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

Silva-Ortega, Sandra; García‐Martínez, Araceli; Jaime, María Nivéiro de; Quesada, María Eugenia Torregrosa; Abarca-Olivas, Javier; Monjas, Irene; Alfonso, Antonio Picó; Aranda, Ignacio

doi:10.1016/j.humpath.2020.12.001

Cited by 9 publications

(12 citation statements)

References 29 publications

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“…4a). This observation is concordant with some other studies reporting NR5A1 expression in a proportion of somatotroph PitNETs [10][11][12][13][14][15][16][17]. Therefore, we paid special attention to the role of DNA methylation in the expression of NR5A1 in somatotroph PitNETs.…”

Section: Relevance Of Dna Methylation In Nr5a1 (Sf-1) Locussupporting

confidence: 91%

“…Epigenetic, DNA methylation-related regulation of NR5A1 was previously described in various cell types expressing SF-1 [29,30,39,40]. NR5A1 encodes SF-1 transcription factor, which serves as a diagnostic marker of pituitary tumors of gonadotrophic lineage origin, but the expression of this gene in a subset of somatotroph tumors has been already reported by independent groups [9][10][11][12][13][14][15][16][17]. Gene expression analysis indicates that NR5A1-positive somatotroph PitNETs are a separate subtype of tumors causing acromegaly [9].…”

Section: Discussionmentioning

confidence: 98%

“…NR5A1 encodes SF-1 transcription factor, an established marker of gonadotroph PitNETs. However, its expression was also observed in some somatotroph tumors [9][10][11][12][13][14][15][16][17]. The role of GIPR expression in the pathogenesis of these somatotroph PitNETs was also already determined [18,19].…”

Section: Introductionmentioning

confidence: 99%

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DNA Methylation Pattern in Somatotroph Pituitary Neuroendocrine Tumors

Kober,

Rymuza,

Baluszek

et al. 2023

Neuroendocrinology

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Introduction: Growth hormone secretion by sporadic somatotroph neuroendocrine pituitary tumors (PitNETs) is a major cause of acromegaly. These tumors are relatively heterogenous in terms of histopathological and molecular features. Our previous transcriptomic profiling of somatotroph tumors revealed three distinct molecular subtypes. This study aimed to investigate the difference in DNA methylation patterns in subtypes of somatotroph PitNETs and its role in distinctive gene expression. Methods: Genome-wide DNA methylation was investigated in 48 somatotroph PitNETs with EPIC microarrays. Gene expression was assessed with RNAseq. Bisulfite pyrosequencing and qRT-PCR were used for verifying the results of DNA methylation and gene expression. Results: Clustering tumor samples based on methylation data reflected the transcriptome-related classification. Subtype 1 tumors are densely granulated without GNAS mutation, characterized by high expression of NR5A1 (SF-1) and GIPR. The expression of both genes is correlated with specific methylation of the gene body and promoter. This subtype has a lower methylation level of 5′ gene regions and CpG islands than the remaining tumors. Subtype 2 PitNETs are densely granulated and frequently GNAS-mutated, while those in subtype 3 are mainly sparsely granulated. Methylation/expression analysis indicates that ∼50% genes located in differentially methylated regions are those differentially expressed between tumor subtypes. Correlation analysis revealed DNA methylation-controlled genes, including CDKN1B, CCND2, EBF3, CDH4, CDH12, MGMT, STAT5A, PLXND1, PTPRE, and MMP16, and genes encoding ion channels and semaphorins. Conclusion: DNA methylation profiling confirmed the existence of three molecular subtypes of somatotroph PitNETs. High expression of NR5A1 and GIPR in subtype 1 tumors is correlated with specific methylation of both genes.

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Section: Relevance Of Dna Methylation In Nr5a1 (Sf-1) Locussupporting

confidence: 91%

Section: Discussionmentioning

confidence: 98%

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DNA Methylation Pattern in Somatotroph Pituitary Neuroendocrine Tumors

Kober,

Rymuza,

Baluszek

et al. 2023

Neuroendocrinology

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“…Other studies were performed on tissue microarrays rather than whole sections, which were utilised here and are routine clinical practice. All other studies were published prior to the release of the 2022 WHO classification, therefore did not include relevant and important changes [5,[7][8][9]. The EPPG proposed hormonal IHC in all cases, with subsequent transcription factor IHC in certain circumstances only such as plurihormonal tumours [8].…”

Section: Discussionmentioning

confidence: 99%

“…1). Adoption of transcription factor analysis has been associated with improved diagnostic and prognostic information, including refinement of classification and improved identification of hormonally silent or 'whispering' tumours [2][3][4][5]. The recent release of the fifth edition of the WHO classification (2022) builds upon the transcription factor-based classification of pituitary tumours with description of new types, summarised in Table 1 [6].…”

Section: Introductionmentioning

confidence: 99%

Development of a cost-effective diagnostic algorithm incorporating transcription factor immunohistochemistry in the evaluation of pituitary tumours

et al. 2022

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Purpose To determine the utility of the 2022 WHO Classification of pituitary tumours in routine clinical practice and to develop an optimal diagnostic algorithm for evaluation of tumour type in a real-world setting. Methods Retrospective evaluation of pituitary tumour immunohistochemistry (IHC), operatively managed at St Vincent’s Hospital Sydney, between 2019 and 2021. Routine IHC comprised evaluation of transcription factors [steroidogenic factor 1 (SF1), T-box transcription factor 19 (TPIT) and pituitary-specific positive transcription factor (PIT1)] and anterior pituitary hormones. Three tiered algorithms were tested, in which hormone IHC was performed selectively based on the initial transcription factor results. These were applied retrospectively and compared with current practice ‘gold standard’ comprising all transcription factor and hormone IHC. Diagnostic accuracy and cost were evaluated for each. Results There were 113 tumours included in the analysis. All three algorithms resulted in 100% concordance with the ‘gold standard’ in the characterisation of tumour lineage. While all three were associated with relative cost reduction, Algorithm #3, which omitted hormone IHC in the setting of positive SF1 or TPIT and performed IHC for growth hormone, prolactin and thyroid stimulating hormone only in the setting of PIT1 positivity, was the most cost-efficient. Additionally, there were 12/113 tumours with no distinct cell lineage. Conclusion A diagnostic algorithm omitting hormone IHC except in cases of PIT1 positivity is an accurate and cost-effective approach to diagnose the type of pituitary tumour. A significant subgroup of pituitary tumours with no distinct cell lineage, frequently plurihormonal, remains difficult to classify with the new WHO criteria and requires further evaluation.

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

Dottermusch,

Ryba,

Ricklefs

et al. 2024

Acta Neuropathol

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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”.

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

Cited by 9 publications

References 29 publications

DNA Methylation Pattern in Somatotroph Pituitary Neuroendocrine Tumors

DNA Methylation Pattern in Somatotroph Pituitary Neuroendocrine Tumors

Development of a cost-effective diagnostic algorithm incorporating transcription factor immunohistochemistry in the evaluation of pituitary tumours

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

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