Potential of testis-derived circular RNAs in seminal plasma to predict the outcome of microdissection testicular sperm extraction in patients with idiopathic non-obstructive azoospermia.

Do testis-derived circular RNAs (circRNAs) in seminal plasma have potential as biomarkers to predict the outcome of microdissection testicular sperm extraction (micro-TESE) in patients with idiopathic non-obstructive azoospermia (NOA)? Testis-derived circRNAs in the seminal plasma can indeed be used for predicting the outcome of micro-TESE in patients with idiopathic NOA. Micro-TESE is an effective method to obtain sperm samples from patients with idiopathic NOA. However, its success rate is only 40-50% in such patients. Six idiopathic NOA patients with different micro-TESE results were included as the discovery cohort. Their testicular tissues were used for extracting and sequencing circRNAs. Five circRNAs with the most significantly different expression levels were selected for further verification. Fifty-two patients with idiopathic NOA were included as the validation cohort. Preoperative seminal plasma samples of 52 patients with idiopathic NOA and 25 intraoperative testicular tissues were collected and divided into 'success' and 'failure' groups according to the results of micro-TESE. Quantitative real-time polymerase chain reaction was performed to verify differences in the expression levels of the selected circRNAs between the two groups in the testicular tissues and seminal plasma. Whether at the seminal plasma or testicular tissue level, the differences in the expression levels of the three circRNAs (hsa_circ_0000277, hsa_circ_0060394 and hsa_circ_0007773) between the success and failure groups were consistent with the sequencing results. A diagnostic receiver operating curve (ROC) analysis of the AUC indicated excellent diagnostic performance of these circRNAs in seminal plasma in predicting the outcome of micro-TESE (AUC values: 0.920, 0.928 and 0.891, respectively). On the basis of least absolute shrinkage and selection operator (LASSO) logistic regression, the three circRNAs were combined to construct a new prediction model. The diagnostic ROC curve analysis of the model showed an AUC value of 0.958. The expression levels of these circRNAs in seminal plasma using three normospermic volunteer samples remained stable after 48 h at room temperature. NA. This was a single-center retrospective study with relatively few cases. The functions of these circRNAs, as well as their relationship with spermatogenesis, have not yet been established. Testis-derived circRNAs in seminal plasma can reflect the microenvironment of the testis and can be used as reliable biomarkers to screen patients with idiopathic NOA who might be suitable for micro-TESE. This article was funded by the National Natural Science Foundation of China (Grant no. 81871151). There were no competing interests.

Ji C ，Wang Y ，Wei X ，Zhang X ，Cong R ，Yao L ，Qin C ，Song N ... -  《-》

Nomogram based on a circular RNA biomarker for predicting the likelihood of successful sperm retrieval via microdissection testicular sperm extraction in patients with idiopathic non-obstructive azoospermia.

Many circular RNAs (circRNAs) are specifically expressed in the testes and seminal plasma of patients with non-obstructive azoospermia (NOA), highlighting them as potential predictors of microdissection testicular sperm extraction (micro-TESE) outcomes. Although research has indicated that circular RNA monoglyceride lipase (circ_MGLL) is highly expressed in the testicular tissues of patients with NOA, the association between circ_MGLL expression and sperm retrieval outcomes (SROs) in patients with idiopathic non-obstructive azoospermia (iNOA) receiving micro-TESE remains unclear. This single-center, retrospective cohort study enrolled 114 patients with iNOA who underwent micro-TESE at Northwest Women's and Children's Hospital from January 2017 to November 2021. A logistic regression model was used to examine associations between SRO and circ_MGLL expression in testicular tissues, the results of which were used in conjunction with previous findings to establish a nomogram. The predictive performance of the circ_MGLL-based nomogram was evaluated via calibration curves, receiver operating characteristic curves, and decision curve analysis (DCA) using an internal validation method. The generalized additive model indicated that the probability of successful SRO for micro-TESE decreased as circ_MGLL expression increased in testicular tissues. Across the entire cohort, univariate logistic regression analysis revealed that circ_MGLL expression was inversely associated with SRO in patients with NOA. This trend did not change after stratification according to age, body mass index, testicular volume, follicle-stimulating hormone (FSH) level, luteinizing hormone (LH) level, testosterone (T) level, or pathological type (or after adjusting for these confounders) (odds ratio <1, P < 0.001). A nomogram was then generated by integrating circ_MGLL, pathological types, and FSH, LH, and T levels. The circ_MGLL-based predictive model achieved satisfactory discrimination, with an area under the curve of 0.857, and the calibration curves demonstrated impressive agreement. The DCA indicated that the net clinical benefit of the circ_MGLL-based predictive model was greater than that of circ_MGLL alone. circ_MGLL is significantly associated with the SRO of micro-TESE in patients with iNOA. The circ_MGLL-based nomogram developed in the current study can predict successful SRO with high accuracy.

