Proteogenomic landscape and clinical characterization of GH-producing pituitary adenomas/somatotroph pituitary neuroendocrine tumors

Predictors of biochemical response to somatostatin receptor ligands in acromegaly

Although predictors of response to first-generation somatostatin receptor ligands (fg-SRLs), and to a lesser extent to pasireotide, have been studied in acromegaly for many years, their use is still not recommended in clinical guidelines. Is there insufficient evidence to use them? Numerous biomarkers including various clinical, functional, radiological and molecular markers have been identified. The first ones are applicable pre-surgery, while the molecular predictors are utilized for patients not cured after surgery. In this regard, factors predicting a good response to fg-SRLs are specifically: low basal GH, a low GH nadir in the acute octreotide test, T2 MRI hypointensity, a densely granulated pattern, high immunohistochemistry staining for somatostatin receptor 2 (SSTR2), and E-cadherin. However, there is still a lack of consensus regarding which of these biomarkers is more useful or how to integrate them into clinical practice. With classical statistical methods, it is complex to define reliable and generalizable cut-off values for a single biomarker. The potential solution to the limitations of traditional methods involves combining systems biology with artificial intelligence, which is currently providing answers to such long-standing questions that may eventually be finally included into the clinical guidelines and make personalized medicine a reality. The aim of this review is to describe the current knowledge of the main fg-SRLs and pasireotide response predictors, discuss their current usefulness, and point to future directions in the research of this field.

Clinicopathological Analysis of Densely and Sparsely Granulated Somatotroph Tumors of Pituitary

OBJECTIVE

Somatotroph tumors are the second most common type of pituitary neuroendocrine tumors, which can be further classified into 2 subtypes-densely granulated somatotroph tumors (DGSTs) and sparsely granulated somatotroph tumors (SGSTs). The aim of this study was to investigate the clinical significance of the 2 subtypes in a retrospective analysis.

METHODS

From the database of the Ningbo Clinical Pathology Diagnosis Center, we collected patients diagnosed with pituitary somatotroph tumors. We then compiled pertinent clinical and radiological data and proceeded with histopathological examination involving hematoxylin-eosin staining and immunohistochemical staining. Subsequent analysis compared the 2 subtypes using either χ2 test or Fisher exact test.

RESULTS

We analyzed 40 cases of somatotroph tumors, 18 cases DGSTs and 22 SGSTs. Male-to-female ratio was 5:4 for DGSTs and 4:7 for SGSTs. Mean age was 52.83 years for DGSTs and 47.18 years for SGSTs. Statistically significant differences were observed between the DGST and SGST groups in invasiveness (P = 0.0267) and postoperative remission (P = 0.007). Cells of both DGSTs and SGSTs exhibited coexpression of PIT1, growth hormone, and CAM5.2, although the patterns of CAM5.2 expression differed between the 2 subtypes.

CONCLUSIONS

The efficacy of CAM5.2 staining in distinguishing between DGSTs and SGSTs was demonstrated. SGSTs, with their increased invasiveness and lower remission rate, are a high-risk subtype. The histological subtype of somatotroph tumors plays a crucial role in guiding treatment decisions and prognostic evaluation in affected patients.

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.

Genetic diagnosis in acromegaly and gigantism: From research to clinical practice

It is usually considered that only 5% of all pituitary neuroendocrine tumours are due to inheritable causes. Since this estimate was reported, however, multiple genetic defects driving syndromic and nonsyndromic somatotrophinomas have been unveiled. This heterogeneous genetic background results in overlapping phenotypes of GH excess. Genetic tests should be part of the approach to patients with acromegaly and gigantism because they can refine the clinical diagnoses, opening the possibility to tailor the clinical conduct to each patient. Even more, genetic testing and clinical screening of at-risk individuals have a positive impact on disease outcomes, by allowing for the timely detection and treatment of somatotrophinomas at early stages. Future research should focus on determining the actual frequency of novel genetic drivers of somatotrophinomas in the general population, developing up-to-date disease-specific multi-gene panels for clinical use, and finding strategies to improve access to modern genetic testing worldwide.

