Uterine Inflammatory Myofibroblastic Tumors: Proposed Risk Stratification Model Using Integrated Clinicopathologic and Molecular Analysis.


Journal

The American journal of surgical pathology
ISSN: 1532-0979
Titre abrégé: Am J Surg Pathol
Pays: United States
ID NLM: 7707904

Informations de publication

Date de publication:
01 02 2023
Historique:
pubmed: 8 11 2022
medline: 18 1 2023
entrez: 7 11 2022
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 36344483
doi: 10.1097/PAS.0000000000001987
pii: 00000478-202302000-00002
doi:

Substances chimiques

Anaplastic Lymphoma Kinase EC 2.7.10.1
Receptor Protein-Tyrosine Kinases EC 2.7.10.1

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

157-171

Informations de copyright

Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest and Source of Funding: This study was funded by the UCSF Department of Pathology Clinical Research Endowment awards granted to N.R.L., K.G., and S.E.U. J.T.R. reports that his spouse receives salary and stock options from Merck and Co. For the remaining authors none were declared.

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Auteurs

Nicholas R Ladwig (NR)

Departments of Pathology.

Gregory R Bean (GR)

Department of Pathology, Stanford University School of Medicine, Stanford, CA.

Melike Pekmezci (M)

Departments of Pathology.

John Boscardin (J)

Medicine and Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA.

Nancy M Joseph (NM)

Departments of Pathology.

Nicole Therrien (N)

Department of Pathology, Logan Health, Kalispell, MT.

Ankur R Sangoi (AR)

Department of Pathology, El Camino Hospital, Mountain View, CA.

Brian Piening (B)

Earle A. Chiles Research Institute, Providence Cancer Institute, Portland, OR.

Venkatesh Rajamanickam (V)

Earle A. Chiles Research Institute, Providence Cancer Institute, Portland, OR.

Matthew Galvin (M)

Earle A. Chiles Research Institute, Providence Cancer Institute, Portland, OR.

Brady Bernard (B)

Earle A. Chiles Research Institute, Providence Cancer Institute, Portland, OR.

Charles Zaloudek (C)

Departments of Pathology.

Joseph T Rabban (JT)

Departments of Pathology.

Karuna Garg (K)

Department of Pathology, Cleveland Clinic, Cleveland, OH.

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