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. 2019 Oct:110:104284.
doi: 10.1016/j.yexmp.2019.104284. Epub 2019 Jul 10.

Identification of a novel diagnostic gene expression signature to discriminate uterine leiomyoma from leiomyosarcoma

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Identification of a novel diagnostic gene expression signature to discriminate uterine leiomyoma from leiomyosarcoma

Crystal L Adams et al. Exp Mol Pathol. 2019 Oct.

Abstract

Leiomyosarcomas are rare, aggressive tumors, which exhibit a poor prognosis regardless of stage. Pre-operative diagnosis can be difficult as leiomyosarcoma can mimic features of the more common, benign uterine leiomyoma. The goal of this study was to identify specific molecular markers to discriminate between uterine leiomyosarcomas and leiomyomas to facilitate timely, accurate diagnosis and treatment. Gene expression profiles of three leiomyosarcomas, leiomyomas, and normal myometrial tissue samples were analyzed using the Affymetrix Human Gene 1.0 ST Array. GC-robust multiarray average calculation and ANOVA statistical testing were used to identify differentially expressed genes. Sixty genes, with functional roles in tumor progression or suppression, exhibited divergent expression profiles in leiomyosarcomas and leiomyomas, compared to normal myometrium. Differential RNA and protein levels of seven genes, with the most discriminatory expression patterns, were confirmed by RTPCR and immunohistochemistry in an additional 10 leiomyosarcoma and 20 leiomyoma independent samples. CHI3L1, MELK, PRC1, TOP2A, and TPX2 were overexpressed in leiomyosarcomas, while HPGD and TES were overexpressed in leiomyomas. Distinguishing leiomyosarcomas from leiomyomas represents a diagnostic challenge, particularly in the context of minimally invasive surgery. The unique gene expression signatures identified in this study may accurately differentiate between these tumor types at the earliest stage and provides potential prognostic factors and novel therapeutic targets for the treatment of leiomyosarcoma.

Keywords: Diagnosis; Gene expression; Leiomyoma; Leiomyosarcoma; Molecular profiling.

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