학술논문

Among seven testis‐specific molecular markers, SPEM1 appears to have a significant clinical value for prediction of sperm retrieval in azoospermic men.
Document Type
Article
Source
Andrology. Nov2018, Vol. 6 Issue 6, p890-895. 6p.
Subject
*SPERMATOGENESIS
*REVERSE transcriptase polymerase chain reaction
*SPERMATOZOA
*INTRACYTOPLASMIC sperm injection
*SERTOLI cells
*RECEIVER operating characteristic curves
Language
ISSN
2047-2919
Abstract
Background: To achieve sperm retrieval in azoospermic men, predicting the success rate seems to be necessary. Objectives: In the present study we aimed to assess expression of seven molecular markers [ESX1, DAZ, DAZL (pre‐meiotic markers), ZMYND15, PRM1, TNP1, and SPEM1 (post‐meiotic markers)] to predict the success of sperm retrieval. Materials and Methods: In this study, 63 azoospermic men [16 OA (obstructive azoospermia) and 47 NOA (nonobstructive azoospermia)] undergoing testicular tissue microdissection (micro‐TESE) for intracytoplasmic sperm injection (ICSI). Expression levels of these target genes were determined by real‐time reverse transcription polymerase chain reaction using the DDCt method, and efficacy of each gene was compared by receiver operating characteristic (ROC) curve analysis. Results: Expression of post‐meiotic transcripts significantly decreases in NOA and its subgroups (SCOS: Sertoli cell only syndrome, MA: maturation arrest, and HS: hypospermatogenesis) with spermatogenic failure compared to normal spermatogenesis (OA), with an exception of ZMYND15 for the HS group. These findings suggest the differential expression of the post‐meiotic ZMYND15 marker is in accordance with histological findings and can discriminate HS from SCOS and MA. Post‐meiotic markers were significantly reduced in negative vs. positive sperm retrieval groups. Discussion and Conclusion: Among the seven markers, SPEM1 had the best positive prediction power (96%) and negative prediction power (85%) at a 0.086 cutoff with the area under the curve (AUC) of 0.91 for receiver operating characteristic 4 (ROC) to predict the micro‐TESE outcome. [ABSTRACT FROM AUTHOR]