[Modern concepts of genetic and immunohistochemical features of prolactin-secreting pituitary adenomas]
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Published on: January 17, 2018
A S Shutova1, L K Dzeranova1, S Yu Vorotnikova1
1Endocrinology Research Centre.
Abstract:
Prolactinomas are the most common secreting adenomas of the pituitary. In 20% of cases resistance to dopamine-agonists treatment is observed. Medical therapy resistance causes progression of pathological symptoms of hyperprolactinemia and negative topographic and anatomical changes of prolactinoma. The causes of ineffectiveness of dopamine agonists therapy are not fully understood as well as approaches to managing patients require clarification. Current concepts of resistance are based on the data obtained as a result of surgery or after a period of long-term ineffective therapy. Thus, it is very important to find methods of assessing the sensitivity of prolactin-secreting adenomas to drug therapy before surgical treatment. Genetic and immunohistochemical studies find special place among these methods, making it possible to predict adenoma's response to drug therapy at early diagnostic stage. Obtained results will allow us to form personalized algorithm for managing patients.
Insights
Dopamine agonist resistance in prolactinomas, the most common pituitary tumors, is poorly understood. Genetic and immunohistochemical studies may predict treatment response, enabling personalized patient management.
Area of Science:
- Endocrinology
- Oncology
- Molecular Biology
Context:
- Prolactinomas are the most common pituitary adenomas.
- 20% of patients exhibit resistance to dopamine agonist therapy.
- Resistance leads to worsening hyperprolactinemia and tumor changes.
Purpose:
- To investigate the causes of dopamine agonist resistance in prolactinomas.
- To identify predictive markers for treatment response.
- To establish personalized management strategies for patients.
Summary:
- Resistance to dopamine agonists in prolactinomas necessitates alternative treatment approaches.
- Genetic and immunohistochemical analyses are crucial for predicting treatment efficacy.
- Early assessment of adenoma sensitivity can guide personalized therapeutic algorithms.
Impact:
- Improved understanding of dopamine agonist resistance mechanisms.
- Development of predictive tools for treatment selection.
- Enhanced patient outcomes through personalized prolactinoma management.
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