Levoketoconazole Treatment in Endogenous Cushing’s Syndrome

Objective: This extended evaluation (EE) of the SONICS study assessed effects of levoketoconazole for an additional 6 months following open-label, 6-month maintenance treatment in endogenous Cushing’s syndrome.

Design/Methods: SONICS included dose-titration (150–600 mg BID), 6-month maintenance, and 6-month EE phases. Exploratory efficacy assessments were performed at Months 9 and 12 (relative to start of maintenance). For pituitary MRI in patients with Cushing’s disease, a threshold of ≥2 mm denoted change from baseline in largest tumor diameter.

Results: Sixty patients entered EE at Month 6; 61% (33/54 with data) exhibited normal mean urinary free cortisol (mUFC). At Months 9 and 12, respectively, 55% (27/49) and 41% (18/44) of patients with data had normal mUFC. Mean fasting glucose, total and LDL-cholesterol, body weight, body mass index, abdominal girth, hirsutism, CushingQoL, and BDI-II scores improved from study baseline at Months 9 and 12. Forty-six patients completed Month 12; 4 (6.7%) discontinued during EE due to adverse events. The most common adverse events in EE were arthralgia, headache, hypokalemia, and QT prolongation (6.7% each). No patient experienced ALT or AST >3× ULN, QTcF interval >460 msec, or adrenal insufficiency during EE. Of 31 patients with tumor measurements at baseline and Month 12 or follow-up, largest tumor diameter was stable in 27 (87%) patients, decreased in 1, and increased in 3 (largest increase 4 mm).

Conclusion: In the first long-term levoketoconazole study, continued treatment through 12-month maintenance period sustained the early clinical and biochemical benefits in most patients completing EE, without new adverse effects.

Read the whole article at https://eje.bioscientifica.com/configurable/content/journals$002feje$002faop$002feje-22-0506$002feje-22-0506.xml?t%3Aac=journals%24002feje%24002faop%24002feje-22-0506%24002feje-22-0506.xml&body=pdf-45566

Development of Human Pituitary Neuroendocrine Tumor Organoids to Facilitate Effective Targeted Treatments of Cushing’s Disease

Abstract

(1) Background: Cushing’s disease (CD) is a serious endocrine disorder caused by an adrenocorticotropic hormone (ACTH)-secreting pituitary neuroendocrine tumor (PitNET) that stimulates the adrenal glands to overproduce cortisol. Chronic exposure to excess cortisol has detrimental effects on health, including increased stroke rates, diabetes, obesity, cognitive impairment, anxiety, depression, and death. The first-line treatment for CD is pituitary surgery. Current surgical remission rates reported in only 56% of patients depending on several criteria. The lack of specificity, poor tolerability, and low efficacy of the subsequent second-line medical therapies make CD a medical therapeutic challenge. One major limitation that hinders the development of specific medical therapies is the lack of relevant human model systems that recapitulate the cellular composition of PitNET microenvironment.
(2) Methods: human pituitary tumor tissue was harvested during transsphenoidal surgery from CD patients to generate organoids (hPITOs).
(3) Results: hPITOs generated from corticotroph, lactotroph, gonadotroph, and somatotroph tumors exhibited morphological diversity among the organoid lines between individual patients and amongst subtypes. The similarity in cell lineages between the organoid line and the patient’s tumor was validated by comparing the neuropathology report to the expression pattern of PitNET specific markers, using spectral flow cytometry and exome sequencing. A high-throughput drug screen demonstrated patient-specific drug responses of hPITOs amongst each tumor subtype. Generation of induced pluripotent stem cells (iPSCs) from a CD patient carrying germline mutation CDH23 exhibited dysregulated cell lineage commitment.
(4) Conclusions: The human pituitary neuroendocrine tumor organoids represent a novel approach in how we model complex pathologies in CD patients, which will enable effective personalized medicine for these patients.

