miR-383-5p, miR-181a-5p, and miR-181b-5p as Predictors of Response to First-Generation Somatostatin Receptor Ligands in Acromegaly

Somatostatin receptors in pituitary somatotroph adenomas as predictors of response to somatostatin receptor ligands: A pathologist's perspective

There are five subtypes of somatostatin receptors (SST1-5), which are expressed in several types of solid neoplasms, neuroendocrine tumors, and pituitary adenomas. Most commonly, SST2 and SST5, are of interest regarding diagnostic, treatment, and prognostic purposes. In this article the basic biological characteristics of SST are briefly reviewed, and focus given to the immunohistochemical evaluation of SST2 and SST5 in growth hormone (GH)-secreting pituitary tumors, and their quantification as predictors of response to treatment with somatostatin receptor ligands (SRL), the mainstay of the pharmacological therapy available for these tumors. Although many different scoring systems for SST2 immunohistochemistry showing correlation with SRL response have been reported, among which the immunoreactivity score (IRS) has been the most consistently used, a universally validated immunohistochemical technique and scoring scheme is lacking. Efforts should be made on collaborative multicenter studies aiming at validating homogeneous immunostaining protocols and a scoring system for SST2 and SST5 expression, to help clinicians to define the optimal therapeutic strategy for the patients with somatotroph tumors.

Using digital PCR to investigate the prevalence of KRAS variants in pituitary tumours

Pituitary tumours (PT) are formed in the pituitary gland, a small gland situated at the base of the brain. These tumours can be categorized according to their histological origin and hormone production. In surgical series, non-functioning PT are the commonest subtype, followed by functioning somatotroph and corticotroph tumours. Different somatic alterations have been implicated in the pathogenesis of these tumours and the objective of our study was to expand our previous new finding of KRAS pathogenic genetic variants in pituitary tumours. We conducted a digital polymerase chain reaction (PCR) analysis on formalin-fixed paraffin-embedded tissue blocks belonging to 189 patients. The results showed that, from the 184 pituitary tumours with good quality samples, 13 tumours (7.1%) presented mutant KRAS. The median age of the mutated group was 47 years old (range 19-77) and most patients with mutant KRAS tumours were from the female gender (61.5%, 8/13) and non-functioning subtype. For the first-time, mutant KRAS in corticotroph and somatotroph tumours were detected, and the variants showed low allele frequencies. In conclusion, we demonstrated that pituitary tumours might have mutant KRAS, and these data were not previously described probably due to lack of sensitivity of previous technologies. By identifying these variants, even at minimal levels, we open doors to a deeper understanding of the tumour microenvironment, clonal evolution and potential therapeutic targets.

The emerging role of miRNAs in pituitary adenomas: From molecular signatures to diagnostic potential

Pituitary adenomas (PAs) are an array of tumors originating from the pituitary gland. PAs are sorted as functional or nonfunctional according to their hormonal activity and classified according to size into microadenomas and macroadenomas. Still, the cellular events that trigger the transformations in pituitary neoplasms are not fully understood, and the current classification methods do not precisely predict clinical behavior. A rising number of researches have emphasized the role of miRNAs, that drawn more attention as oncogenic molecules or tumor suppressors. The etiopathological mechanisms of PAs include multiple molecular cascades that are influenced by different miRNAs. miRNAs control the cell cycle control, pro- or antiapoptotic processes, and tumor invasion and metastasis. miRNAs offer a novel perspective on tumor features and behaviors and might be valuable in prognostication and therapeutic plans. In pituitary adenomas, miRNAs showed a specific expression pattern depending on their size, cell origin, remission, and treatments. Screening miRNA expression patterns is promising to monitor and evaluate recurrence, as well as to investigate the efficacy of radiation and chemotherapy for PAs exhibiting aggressive behavior. Thus, the current review investigated the interplay of the miRNAs' pivotal role in offering new opportunities to translate these innovative epigenetic tools into healthcare applications.

New molecular tools for precision medicine in pituitary neuroendocrine tumors

Precision, personalized, or individualized medicine in pituitary neuroendocrine tumors (PitNETs) has become a major topic in the last few years. It is based on the use of biomarkers that predictively segregate patients and give answers to clinically relevant questions that help us in the individualization of their management. It allows us to make early diagnosis, predict response to medical treatments, predict surgical outcomes and investigate new targets for therapeutic molecules. So far, substantial progress has been made in this field, although there are still not enough precise tools that can be implemented in clinical practice. One of the main reasons is the excess overlap among clustered patients, with an error probability that is not currently acceptable for clinical practice. This overlap is due to the high heterogeneity of PitNETs, which is too complex to be overcome by the classical biomarker investigation approach. A systems biology approach based on artificial intelligence techniques seems to be able to give answers to each patient individually by building mathematical models through the interaction of multiple factors, including those of omics sciences. Integrated studies of different molecular omics techniques, as well as radiomics and clinical data are necessary to understand the whole system and to finally achieve the key to obtain precise biomarkers and implement personalized medicine. In this review we have focused on describing the current advances in the area of PitNETs based on the omics sciences, that are clearly going to be the new tool for precision medicine.

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.

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.

Newer parameters of the octreotide test in patients with acromegaly

PURPOSE

Predicting the therapeutic effects of first-generation somatostatin receptor ligands (fg-SRLs) is important when assessing or planning effective treatment strategies in patients with acromegaly. The oft-used maximum growth hormone (GH) suppression rate parameter of the octreotide test has a suboptimal predictive value. Therefore, this study explored newer parameters of the octreotide test for predicting the therapeutic effect of long-acting fg-SRLs.

METHODS

In this single-center retrospective study, the octreotide test parameters and the therapeutic effects of fg-SRL at 3 months were investigated in 45 consecutive treatment-naïve patients with acromegaly between April 2008 and March 2023. Additionally, the relationship between the octreotide test parameters and the therapeutic effects of fg-SRLs was investigated. Tumor shrinkage was evaluated based on changes in the longitudinal diameter of the macroadenomas. The area GH suppression rate-time under the curve (AUC) and the time to nadir GH level were calculated and compared with the maximum GH suppression rate.

RESULTS

The AUC estimated reductions in serum insulin-like growth factor I, and tumor shrinkage. The time to nadir GH level predicted tumor shrinkage more robustly than the maximum GH suppression rate in patients with macroadenoma.

CONCLUSION

The AUC and time to nadir GH level may potentially be newer parameters of the octreotide test for estimating the therapeutic effect of fg-SRLs.

Biomarkers of response to treatment in acromegaly

INTRODUCTION

Medical treatment of acromegaly is based in a `trial and error` approach. First-generation somatostatin receptor ligands (fg-SRL) are prescribed as first-line medical therapy to the vast majority of patients, despite lack of disease control in approximately 60% of patients. However, other drugs used in acromegaly treatment are available (cabergoline, pasireotide and pegvisomant).

AREAS COVERED

In this article, we review and discuss the biomarkers of response to medical treatment in acromegaly.

EXPERT OPINION

Biomarkers for fg-SRL that can already be applied in clinical practice are: gender, age, pretreatment GH and IGF-I levels, cytokeratin granulation pattern, and the expression of somatostatin receptor type 2. Using biomarkers of response could guide treatment towards precision medicine with greater efficacy and lower costs.

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.