Medication for Acromegaly Reduces Expression of MUC16, MACC1 and GRHL2 in Pituitary Neuroendocrine Tumour Tissue

The molecular biology of sporadic acromegaly

GH-secreting tumors represent 15 % to 20 % of all pituitary neuroendocrine tumors (pitNETs), of which 95 % occur in a sporadic context, without an identifiable inherited cause. Recent multi-omic approaches have characterized the epigenomic, genomic, transcriptomic, proteomic and kynomic landscape of pituitary tumors. Transcriptomic analysis has allowed us to discover specific transcription factors driving the differentiation of pituitary tumors and gene expression patterns. GH-secreting, along with PRL- and TSH-secreting pitNETs are driven by POU1F1; ACTH-secreting tumors are determined by TBX19; and non-functioning tumors, which are predominantly of gonadotrope differentiation are conditioned by NR5A1. Upregulation of certain miRNAs, such as miR-107, is associated with tumor progression, while downregulation of others, like miR-15a and miR-16-1, correlates with tumor size reduction. Additionally, miRNA expression profiles are linked to treatment resistance and clinical outcomes, providing insights into potential therapeutic targets. Specific somatic mutations in GNAS, PTTG1, GIPR, HGMA2, MAST and somatic variants associated with cAMP, calcium signaling, and ATP pathways have also been associated with the development of acromegaly. This review focuses on the oncogenic mechanisms by which sporadic acromegaly can develop, covering a complex series of molecular alterations that ultimately alter the balance between proliferation and apoptosis, and dysregulated hormonal secretion.

DNA Methylation Pattern in Somatotroph Pituitary Neuroendocrine Tumors

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.

Large Scale Molecular Studies of Pituitary Neuroendocrine Tumors: Novel Markers, Mechanisms and Translational Perspectives

Simple Summary

Pituitary neuroendocrine tumors are non-cancerous tumors of the pituitary gland, that may overproduce hormones leading to serious health conditions or due to tumor size cause chronic headache, vertigo or visual impairment. In recent years pituitary neuroendocrine tumors are studied with the latest molecular biology methods that simultaneously investigate a large number of factors to understand the mechanisms of how these tumors develop and how they could be diagnosed or treated. In this review article, we have studied literature reports, compiled information and described molecular factors that could affect the development and clinical characteristics of pituitary neuroendocrine tumors, discovered factors that overlap between several studies using large scale molecular analysis and interpreted the potential involvement of these factors in pituitary tumor development. Overall, this study provides a valuable resource for understanding the biology of pituitary neuroendocrine tumors.

Abstract

Pituitary neuroendocrine tumors (PitNETs) are non-metastatic neoplasms of the pituitary, which overproduce hormones leading to systemic disorders, or tumor mass effects causing headaches, vertigo or visual impairment. Recently, PitNETs have been investigated in large scale (exome and genome) molecular analyses (transcriptome microarrays and sequencing), to uncover novel markers. We performed a literature analysis on these studies to summarize the research data and extrapolate overlapping gene candidates, biomarkers, and molecular mechanisms. We observed a tendency in samples with driver mutations (GNAS, USP8) to have a smaller overall mutational rate, suggesting driver-promoted tumorigenesis, potentially changing transcriptome profiles in tumors. However, direct links from drivers to signaling pathways altered in PitNETs (Notch, Wnt, TGF-β, and cell cycle regulators) require further investigation. Modern technologies have also identified circulating nucleic acids, and pinpointed these as novel PitNET markers, i.e., miR-143-3p, miR-16-5p, miR-145-5p, and let-7g-5p, therefore these molecules must be investigated in the future translational studies. Overall, large-scale molecular studies have provided key insight into the molecular mechanisms behind PitNET pathogenesis, highlighting previously reported molecular markers, bringing new candidates into the research field, and reapplying traditional perspectives to newly discovered molecular mechanisms.