Frontiers in Endocrinology (Dec 2019)
Clinical Relevance of Genetic Analysis in Patients With Pituitary Adenomas: A Systematic Review
Abstract
Pituitary adenomas (PA) are amongst the most prevalent intracranial tumors, causing complications by hormonal overproduction or deficiency and tumor mass effects, with 95% of cases occurring sporadically. Associated germline mutations (AIP, MEN1, CDKN1B, PRKAR1A, SDHx) and Xq26.3 microduplications are increasingly identified, but the clinical consequences in sporadic PA remain unclear. This systematic review evaluates predictors of a genetic cause of sporadic PA and the consequences for treatment outcome. We undertook a sensitive MEDLINE/Pubmed, EMBASE, and Web of Science search with critical appraisal of identified studies. Thirty-seven studies on predictors of mutations and 10 studies on the influence on treatment outcome were included. AIP and MEN1 mutations were associated with young age of PA diagnosis. AIP mutations were also associated with gigantism and macroadenomas at time of diagnosis. Xq26.3 microduplications were associated with PA below the age of five. AIP and MEN1 mutation analysis is therefore recommended in young patients (≤30 years). AIP mutation analysis is specifically recommended for patients with PA induced gigantism and macroadenoma. Screening for Xq26.3 microduplications is advisable in children below the age of five with increased growth velocity due to PA. There is no evidence supporting mutation analysis of other genes in sporadic PA. MEN1 mutation related prolactinoma respond well to dopamine agonists while AIP mutation associated somatotroph and lactotroph adenoma are frequently resistant to medical treatment. In patients harboring an Xq26.3 microduplication treatment is challenging, although outcome is not different from other patients with PA induced gigantism. Effective use of genetic analysis may lead to early disease identification, while knowledge of the impact of germline mutations on susceptibility to various treatment modalities helps to determine therapeutic strategies, possibly lowering disease morbidity.
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