Integrative Clinical, Hormonal and Molecular Data associate with Invasiveness in Acromegaly: REMAH Study.

INTRODUCTION: Growth-hormone (GH)-secreting pituitary-tumors (GHomas) are the most common acromegaly cause. At diagnosis, most of them are macroadenomas, and up to 56% display cavernous sinus invasion. Biomarkers assessment associated with tumor-growth and invasion are important to optimize their management. OBJECTIVES: To identify clinical/hormonal/molecular-biomarkers associated with tumor-size and invasiveness in GHomas, and to analyze the influence of pre-treatment with somatostatin-analogs or dopamine-agonists in key molecular biomarkers expression. METHODS: Clinical/analytical/radiological-variables were evaluated in 192 patients from the REMAH-study (ambispective multicenter post-surgery study of the Spanish Society of Endocrinology and Nutrition). Expression of somatostatin/ghrelin/dopamine-systems components, and key pituitary/proliferation-markers were evaluated in GHomas after the first surgery. Univariate/multivariate regression studies were performed to identify association between variables. RESULTS: 80% of patients harbor macroadenomas (63.8% with extrasellar-growth). Associations between larger and more invasive GHomas with younger age, visual-abnormalities, higher IGF1-levels, extrasellar/suprasellar-growth and/or cavernous-sinus invasion were found. Higher GH1 and lower PRL/POMC/CGA/AVPR1B/DRD2T/DRD2L expression levels (p<0.05) were associated to tumor invasiveness. LASSO´s penalized regression identified combinations of clinical and molecular features with AUCs between 0.67-0.82. Preoperative therapy with dopamine-agonist or somatostatin-analogs did not alter the expression of any of the markers analyzed except for DRD1/AVPR1B (up-regulated with dopamine-agonist), and FSHB/CRHR1 (down-regulated with somatostatin-analogs). CONCLUSIONS: A specific combination of clinical/analytical/molecular variables was found to be associated with tumor invasiveness and growth capacity in GHomas. Pre-treatment with first-line drugs for acromegaly did not significantly modify the expression of the most relevant biomarkers in our association model. These findings provide valuable insights for risk stratification and personalized management of GHomas.

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.

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 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.

Revisiting the usefulness of the short acute octreotide test to predict treatment outcomes in acromegaly.

Introduction: We previously described that a short version of the acute octreotide test (sAOT) can predict the response to first-generation somatostatin receptor ligands (SRLs) in patients with acromegaly. We have prospectively reassessed the sAOT in patients from the ACROFAST study using current ultra-sensitive GH assays. We also studied the correlation of sAOT with tumor expression of E-cadherin and somatostatin receptor 2 (SSTR2) . Methods: A total of 47 patients treated with SRLs for 6 months were evaluated with the sAOT at diagnosis and correlated with SRLs' response. Those patients whose IGF1 decreased to <3SDS from normal value were considered responders and those whose IGF1 was ≥3SDS, were considered non-responders. The 2 hours GH value (GH2h) after s.c. administration of 100 mcg of octreotide was used to define predictive cutoffs. E-cadherin and SSTR2 immunostaining in somatotropinoma tissue were investigated in 24/47 and 18/47 patients, respectively. Results: In all, 30 patients were responders and 17 were non-responders. GH2h was 0.68 (0.25-1.98) ng/mL in responders vs 2.35 (1.59-9.37) ng/mL in non-responders (p<0.001). GH2h = 1.4ng/mL showed the highest ability to identify responders (accuracy of 81%, sensitivity of 73.3%, and specificity of 94.1%). GH2h = 4.3ng/mL was the best cutoff for non-response prediction (accuracy of 74%, sensitivity of 35.3%, and specificity of 96.7%). Patients with E-cadherin-positive tumors showed a lower GH2h than those with E-cadherin-negative tumors [0.9 (0.3-2.1) vs 3.3 (1.5-12.1) ng/mL; p<0.01], and patients with positive E-cadherin presented a higher score of SSTR2 (7.5 ± 4.2 vs 3.3 ± 2.1; p=0.01). Conclusion: The sAOT is a good predictor tool for assessing response to SRLs and correlates with tumor E-cadherin and SSTR2 expression. Thus, it can be useful in clinical practice for therapeutic decision-making in patients with acromegaly.

Molecular characterization of epithelial-mesenchymal transition and medical treatment related-genes in non-functioning pituitary neuroendocrine tumors.

