Rebeca Martínez‐Hernández, Fernando F Méndez-García, Ana Serrano-Somavilla, Pablo Sacristán-Gómez, Nuria Sánchez de la Blanca, Miguel Sampedro‐Núñez, Víctor Navas-Moreno, Fernando Sebastián‐Valles, J.F. Alén, Betina Biagetti, Ignacio Ruz‐Caracuel, Marta Araujo‐Castro, Manel Puig‐Domingo, Mónica Marazuela
INTRODUCTION: Acromegaly is a rare disease usually caused by a pituitary neuroendocrine tumor (PitNET) that produces GH PitNET. PitNETs secreting GH and prolactin (GH&PRL PitNETs) contribute up to 30% to the spectrum of acromegaly and have been attributed a more aggressive behavior. GH&PRL PitNETs can be classified into 2 predominant phenotypes: mammosomatotroph arising from a single-cell population of Pit-1 lineage and mixed somatotroph-lactotroph PitNETs (mixed SL PitNETs). PURPOSE: To evaluate the clinical and molecular differences between GH PitNETs, mammosomatotroph, and mixed SL PitNETs. METHODS: We quantified GH and PRL expression by double immunofluorescence in 51 PitNETs (23 GH PitNETs, 20 mammosomatotrophs, and 8 mixed SL PitNETs) from patients with acromegaly. These findings were correlated with clinical data and histologic markers such as somatostatin receptor (SSTR)2, SSTR3, SSTR5, E-cadherin, and CAM 5.2. RESULTS: Our results did not reveal significant differences in GH or IGF-1 levels between GH PitNETs and mixed SL PitNETs, but PRL levels were significantly higher in mammosomatotrophs. Tumor size and invasiveness were comparable between the 2 groups. Interestingly, 41% of prolactin (PRL)-positive tumors did not show hyperprolactinemia, representing silent PRL-positive GH PitNETs. Mixed SL PitNETs exhibited reduced SSTR2 expression, while GH PitNETs exhibited higher SSTR5 levels. Moreover, all tumors lacking cytokeratin expression were nonresponders to medical therapy. CONCLUSION: These findings highlight the heterogeneity within GH&PRL PitNETs, including silent PRL-positive GH PitNETs. Our data suggest mixed SL tumors may be less responsive to SSTR ligands, emphasizing the need for tailored strategies based on tumor subtype and receptor profile.