1. Introduction

Cushing’s disease (CD) is a serious endocrine disorder caused by an adrenocorticotropic hormone (ACTH)-secreting pituitary neuroendocrine tumor (PitNET) that stimulates the adrenal glands to overproduce cortisol [1,2,3,4]. The WHO renamed pituitary adenomas as PitNETs [5]. While PitNETs have been defined as benign, implying that these tumors cause a disease that is not life threatening or harmful to health, in fact chronic exposure to excess cortisol has wide-ranging and detrimental effects on health. Hypercortisolism causes increased stroke rates, diabetes, obesity, depression, anxiety, and a three-fold increase in the risk of death from cardiovascular disease and cancer [4,6,7,8].
The first-line treatment for CD is pituitary surgery, which is followed by disease recurrence in 50% of patients during the 10-year follow-up period after surgery in the hands of an experienced surgeon [9,10,11]. Studies have demonstrated that surgical failures and recurrences of CD are common, and despite multiple treatments, biochemical control is not achieved in approximately 30% of patients. This suggests that in routine clinical practice, initial and long-term disease remission is not achieved in a substantial number of CD patients [7,12]. Hence, medical therapy is often considered in the following situations: when surgery is contraindicated or fails to achieve remission, or when recurrence occurs after apparent surgical remission. While stereotactic radiosurgery treats incompletely resected or recurrent PitNETs, the main drawbacks include the longer time to remission (12–60 months) and the risk of hypopituitarism [3,13,14]. There is an inverse relationship between disease duration and reversibility of complications associated with the disease, thus emphasizing the importance of identifying an effective medical strategy to rapidly normalize cortisol production by targeting the pituitary adenoma [4,7,12]. Unfortunately, the lack of current standard of care treatments with low efficacy and tolerability makes CD a medical therapeutic challenge.
The overall goal of medical therapy for CD is to target the signaling mechanisms to lower cortisol levels in the body [15,16]. The drugs offered for treatment of CD vary in the mechanism of action, safety, tolerability, route of administration, and drug–drug interactions [15,16]. In the era of precision medicine [17], where it is imperative to identify effective therapies early, there is an urgent need to accelerate the identification of therapies targeted to the ACTH-secreting pituitary tumor which are tailored for each individual patient. The absence of preclinical models that replicate the complexity of the PitNET microenvironment has prevented us from acquiring the knowledge to advance clinical care by implementing therapies specifically targeting the tumor, which would have a higher efficacy and tolerability for CD patients. In this instance, organoids can replicate much of the complexity of an tumor. An “organoid” is defined as a three-dimensional cell structure, grown from primary cells of dissociated pituitary tumors in Matrigel matrix, which proliferate, and differentiate in three dimensions, eventually replicating key biological properties of the tissue [18]. While pituitary cell lines predominantly represent hormonal lineages, these cultures do not reproduce the primary pituitary tissue because of the tumor transformation and non-physiological 2D culture conditions [19,20,21]. Pituitary tissue-derived organoids have been generated from mouse models [22,23]. While several human and rat pituitary spheroid/aggregate/tumoroid models have been reported, these cultures consist of poorly differentiated cells with high replicative potential which can affect drug response and produce data that poorly translate to the clinic [24,25]. In this study, we developed an organoid model derived from human PitNETs that replicated much of the cellular complexity and function of the patient’s tumor. Organoids derived from corticotroph PitNETs retained the genetic alterations of the patient’s primary tissue.

2. Materials and Methods

2.1. Generation and Culture of Human Pituitary Neuroendocrine Tumor (PitNET) Organoids

Patients with planned transsphenoidal surgery for pituitary tumors were identified in the outpatient neurosurgery clinics. Tissues were collected under the St. Joseph’s Hospital and Barrow Neurological Institute Biobank collection protocol PHXA-05TS038 and collection of outcomes data protocol PHXA-0004-72-29, with the approval of the Institutional Review Board (IRB) and patient consent. Samples were de-identified and shipped to the Zavros laboratory (University of Arizona) for processing.
Pituitary tumor tissue was collected in Serum-Free Defined Medium (SFDM) supplemented with ROCK inhibitor (Y27632, 10 µM), L-glutamine (2 mM), A83-01 (activin receptor-like kinase (Alk) 4/5/7 inhibitor, 0.5 mM), penicillin/streptavidin (1%), kanamycin (1%), amphotericin/gentamycin (0.2%), CHIR-98014 (4 mM), and thiazovivin (TZV, 2.5 mM). Tissues that contained red blood cells were incubated with Red Blood Cell (RBC) Lysis Buffer according to the manufacturer’s protocol (Thermo Fisher Scientific, San Fransisco, CA, USA). Tissues were dissected into small pieces, transferred to digestion buffer (DMEM/F12 supplemented with 0.4% collagenase 2, 0.1% hyaluronic acid, 0.03% trypsin-EDTA) and incubated for 5–10 min at 37 °C with gentle shaking. Tissue was further incubated with Accutase™ (Thermo Fisher Scientific) for 5 min at 37 °C. Enzymatically dissociated cells were pelleted and washed in DPBS supplemented with antibiotics at a 400 relative centrifugal force (RCF) for 5 min. Dissociated adenoma cells were resuspended in Matrigel™, and Matrigel™ domes containing the cells were then plated in culture dishes and overlaid with pituitary growth media (Supplemental Table S1). The culture was maintained at 37 °C at a relative humidity of 95% and 5% CO2. Organoid growth medium was replenished every 3–4 days and passaged after 15 days in culture.

