TY - JOUR
T1 - Immunohistochemical panel to differentiate endometrial stromal sarcoma, uterine leiomyosarcoma and leiomyoma
T2 - Something old and something new
AU - Hwang, Helena
AU - Matsuo, Koji
AU - Duncan, Kara
AU - Pakzamir, Elham
AU - Pham, Huyen Q.
AU - Correa, Adrian
AU - Fedenko, Alexander
AU - Mhawech-Fauceglia, Paulette
PY - 2015/9/1
Y1 - 2015/9/1
N2 - Aims To evaluate an immunohistochemical panel differentiating endometrial stromal sarcoma (ESS) from uterine leiomyosarcoma (ULMS) and leiomyoma (LM). Methods 94 cases (28 ESS, 41 ULMS, 25 LM) were retrieved and arrayed. 10 immunomarkers (estrogen receptor (ER), progesterone receptor (PR), CD10, smooth muscle actin, desmin, h-caldesmon, transgelin, GEM, ASC1, stathmin1) were used. A predictive model was constructed and examined by receiver operating characteristics curve analysis to determine area under the curve (AUC). Results The combination of ER+/PR+/CD10+/GEM-/hcaldesmon-/ transgelin- can predict ESS versus ULMS with AUC predictive value of 0.872 (95% CI 0.784 to 0.961, p<0.0001). The combination of ER+/PR+/CD10+/ h-caldesmon-/transgelin- can predict low grade (LG) ESS from 'LG' ULMS with AUC predictive value of 0.914 (95% CI 0.832 to 0.995, p<0.0001). Finally, ULMS and ESS, including the LGs, were more likely to be stathmin1+ than LM. Conclusions Due to the different clinical course and management, adding novel antibodies (GEM, transgelin) to the well established immunohistochemistry panel seemed to be useful in distinguishing ESS from ULMS and LG ESS from 'LG' ULMS. Finally, stathmin1 expression could be of value in differentiating LM from uterine sarcomas.
AB - Aims To evaluate an immunohistochemical panel differentiating endometrial stromal sarcoma (ESS) from uterine leiomyosarcoma (ULMS) and leiomyoma (LM). Methods 94 cases (28 ESS, 41 ULMS, 25 LM) were retrieved and arrayed. 10 immunomarkers (estrogen receptor (ER), progesterone receptor (PR), CD10, smooth muscle actin, desmin, h-caldesmon, transgelin, GEM, ASC1, stathmin1) were used. A predictive model was constructed and examined by receiver operating characteristics curve analysis to determine area under the curve (AUC). Results The combination of ER+/PR+/CD10+/GEM-/hcaldesmon-/ transgelin- can predict ESS versus ULMS with AUC predictive value of 0.872 (95% CI 0.784 to 0.961, p<0.0001). The combination of ER+/PR+/CD10+/ h-caldesmon-/transgelin- can predict low grade (LG) ESS from 'LG' ULMS with AUC predictive value of 0.914 (95% CI 0.832 to 0.995, p<0.0001). Finally, ULMS and ESS, including the LGs, were more likely to be stathmin1+ than LM. Conclusions Due to the different clinical course and management, adding novel antibodies (GEM, transgelin) to the well established immunohistochemistry panel seemed to be useful in distinguishing ESS from ULMS and LG ESS from 'LG' ULMS. Finally, stathmin1 expression could be of value in differentiating LM from uterine sarcomas.
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U2 - 10.1136/jclinpath-2015-202915
DO - 10.1136/jclinpath-2015-202915
M3 - Article
C2 - 25991737
AN - SCOPUS:84940036540
SN - 0021-9746
VL - 68
SP - 710
EP - 717
JO - Journal of clinical pathology
JF - Journal of clinical pathology
IS - 9
ER -