Predicting which acromegaly patients could benefit from somatostatin receptor ligands (SRL) is a must for personalized medicine. Although many biomarkers linked to SRL response have been identified, there is no consensus criterion on how to assign this pharmacologic treatment according to biomarker levels. Our aim is to provide better predictive tools for an accurate acromegaly patient stratification regarding the ability to respond to SRL. We took advantage of a multicenter study of 71 acromegaly patients and we used advanced mathematical modelling to predict SRL response combining molecular and clinical information. Different models of patient stratification were obtained, with a much higher accuracy when the studied cohort is fragmented according to relevant clinical characteristics. Considering all the models, a patient stratification based on the extrasellar growth of the tumor, sex, age and the expression of E-cadherin, GHRL, IN1-GHRL, DRD2, SSTR5 and PEBP1 is proposed, with accuracies that stand between 71 to 95%. In conclusion, the use of data mining could be very useful for implementation of personalized medicine in acromegaly through an interdisciplinary work between computer science, mathematics, biology and medicine. This new methodology opens a door to more precise and personalized medicine for acromegaly patients.
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http://dx.doi.org/10.1038/s41598-022-12955-2 | DOI Listing |
Expert Opin Pharmacother
December 2024
Pituitary Center, Oregon Health & Science University, Portland, OR, USA.
Clin Endocrinol (Oxf)
December 2024
Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy.
Objective: Many review articles have explored data regarding the coexistence of specific types of pituitary adenomas (PAs) and polycystic ovary syndrome (PCOS), particularly focusing on the potential pathogenesis of this intersection and overlapping features. However, a comprehensive evaluation encompassing the full spectrum of PAs and their association with PCOS remains lacking. This review aims to provide a broad assessment of the interactions between these entities, emphasizing pathophysiological mechanisms, clinical presentations, diagnostic challenges and therapeutic implications.
View Article and Find Full Text PDFEur J Endocrinol
December 2024
Endocrinology Unit, Department of Internal Medicine and Medical Specialties (DIMI), University of Genova, Genova, Italy.
Immunohistochemistry of somatostatin receptor subtype 2 (SSTR2) can predict response to first-generation somatostatin receptor ligands (fg-SRLs) in acromegaly. Recently, we validated an open-source digital image analysis (DIA) to quantify SSTR2 expression. We aimed to validate the DIA also on SSTR5 in a new cohort of GH-secreting pituitary tumors, with immunohistochemistry performed in a different laboratory, and to correlate fg-SRL response with SSTs expression.
View Article and Find Full Text PDFEndocrine
December 2024
Department of Neurosurgery, Dongfang Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Purpose: The growth hormone (GH) level on postoperative day one (POD1), i.e., POD1GH, holds significant value in assessing surgical efficacy and predicting long-term remission in patients with acromegaly.
View Article and Find Full Text PDFThyroid
December 2024
Department of Ophthalmology, Western University, London, Ontario, Canada.
Extraocular muscle (EOM) enlargement occurs in both acromegaly and Graves' disease, but the degree and pattern of enlargement have not been directly compared in these patient groups. This study investigated whether acromegaly and Graves' orbitopathy (GO) are associated with different patterns of EOM enlargement at the time of diagnosis. Retrospective cohort.
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