Radiological and Immunohistochemical Characteristics of PitNETs in 79 Patients Undergoing Neurosurgery
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective: The objective of the study was to provide radiological and immunohistochemical evaluation of pituitary neuroendocrine tumors (PitNETs) concentrating on their invasiveness, endocrine function and expression of transcription factors. Methods: 79 cases of PitNETs were analyzed. The analysis included their MRI features, invasiveness and immunophenotype (immunoexpression of transcription factors Pit-1, SF1, TPit and the hormones). Results: Tumors from the SF1 line were statistically significantly more likely to show a tendency to invade the sella turcica (p<0.0001), while tumors from the Pit-1 and TPit factor lines were demonstrated to be both invasive and non-invasive, and the difference was not statistically significant. No statistically significant difference was found in the invasion of the cavernous sinuses by the pituitary tumors regardless of the transcription factor from which they originated. No statistically significant differences were observed between hormonally active and inactive tumors in terms of gender, age, invasiveness, size, or volume. Conclusions: PitNETs, also known as pituitary adenomas, continue to represent a significant challenge for clinicians. Tumors from the SF1 factor line are characterized by a statistically significantly more frequent invasion directed towards the sella turcica, while tumors from the Pit-1 and TPit lines do not show such a relationship. Patients with corticotroph PitNETs need to be controlled due to the proclivity of the tumors for aggressive behavior. Other types of PitNETs are less common. Tumors that express multiple transcription factors necessitate the patient to be subjected to further diagnostic and investigative procedures.
Source: Cancers
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,499
Award: G507809895
OpenAlex ID: W4407640725
