Metabolomics-A Promising Approach to Pituitary Adenomas

Strategy for Identifying a Robust Metabolomic Signature Reveals the Altered Lipid Metabolism in Pituitary Adenoma

Despite the well-established connection between systematic metabolic abnormalities and the pathophysiology of pituitary adenoma (PA), current metabolomic studies have reported an extremely limited number of metabolites associated with PA. Moreover, there was very little consistency in the identified metabolite signatures, resulting in a lack of robust metabolic biomarkers for the diagnosis and treatment of PA. Herein, we performed a global untargeted plasma metabolomic profiling on PA and identified a highly robust metabolomic signature based on a strategy. Specifically, this strategy is unique in (1) integrating repeated random sampling and a consensus evaluation-based feature selection algorithm and (2) evaluating the consistency of metabolomic signatures among different sample groups. This strategy demonstrated superior robustness and stronger discriminative ability compared with that of other feature selection methods including Student's t-test, partial least-squares-discriminant analysis, support vector machine recursive feature elimination, and random forest recursive feature elimination. More importantly, a highly robust metabolomic signature comprising 45 PA-specific differential metabolites was identified. Moreover, metabolite set enrichment analysis of these potential metabolic biomarkers revealed altered lipid metabolism in PA. In conclusion, our findings contribute to a better understanding of the metabolic changes in PA and may have implications for the development of diagnostic and therapeutic approaches targeting lipid metabolism in PA. We believe that the proposed strategy serves as a valuable tool for screening robust, discriminating metabolic features in the field of metabolomics.

Metabolomics in acromegaly: a systematic review

The therapeutic response heterogeneity in acromegaly persists, despite the medical-surgical advances of recent years. Thus, personalized medicine implementation, which focuses on each patient, is justified. Metabolomics would decipher the molecular mechanisms underlying the therapeutic response heterogeneity. Identification of altered metabolic pathways would open new horizons in the therapeutic management of acromegaly. This research aimed to evaluate the metabolomic profile in acromegaly and metabolomics' contributions to understanding disease pathogenesis. A systematic review was carried out by querying four electronic databases and evaluating patients with acromegaly through metabolomic techniques. In all, 21 studies containing 362 patients were eligible. Choline, the ubiquitous metabolite identified in growth hormone (GH)-secreting pituitary adenomas (Pas) by in vivo magnetic resonance spectroscopy (MRS), negatively correlated with somatostatin receptors type 2 expression and positively correlated with magnetic resonance imaging T2 signal and Ki-67 index. Moreover, elevated choline and choline/creatine ratio differentiated between sparsely and densely granulated GH-secreting PAs. MRS detected low hepatic lipid content in active acromegaly, which increased after disease control. The panel of metabolites of acromegaly deciphered by mass spectrometry (MS)-based techniques mainly included amino acids (especially branched-chain amino acids and taurine), glyceric acid, and lipids. The most altered pathways in acromegaly were the metabolism of glucose (particularly the downregulation of the pentose phosphate pathway), linoleic acid, sphingolipids, glycerophospholipids, arginine/proline, and taurine/hypotaurine. Matrix-assisted laser desorption/ionization coupled with MS imaging confirmed the functional nature of GH-secreting PAs and accurately discriminated PAs from healthy pituitary tissue.

Recommendations for the diagnosis and radiological follow-up of pituitary neuroendocrine tumours

Pituitary neuroendocrine tumours (PitNETs) constitute a heterogeneous group of tumours with a gradually increasing incidence, partly accounted for by more sensitive imaging techniques and more extensive experience in neuroradiology in this regard. Although most PitNETs are indolent, some exhibit aggressive behaviour, and recurrence may be seen after surgical removal. The changes introduced in the WHO classification in 2017 and terminological debates in relation to neuroendocrine tumours warrant an update of the guidelines for the diagnosis, preoperative and postoperative management, and follow-up of response to treatment of PitNETs. This multidisciplinary document, an initiative of the Neuroendocrinology area of the Sociedad Española de Endocrinología y Nutrición [Spanish Society of Endocrinology and Nutrition] (SEEN), focuses on neuroimaging studies for the diagnosis, prognosis and follow-up of PitNETs. The basic requirements and elements that should be covered by magnetic resonance imaging are described, and a minimum radiology report to aid clinicians in treatment decision-making is proposed. This work supplements the consensus between the Neuroendocrinology area of the SEEN and the Sociedad Española de Anatomía Patológica [Spanish Society of Pathology] (SEAP) for the pathological study of PitNETs.