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".

Predictors of Response to Treatment with First-Generation Somatostatin Receptor Ligands in Patients with Acromegaly

BACKGROUND AND AIMS

Predictors of first-generation somatostatin receptor ligands (fgSRLs) response in acromegaly have been studied for over 30 years, but they are still not recommended in clinical guidelines. Is there not enough evidence to support their use? This systematic review aims to describe the current knowledge of the main predictors of fgSRLs response and discuss their current usefulness, as well as future research directions.

METHODS

A systematic search was performed in the Scopus and PubMed databases for functional, imaging, and molecular predictive factors.

RESULTS

A total of 282 articles were detected, of which 64 were included. Most of them are retrospective studies performed between 1990 and 2023 focused on the predictive response to fgSRLs in acromegaly. The usefulness of the predictive factors is confirmed, with good response identified by the most replicated factors, specifically low GH nadir in the acute octreotide test, T2 MRI hypointensity, high Somatostatin receptor 2 (SSTR2) and E-cadherin expression, and a densely granulated pattern. Even if these biomarkers are interrelated, the association is quite heterogeneous. With classical statistical methods, it is complex to define reliable and generalizable cut-off values worth recommending in clinical guidelines. Machine-learning models involving omics are a promising approach to achieve the highest accuracy values to date.

CONCLUSIONS

This survey confirms a sufficiently robust level of evidence to apply knowledge of predictive factors for greater efficiency in the treatment decision process. The irruption of artificial intelligence in this field is providing definitive answers to such long-standing questions that may change clinical guidelines and make personalized medicine a reality.

Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine

The clinical characteristics and prognoses of acromegaly vary among patients. Assessment of current and novel predictors can lead to multilevel categorization of patients, allowing integration into new clinical guidelines and a reduction in the increased morbidity and mortality associated with acromegaly. Despite advances in the diagnosis and treatment of acromegaly, its pathophysiology remains unclear. Recent advancements in multiomics technologies, including genomics, transcriptomics, proteomics, metabolomics, and radiomics, have offered new opportunities to unravel the complex pathophysiology of acromegaly. This review comprehensively explores the emerging role of multiomics approaches in elucidating the molecular landscape of acromegaly. We discuss the potential implications of multiomics data integration in the development of novel diagnostic tools, identification of therapeutic targets, and the prospects of precision medicine in acromegaly management. By integrating diverse omics datasets, these approaches can provide valuable insights into disease mechanisms, facilitate the identification of diagnostic biomarkers, and identify potential therapeutic targets for precision medicine in the management of acromegaly.

Drug Repositioning for Refractory Benign Tumors of the Central Nervous System

Drug repositioning (DR) is the process of identifying novel therapeutic potentials for already-approved drugs and discovering new therapies for untreated diseases. DR can play an important role in optimizing the pre-clinical process of developing novel drugs by saving time and cost compared with the process of de novo drug discovery. Although the number of publications related to DR has rapidly increased, most therapeutic approaches were reported for malignant tumors. Surgical resection represents the definitive treatment for benign tumors of the central nervous system (BTCNS). However, treatment options remain limited for surgery-, chemotherapy- and radiation-refractory BTCNS, as well as malignant tumors. Meningioma, pituitary neuroendocrine tumor (PitNET), and schwannoma are the most common BTCNS. The treatment strategy using DR may be applied for refractory BTCNS, such as Grade 2 meningiomas, neurofibromatosis type 2-related schwannomatosis, and PitNETs with cavernous sinus invasion. In the setting of BTCNS, stable disease can provide significant benefit to the patient. DR may provide a longer duration of survival without disease progression for patients with refractory BTCNS. This article reviews the utility of DR for refractory BTCNS.

Development of a Simple and Stable NanoESI Spray System Using Suction Wind from the MS Inlet

Improving the reproducibility of proteome analysis systems presents a challenge; therefore, in this study, we developed a new insertion spray ionization (InSpIon) system wherein an InSpIon tube was designed with a spray tip inserted into the tube. This system stabilized the spray and subsequently improved the reproducibility of the analysis.