miR-497-5p Decreased Expression Associated with High-Risk Endometrial Cancer

被引:21
|
作者
Fridrichova, Ivana [1 ]
Kalinkova, Lenka [1 ]
Karhanek, Miloslav [2 ]
Smolkova, Bozena [3 ]
Machalekova, Katarina [4 ]
Wachsmannova, Lenka [1 ]
Nikolaieva, Nataliia [1 ]
Kajo, Karol [4 ]
机构
[1] Slovak Acad Sci, Dept Genet, Biomed Res Ctr, Canc Res Inst, Bratislava 84505, Slovakia
[2] Slovak Acad Sci, Lab Bioinformat, Biomed Res Ctr, Bratislava 84505, Slovakia
[3] Slovak Acad Sci, Dept Mol Oncol, Biomed Res Ctr, Canc Res Inst, Bratislava 84505, Slovakia
[4] St Elisabeth Canc Inst, Dept Pathol, Bratislava 81250, Slovakia
关键词
miR-497-5p expression; endometrioid endometrial carcinoma; serous endometrial carcinoma; rare subtypes of endometrial carcinoma; machine learning evaluation; MESENCHYMAL TRANSITION; CARCINOMA; MICRORNA-497; ESTROGEN; OCT4;
D O I
10.3390/ijms22010127
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The current guidelines for diagnosis, prognosis, and treatment of endometrial cancer (EC), based on clinicopathological factors, are insufficient for numerous reasons; therefore, we investigated the relevance of miRNA expression profiles for the discrimination of different EC subtypes. Among the miRNAs previously predicted to allow distinguishing of endometrioid ECs (EECs) according to different grades (G) and from serous subtypes (SECs), we verified the utility of miR-497-5p. In ECs, we observed downregulated miR-497-5p levels that were significantly decreased in SECs, clear cell carcinomas (CCCs), and carcinosarcomas (CaSas) compared to EECs, thereby distinguishing EEC from SEC and rare EC subtypes. Significantly reduced miR-497-5p expression was found in high-grade ECs (EEC G3, SEC, CaSa, and CCC) compared to low-grade carcinomas (EEC G1 and mucinous carcinoma) and ECs classified as being in advanced FIGO (International Federation of Gynecology and Obstetrics) stages, that is, with loco-regional and distant spread compared to cancers located only in the uterus. Based on immunohistochemical features, lower miR-497-5p levels were observed in hormone-receptor-negative, p53-positive, and highly Ki-67-expressing ECs. Using a machine learning method, we showed that consideration of miR-497-5p expression, in addition to the traditional clinical and histopathologic parameters, slightly improves the prediction accuracy of EC diagnosis. Our results demonstrate that changes in miR-497-5p expression influence endometrial tumorigenesis and its evaluation may contribute to more precise diagnoses.
引用
收藏
页码:1 / 18
页数:18
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