2.2. Generation of Induced Pluripotent Stem Cells (iPSCs)

Induced pluripotent stem cell lines (iPSC lines) were generated from control individuals (no reported disease) or CD patients according to published protocols by the University of Arizona iPSC Core [26]. All human iPSC lines were tested and found to be negative for mycoplasma contamination using the Mycoalert Mycoplasma testing kits (LT07-318, Lonza), and no karyotype abnormalities were found (KaryoStat+, Thermo).

2.3. Pituitary Organoids Generated from iPSCs

Six well culture plates were coated with 2 mL/well 0.67% Matrigel (diluted in E8 media, UA iPSC core, 151169-01) and incubated at 37 °C at a relative humidity of 95% and 5% CO2 overnight. The iPSC lines were reprogrammed from the blood of either a healthy donor (JCAZ001) or a CD patient (iPSC7 and iPSC1063) at the University of Arizona iPSC Core. Passage 12 iPSCs were plated onto the coated plates and incubated at 37 °C at a relative humidity of 95% and 5% CO2. At 70% confluency, cells were passaged to freshly coated 24 well plates at a ratio of 1:8 and grown to 85–90% confluency before beginning the directed differentiation schedule. From days 0 to 3, cells were cultured in E6 media supplemented with 1% penicillin/streptomycin, 10 μM SB431542, and 5 ng/mL BMP4. BMP4 was withdrawn from the culture at day 3. Starting on day 4, the cells were cultured in E6 media, supplemented with 10 μM SB431542, 30 ng/mL human recombinant SHH, 100 ng/mL FGF8b, 10 ng/mL FGF18, and 50 ng/mL FGF10. Fifteen days after culture, the cells were harvested in cold E6 media by pipetting and resuspended in Matrigel™ (20,000 cells/50 mL Matrigel™). Matrigel™ domes containing the cells were plated in culture dishes and overlaid with differentiation media containing E6 media which was supplemented with 10 μM Y-27632, 30 ng/mL human recombinant SHH, 100 ng/mL FGF8b, 10 ng/mL FGF18, and 50 ng/mL FGF10 (Supplemental Table S2). Organoids were cultured for a further 15 days at 37 °C at a relative humidity of 95% and 5% CO2.

2.4. Spectral Flow Cytometry (Cytek™ Aurora)

The multicolor flow cytometry panel was designed using the Cytek® Full Spectrum Viewer online tool to calculate the similarity index (Supplemental Figure S1). The organoids were harvested in cold SFDM media and centrifuged at 400× g for 5 min. Supernatant was discarded and organoids were dissociated to single cells using Accutase® (Thermo Fisher Scientific 00-4555-56). The enzymatic reaction was stopped using prewarmed DPBS, and cells were then centrifuged at 400× g for 5 min and incubated with fluorochrome-conjugated/unconjugated primary surface or cytoplasmic antibodies (Supplemental Figure S1) at 4 °C for 30 min. Cells were then washed with Cell Staining Buffer (BioLegend # 420-201) and incubated with secondary antibodies (Supplemental Figure S1) at 4 °C for 30 min. Cells were fixed using Cytofix/Cytoperm™ Fixation/Permeabilization Solution (BD Biosciences # 554714) at 4 °C for 20 min, followed by washing with Fixation/Permeabilization wash buffer. Cells were labeled with fluorochrome-conjugated/unconjugated intracellular primary antibodies (Supplemental Figure S1) at 4 °C for 30 min, then washed and incubated with secondary antibodies at 4 °C for 30 min. Cells were resuspended in cell staining buffer and fluorescence and measured using the Cytek Aurora 5 Laser Spectral Flow Cytometer. An unstained cell sample was fixed and used as a reference control. UltraComp eBeads™, Compensation Beads (Thermo Fisher Scientific # 01-2222-42) were stained with the individual antibodies and used as single stain controls for compensation and gating. Data were acquired using the Cytek™ Aurora and analyzed using Cytobank software (Beckman Coulter, Indianapolis, IN, USA).