The use of mass spectrometry in a proteome-centered multiomics study of human pituitary adenomas

A pituitary adenoma (PA) is a common intracranial neoplasm, and is a complex, chronic, and whole-body disease with multicausing factors, multiprocesses, and multiconsequences. It is very difficult to clarify molecular mechanism and treat PAs from the single-factor strategy model. The rapid development of multiomics and systems biology changed the paradigms from a traditional single-factor strategy to a multiparameter systematic strategy for effective management of PAs. A series of molecular alterations at the genome, transcriptome, proteome, peptidome, metabolome, and radiome levels are involved in pituitary tumorigenesis, and mutually associate into a complex molecular network system. Also, the center of multiomics is moving from structural genomics to phenomics, including proteomics and metabolomics in the medical sciences. Mass spectrometry (MS) has been extensively used in phenomics studies of human PAs to clarify molecular mechanisms, and to discover biomarkers and therapeutic targets/drugs. MS-based proteomics and proteoform studies play central roles in the multiomics strategy of PAs. This article reviews the status of multiomics, multiomics-based molecular pathway networks, molecular pathway network-based pattern biomarkers and therapeutic targets/drugs, and future perspectives for personalized, predeictive, and preventive (3P) medicine in PAs.

Metabolomics Profiling of Pituitary Adenomas by Raman Spectroscopy, Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy, and Mass Spectrometry of Serum Samples

To date, no studies are available in which pituitary adenomas (PAs) have been studied using techniques like confocal Raman spectroscopy, attenuated total reflection-Fourier transform infrared (FT-IR), and liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the same serum samples. To understand the metabolomics fingerprint, Raman spectra of 16 acromegaly, 19 Cushing's, and 33 nonfunctional PA (NFPA) and ATR-FTIR spectral acquisition of 16 acromegaly, 18 Cushing's, and 22 NFPA patient's serum samples were acquired. Next, Principal component-based linear discriminant analysis (PC-LDA) models were developed, Raman spectral analysis classified acromegaly with an accuracy of 79.17%, sensitivity of 75%, and specificity of 81.25%, Cushing's with an accuracy of 66.67%, sensitivity of 100%, and specificity of 52.63%, and NFPA with an accuracy of 73.17%, sensitivity of 75%, and specificity of 72.73%. ATR-FTIR spectral analysis classified acromegaly with an accuracy of 95.83%, sensitivity of 100%, and specificity of 93.75%, Cushing's with an accuracy of 65.38%, sensitivity of 87.5%, and specificity of 55.56%, and NFPA with an accuracy of 70%, sensitivity of 87.5%, and specificity of 43.75%. In either of the cases, healthy individual cohorts were clearly segregated from the disease cohort, which identified differential regulated regions of nucleic acids, lipids, amides, phosphates, and polysaccharide/C-C residue α helix regions. Furthermore, LC-MS/MS-based analysis of sera samples resulted in the identification of various sphingosine, lipids, acylcarnitines, amino acids, ethanolamine, choline, and their derivatives that differentially regulated in each tumor cohort. We believe cues obtained from the study may be used to generate the metabolite-based test to diagnose PAs from serum in addition to conventional techniques and also to understand disease biology for better disease management, point of care, and improving quality of life in PA patients.

Drp1 Regulated Mitochondrial Hypofission Promotes the Invasion and Proliferation of Growth Hormone-Secreting Pituitary Adenomas via Activating STAT3

The invasiveness and high proliferation rate of growth hormone-secreting pituitary adenomas (GHPAs) are closely related to poor prognosis in patients. We previously reported that abnormal glycolysis participates in this process; however, the role of mitochondria in the invasion and proliferation of GHPAs remains unknown. In the current study, stereological methods were first used to quantitatively calculate the number and morphology of mitochondria. The results revealed that the numbers, volumes and membrane areas of mitochondria were decreased in invasive GHPAs (IGHPAs) samples compared to noninvasive GHPAs (NIGHPAs) samples. Furthermore, significantly downregulated mRNA and protein levels of dynamin-related protein 1 (Drp1) were detected in IGHPAs, but no notable changes in fusion related molecules (Mfn1, Mfn2 and OPA1) were detected, suggesting that the abnormal mitochondrial dynamics in IGHPAs are characterized by hypofission. Mitochondrial hypofission caused by Mdivi-1, a specific Drp1 inhibitor, enhanced the invasion and proliferation of GH3 cell lines and primary cells from patients with GHPAs in vitro and in vivo, while overexpression of Drp1 reversed these processes. Mechanistically, mitochondrial hypofission might activate signal transducer and activator of transcription 3 (STAT3). Specifically, elevated nuclear pSTAT3^Y705 may promote GH3 cell invasion by upregulating the activity of matrix metalloproteinase 2/9, and elevated mitochondrial pSTAT3^S727 may promote GH3 cell proliferation by inhibiting the mitochondria-dependent apoptotic pathway. Taken together, our findings suggest that mitochondrial hypofission induced by Drp1 might strengthen the invasion and proliferation of GHPA tumor cells by activating STAT3, providing us with a new perspective on how mitochondria regulate the development of IGHPAs.

