic risk stratification score to identify low-risk and high-risk tumors, and recommend molecular testing to further classify intermediate-risk tumors.
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