Introduction: Different medical therapies have been developed for pituitary adenomas. However, Non-Functioning Pituitary Neuroendocrine Tumors (NF-PitNET) have shown little response to them. Furthermore, epithelial-mesenchymal transition (EMT) has been linked to resistance to medical treatment in a significant number of tumors, including pituitary adenomas. Methods: We aimed to evaluate the expression of EMT-related markers in 72 NF-PitNET and 16 non-tumoral pituitaries. To further explore the potential usefulness of medical treatment for NF-PitNET we assessed the expression of somatostatin receptors and dopamine-associated genes. Results: We found that SNAI1, SNAI2, Vimentin, KLK10, PEBP1, Ki-67 and SSTR2 were associated with invasive NF-PitNET. Furthermore, we found that the EMT phenomenon was more common in NF-PitNET than in GH-secreting pituitary tumors. Interestingly, PEBP1 was overexpressed in recurrent NF-PitNET, and could predict growth recurrence with 100% sensitivity but only 43% specificity. In parallel with previously reported studies, SSTR3 is highly expressed in our NF-PitNET cohort. However, SSTR3 expression is highly heterogeneous among the different histological variants of NF-PitNET with very low levels in silent corticotroph adenomas. Conclusion: NF-PitNET showed an enhanced EMT phenomenon. SSTR3 targeting could be a good therapeutic candidate in NF-PitNET except for silent corticotroph adenomas, which express very low levels of this receptor. In addition, PEBP1 could be an informative biomarker of tumor regrowth, useful for predictive medicine in NF-PitNET.

Data mining analyses for precision medicine in acromegaly: a proof of concept.

Predicting which acromegaly patients could benefit from somatostatin receptor ligands (SRL) is a must for personalized medicine. Although many biomarkers linked to SRL response have been identified, there is no consensus criterion on how to assign this pharmacologic treatment according to biomarker levels. Our aim is to provide better predictive tools for an accurate acromegaly patient stratification regarding the ability to respond to SRL. We took advantage of a multicenter study of 71 acromegaly patients and we used advanced mathematical modelling to predict SRL response combining molecular and clinical information. Different models of patient stratification were obtained, with a much higher accuracy when the studied cohort is fragmented according to relevant clinical characteristics. Considering all the models, a patient stratification based on the extrasellar growth of the tumor, sex, age and the expression of E-cadherin, GHRL, IN1-GHRL, DRD2, SSTR5 and PEBP1 is proposed, with accuracies that stand between 71 to 95%. In conclusion, the use of data mining could be very useful for implementation of personalized medicine in acromegaly through an interdisciplinary work between computer science, mathematics, biology and medicine. This new methodology opens a door to more precise and personalized medicine for acromegaly patients.

Implications of Heterogeneity of Epithelial-Mesenchymal States in Acromegaly Therapeutic Pharmacologic Response.

Acromegaly is caused by excess growth hormone (GH) produced by a pituitary tumor. First-generation somatostatin receptor ligands (SRLs) are the first-line treatment. Several studies have linked E-cadherin loss and epithelial-mesenchymal transition (EMT) with resistance to SRLs. Our aim was to study EMT and its relationship with SRLs resistance in GH-producing tumors. We analyzed the expression of EMT-related genes by RT-qPCR in 57 tumors. The postsurgical response to SRLs was categorized as complete response, partial response, or nonresponse if IGF-1 was normal, had decreased more than 30% without normalization, or neither of those, respectively. Most tumors showed a hybrid and variable EMT expression profile not specifically associated with SRL response instead of a defined epithelial or mesenchymal phenotype. However, high SNAI1 expression was related to invasive and SRL-nonresponsive tumors. RORC was overexpressed in tumors treated with SRLs before surgery, and this increased expression was more prominent in those cases that normalized postsurgical IGF-1 levels under SRL treatment. In conclusion, GH-producing tumors showed a heterogeneous expression pattern of EMT-related genes that would partly explain the heterogeneous response to SRLs. SNAI1 and RORC may be useful to predict response to SRLs and help medical treatment decision making.

Differential Behavior of 25(OH)D and f25(OH)D3 in Patients with Morbid Obesity After Bariatric Surgery.

