MicroRNA as a Liquid Biomarker to Detect Malignancy in Small Testicular Masses.

Background and objective: Approximately 1-4% of individuals undergoing scrotal ultrasound are found with incidental small (≤2 cm) testicular masses (STMs), with the vast majority being benign (∼13-21% malignant). This study explores the potential of microRNAs (miRNAs) as liquid biomarkers for predicting germ cell tumors (GCTs) in STMs.

Methods: From 2009 to 2023, we identified patients with STMs who had banked serum/plasma prior to orchiectomy. Eligible samples were analyzed using different miRNA expression methods (reverse transcription quantitative polymerase chain reaction [RT-qPCR] and digital droplet polymerase chain reaction) and platforms across three research laboratory facilities (Portugal, Vancouver, and Toronto). The miRNA assays included 371a-3p, 372, 373, and 367. The primary objective was to evaluate the diagnostic accuracy of miR-371a-3p to predict the presence of testicular cancer using the area under the curve (AUC).

Key findings and limitations: Our cohort included 61 patients: 37 patients with confirmed GCTs, 20 patients with benign histology, and four patients who had been on surveillance for >24 mo and were deemed to have benign STMs. Across all three laboratories, miR-371a-3p consistently outperformed all the miRNAs, with the other miRNAs proving uninformative. Extraction from plasma and an RT-qPCR analysis (Vancouver laboratory) proved best, with sensitivity of 87% and specificity of 91%, translating into an AUC of 0.93. The receiver operating characteristic scores for the other two laboratories were 0.77 and 0.73 for Portugal and Toronto, respectively. This single-center study is limited by a potential selection bias and fewer evaluable samples due to technical and logistical issues.

Conclusions and clinical implications: This is the largest series of STMs with banked blood/serum to date. Among the miRNAs, miR-371a-3p was found to be sensitive and specific for detecting the presence of GCTs in STMs. Plasma with an RT-qPCR approach proved to be a superior method of analysis.