Leydig cell tumor of a testis with azoospermia: A case report and literature review.

RATIONALE: Testicular tumors represent 1% to 1.5% of all tumors in men. Those derived from Leydig cells are rare and account for 1% of testicular tumors. Leydig tumor cells can produce steroid hormones such as estrogen, progesterone and testosterone. The amount and type of hormones secreted by these tumors may produce complicated clinical characteristics in these patients. PATIENT CONCERNS: Here, we report a patient with azoospermia, a testicular Leydig cell tumor (LCT), and elevated plasma testosterone levels. We describe the diagnostic and therapeutic experience of this case, and our follow-up of the patient's clinical indicators and fertility status. DIAGNOSIS: The patient was diagnosed with azoospermia and a testicular LCT. INTERVENTIONS: The patient underwent testicular tumor removal and long-term follow-up. OUTCOMES: After 4 months of follow-up, the patient's semen examination index significantly improved and his wife became naturally pregnant. At 4 months of gestation, the fetus was delivered because of a ruptured amniotic cavity. Twenty-six months after tumor removal, the patient's sex hormone levels had completely returned to normal and spermatogenic function had partially recovered, but there was no natural pregnancy with his partner. CONCLUSION: For LCTs, testis sparing surgery may provide a safe and feasible option to restore spermatogenic function, although longer-term follow-up is required. Drug assistance may be required to maintain spermatogenic function and achieve fertility, and further research is required.

Comprehensive Gene Expression Analysis in NMIBC Using RNA-seq Reveals New Therapy Strategies.

Non-muscle invasive bladder cancer (NMIBC) patients often have fewer treatment options, and suffer the progression of disease due to mechanisms that are not clear, as well as due to its diversity. This study was designed to explore the molecular mechanism of bladder cancer through an RNA-seq. In addition to conventional analyses, we also simplified the network through modularization using the WGCNA algorithm, with the help of the topological overlapping matrix and hierarchical cluster tree, which are based on the PPI network of STRING. Furthermore, the hub genes were confirmed through survival analyses in the independent cohorts (n = 431). Among them, 15 genes were significantly associated with poor prognosis. Finally, we validated the results at mRNA and protein level using qRT-PCR, IHC and western blotting. Taken together, our research is important for the prediction, as well as the prospective clinical development of drug targets and biomarkers.