Shi S ，Wang T ，Wang L ，Wang M ... -  《Frontiers in Endocrinology》

A panel of extracellular vesicle long noncoding RNAs in seminal plasma for predicting testicular spermatozoa in nonobstructive azoospermia patients.

Whether the testis-specific extracellular vesicle (EV) long noncoding RNAs (lncRNAs) in seminal plasma could be utilized to predict the presence of testicular spermatozoa in nonobstructive azoospermia (NOA) patients? Our findings indicate that the panel based on seminal plasma EV lncRNAs was a sensitive and specific method in predicting the presence of testicular spermatozoa and may improve clinical decision-making of NOA. The adoption of sperm retrieval techniques, especially microdissection testicular sperm extraction (mTESE), in combination with ICSI has revolutionized treatment for NOA. However, there are no precise and noninvasive methods for predicting whether there are testicular spermatozoa in NOA patients before mTESE. RNA sequencing was performed on seminal plasma EVs from 6 normozoospermic men who underwent IVF due to female factor and 5 idiopathic NOA patients who failed to obtain testicular spermatozoa by mTESE and were diagnosed as having Sertoli cell-only syndrome by postoperative pathology. A biomarker panel of lncRNAs was constructed and verified in 96 NOA patients who underwent mTESE. Decision-making process was established based on the panel in seminal plasma EVs from 45 normozoospermia samples, 43 oligozoospermia samples, 62 cryptozoospermia samples, 96 NOA samples. RNA sequencing was done to examine altered profiles of EV lncRNAs in seminal plasma. Furthermore, a panel consisting of EV lncRNAs was established and evaluated in training set and validation sets. A panel consisting of nine differentially expressed testis-specific lncRNAs, including LOC100505685, SPATA42, CCDC37-DT, GABRG3-AS1, LOC440934, LOC101929088 (XR_927561.2), LOC101929088 (XR_001745218.1), LINC00343 and LINC00301, was established in the training set and the AUC was 0.986. Furthermore, the AUC in the validation set was 0.960. Importantly, the panel had a unique advantage when compared with models based on serum hormones from the same group of NOA cases (AUC, 0.970 vs 0.723; 0.959 vs 0.687, respectively). According to the panel of lncRNAs, a decision-making process was established, that is when the score of an NOA case exceeds 0.532, sperm retrieval surgery may be recommended. In the future, the sample size needs to be further expanded. Meanwhile, the regulatory functions and mechanism of lncRNAs in spermatogenesis also need to be elucidated. When the score of our panel is below 0.532, subjecting the NOA patients to ineffective surgical interventions may not be recommended due to poor sperm retrieval rate. This work was supported by the National Natural Science Foundation of China (81871110, 81971314 and 81971759); the Guangdong Special Support Plan-Science and Technology Innovation Youth Top Talents Project (2016TQ03R444); the Science and Technology Planning Project of Guangdong Province (2016B030230001 and 201707010394); the Key Scientific and Technological Program of Guangzhou City (201604020189); the Pearl River S&T Nova Program of Guangzhou (201806010089); the Transformation of Scientific and Technological Achievements Project of Sun Yat-sen University (80000-18843235) and the Youth Teacher Training Project of Sun Yat-sen University (17ykpy68 and 18ykpy09). There are no competing interests related to this study. N/A.

Xie Y ，Yao J ，Zhang X ，Chen J ，Gao Y ，Zhang C ，Chen H ，Wang Z ，Zhao Z ，Chen W ，Lv L ，Li Y ，Gao F ，Xie M ，Zhang J ，Zhao L ，Wang Z ，Liang X ，Sun X ，Zou X ，Deng C ，Liu G ... -  《-》

Prediction model for obtaining spermatozoa with testicular sperm extraction in men with non-obstructive azoospermia.

