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

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.

Resistance to Somatostatin Analogs in Italian Acromegaly Patients: The MISS Study

Approximately 60% of acromegaly patients are not adequately controlled by first-generation somatostatin receptor ligands. This multicenter retrospective study aimed to identify the most relevant biomarkers specific for the Italian acromegaly population. Resistant patients were enrolled consecutively based on time of neurosurgery, while responders were collected in a 1:2 ratio. Clinical characteristics and T2-intensity on MRI scans at diagnosis were retrospectively re-evaluated. Histological analyses of CAM5.2 granulation patterns and SSTR2 expression were centrally performed. Sixty-three resistant patients and thirty-three responders were enrolled. A low-grade SSTR2 expression was the most relevant predictor of resistance identified (OR 4.58, p = 0.013), even considering CAM5.2 immunohistochemistry (OR 2.65, p = 0.047). T2-iso/hyperintense pattern on MRI was also associated with a 3.3-fold greater probability of poor response to medical treatment (p = 0.027), as well as a young age at diagnosis (OR 0.96, p = 0.035). In those patients treated only after neurosurgery due to persistent GH-hypersecretion (51, 53.1%) the absence of any appreciable adenomatous remnant on postoperative MRI was associated with a negligible risk of resistance (OR 0.04, p = 0.003). In the Italian acromegaly population, a low-grade SSTR2 expression seems to be the most relevant predictor of resistance to first-generation somatostatin receptor ligands, followed by a SG/intermediate cytokeratin pattern and a T2-iso/hyperintense MRI signal.

Transcriptomic Classification of Pituitary Neuroendocrine Tumors Causing Acromegaly

Acromegaly results from growth hormone hypersecretion, predominantly caused by a somatotroph pituitary neuroendocrine tumor (PitNET). Acromegaly-causing tumors are histologically diverse. Our aim was to determine transcriptomic profiles of various somatotroph PitNETs and to evaluate clinical implication of differential gene expression. A total of 48 tumors were subjected to RNA sequencing, while expression of selected genes was assessed in 134 tumors with qRT-PCR. Whole-transcriptome analysis revealed three transcriptomic groups of somatotroph PitNETs. They differ in expression of numerous genes including those involved in growth hormone secretion and known prognostic genes. Transcriptomic subgroups can be distinguished by determining the expression of marker genes. Analysis of the entire cohort of patients confirmed differences between molecular subtypes of tumors. Transcriptomic group 1 includes ~20% of acromegaly patients with GNAS mutations-negative, mainly densely granulated tumors that co-express GIPR and NR5A1 (SF-1). SF-1 expression was verified with immunohistochemistry. Transcriptomic group 2 tumors are the most common (46%) and include mainly GNAS-mutated, densely granulated somatotroph and mixed PitNETs. They have a smaller size and express favorable prognosis-related genes. Transcriptomic group 3 includes predominantly sparsely granulated somatotroph PitNETs with low GNAS mutations frequency causing ~35% of acromegaly. Ghrelin signaling is implicated in their pathogenesis. They have an unfavorable gene expression profile and higher invasive growth rate.

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.

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.

Epithelial-Mesenchymal Transition in the Resistance to Somatostatin Receptor Ligands in Acromegaly

Epithelial-mesenchymal transition (EMT) is a dynamic process by which epithelial cells loss their phenotype and acquire mesenchymal traits, including increased migratory and invasive capacities. EMT is involved in physiological processes, such as embryogenesis and wound healing, and in pathological processes such as cancer, playing a pivotal role in tumor progression and metastasis. Pituitary tumors, although typically benign, can be locally invasive. Different studies have shown the association of EMT with increased tumor size and invasion in pituitary tumors, and in particular with a poor response to Somatostatin Receptor Ligands (SRLs) treatment in GH-producing pituitary tumors, the main cause of acromegaly. This review will summarize the current knowledge regarding EMT and SRLs resistance in acromegaly and, based on this relation, will suggest new biomarkers and possible therapies to SRLs resistant tumors.