Circulating microRNAs in seminal plasma as predictors of sperm retrieval in microdissection testicular sperm extraction.
Circulating microRNAs in seminal plasma as predictors of sperm retrieval in microdissection testicular sperm extraction.
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精浆中的循环 microRNA 作为显微切割睾丸精子提取中精子回收的预测因子
DOI：
10.21037/atm-21-5100
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发表时间：
2022-04
影响因子：
--
通讯作者：
Zhang, Xinzong
中科院分区：
文献类型：
--
作者：
Zhang, Ying;Tang, Yuan;Huang, Jing;Liu, Huang;Liu, Xiaohua;Zhou, Yu;Ma, Chunjie;Wang, Qiling;Yang, Jigao;Sun, Fei;Zhang, Xinzong
关键词：
由于部分非梗阻性无精子症（NOA）患者存在局灶性精子生成，因此可以通过显微切割睾丸精子提取（micro-TESE）进行卵胞浆内单精子注射（ICSI）来回收睾丸精子，以实现成功受精。目前，睾丸活检被广泛用于micro-TESE的预后;然而，由于穿刺的“盲目方式”，它可能会错过具有活跃精子发生的病灶，这突出了对可以指示睾丸中实际精子发生条件的生物标志物的需求。因此，我们筛选精浆中的microRNA作为潜在的生物标志物，为micro-TESE提供一种非侵入性和可靠的术前评估。我们通过RNA测序筛选了NOA患者（每组n=6）和生育男性（n = 6）的精浆microRNA，并通过定量聚合酶链反应（qPCR）验证了所选microRNA。接下来，通过使用56个样本的qPCR数据进行有序逻辑回归来建立预测模型，并且以盲态方式使用另外40个样本来评价该模型的预测准确性。四种微小rna（hsa-miR-34 b-3 p、hsa-miR-34 c-3 p、hsa-miR-3065- 3 p和hsa-miR-4446- 3 p）被鉴定为生物标志物，通过机器学习建立了预测模型Logit = 2.0881+ 0.13448 mir-34 b-3 p + 0.58679 mir-34 c-3 p + 0.15636 mir-3065- 3 p + 0.09523 mir-4446- 3 p。该模型具有较高的预测准确性（AUC =0.927）。我们开发了一个预测模型，具有高精度的micro-TESE，NOA患者可能会获得准确的评估术前睾丸精子发生的条件。
Because of focal spermatogenesis in some nonobstructive azoospermia (NOA) patients, testicular spermatozoa can be retrieved by microdissection testicular sperm extraction (micro-TESE) for intracytoplasmic sperm injection (ICSI) to achieve successful fertilization. Currently, testicular biopsy is widely performed for the prognosis of micro-TESE; however, it might miss foci with active spermatogenesis because of the ‘blind manner’ of puncture, highlighting the needs for biomarkers that could indicate actual spermatogenesis conditions in the testis. Thus, we screened microRNAs in the seminal plasma for potential biomarkers to provide a non-invasive and reliable preoperative assessment for micro-TESE. We screened the seminal plasma microRNAs from NOA patients with and without sperm retrieval (n=6 in each group) together with fertile men (n=6) by RNA sequencing, and the selected microRNAs were validated by quantitative polymerase chain reaction (qPCR). Next, a predictive model was established by performing ordered logistic regression using the qPCR data of 56 specimens, and the predictive accuracy of this model was evaluated using 40 more specimens in a blind manner. Four microRNAs (hsa-miR-34b-3p, hsa-miR-34c-3p, hsa-miR-3065-3p, and hsa-miR-4446-3p) were identified as biomarkers, and the predictive model Logit = 2.0881+ 0.13448 mir-34b-3p + 0.58679 mir-34c-3p + 0.15636 mir-3065-3p + 0.09523 mir-4446-3p was established by machine learning. The model provided a high predictive accuracy (AUC =0.927). We developed a predictive model with high accuracy for micro-TESE, with which NOA patients might obtain accurate assessment of spermatogenesis conditions in testes before surgery.
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影响因子：
11.2
作者：
Moltzahn F;Olshen AB;Baehner L;Peek A;Fong L;Stöppler H;Simko J;Hilton JF;Carroll P;Blelloch R
通讯作者：
Blelloch R
影响因子：
3
作者：
Choi SH;Labadorf AT;Myers RH;Lunetta KL;Dupuis J;DeStefano AL
通讯作者：
DeStefano AL
DOI：
10.4021/jocmr542w
发表时间：
2011-05-19
期刊：
Journal of clinical medicine research
影响因子：
--
作者：
Ghalayini IF;Al-Ghazo MA;Hani OB;Al-Azab R;Bani-Hani I;Zayed F;Haddad Y
通讯作者：
Haddad Y
男性不育分子诊断中精浆 microRNA 谱的改变
影响因子：
9.3
作者：
Wang, Cheng;Yang, Cuihua;Zhang, Chunni
通讯作者：
Zhang, Chunni
正常精子症和无精子症精浆中游离 DNA 的快速恢复和表征：对非侵入性遗传实用程序的影响。
影响因子：
2.9
作者：
Li, Hong-Gang;Huang, Shi-Yun;Xiong, Cheng-Liang
通讯作者：
Xiong, Cheng-Liang