Digital Quantification of Ki-67 and PHH3 in the Classification of Uterine Smooth Muscle Tumors

Uterine smooth muscle tumors are the most common tumors of the female genital tract and include leiomyoma (LM) and its variants, smooth muscle tumors of uncertain malignant potential (STUMP), and leiomyosarcoma (LMS). Accurate diagnosis of LMS is determined by nuclear atypia, mitotic count, and the...

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Bibliographic Details
Published inInternational journal of gynecological pathology Vol. 40; no. 6; p. 549
Main Authors Cao, Connie D, Rico-Castillo, Jesus, De Cotiis, Dan, Richard, Scott D, Rosenblum, Norman G, Chan, Joanna S Y
Format Journal Article
LanguageEnglish
Published United States 01.11.2021
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Summary:Uterine smooth muscle tumors are the most common tumors of the female genital tract and include leiomyoma (LM) and its variants, smooth muscle tumors of uncertain malignant potential (STUMP), and leiomyosarcoma (LMS). Accurate diagnosis of LMS is determined by nuclear atypia, mitotic count, and the presence or absence of tumor cell necrosis, a process which is often difficult and subjective. In this study, we correlated digital quantification of proliferation marker Ki-67 and mitotic marker phosphohistone H3 (PHH3) to mitotic count, classification of uterine smooth muscle tumors, and clinical outcomes. A total of 39 cases (17 LMS, 5 STUMP, 10 LM with bizarre nuclei, and 7 LM) were included. Mitotic count, Ki-67, and PHH3 were significantly correlated. When comparing the LMS group to the STUMP, LM with bizarre nuclei, and LM groups combined, LMS showed a significantly greater digital quantification of Ki-67 (median 10.6% vs. 0.4%, P<0.001) and PHH3 (median 0.5% vs. 0.14%, P=0.022). Ki-67 was a better predictor of LMS compared with PHH3 (area under the curve 0.92 vs. 0.73, P=0.017). Above a threshold Ki-67 value of 3.8%, the sensitivity was 82% and specificity was 91%. Clinical outcomes were available for 10 patients (8 LMS and 2 STUMP), and inferior progression-free survival was noted for patients with higher Ki-67 values. Overall, this study suggests that digital quantification of Ki-67 can potentially aid in diagnosis of LMS.
ISSN:1538-7151
DOI:10.1097/PGP.0000000000000739