Practical approaches to diagnosing PitNETs/adenomas based on cell lineage.

Area of Science:

• Endocrinology
• Pathology
• Oncology

Background:

• Pituitary adenomas (PitNETs) classification evolved to transcription factor (TF) immunohistochemistry (IHC), establishing a cell lineage-based system.
• Current diagnostic protocols face challenges including financial and logistical burdens of extensive IHC testing.
• The emergence of "multilineage" PitNETs, like PIT1-SF1 co-expressing tumors, challenges the existing classification framework.

Purpose of the Study:

• To review practical diagnostic approaches for PitNETs.
• To examine PitNET subtypes that challenge the current classification system and their clinical implications.
• To assess limitations within the existing PitNET classification system.

Main Methods:

• Literature review of diagnostic algorithms for PitNETs.
• Analysis of reported PitNET types with multiple TF expression.
• Assessment of limitations in current IHC interpretation standardization.

Main Results:

• Algorithms have been proposed to reduce the number of IHC tests, with variable diagnostic accuracy.
• The use of TFs has decreased the reported proportion of null cell tumors.
• Multilineage PitNETs, particularly those co-expressing PIT1 and SF1, are recognized but lack a defined place in the current classification.

Conclusions:

• The current cell lineage-based classification of PitNETs requires refinement to accommodate newly identified tumor subtypes.
• Standardization of IHC interpretation is crucial for accurate and consistent PitNET diagnosis.
• Future classification systems must address multilineage PitNETs and optimize diagnostic workflows.