BACKGROUND: Total 25-OH-vitamin D (25(OH)D) levels are decreased in patients with obesity, but few data exist regarding free-vitamin D3 (f25(OH)D3) concentrations. We aimed to evaluate the effect of bariatric surgery on 25(OH)D and f25(OH)D3 in a cohort of patients with morbid obesity. METHODS: Twenty-four patients submitted to sleeve gastrectomy (SG) (mean age 48 years, body mass index (BMI) 48.16±10.73k/m2) were evaluated before and 1 year after surgery. Anthropometric data, parathormone (PTH), calcium, alkaline phosphatase, 25(OH)D, and f25(OH)D3 were recorded. RESULTS: 25(OH)D and f25(OH)D3 correlated well before and after SG. Baseline determinations did not correlate with BMI, but they inversely correlated with BMI 1 year after surgery (rs=-0.46, p=0.02 and rs=-0.60, p=0.002, respectively). Post-surgery % total body weight loss (%TBWL) was 27.4±13.8 %; f25(OH)D3 concentrations increased significantly (5.28±2.29 pg/mL vs 6.64±2.25 pg/mL; p=0.03), whereas 25(OH)D did not change. Patients who achieved a BMI <35 kg/m2 1 year after surgery had significantly higher concentrations of f25(OH)D3 (7.9±1 pg/mL vs 4.8±1.1, p<0.001) and 25(OH)D (30.9±9.4 ng/mL vs 22.3±13.4; p=0.03) compared to those who remained with BMI >35 kg/m2. CONCLUSION: There is a significant inverse relationship between BMI and both f25(OH)D3 and 25(OH)D 1 year after surgery. Only f25(OH)D3 concentrations increased 1 year after surgery, which could be explained by a greater f25(OH)D3 sequestration before SG in the adipose tissue, potentially due to the more liposoluble nature of f25(OH)D3 than the protein-bound form 25(OH)D.

Pasireotide in the Personalized Treatment of Acromegaly.

The delay in controlling the disease in patients who do not respond to first-line treatment with first generation somatostatin receptor ligands (first-generation SRLs) can be quantified in years, as every modification in the medical therapy requires some months to be fully evaluated. Considering this, acromegaly treatment should benefit from personalized medicine therapeutic approach by using biomarkers identifying drug response. Pasireotide has been positioned mostly as a compound to be used in first-generation SRLs resistant patients and after surgical failure, but sufficient data are now available to indicate it is a first line therapy for patients with certain characteristics. Pasireotide has been proved to be useful in patients in which hyperintensity T2 MRI signal is shown and in those depicting low SST2 and high expression of SST5, low or mutated AIP condition and sparsely granulated immunohistochemical pattern. This combination of clinical and pathological characteristics is unique for certain patients and seems to cluster in the same cases, strongly suggesting an etiopathogenic link. Thus, in this paper we propose to include this clinico-pathologic phenotype in the therapeutic algorithm, which would allow us to use as first line medical treatment those compounds with the highest potential for achieving the fastest control of GH hypersecretion as well as a positive effect upon tumor shrinkage, therefore accelerating the implementation of precision medicine for acromegaly. Moreover, we suggest the development, validation and clinical use of a pasireotide acute test, able to identify patients responsive to pasireotide LAR as the acute octreotide test is able to do for SRLs.

Molecular determinants of enhanced response to somatostatin receptor ligands after debulking in large GH-producing adenomas.

OBJECTIVE: Large somatotrophic adenomas depict poor response to somatostatin receptor ligands (SRLs). Debulking has shown to enhance SRLs effect in some but not all cases and tumour volume reduction has been proposed as the main predictor of response. No biological studies have been performed so far in this matter. We aimed to identify molecular markers of response to SRLs after surgical debulking in GH-secreting adenomas. DESIGN: We performed a multicenter retrospective study. PATIENTS: 24 patients bearing large GH-producing tumours. MEASUREMENTS: Clinical data and SRLs response both before and after surgical debulking were collected, and 21 molecular biomarkers of SRLs response were studied in tumour samples by gene expression. RESULTS: From the 21 molecular markers studied, only two of them predicted enhanced SRLs response after surgery. Tumours with improved response to SRLs after surgical debulking showed lower levels of Ki-67 (MKI67, FC = 0.17 and P = .008) and higher levels of RAR-related orphan receptor C (RORC) (FC = 3.1 and P Ë‚ .001). When a cut-off of no detectable expression was used for Ki-67, the model provided a sensitivity of 100% and a specificity of 52.6% with an area under the curve of 65.8%. Using a cut-off of 2 units of relative expression of RORC, the prediction model showed 100% of sensitivity and specificity. CONCLUSIONS: High levels of RORC and low levels of Ki-67 identify improved SRLs response after surgical debulking in large somatotropic adenomas. To determine their expression would facilitate medical treatment decision-making after surgery.

Molecular profiling for acromegaly treatment: a validation study.

