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Molecular-Based Immunohistochemical Algorithm for Uterine Leiomyosarcoma Diagnosis.
Momeni-Boroujeni, Amir; Yousefi, Elham; Balakrishnan, Ridin; Riviere, Stephanie; Kertowidjojo, Elizabeth; Hensley, Martee L; Ladanyi, Marc; Ellenson, Lora H; Chiang, Sarah.
Afiliação
  • Momeni-Boroujeni A; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Yousefi E; Department of Pathology and Cell Biology, Columbia University, New York, New York.
  • Balakrishnan R; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Riviere S; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Kertowidjojo E; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Hensley ML; Department of Medicine, Gynecologic Medical Oncology Service, Memorial Sloan Kettering Cancer Center, New York, New York; Department of Medicine, Weill Cornell Medical College, New York, New York.
  • Ladanyi M; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Ellenson LH; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Chiang S; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York. Electronic address: chiangs@mskcc.org.
Mod Pathol ; 36(4): 100084, 2023 04.
Article em En | MEDLINE | ID: mdl-36788080
ABSTRACT
The morphologic assessment of uterine leiomyosarcoma (LMS) may be challenging, and diagnostic immunohistochemical (IHC) analysis is currently lacking. We evaluated the genomic landscape of 167 uterine LMS by targeted next-generation sequencing (NGS) to identify common genomic alterations. IHC analyses corresponding to these genomic landmarks were applied to a test cohort of 16 uterine LMS, 6 smooth muscle tumors of uncertain malignant potential (STUMP), and 6 leiomyomas with NGS data and a validation cohort of 8 uterine LMS, 12 STUMP, 21 leiomyomas and leiomyoma variants, 7 low-grade endometrial stromal sarcomas, and 2 diagnostically challenging uterine smooth muscle tumors. IHC results were individually interpreted by 3 pathologists blinded to NGS data. Overall, 94% of LMS showed ≥1 genomic alteration involving TP53, RB1, ATRX, PTEN, CDKN2A, or MDM2, with 80% showing alterations in ≥2 of these genes. In the test cohort, an initial panel of p53, Rb, PTEN, and ATRX was applied, followed by a panel of DAXX, MTAP, and MDM2 in cases without abnormalities. Abnormal p53, Rb, PTEN, and ATRX IHC expression was seen in 75%, 88%, 44%, and 38% of LMS, respectively, in the test cohort. Two or more abnormal IHC results among these markers were seen in 81% of LMS. STUMPs demonstrated only 1 IHC abnormality involving these markers. No IHC abnormalities were seen in leiomyomas. In the validation cohort, abnormal p53, Rb, and PTEN IHC results were seen in LMS, whereas rare STUMP or leiomyomas with bizarre nuclei showed IHC abnormalities involving only 1 of the markers. Abnormalities in ≥2 markers were present in both diagnostically challenging smooth muscle tumors, confirming LMS. Concordance was excellent among pathologists in the interpretation of IHC (κ = 0.97) and between IHC and NGS results (κ = 0.941). Uterine LMS exhibit genomic landmark alterations for which IHC surrogates exist, and a diagnostic algorithm involving molecular-based IHC may aid in the evaluation of unusual uterine smooth muscle tumors.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Uterinas / Algoritmos / Imuno-Histoquímica / Leiomiossarcoma Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Uterinas / Algoritmos / Imuno-Histoquímica / Leiomiossarcoma Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article