2.5. Whole Mount Immunofluorescence

Organoids were immunostained using published protocols by our laboratory [27,28,29]. Proliferation was measured by using 5-ethynyl-2′-deoxyuridine (EdU) incorporation according to the Manufacturer’s protocol (Click-IT EdU Alexa Fluor 555 Imaging Kit, Thermo Fisher Scientific C10338). Co-staining was performed by blocking fixed organoids with 2% donkey serum (Jackson Immuno Research, # 017-000-121) diluted in 0.01% PBST for 1hr at room temperature. Organoids were then incubated overnight at 4 °C with primary antibodies, followed by secondary antibodies and Hoechst (Thermo Fisher Scientific H1399, 1:1000 in 0.01% PBST) for 1 h at room temperature. Human specific primary antibodies used included: rabbit anti-ACTH (Thermo Fisher Scientific 701293, 1:250), rabbit anti-Synaptophysin (Thermo Fisher Scientific PA5-27286, 1:100), species PIT1 (Thermo Fisher Scientific PA5-98650, 1:50), rabbit anti-LH (Thermo Fisher Scientific PA5-102674, 1:100), mouse anti-FSH (Thermo Fisher Scientific MIF2709, 1:100), mouse anti-PRL (Thermo Fisher Scientific CF500720, 1:100), Alexa Flour conjugated GH (NB500-364AF647, 1:100), and mouse anti-CAM5.2 (SIGMA 452M-95, 1:250). The secondary antibodies used included Alexa Fluor 488 Donkey Anti Rabbit IgG (H+L) (Thermo Fisher Scientific A21206, 1:100) or Alexa Fluor 647 Donkey Anti Mouse IgG (H+L) (Thermo Fisher Scientific A31571, 1:100). Organoids were visualized and images were acquired by confocal microscopy using the Nikon CrestV2 Spinning Disk (Nikon, Melville, NY, USA). Fluorescence intensity and percentage of EdU positive cells of total cells, were calculated using Nikon Elements Software (Version 5.21.05, Nikon, Melville, NY, USA).

2.6. Nuclear Morphometric Analysis (NMA)

Nuclear Morphometric Analysis (NMA) using treated organoids was performed based on a published protocol that measures cell viability based on the changes in nuclear morphology of the cells, using nuclear stain Hoechst or DAPI [30]. Images of organoid nuclei were analyzed using the ImageJ Nuclear Irregularity Index (NII) plugin for key parameters, which included cell area, radius ratio, area box, aspect, and roundness. Using the published spreadsheet template [30], the NII of each cell was calculated with the following formula: NII = Aspect − Area Box + Radius Ratio + Roundness. The area vs. NII of vehicle-treated cells were plotted as a scatter plot using the template, and was considered as the normal cell nuclei. The same plots were generated for each condition, and the NII and area of treated cells were compared to the normal nuclei, and classified as one of the following NMA populations: Normal (N; similar area and NII), Mitotic (S; similar area, slightly higher NII), Irregular (I; similar area, high NII), Small Regular (SR; apoptotic, low area and NII), Senescent (LR; high area, low NII), Small Irregular (SI; low area, high NII), or Large Irregular (LI; high area, high NII). Cells classified as SR exhibited early stages of apoptosis, and cells classified as either I, SI, or LI exhibited significant nuclear damage. The percentage of cells in each NII classification category were calculated and plotted as a histogram using GraphPad Prism.

2.7. ELISA

Concentration of secreted ACTH in conditioned media that was collected from organoid cultures was measured using the Human ACTH ELISA Kit (Novus Biologicals, NBP2-66401), according to the manufacturer’s protocol. The enzyme–substrate reaction was measured spectrophotometrically (BioTek Gen5 Micro Plate Reader Version 3.11, Santa Clara, CA, USA) at a wavelength of 450 nm, and the ACTH concentration (pg/mL) was interpolated by a standard curve with a 4-parameter logistic regression analysis, using GraphPad Prism (Version 9.2.0, San Diego, CA, USA).