Applications of spatially resolved omics in the field of endocrine tumors

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Cushing's Disease Management: Glimpse Into 2051

Major advancements are expected in medicine and healthcare in the 21st century- "Digital Age", mainly due to the application of data technologies and artificial intelligence into healthcare. In this perspective article we share a short story depicting the future Cushings' Disease patient and the postulated diagnostic and management approaches. In the discussion, we explain the advances in recent times which makes this future state plausible. We postulate that endocrinology care will be completely reinvented in the Digital Age.

Metabolic Characteristics and M2 Macrophage Infiltrates in Invasive Nonfunctioning Pituitary Adenomas

OBJECTIVE

The aim of this study was to investigate the metabolic differences between invasive and non-invasive nonfunctioning pituitary adenomas (NFPAs), determine the expression of an M2 macrophage marker in NFPAs, and analyze the effects of metabolic changes in invasive NFPAs on M2 macrophage infiltrates.

METHODS

Tissue samples of NFPAs from patients who underwent transsphenoidal or craniotomy surgery from January 2021 to August 2021 were collected. NFPA tissues were analyzed based on a gas chromatography-mass spectrometry non-targeted metabolomics platform, and immunohistochemical staining for M2 macrophage marker CD206 was performed.

RESULTS

We evaluated 15 invasive and 21 non-invasive NFPAs. A total of 22 metabolites were identified through non-targeted metabolomics analysis. Among them, the expression of 1-octadecanol, inosine 5'-monophosphate, adenosine 5'-monophosphate, guanosine 5'-monophosphate, creatinine, desmosterol, taurine, hypotaurine, lactic acid, and succinic acid was upregulated in invasive NFPAs, while that of 1-oleoylglycerol, arachidonic acid, cis-11-eicosenoic acid, docosahexaenoic acid, glyceric acid, hypoxanthine, linoleic acid, lysine, oleic acid, uracil, valine, and xanthine was downregulated. Immunohistochemical analysis suggested that the number of CD206-positive cells was higher in invasive NFPAs than in non-invasive NFPAs.

CONCLUSION

Invasive and non-invasive NFPAs showed distinct metabolite profiles. The levels of succinic acid and lactic acid were higher in invasive NFPAs, and the high expression of the M2 macrophage marker was verified in invasive NFPAs.

An Update on Silent Corticotroph Adenomas: Diagnosis, Mechanisms, Clinical Features, and Management

Simple Summary

The 2017 World Health Organization classification of endocrine tumors defines pituitary adenomas based on their cell lineages. T-PIT can serve as a complimentary tool for further identification of silent corticotroph adenomas (SCAs). Unlike functioning corticotroph adenomas in patients with Cushing’s disease, SCAs present no clinical and biochemical features of Cushing’s syndrome. SCAs have been shown to exhibit a more aggressive course characterized by a higher probability of recurrence and resistance to conventional treatment due to their intrinsic histological features. The aim of our review is to offer an update on the diagnosis, mechanisms, clinical features and management of SCAs. Studies of the molecular mechanisms of SCA pathogenesis will provide new directions for the diagnosis and management of SCAs.

Abstract

With the introduction of 2017 World Health Organization (WHO) classification of endocrine tumors, T-PIT can serve as a complementary tool for identification of silent corticotroph adenomas (SCAs) in some cases if the tumor is not classifiable by pituitary hormone expression in pathological tissue samples. An increase of the proportion of SCAs among the non-functioning pituitary adenomas (NFPAs) has been witnessed under the new rule with the detection of T-PIT-positive ACTH-negative SCAs. Studies of molecular mechanisms related to SCA pathogenesis will provide new directions for the diagnosis and management of SCAs. A precise pathological diagnosis can help clinicians better identify SCAs. Understanding clinical features in the context of the pathophysiology of SCAs is critical for optimal management. It could provide information on appropriate follow-up time and aid in early recognition and treatment of potentially aggressive forms. Management approaches include surgical, radiation, and/or medical therapies.

Utility of 3T single-voxel proton MR spectroscopy for differentiating intracranial meningiomas from intracranial enhanced mass lesions

Background

Proton magnetic resonance spectroscopy (MRS) provides structural and metabolic information that is useful for the diagnosis of meningiomas with atypical radiological appearance. However, the metabolite that should be prioritized for the diagnosis of meningiomas has not been established.

