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Unsupervised Clustering of Immunohistochemical Markers to Define High-Risk Endometrial Cancer

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Pathology & Oncology Research

Abstract

Considerable heterogeneity exists in outcomes of early endometrial cancer (EC) according to the type but also the histological grading. Our goal was to describe the immunohistochemical profiles of type I EC according to grades and type II EC, to identify groups of interacting proteins using principal component analysis (PCA) and unsupervised clustering. We studied 13 immunohistochemical markers (steroid receptors, pro/anti-apoptotic proteins, metalloproteinases (MMP) and tissue inhibitor of metalloproteinase (TIMP), and CD44 isoforms known for their role in endometrial pathology. Co-expressed proteins associated with the type, grade and outcome of EC were determined by PCA and unsupervised clustering. PCA identified three functional groups of proteins from 43 tissue samples (38 type I and 5 type II EC): the first was characterized by p53 expression; the second by MMPs, bcl-2, PR B and CD44v6; and the third by ER alpha, PR A, TIMP-2 and CD44v3. Unsupervised clustering found two main clusters of proteins, with both type I grade 3 and type II EC exhibiting the same cluster profile. PCA and unsupervised clustering of immunohistochemical markers in EC contribute to a better comprehension and classification of the disease.

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Authors and Affiliations

  1. Service de Gynécologie-Obstétrique, Hôpital Tenon, AP-HP, 4 rue de la Chine, 75020, Paris, France

    Enora Laas, Marcos Ballester & Emile Daraï

  2. Institut Universitaire de Cancérologie, Université Pierre et Marie Curie, Paris 6, France

    Enora Laas, Marcos Ballester, Annie Cortez & Emile Daraï

  3. UMRS-938, Université Pierre et Marie Curie, Paris 6, France

    Marcos Ballester & Emile Daraï

  4. Service d’Anatomie Pathologie, Hôpital Tenon, AP-HP, 4 rue de la Chine, 75020, Paris, France

    Annie Cortez

  5. Service de gynécologie-obstétrique, Hôpital Alix de Champagne, CHU de Reims, 45 rue Cognacq-Jay, 51100, Reims, France

    Olivier Graesslin

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  1. Enora Laas
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  2. Marcos Ballester
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Correspondence to Enora Laas.

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Laas, E., Ballester, M., Cortez, A. et al. Unsupervised Clustering of Immunohistochemical Markers to Define High-Risk Endometrial Cancer. Pathol. Oncol. Res. 25, 461–469 (2019). https://doi.org/10.1007/s12253-017-0335-y

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