Multilineage Pituitary Neuroendocrine Tumors (PitNETs) Expressing PIT1 and SF1

Reassessment of Plurihormonal Pituitary Adenomas/PitNETs

Plurihormonal pituitary adenomas/neuroendocrine tumors express multiple pituitary hormones and/or transcription factors, as determined by immunohistochemistry (IHC). Three types exist based on Endocrine WHO 2022 classification: mature plurihormonal PIT1 (pituitary-specific POU-class homeodomain factor-1), immature PIT1-lineage tumors, and a third type with unusual combinations of pituitary hormones and/or transcription factors. However, since then, "somatogonatotroph"/"multilineage" tumors with PIT1/SF1 (steroidogenic factor 1) co-expression have been described, possibly confounding this classification. We performed a database search, from 2018 to 2023, to identify and reclassify tumors, correlating with neuroimaging and endocrinological features at presentation. We identified 22 cases: M 9:F 13, mean age at surgery 51±16 years. The most common symptoms at initial presentation were headaches and/or vision changes (6/22) and acromegaly (5/22). All tumors were macroadenomas, mean diameter of 25±17mm; 11/22 (50%) had cavernous sinus invasion. More than 70% of tumors clinically secreted at least 1 hormone, and 27% tumors secreted at least 2 different hormones. Four patients underwent >1 surgical intervention. Reclassification by IHC yielded almost exclusively 2 types: immature PIT1-lineage (9/22) and "somatogonadotroph"/"multilineage tumors" with PIT1/SF1 co-expression (12/22), the latter replacing mature plurihormonal tumors. One true unusual plurihormonal tumor was identified. The extent of growth hormone, prolactin, thyroid stimulating hormone, PIT1, and SF1 IHC was variable, but immunopositivity for follicle-stimulating hormone and/or luteinizing hormone was nearly confined to co-expressors, distinguishing these from immature PIT1-lineage tumors. In conclusion, tumor size, invasiveness, and endocrinopathies do not distinguish PIT1/SF1 co-expressing tumors from immature PIT1-lineage tumors preoperatively; only full IHC pituitary workup allows distinction.

Practical approaches to diagnosing PitNETs/adenomas based on cell lineage

The evolution of classification systems of pituitary adenomas (now PitNETs) has culminated in the use of transcription factor (TF) immunohistochemistry (IHC), forming a cell lineage-based system. However, several issues remain to be addressed, including the additional financial and logistic burden of undertaking the complete array of anterior pituitary hormones and TF IHC. To that end, several groups have suggested algorithms to minimise the number of tests performed, with varying levels of diagnostic accuracy. Although the proportion of null cell tumours has decreased following the use of TFs, "multilineage" tumours have been reported and characterised using transcriptomic signatures, most prominently the PIT1-SF1 co-expressing PitNETs, which do not bear a position in the present system of classification. In this review, we examine the proposed practical approaches to the diagnosis of PitNETs. We review the literature on reported PitNET types that challenge the existing classification system, such as those that express multiple TFs, with their potential clinical implications. Finally, we assess limitations in the present system, such as the lack of a standardised system for IHC interpretation, that need to be addressed in the future.

Single-Cell RNA Sequencing and Its Applications in Pituitary Research

BACKGROUND

Mounting evidence underscores the significance of cellular diversity within the endocrine system and the intricate interplay between different cell types and tissues, essential for preserving physiological balance and influencing disease trajectories. The pituitary gland, a central player in the endocrine orchestra, exemplifies this complexity with its assortment of hormone-secreting and nonsecreting cells.

SUMMARY

The pituitary gland houses several types of cells responsible for hormone production, alongside nonsecretory cells like fibroblasts and endothelial cells, each playing a crucial role in the gland's function and regulatory mechanisms. Despite the acknowledged importance of these cellular interactions, the detailed mechanisms by which they contribute to pituitary gland physiology and pathology remain largely uncharted. The last decade has seen the emergence of groundbreaking technologies such as single-cell RNA sequencing, offering unprecedented insights into cellular heterogeneity and interactions. However, the application of this advanced tool in exploring the pituitary gland's complexities has been scant. This review provides an overview of this methodology, highlighting its strengths and limitations, and discusses future possibilities for employing it to deepen our understanding of the pituitary gland and its dysfunction in disease states.

KEY MESSAGE

Single-cell RNA sequencing technology offers an unprecedented means to study the heterogeneity and interactions of pituitary cells, though its application has been limited thus far. Further utilization of this tool will help uncover the complex physiological and pathological mechanisms of the pituitary, advancing research and treatment of pituitary diseases.