Purpose

To evaluate the differences between the metabolic peaks of meningiomas and other intracranial enhanced mass lesions (non-meningiomas) using MR spectroscopy in short echo time (TE) spectra and the most useful metabolic peak for discriminating between the groups.

Material and Methods

The study involved 9 meningiomas, 22 non-meningiomas, intracranial enhancing tumors and abscesses, and 15 normal controls. The ranking of the peak at 3.8 ppm, peak at 3.8 ppm/Creatine (Cr), β-γ Glutamine-Glutamate (bgGlx)/Cr, N-acetyl compounds (NACs)/Cr, choline (Cho)/Cr, lipid and/or lactate (Lip-Lac) at 1.3 ppm/Cr, and the presence of alanine (Ala) were derived. The metabolic peaks were compared using the Mann-Whitney U test. ROC analysis was used to determine the cut-off values for differentiating meningiomas from non-meningiomas using statistically significant metabolic peaks.

Results

The ranking of the peak at 3.8 ppm among all the peaks, peak at 3.8 ppm/Cr, bgGlx/Cr, Lip-Lac/Cr, and the presence of Ala discriminated meningiomas from non-meningiomas with moderate to high accuracy. The highest accuracy was 96.9% at a threshold value of 3 for the rank of the peak at 3.8 ppm.

Conclusion

A distinct elevated peak at 3.8 ppm, ranked among the top three highest peaks, allowed the detection of meningiomas.

UPLC-MS/MS-based Lipidomic Profiles Revealed Aberrant Lipids Associated with Invasiveness of Silent Corticotroph Adenoma

CONTEXT

The accumulation of aberrant lipids and abnormal lipid metabolism in silent corticotroph adenomas (SCAs) could contribute to changes in clinical phenotypes, especially sphenoid sinus invasion.

OBJECTIVE

To systematically investigate lipidomic and transcriptomic alterations associated with invasiveness and their potential molecular mechanisms in SCAs and to provide candidate biomarkers for predicting invasiveness and novel treatment options for invasive SCAs by targeting lipids.

METHODS

Fifty-four SCAs (34 invasive/20 noninvasive) were subjected to lipidomic analysis based on ultraperformance liquid chromatography mass spectrometry, and 42 clinically nonfunctioning pituitary adenomas (23 invasive/19 noninvasive) were subjected to transcriptomic analysis. Differential analysis was performed to determine differential lipids and genes between invasive and noninvasive tumors. A functionally connected network was constructed with the molecular pathways as cores. Multiple machine learning methods were applied to identify the most critical lipids, which were further used to construct a lipidomic signature to predict invasive SCAs by multivariate logistic regression, and its performance was evaluated by receiver operating characteristic analysis.

RESULTS

Twenty-eight differential lipids were identified, and a functionally connected network was constructed with 2 lipids, 17 genes, and 4 molecular pathways. Connectivity Map (CMap) analysis further revealed 32 potential drugs targeting 4 genes and related pathways. The 4 most critical lipids were identified as risk factors contributing to the invasive phenotype. A lipidomic signature was constructed and showed excellent performance in discriminating invasive and noninvasive SCAs.

CONCLUSIONS

The lipidomic signature could serve as a promising predictor for the invasive SCA phenotype and provide potential therapeutic targets for SCAs.

Advances in the Imaging of Pituitary Tumors

In most patients with pituitary adenomas magnetic resonance imaging (MRI) is essential to guide effective decision-making. T1- and T2-weighted sequences allow the majority of adenomas to be readily identified. Supplementary MR sequences (e.g. FLAIR; MR angiography) may also help inform surgery. However, in some patients MRI findings are 'negative' or equivocal (e.g. with failure to reliably identify a microadenoma or to distinguish postoperative change from residual/recurrent disease). Molecular imaging [e.g. ¹¹C-methionine PET/CT coregistered with volumetric MRI (Met-PET/MR^CR)] may allow accurate localisation of the site of de novo or persistent disease to guide definitive treatment (e.g. surgery or radiosurgery).

Cyclooxygenase enzyme and PGE2 expression in patients with functional and non-functional pituitary adenomas

BACKGROUND

Pituitary adenomas as multifactorial intracranial neoplasms impose a massive burden of morbidity on patients and characterizing the molecular mechanism underlying their pathogenesis has received considerable attention. Despite the appealing role of cyclooxygenase enzymes and their bioactive lipid products in cancer pathogenesis, their relevance to pituitary adenoma pathogenesis is debated and yet to be determined. Thus, the current study perused this relevance.

