Seminal plasma biomarkers for predicting successful sperm retrieval in patients with nonobstructive azoospermia: a narrative review of human studies.

backgroundNon-obstructive azoospermia (NOA) is considered to be the most severe form of male infertility. Before the emergence of surgical testicular sperm extraction and assisted reproductive technology, NOA patients could hardly become biological fathers of their children. However, failure of the surgery could cause physical and psychological harm to patients such as testicular damage, pain, hopeless of fertility and additional cost. Therefore, predicting the successful sperm retrieval (SSR) is so important for NOA patients to make their choice whether to do the surgery or not. Because seminal plasma is secreted by the testes and accessory gonads, it can reflect the spermatogenic environment, making it a preferential choice for SSR valuation. The purpose of this paper is to summarize the available evidence and provide the reader with a broad overview of biomarkers in seminal plasma for SSR prediction.

resultsA total of 15,390 studies were searched from PUBMED, EMBASE, CENTRAL and Web of Science, but only 6615 studies were evaluated after duplications were removed. The abstracts of 6513 articles were excluded because they were irrelevant to the topic. The full texts of 102 articles were obtained, with 21 of them being included in this review. The included studies range in quality from medium to high. In the included articles, surgical sperm extraction methods included conventional testicular sperm extraction (TESE) and microdissection testicular sperm extraction (micro-TESE). Currently, the biomarkers in seminal plasma used to predict SSR are primarily RNAs, metabolites, AMH, inhibin B, leptin, survivin, clusterin, LGALS3BP, ESX1, TEX101, TNP1, DAZ, PRM1 and PRM2.

conclusionThe evidence does not conclusively indicate that AMH and INHB in seminal plasma are valuable to predict the SSR. It is worth noting that RNAs, metabolites and other biomarkers in seminal plasma have shown great potential in predicting SSR. However, existing evidence is insufficient to provide clinicians with adequate decision support, and more prospective, large sample size, and multicenter trials are urgently needed.