Multilineage pituitary neuroendocrine tumors with PIT1/SF1 co-expression
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1034042 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Pituitary neuroendocrine tumors (PitNET)/adenomas are classified according to cell lineage, which requires immunohistochemistry for the transcription factors (TFs) PIT1, SF1, and TPIT. Co-expression of PIT1/SF1 was previously reported in PitNETs, which otherwise correspond to the somatotroph lineage. However, little is known about the clinicopathological features of these tumors. We compiled an in-house case series of 100 tumors, previously diagnosed as densely or sparsely granulated somatotroph PitNETs. Following TF staining, histopathological features associated with PIT1/SF1-coexpression were assessed. Global DNA methylation profiling was conducted on 31 of 100 in-house samples and integrated with publicly available sample data. The majority (74%, 52/70) of our densely granulated somatotroph PitNETs (DGST) unequivocally co-expressed PIT1 and SF1 (DGST-PIT1/SF1). None of our SGST (0%, 0/30) stained positive for SF1 (SGST-PIT1). Integrated molecular analyses including publicly available sample data confirmed that DGST-PIT1/SF1, DGST-PIT1 and SGST-PIT1 represent distinct tumour subtypes. In summary, we spotlight that a substantial proportion of previously diagnosed densely granulated somatotroph PitNET co-express PIT1 and SF1 and exhibit clinical, histopathological, and molecular distinctness from other pure PIT1-lineage somatotroph PitNET.
2024-01-24 | GSE246645 | GEO
Project description:Corticotroph pituitary neuroendocrine tumors (PitNETs) are heterogeneous sellar neoplasms with variable clinical manifestations and outcomes. This deposit comprises proteomic data generated as part of an integrative meta-analysis of corticotroph PitNETs, which included epigenomic, transcriptomic, and proteomic investigations. Proteomic profiling was performed on 39 internal tumor samples. These data were integrated with previously published external molecular datasets. The combined analyses defined four clinically relevant molecular subgroups of corticotroph PitNETs.
2026-07-02 | PXD073952 | Pride
Project description:Methylome analysis in pituitary neuroendocrine tumors
| PRJEB50807 | ENA
Project description: Not available
| S-EPMC10791732 | biostudies-literature
Project description:Corticotroph pituitary neuroendocrine tumors (PitNETs) are heterogeneous sellar neoplasms with variable clinical manifestations and growth behaviour. In this study, epigenomic data was generated as part of an integrative meta-analysis of corticotroph PitNETs, which included epigenomic, transcriptomic, and proteomic investigations. This deposit comprises idat files of tumor samples and adenohypophysial non-neoplastic control samples. These data were integrated with previously published external molecular datasets. The combined analyses defined four clinically relevant molecular subgroups of corticotroph PitNETs.
2026-07-03 | E-MTAB-16589 | biostudies-arrayexpress
Project description:Pituitary neuroendocrine tumors (PitNETs) are the most common intracranial neuroendocrine tumors. PitNETs are difficult to classify, and current recommendations include a large immunohistochemical panel to differentiate among 14 WHO-recognized categories. In this study, we analyzed 118 PitNETs to develop a clinico-molecular approach to classifying PitNETs. Comparison of clinical, immunohistochemical, and DNA methylation showed that PitNETs can be classified into distinct clinical and molecular subgroups. Unsupervised DNA methylation separated PitNETs into two major clusters. The first major cluster was composed of tumors currently labeled as gonadotrophs, which form a biologically distinct group of PitNETs characterized by clinical silence, weak hormonal expression on immunohistochemistry, and simple copy number profile. The second major cluster was composed of Corticotrophs and Pit1 lineage PitNETs, which could be further classified using DNA methylation into distinct subclusters that correspond to clinically active and silent tumors and consistent with degree of differentiation. Analysis of promoter methylation patterns correlates with lineage for corticotrophs and Pit1 lineage subtypes. However, the gonadotrophic genes do not show a distinct promoter methylation pattern in gonadotroph tumors compared to other lineages. Promoter of the NR5A1 gene, which encodes SF1, was hypermethylated across all PitNETs clinical and molecular subtypes including gonadotrophs with strong SF1 protein expression indicating alternative epigenetic regulation. These findings suggest that future classification of PitNETs may need to include DNA methylation for clinicopathological stratification.
2025-04-29 | GSE283928 | GEO
Project description:DNA methylation pattern in somatotroph pituitary neuroendocrine tumors
| PRJNA941347 | ENA
Project description:Proteogenomic Landscape and Clinical Characterization of GH-producing pituitary adenomas/ somatotroph pituitary neuroendocrine tumors
| PRJNA881301 | ENA
Project description:Background: Lactotroph pituitary neuroendocrine tumors (PitNETs) are common pituitary tumors, but their underlying molecular mechanisms remain unclear. This study aimed to investigate the transcriptomic landscape of lactotroph PitNETs and identify potential molecular mechanisms and therapeutic targets through RNA sequencing and ingenuity pathway analysis (IPA). Methods: Lactotroph PitNET tissues from five surgical cases without dopamine agonist treatment underwent RNA sequencing. Normal pituitary tissues from three patients served as controls. Differentially expressed genes (DEGs) were identified, and the functional pathways and gene networks were explored by IPA. Results: Transcriptome analysis revealed that lactotroph PitNETs had gene expression patterns that were distinct from normal pituitary tissues. We identified 1,172 upregulated DEGs, including nine long intergenic noncoding RNAs (lincRNAs) belonging to the top 30 DEGs. IPA of the upregulated DEGs showed that the estrogen receptor signaling, oxidative phosphorylation signaling, and EIF signaling were activated. In gene network analysis, key upstream regulators, such as EGR1, PRKACA, PITX2, CREB1, and JUND, may play critical roles in lactotroph PitNETs.
2024-04-26 | GSE240781 | GEO
Project description:Secretion of growth hormone by sporadic somatotroph neuroendocrine pituitary tumors (PitNETs) is the most common cause of acromegaly.Genome-wide DNA methylation was investigated in 48 somatotroph PitNETs with EPIC microarrays. Three subtypes of the tumors were identified. Subtype 1 tumors are densely granulated tumors without GNAS mutation characterized by high expression of NR5A1 (SF-1) and GIPR. The expression of both genes is correlated with specific methylation pattern at gene body and promoter methylation. Subtype 1 has generally lower methylation level at 5’ gene regulatory regions and CpG islands as compared to other tumor clusters. Subtype 2 are densely granulated PiNETs with common GNAS-mutations while Subtype 3 are mainly sparsely granulated tumors. Methylation/expression analysis indicate that the levels of ~50% genes differentially expressed genes between tumor subtypes that are located at in differentially methylated regions are DNA methylation dependent. These DNA methylation-controlled genes include CDKN1B, CCND2, EBF3, CDH4, CDH12 MGMT, STAT5A, PLXND1, PTPRE and MMP16 as wells as genes encoding ion channels and semaphorins. Results of DNA methylation profiling confirms three molecular subtypes of somatotroph PitNETs that differ in both gene expression and methylation pattern. High expression of NR5A1 and GIPR in subtype 1 tumors is correlated to specific methylation at both genes.
2023-09-25 | GSE226764 | GEO