Is radiomics a useful addition to magnetic resonance imaging in the preoperative classification of PitNETs?

BACKGROUND

The WHO 2021 introduced the term pituitary neuroendocrine tumours (PitNETs) for pituitary adenomas and incorporated transcription factors for subtyping, prompting the need for fresh diagnostic methods. Current biomarkers struggle to distinguish between high- and low-risk non-functioning PitNETs. We explored if radiomics can enhance preoperative decision-making.

METHODS

Pre-treatment magnetic resonance (MR) images of patients who underwent surgery between 2015 and 2019 with available WHO 2021 classification were used. The tumours were manually segmented on the T1w, T1-contrast enhanced, and T2w images using 3D Slicer. One hundred Pyradiomic features were extracted from each MR sequence. Models were built to classify (1) somatotroph and gonadotroph PitNETs and (2) high- and low-risk subtypes of non-functioning PitNETs. Feature were selected independently from the MR sequences and multi-sequence (combining data from more than one MR sequence) using Boruta and Pearson correlation. Support vector machine (SVM), logistic regression (LR), random forest (RF), and multi-layer perceptron (MLP) were the classifiers used. Data imbalance was addressed using the Synthetic Minority Oversampling TEchnique (SMOTE). Performance of the models were evaluated using area under the receiver operating curve (AUC), accuracy, sensitivity, and specificity.

RESULTS

A total of 222 PitNET patients (train, n = 149; test, n = 73) were enrolled in this retrospective study. Multi-sequence-based LR model discriminated best between somatotroph and gonadotroph PitNETs, with a test AUC of 0.84, accuracy of 0.74, specificity of 0.81, and sensitivity of 0.70. Multi-sequence-based MLP model perfomed best for the high- and low-risk non-functioning PitNETs, achieving a test AUC of 0.76, accuracy of 0.67, specificity of 0.72, and sensitivity of 0.66.

CONCLUSIONS

Utilizing pre-treatment MRI and radiomics holds promise for distinguishing high-risk from low-risk non-functioning PitNETs based on the latest WHO classification. This could assist neurosurgeons in making critical decisions regarding surgery or alternative management strategies for PitNETs after further clinical validation.

Clinical and Pathological Features of Pit1/SF1 Multilineage Pituitary Neuroendocrine Tumor

BACKGROUND AND OBJECTIVES

Lineage-based classification has critical clinical implications in pituitary neuroendocrine tumor (PitNET). As the most prevalent subtype of multilineage PitNET, PitNET originating from both pituitary-specific positive transcription factor 1 (Pit1) and steroidogenic factor-1 (SF1) lineages (Pit1/SF1-adenoma) is expected to exhibit rich and varied clinical behaviors. A comprehensive understanding of the clinical and pathological characteristics of Pit1/SF1-adenoma will provide mechanistic insight and influence the prognosis and treatment of PitNET.

METHODS

A retrospective study was conducted by reviewing 57 cases of Pit1/SF1-adenoma between 2018 and 2022. We also included 88 cases of PitNET arising from Pit1 cell lineage (Pit1-adenoma) and 70 cases of PitNET arising from SF1 cell lineage (SF1-adenoma) as controls. Comprehensive data, including demographic, symptom, endocrinal, radiological, surgical, pathological, and prognostic information, were systematically collected. All specimens were immunostained for pituitary transcription factors (PTFs) and pituitary hormones.

RESULTS

The detection rate was 8.0% for Pit1/SF1-adenoma within PitNET surgical specimens. Pit1/SF1-adenoma displayed a male predominance, with the mean diagnosis age falling between Pit1-adenoma and SF1-adenoma. The endocrine activity of Pit1/SF1-adenoma was lower than Pit1-adenoma but higher than SF1-adenoma. Pit1/SF1-adenoma had a higher incidence of cavernous sinus invasion (56.1%) than both Pit1-adenoma (38.6%, P = .039) and SF1-adenoma (27.1%, P = .001). Furthermore, Pit1/SF1-adenoma showed more postoperative complications than Pit1-adenoma (29.8% vs 8.0%, P = .001). Nonfunctional Pit1/SF1-adenoma had a higher radiological tumor recurrence rate than nonfunctional SF1-adenoma (34.8% vs 10.9%, P = .021). Notably, the immunostaining pattern was diverse in Pit1/SF1-adenoma, with various combinations of staining intensity for PTFs and 15 combinations for 6 pituitary hormones. Intriguingly, various PTFs combinations had no different impact on the outcome of Pit1/SF1-adenoma.

CONCLUSION

Pit1/SF1-adenoma represents a unique pathological subtype of PitNET, characterized by distinctive clinical behaviors. Identifying Pit1/SF1-adenoma can facilitate more precise management of PitNET by the practical use of Pit1/SF1 immunostaining.