Pharmacologic treatment of acromegaly is currently based upon assay-error strategy, the first-generation somatostatin receptor ligands (SRL) being the first-line treatment. However, about 50% of patients do not respond adequately to SRL. Our objective was to evaluate the potential usefulness of different molecular markers as predictors of response to SRL. We used somatotropinoma tissue obtained after surgery from a national cohort of 100 acromegalic patients. Seventy-one patients were treated with SRL during at least 6 months under maximal therapeutic doses according to IGF1 values. We analyzed the expression of SSTR2, SSTR5, AIP, CDH1 (E-cadherin), MKI67 (Ki-67), KLK10, DRD2, ARRB1, GHRL, In1-Ghrelin, PLAGL1 and PEBP1 (RKIP) by RT-qPCR and mutations in GNAS gene by Sanger sequencing. The response to SRL was categorized as complete response (CR), partial (PR) or non-response (NR) if IGF1 was normal, between >2<3 SDS or >3 SDS IGF1 at 6 months of follow-up, respectively. From the 71 patients treated, there were 27 CR (38%), 18 PR (25%) and 26 NR (37%). SSTR2, Ki-67 and E-cadherin were associated with SRL response (P < 0.03, P < 0.01 and P < 0.003, respectively). E-cadherin was the best discriminator for response prediction (AUC = 0.74, P < 0.02, PPV of 83.7%, NPV of 72.6%), which was validated at protein level. SSTR5 expression was higher in patients pre-treated with SRL before surgery. We conclude that somatotropinomas showed heterogeneity in the expression of genes associated with SRL response. E-cadherin was the best molecular predictor of response to SRL. Thus, the inclusion of E-cadherin in subsequent treatment-decision after surgical failure may be useful in acromegaly.

New Metrics to Assess Type 2 Diabetes After Bariatric Surgery: The "Time-Within-Remission Range".

Almost one third of patients do not achieve type 2 diabetes remission after bariatric surgery or are unable to sustain this effect long term. Our objective was to delve further into the dynamic responses of diabetes after bariatric surgery and to evaluate the "time-within-remission range" as a variable of metabolic control. A descriptive cohort study was done using a computerised multicentre and multidisciplinary registry. All data were adjusted by propensity score. A total of 1186 subjects with a follow-up of 4.5 ± 2.5 years were included. Type of surgery, diabetes remission, recurrence of diabetes, "time-within-remission range" and key predictors of diabetes outcomes were assessed. All patients (70% women, 51.4 ± 9.2 years old, body mass index (BMI) 46.3 ± 6.9 kg/m2) underwent primary bariatric procedures. "Time-within-remission range" were 83.3% (33.3-91.6) after gastric bypass, 68.7% (7.1-87.5) after sleeve gastrectomy and 90% (83.3-92.8) after malabsorptive techniques (p < 0.001 for all). Duration of diabetes, baseline HbA1c and insulin treatment were significantly negatively correlated with the "time-within-remission range". The association of bariatric techniques with "time-within-remission range", using gastric bypass as a reference, were: odds ratio (OR) 3.70 (2.34-5.84), p < 0.001 for malabsorptive techniques and OR 0.55 (0.40-0.75), p < 0.001 for sleeve gastrectomy. Characteristics of type 2 diabetes powerfully influence the outcomes of bariatric surgery. The "time-within-remission range" unveils a superiority of gastric bypass compared to sleeve gastrectomy.

Endocrine adverse events related to immune-oncology agents: retrospective experience of a single institution.

BACKGROUND: Immune-oncology agents (IOA) represent a turning point in the treatment of several solid tumors (ST). Although their toxicity compares favorably with other treatments, IOA associate immune-related adverse events (IR-AE), among which endocrine-related AE stand out. We retrospectively evaluated the occurrence of endocrine (E) IR-AE in a cohort of patients with several ST treated with IOA. In addition, we assessed the correlation between likelihood of survival and the occurrence of IR-AE. METHODS: We collected data on clinical and molecular characteristics, efficacy and AE of 260 patients with ST treated with IOA from 2013 to 2017. We excluded patients with prior conditions or treatments potentially affecting thyroid test results. RESULTS: Lung cancer was the most prevalent diagnosis (70.2%). EIR-AE appeared in 18.1% of patients (total of 38 EIR-AE) and consisted of hypothyroidism, hyperthyroidism, pituitary disorders and type 1 diabetes mellitus in 60.5%, 21.1%, 15.8% and 2.6% of patients, respectively. EIR-AE were associated mainly to nivolumab, nivolumab plus ipilimumab (41.2% and 26.5%) and appeared after a median of 4.2 cycles of treatment. Specific therapy was required in 65.8% patients. There were significant differences in both progression-free survival (PFS) and overall survival (OS) for patients who experienced EIR-AE compared to those who did not [PFS: 56.7 (NC-NC) vs. 27.7 (14.3-41.3) months, P=0.008; OS: NC (NC-NC) vs. 31.4 (20.7-42.1) months, P=0.001]. CONCLUSIONS: The incidence of EIR-AE in our study is similar to other series. Patients who develop EIR-AE might have a better prognosis compared to those who do not experience them.