METHODS

The expression level of the isoforms of cyclooxygenase (COX-1 and COX-2) was evaluated in hormone-secreting and in-active pituitary adenoma tumors and normal pituitary tissues through Real-Time PCR. The level of PGE2, as the main product of enzymes, was assessed using enzyme immunoassay kits in patients and healthy subjects.

RESULTS

The results of the current study demonstrated that COX-1 and COX-2 expression levels were increased in pituitary tumors including non-functional pituitary adenoma (NFPA), acromegaly, Cushing's disease and prolactinoma compared with normal pituitary tissues. A significant expression level of COX-2 was observed in NFPA compared with the other pituitary tumors. Furthermore, the COX-2 expression level was significantly increased in macroadenoma and invasive tumors. The level of PGE2 was consistent with COX enzymes enhanced in pituitary adenoma tumors compared with healthy pituitary tissue. A significant elevation in the PGE2 level was detected in NFPA compared with hormone-secreting pituitary tumors. Additionally, the PGE2 level was increased in macroadenoma compared with microadenoma and in invasive compared with non-invasive pituitary tumors. The diagnostic values of cyclooxygenase isoforms and PGE2 were considerable between patients and healthy groups; however, COX-2 revealed more value in distinguishing endocrinologically active and non-active pituitary tumors.

CONCLUSIONS

Data from the current study provides expression patterns of COX-1, COX-2 and PGE2 in prevalent pituitary tumors and their association with patients' clinical features which may open up new molecular targets for early diagnosis/follow up of pituitary tumor growth.

Molecular Mechanisms of Pituitary Cell Plasticity

The mechanisms that mediate plasticity in pituitary function have long been a subject of vigorous investigation. Early studies overcame technical barriers and challenged conceptual barriers to identify multipotential and multihormonal cell populations that contribute to diverse pituitary stress responses. Decades of intensive study have challenged the standard model of dedicated, cell type-specific hormone production and have revealed the malleable cellular fates that mediate pituitary responses. Ongoing studies at all levels, from animal physiology to molecular analyses, are identifying the mechanisms underlying this cellular plasticity. This review describes the findings from these studies that utilized state-of-the-art tools and techniques to identify mechanisms of plasticity throughout the pituitary and focuses on the insights brought to our understanding of pituitary function.

Modern imaging of pituitary adenomas

Decision-making in pituitary disease is critically dependent on high quality imaging of the sella and parasellar region. Magnetic resonance imaging (MRI) is the investigation of choice and, for the majority of patients, combined T1 and T2 weighted sequences provide the information required to allow surgery, radiotherapy (RT) and/or medical therapy to be planned and long-term outcomes to be monitored. However, in some cases standard clinical MR sequences are indeterminate and additional information is needed to help inform the choice of therapy for a pituitary adenoma (PA). This article reviews current recommendations for imaging of PA, examines the potential added value that alternative MR sequences and/or CT can offer, and considers how the use of functional/molecular imaging might allow definitive treatment to be recommended for a subset of patients who would otherwise be deemed unsuitable for (further) surgery and/or RT.

Identification of Transcriptional Metabolic Dysregulation in Subtypes of Pituitary Adenoma by Integrated Bioinformatics Analysis

BACKGROUND

Pituitary adenoma (PA) is a prevalent intracranial tumor. Metabolites differ between pituitary tumor and healthy tissues or among different tumor subtypes. However, the transcriptional changes in metabolic enzymes, which are usually seemed as targets for metabolic therapy, remain unidentified.

METHODS

Using microarray data for 160 samples from the Gene Expression Omnibus database, across the four most common tumor subtypes, we present the integrated identification of differentially expressed genes (DEGs) between tumors and controls.

RESULTS

Subtype-specific DEGs revealed 1081 prolactin tumor-specific DEGs, 437 nonfunctioning tumor-specific DEGs, and 217 common DEGs among the four subtypes. Functional enrichment showed that a lot of biological functions related to metabolism had changed. Twenty-one prolactin and twenty-three nonfunctioning tumor-specific metabolic-related DEGs are mainly involved in fatty acid and nucleotide metabolism, redox reaction, and gluconeogenesis. Eighteen metabolic-related DEGs enriched in the metabolism of xenobiotics by the cytochrome P450 pathway, sulfur metabolism, retinoid metabolism, and glucose homeostasis were abnormal in all subtypes of PA.

CONCLUSION

Based on a comprehensive bioinformatics analysis of the available PA-related transcriptomics data, we identified specific DEGs related to metabolism, and some of them might be new attractive therapeutic targets. Especially, PDK4 and PCK1 might be new attractive biomarkers and therapeutic targets.