Pituitary neuroendocrine tumors with PIT1/SF1 co-expression show distinct clinicopathological and molecular features

Pituitary neuroendocrine tumors (PitNETs) are classified according to cell lineage, which requires immunohistochemistry for adenohypophyseal hormones and the transcription factors (TFs) PIT1, SF1, and TPIT. According to the current WHO 2022 classification, PitNETs with co-expression of multiple TFs are termed "plurihormonal". Previously, PIT1/SF1 co-expression was prevailingly reported in PitNETs, which otherwise correspond to the somatotroph lineage. However, little is known about such tumors and the WHO classification has not recognized their significance. We compiled an in-house case series of 100 tumors, previously diagnosed as somatotroph PitNETs. Following TF staining, histopathological features associated with PIT1/SF1 co-expression were assessed. Integration of in-house and publicly available sample data allowed for a meta-analysis of SF1-associated clinicopathological and molecular features across a total of 270 somatotroph PitNETs. The majority (74%, 52/70) of our densely granulated somatotroph PitNETs (DGST) unequivocally co-expressed PIT1 and SF1 (DGST-PIT1/SF1). None (0%, 0/30) of our sparsely granulated somatotroph PitNETs (SGST) stained positive for SF1 (SGST-PIT1). Among DGST, PIT1/SF1 co-expression was significantly associated with scarce FSH/LH expression and fewer fibrous bodies compared to DGST-PIT1. Integrated molecular analyses including publicly available samples confirmed that DGST-PIT1/SF1, DGST-PIT1 and SGST-PIT1 represent distinct tumor subtypes. Clinicopathological meta-analyses indicated that DGST-PIT1 respond more favorably towards treatment with somatostatin analogs compared to DGST-PIT1/SF1, while both these subtypes show an overall less aggressive clinical course than SGST-PIT1. In this study, we spotlight that DGST with co-expression of PIT1 and SF1 represent a common, yet underrecognized, distinct PitNET subtype. Our study questions the rationale of generally classifying such tumors as "plurihormonal", and calls for a refinement of the WHO classification. We propose the term "somatogonadotroph PitNET".

Pathogenesis, clinical features, and treatment of plurihormonal pituitary adenoma

Plurihormonal pituitary adenoma (PPA) is a type of pituitary tumor capable of producing two or more hormones and usually presents as an aggressive, large adenoma. As yet, its pathogenesis remains unclear. This is the first study to systematically summarize the underlying pathogenesis of PPA. The pathogenesis is related to plurihormonal primordial stem cells, co-transcription factors, hormone co-expression, differential gene expression, and cell transdifferentiation. We conducted a literature review of PPA and analyzed its clinical characteristics. We found that the average age of patients with PPA was approximately 40 years, and most showed only one clinical symptom. The most common manifestation was acromegaly. Currently, PPA is treated with surgical resection. However, recent studies suggest that immunotherapy may be a potentially effective treatment.

Prolactin and Growth Hormone Signaling and Interlink Focused on the Mammosomatotroph Paradigm: A Comprehensive Review of the Literature

Prolactin (PRL) and growth hormone (GH) are peptide hormones that bind to the class 1 cytokine receptor superfamily, a highly conserved cell surface class of receptors. Both hormones control their own secretion via a negative autocrine loop in their own mammosomatotroph, lactotroph or somatotroph. In this regard, GH and PRL are regulated by similar signaling pathways involving cell growth and hormone secretion. Thus, GH and PRL dysregulation and pituitary neuroendocrine tumor (PitNET) development may have common pathogenic pathways. Based on cell linage, lactotroph and somatotroph PitNETs come from pituitary-specific POU-class homeodomain transcription factor (Pit-1). Mammosomatotroph and plurihormonal PitNETs are a unique subtype of PitNETs that arise from a single-cell population of Pit-1 lineage. In contrast, mixed somatotroph-lactotroph PitNETs are composed of two distinct cell populations: somatotrophs and lactotrophs. Morphologic features that distinguish indolent PitNETs from locally aggressive ones are still unidentified, and no single prognostic parameter can predict tumor aggressiveness or treatment response. In this review, we aim to explore the latest research on lactotroph and somatotroph PitNETs, the molecular mechanisms involved in PRL and GH axis regulation and the signaling pathways involved in their aggressiveness, particularly focused on mammosomatotroph and mixed subtypes. Finally, we summarize epidemiological, clinical, and radiological features of these exceptional tumors. We aim to shed light, from basic to clinical settings, on new perspectives and scientific gaps in this field.