Proposal of a clinically relevant working classification of pituitary neuroendocrine tumors based on pituitary transcription factors

Abstract

The immunohistochemistry (IHC) characterization of pituitary transcription factors (PTFs) PIT1, TPIT, and SF1, which enable the identification of three different adenohypophyseal cell lines, has been incorporated into the latest classification system of the World Health Organization (WHO) for pituitary adenomas. This change overturns the concept of the adenoma as solely a hormone producer and classifies these tumors based on their cell lineage. The aim of the study was to provide a diagnostic algorithm, based on IHC expression of hypophyseal hormones with potential use in diagnostic practice, contributing to an improved classification of pituitary adenomas. Our sample included 146 pituitary adenomas previously classified based on hormonal subtypes by IHC (former 2004 WHO criteria) and re-evaluated after the IHC quantification of PIT1, TPIT, and SF1 expression, under WHO 2017 recommendations. We assessed the correlation between expression of PTFs and the classification as per hormonal IHCand correlated clinicopathological profiles based on PTFs. The IHC study of PTFs allowed reclassification of 82% of tumors that were negative for all pituitary hormones, with 21 positive cases for SF1 (reclassified as gonadotroph tumors), 1 positive case for TPIT (reclassified as a corticotroph tumor), and 4 positive cases for PIT1. Using SF1 enabled detection of a substantial portion of gonadotroph tumors, reducing the estimated prevalence of null cell tumors to less than 5%, and identification of plurihormonal pituitary neuroendocrine tumors with PIT1-SF1 coexpression and hormone-negative PIT1s, a group in which we did not observe differences in the clinical behavior compared with the rest of the tumors of the same cell lineage.Our results suggest that applying a diagnostic algorithm based on the study of PTFs could contribute to improving the classification of pituitary adenomas. By adding TPIT assessment, we propose a two-step algorithm, with hypophyseal hormones being used in a selective modality, depending on initial results.