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MicroRNAs as Predictors of Future Uterine Malignancy in Endometrial Hyperplasia without Atypia

Authors :
Chiao-Yun Lin
Ren-Chin Wu
Lan-Yan Yang
Shih-Ming Jung
Shir-Hwa Ueng
Yun-Hsin Tang
Huei-Jean Huang
Hsiu-Jung Tung
Cheng-Tao Lin
Hsuan-Yu Chen
Angel Chao
Chyong-Huey Lai
Source :
Journal of Personalized Medicine; Volume 12; Issue 2; Pages: 311
Publication Year :
2022
Publisher :
Multidisciplinary Digital Publishing Institute, 2022.

Abstract

The histological criteria for classifying endometrial hyperplasia (EH) are based on architectural crowding and nuclear atypia; however, diagnostic agreement among pathologists is poor. We investigated molecular biomarkers of endometrial cancer (EC) risk in women with simple hyperplasia or complex hyperplasia without atypia (SH/CH-nonA). Forty-nine patients with EC preceded by SH/CH-nonA were identified, of which 23 were excluded (15 with complex atypical hyperplasia (CAH), six not consenting, one with a diagnosis 4) between the control (n = 12) and case (n = 6) patients. Multiplex RT-qPCR for the 20 miRNAs in the expanded cohort (94 control and 25 case patients) led to the validation of miR-30a-3p (p = 0.0009), miR-141 (p < 0.0001), miR-200a (p < 0.0001), and miR-200b (p < 0.0001) as relevant biomarkers, among which miR-141, miR-200a, and miR-200b regulate the expression of phosphatase and tensin homolog (PTEN). For the prediction of EC, the area under the curve for miR-30a-3p, miR-141, miR-200a, and miR-200b was 0.623, 0.754, 0.783, and 0.704, respectively. The percentage of complete PTEN loss was significantly higher in the case group than in the control group (24% vs. 0%, p < 0.001, Fisher’s exact test). A combination of complete PTEN loss and miR-200a provided optimal prediction performance (sensitivity = 0.760; specificity = 1.000; positive predictive value = 1.000; negative predictive value = 0.937; accuracy = 0.947). MiR-30a-3p, miR-141, miR-200a, miR-200b, and complete PTEN loss may be useful tissue biomarkers for predicting EC risk among patients with SH/CH-nonA.

Details

Language :
English
ISSN :
20754426
Database :
OpenAIRE
Journal :
Journal of Personalized Medicine; Volume 12; Issue 2; Pages: 311
Accession number :
edsair.doi.dedup.....90215ba6bd8b437ee6c5447a539b27fb
Full Text :
https://doi.org/10.3390/jpm12020311