Unveiling the identities of null cell tumours: Epigenomics corroborate subtle histological cues in pituitary neuroendocrine tumour/adenoma classification.

Abstract

Pituitary neuroendocrine tumour (PitNET)/adenoma classification is based on cell lineage and requires immunopositivity for adenohypophysial hormones and/or transcription factors (TFs) SF1, TPIT, or PIT1. PitNET/adenomas lacking lineage affiliation are termed "null cell" tumours (NCTs). NCT diagnosis may be afflicted by methodological limitations and inconsistent diagnostic approaches. Previous studies have questioned the existence of true NCTs. In this study, we explore the epigenomic identities of PitNET/adenomas lacking clear TF-immunopositivity. 74 hormone-negative PitNET/adenomas were immunostained and scored for SF1, TPIT, and PIT1 expression. All tumours were classified as gonadotroph, corticotroph, PIT1-positive or "null cell". NCTs were subjected to global DNA methylation analysis. Epigenomic profiles of NCTs were compared to reference tumours using UMAP plotting and methylation-based classification. TF-immunostaining revealed definite lineage identity in 59 of 74 (79.7%) hormone-negative PitNET/adenomas. Of the remaining 15 NCTs, 13 demonstrated minimal and inconclusive nuclear SF1- or TPIT-expression (5 and 8, respectively). Two NCTs were entirely immunonegative. UMAP plotting and methylation-based classification demonstrated that the epigenomes of NCTs with minimal SF1- or TPIT-expression, were adequately affiliated with gonadotroph or corticotroph lineages, respectively. The two immunonegative NCTs were located near the corticotroph PitNET/adenomas via UMAP, while the methylation classifier could not match these two cases to predefined tumour classes. Epigenomic analyses substantiate lineage identification based on minimal TF-immunopositivity in PitNET/adenomas. This strategy dramatically decreases the incidence of NCTs and further challenges the legitimacy of NCTs as a distinct PitNET/adenoma subtype. Our study may be useful for guiding diagnostic efforts and future considerations of PitNET/adenoma classification.