Overview of omics biomarkers in pituitary neuroendocrine tumors to design future diagnosis and treatment strategies
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CitationAydin, B., Caliskan, A., & Arga, K. Y. (2021). Overview of omics biomarkers in pituitary neuroendocrine tumors to design future diagnosis and treatment strategies. EPMA Journal, 1-19.
Pituitary neuroendocrine tumors (PitNETs) are the second most common type of intracranial neoplasia. Since their manifestation usually causes hormone hypersecretion, effective management of PitNETs is indisputably necessary. Most of the non-functioning PitNETs pose a real challenge in diagnosis as they grow without giving any signs. Despite the good response of prolactinomas to dopamine agonist therapy, some of these tumors persist or recur; also, about 20% are resistant and 10% behave aggressively. The silent corticotropinomas may not cause symptoms until the tumor mass causes a complication. In somatotropinomas, the possibility of recurrence after transsphenoidal resection is more common in pediatric patients than in adult patients. Therefore, detection of tumors at early stages or identification of recurrence and remission after transsphenoidal surgery would allow wiser management of the disease. Extensive studies have been performed to uncover potential signatures that can be used for preventive diagnosis and/or prognosis of PitNETs as well as for targeted therapy. These molecular signatures at multiple biological levels hold promise for the convergence of preventive approaches and patient-centered disease management and offer potential therapeutic strategies. In this review, we provide an overview of the omics-based biomarker research and highlight the multi-omics signatures that have been proposed as pitNET biomarkers. In addition, understanding the multi-omics data integration of current biomarker discovery strategies was discussed in terms of preventive, predictive, and personalized medicine. The topics discussed in this review will help to develop broader visions for pitNET research, diagnosis, and therapy, particularly in the context of personalized medicine.