Pituitary neuroendocrine tumors (PitNETs) are generally benign; however, functional subtypes cause hormone hypersecretion, leading to systemic complications. In somatotroph PitNETs, growth hormone (GH) excess increases mortality and necessitates complete tumor resection to achieve endocrinological remission. Although extracapsular resection along the pseudocapsule is preferred, the plane may be poorly defined with tumor cells infiltrating adjacent normal tissue, necessitating further resection of the outer layer. Conversely, excessive resection increases the risk of postoperative hypopituitarism; therefore, precise intraoperative delineation of tumor boundaries is essential. Approximately half of the somatotroph PitNETs harbor GNAS mutations. We used a microfluidic real-time PCR platform (GeneSoC®) that detects mutations within approximately 15 min for intraoperative molecular boundary diagnosis. First, archival frozen samples were analyzed using Sanger sequencing, which identified GNAS R201C mutations in 11 of 24 samples (45.8%), with no other point mutations detected. After optimizing the real-time PCR using Sanger-validated samples, plasmids with defined variant allele frequencies (VAFs) were engineered to confirm detection accuracy. Real-time PCR demonstrated sensitivity and specificity of 1.000 in this cohort with a fluorescence intensity cutoff of 40, reliably detecting mutations ≥ VAFs 2%. Intraoperative analyses of multiple sites (23 samples) from five GNAS R201C-positive cases demonstrated concordance between real-time PCR results and those of droplet digital PCR. Notably, mutations were detected even at sites where tumor cells could not be clearly identified histopathologically. All patients achieved complete resection with preservation of pituitary function. These findings indicate that real-time PCR provides a rapid and objective method for intraoperative molecular boundary diagnosis of somatotroph PitNETs, facilitates safe and radical resection, and may also be applicable for other tumors harboring detectable genetic mutations.
Sato et al. (Mon,) studied this question.