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  • Title: The Genomic Heterogeneity of FIGO Grade 3 Endometrioid Carcinoma Impacts Diagnostic Accuracy and Reproducibility.
    Author: Hussein YR, Broaddus R, Weigelt B, Levine DA, Soslow RA.
    Journal: Int J Gynecol Pathol; 2016 Jan; 35(1):16-24. PubMed ID: 26166718.
    Abstract:
    The Cancer Genome Atlas (TCGA) identified 4 groups of endometrial carcinomas based on an integrated genomic characterization: POLE ultramutated (POLE), microsatellite instability-high, copy number-low (CN-L), and copy number-high (CN-H). In that study, CN-H comprised all of the serous carcinoma cases and 25% of all International Federation of Gynecology and Obstetrics (FIGO) Grade 3 endometrioid carcinoma cases. In this study, 2 expert gynecologic pathologists undertook a morphologic reassessment of the FIGO Grade 3 endometrioid carcinoma subset of the TCGA study cohort, including an analysis for evidence of serous differentiation. Interobserver variability κvalues are reported for the histologic evaluation of all 4 genomic clusters, and diagnostic discrepancies are discussed. Overall, there were 55 agreements, 6 disagreements, and 14 deferrals. Of the 75 cases analyzed, 6 cases had a consensus morphologic diagnosis of serous carcinoma, but only 2 of these cases had a serous carcinoma genotype, whereas the remaining 4 cases were genotypically endometrioid carcinoma. For the CN-H group, 2 of 15 cases were serous carcinoma by morphology and genotype, whereas at least 1 pathologist interpreted the remaining 13 cases as endometrioid carcinoma. The interobserver agreement rate was highest in the CN-L group (90%; κ=0.9), compared with the other genomic groups (POLE: 62%, κ=0.55; microsatellite instability-high: 78%, κ=0.74; and CN-H: 53%, κ=0.48). Our review confirms that most high-grade endometrial carcinomas diagnosed by TCGA as FIGO Grade 3 endometrioid carcinoma are indeed endometrioid carcinomas by morphology and genotype, and that the reproducibility of histologic diagnosis between pathologists varies between the TCGA-integrated genomic clusters.
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