Multilineage pituitary neuroendocrine tumors with PIT1/SF1 co-expression
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ABSTRACT:
PROVIDER: PRJNA1034042 | ENA |
REPOSITORIES: ENA
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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:Methylome analysis in pituitary neuroendocrine tumors
| PRJEB50807 | ENA
Project description: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".
| S-EPMC10791732 | biostudies-literature
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
Project description:Acromegaly is a severe and life-threatening disease caused by persistent excess of growth hormone (GH) which stimulates the synthesis and secretion of insulin-like growth factor-1 (IGF-1). In the majority (95%) of patients acromegaly is caused by sporadic GH-secreting neuroendocrine pituitary tumor (PitNET). Acromegaly-causing tumors are histologically diverse. The aim was to determine transcriptomic profiles in different histological subtypes and evaluate clinical implication of differential gene expression.
2022-12-01 | E-MTAB-11889 | biostudies-arrayexpress
Project description:Corticotropin (ACTH)-secreting pituitary adenomas give rise to a severe endocrinological disorder, i.e., Cushing’s disease, with multifaceted clinical presentation and treatment outcomes. Experimental studies suggested that disease variability is inherent to the pituitary tumor, thus pointing to the need for further studies into tumor biology. Aim of the present study was to evaluate transcriptome expression pattern in a large series of ACTH-secreting pituitary adenoma specimens, in order to identify molecular signatures of these tumors. Gene expression profiling of formalin-fixed paraffin-embedded specimens from 40 human ACTH-secreting pituitary adenomas revealed significant expression of genes involved in protein biosynthesis and ribosomal function, in keeping with neuroendocrine cell profile. Unsupervised cluster analysis identified three distinct gene profile clusters and several genes were uniquely overexpressed in a given cluster, accounting for different molecular signatures. Of note, gene expression profiles were associated with clinical features such as age and size of the tumor. Altogether, our study shows that corticotrope tumors are characterized by neuroendocrine gene expression profile and present subgroup-specific molecular features.
2018-06-18 | GSE93825 | GEO
Project description:The clinical characteristics of growth hormone (GH)-producing pituitary adenomas vary across patients. In this study, we aimed to integrate the genetic alterations, protein expression profiles, transcriptomes, and clinical characteristics of GH-producing pituitary adenomas to detect molecules associated with acromegaly characteristics. Targeted capture sequencing and copy number analysis of 36 genes and non-targeted proteomics analysis were performed on fresh-frozen samples from 121 sporadic GH-producing pituitary adenomas. Targeted capture sequencing revealed GNAS as the only driver gene, as previously reported. Classification by consensus clustering using both RNA sequencing and proteomics revealed many similarities between the proteome and the transcriptome. Gene ontology analysis was performed for differentially expressed proteins between wild-type and mutant GNAS samples identified by non-targeted proteomics analysis and involved in G protein–coupled receptor (GPCR) pathways. The results suggested that GNAS mutations impact endocrinological features in acromegaly through GPCR pathway induction. ATP2A2 and ARID5B correlated with the GH change rate in the octreotide loading test, and WWC3, SERINC1, and ZFAND3 correlated with the tumor volume change rate after somatostatin analog treatment. These results identified a biological connection between GNAS mutations and the clinical and biochemical characteristics of acromegaly, revealing novel molecules associated with acromegaly that may affect medical treatment efficacy.
2022-11-25 | GSE213527 | GEO