Can an externally validated model, based on biological variables, be developed to predict successful sperm retrieval with testicular sperm extraction (TESE) in men with non-obstructive azoospermia (NOA) using a large nationwide cohort? Our prediction model including six variables was able to make a good distinction between men with a good chance and men with a poor chance of obtaining spermatozoa with TESE. Using ICSI in combination with TESE even men suffering from NOA are able to father their own biological child. Only in approximately half of the patients with NOA can testicular sperm be retrieved successfully. The few models that have been developed to predict the chance of obtaining spermatozoa with TESE were based on small datasets and none of them have been validated externally. We performed a retrospective nationwide cohort study. Data from 1371 TESE procedures were collected between June 2007 and June 2015 in the two fertility centres. All men with NOA undergoing their first TESE procedure as part of a fertility treatment were included. The primary end-point was the presence of one or more spermatozoa (regardless of their motility) in the testicular biopsies.We constructed a model for the prediction of successful sperm retrieval, using univariable and multivariable binary logistic regression analysis and the dataset from one centre. This model was then validated using the dataset from the other centre. The area under the receiver-operating characteristic curve (AUC) was calculated and model calibration was assessed. There were 599 (43.7%) successful sperm retrievals after a first TESE procedure. The prediction model, built after multivariable logistic regression analysis, demonstrated that higher male age, higher levels of serum testosterone and lower levels of FSH and LH were predictive for successful sperm retrieval. Diagnosis of idiopathic NOA and the presence of an azoospermia factor c gene deletion were predictive for unsuccessful sperm retrieval. The AUC was 0.69 (95% confidence interval (CI): 0.66-0.72). The difference between the mean observed chance and the mean predicted chance was <2.0% in all groups, indicating good calibration. In validation, the model had moderate discriminative capacity (AUC 0.65, 95% CI: 0.62-0.72) and moderate calibration: the predicted probability never differed by more than 9.2% of the mean observed probability. The percentage of men with Klinefelter syndrome among men diagnosed with NOA is expected to be higher than in our study population, which is a potential selection bias. The ability of the sperm retrieved to fertilize an oocyte and produce a live birth was not tested. This model can help in clinical decision-making in men with NOA by reliably predicting the chance of obtaining spermatozoa with TESE. This study was partly supported by an unconditional grant from Merck Serono (to D.D.M.B. and K.F.) and by the Department of Obstetrics and Gynaecology of Radboud University Medical Center, Nijmegen, The Netherlands, the Department of Obstetrics and Gynaecology, Jeroen Bosch Hospital, Den Bosch, The Netherlands, and the Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, The Netherlands. Merck Serono had no influence in concept, design nor elaboration of this study. Not applicable.

Cissen M ，Meijerink AM ，D'Hauwers KW ，Meissner A ，van der Weide N ，Mochtar MH ，de Melker AA ，Ramos L ，Repping S ，Braat DD ，Fleischer K ，van Wely M ... -  《-》

Prediction of sperm extraction in non-obstructive azoospermia patients: a machine-learning perspective.

Can a machine-learning-based model trained in clinical and biological variables support the prediction of the presence or absence of sperm in testicular biopsy in non-obstructive azoospermia (NOA) patients? Our machine-learning model was able to accurately predict (AUC of 0.8) the presence or absence of spermatozoa in patients with NOA. Patients with NOA can conceive with their own biological gametes using ICSI in combination with successful testicular sperm extraction (TESE). Testicular sperm retrieval is successful in up to 50% of men with NOA. However, to the best of our knowledge, there is no existing model that can accurately predict the success of sperm retrieval in TESE. Moreover, machine-learning has never been used for this purpose. A retrospective cohort study of 119 patients who underwent TESE in a single IVF unit between 1995 and 2017 was conducted. All patients with NOA who underwent TESE during their fertility treatments were included. The development of gradient-boosted trees (GBTs) aimed to predict the presence or absence of spermatozoa in patients with NOA. The accuracy of these GBTs was then compared to a similar multivariate logistic regression model (MvLRM). We employed univariate and multivariate binary logistic regression models to predict the probability of successful TESE using a dataset from a retrospective cohort. In addition, we examined various ensemble machine-learning models (GBT and random forest) and evaluated their predictive performance using the leave-one-out cross-validation procedure. A cutoff value for successful/unsuccessful TESE was calculated with receiver operating characteristic (ROC) curve analysis. ROC analysis resulted in an AUC of 0.807 ± 0.032 (95% CI 0.743-0.871) for the proposed GBTs and 0.75 ± 0.052 (95% CI 0.65-0.85) for the MvLRM for the prediction of presence or absence of spermatozoa in patients with NOA. The GBT approach and the MvLRM yielded a sensitivity of 91% vs. 97%, respectively, but the GBT approach has a specificity of 51% compared with 25% for the MvLRM. A total of 78 (65.3%) men with NOA experienced successful TESE. FSH, LH, testosterone, semen volume, age, BMI, ethnicity and testicular size on clinical evaluation were included in these models. This study is a retrospective cohort study, with all the associated inherent biases of such studies. This model was used only for TESE, since micro-TESE is not performed at our center. Machine-learning models may lay the foundation for a decision support system for clinicians together with their NOA patients concerning TESE. The findings of this study should be confirmed with further larger and prospective studies. The study was funded by the Division of Obstetrics and Gynecology, Soroka University Medical Center, there are no potential conflicts of interest for all authors.

Zeadna A ，Khateeb N ，Rokach L ，Lior Y ，Har-Vardi I ，Harlev A ，Huleihel M ，Lunenfeld E ，Levitas E ... -  《-》