2.8. Drug Assay

Patient adenoma-derived pituitary organoids were grown in 96-well plates and treated with 147 small molecules taken from the NCI AOD9 compound library for 72 h. (https://dtp.cancer.gov/organization/dscb/obtaining/available_plates.html (accessed on 22 August 2021)). Drugs were diluted from 10 mM DMSO stock plates into 100 M DMSO working stocks with a final concentration of 1μM. All vehicle controls were treated with 0.1% DMSO. Organoid proliferation was measured using a CellTiter 96® AQueous One Solution Cell Proliferation Assay kit (MTS, Promega, G3582, Madison, WI, USA) according to the manufacturer’s instruction. Organoid death was calculated based on the absorbance readings at 490 nm, collected from the MTS assay relative to the vehicle controls. Drug screens were performed with biological replicates in the same screen. Drugs were selected based on their ability to target key signaling pathways as well as clinical relevance to the treatment. Drug sensitivity is represented by cell viability, and is significant at <0.5 suppressive effect of the drugs. The percent of cell viability relative to the vehicle control was calculated. Correlation coefficients across each organoid were calculated using the Pearson method to assess confidence in replication. The variance component was detected for each drug across all organoids. A random effect model was run with a single random factor for each drug, and estimated variance was calculated by rejecting the null hypothesis that variation was not present among samples. The drug responses were grouped by variance factor, into large (vc > 100), median (100 > vc > 50), and small (vc < 50). A heatmap was used to display the differential responses in cell viability for the drugs.
Drugs that clustered together and showed response within corticotrophs were investigated further based on their mode of action. Pathways (Kegg and Reactome) and gene ontology mapping were conducted for the genes that were being targeted by the drugs, in order to evaluate the key responses in cellular processes. A network was constructed in Cytoscape v 3.8.2 (San Diego, CA, USA) for the purpose of association between the drugs and genes.

2.9. Drug Dose Responses

Organoids were grown in Matrigel™ domes within 96-well round-bottom culture plates. Recombinant human SHH was removed from the pituitary organoid growth media, 24 h prior to drug treatment. Organoids were treated with either vehicle (DMSO), cabergoline (Selleckchem S5842), ketoconazole (Selleckchem S1353), roscovitine (Selleckchem S1153), GANT61 (Stemcell Technologies 73692), pasireotide (TargetMol TP2207), mifeprostone (Selleckchem S2606), etomidate (Selleckchem S1329), mitotane (Selleckchem S1732), metyropane (Selleckchem S5416), or osilodrostat (Selleckchem S7456) at concentrations of 0, 1, 10, 100, 1000, and 10,000 nM, for 72 h. The percentage of cell viability was measured using an MTS assay (Promega G3580). Absorbance was measured at 490 nm and normalized to the vehicle. Concentrations were plotted in a logarithmic scale, and a nonlinear dose response curve regression was calculated using GraphPad Prism. An IC50 value for each drug treatment was determined based on the dose response curve, using GraphPad Prism analysis software.

2.10. Calculation of Area under the Curve (AUC)

AUC (area under the curve) was determined by plotting the normalized % cell viability versus transformed concentration of the drugs, using a trapezoidal approximation for the area [31]. The formula was based on splitting the curve into trapezoids with bases equal to the % viability (V) and height equal to the interval length (difference in concentrations (C), and then summing the areas of each trapezoid:

n0(Vn+Vn1)2(CnCn1)

2.11. Quantitative RT PCR (qRT-PCR)

RNA was collected from patient-derived organoid cultures using the RNeasy Mini Kit (Qiagen). cDNA was generated from the extracted RNA, and then pre-amplified using TaqMan PreAmp Master Mix (Thermo Fisher Scientific 391128). The primers used were human-specific GAPDH (Thermo Fisher Scientific, Applied Biosystems Hs02786624_g1), NR5A1 (SF1) (Thermo Fisher Scientific, Hs00610436_m1), PIT1 (Thermo Fisher Scientific, Hs00230821_m1), TPit (Thermo Fisher Scientific, Hs00193027), and POMC (Thermo Fisher Scientific, Hs01596743_m1). Each PCR reaction was performed using a final volume of 20 µL, composed of 20X TaqMan Expression Assay primers, 2X TaqMan Universal Master Mix (Applied Biosystems, TaqMan® Gene Expression Systems), and a cDNA template. Amplification of each PCR reaction was conducted in a StepOne™ Real-Time PCR System (Applied Biosystems, Foster City, CA, USA), using the following PCR conditions: 2 min at 50 °C, 10 min at 95 °C, denaturing for 15 s at 95 °C, and annealing/extending for 1 min at 60 °C, for a total of 40 cycles. Relative fold change was calculated using the 2 − ∆∆Ct method [32], where CT = threshold cycle. Results were analyzed as the average fold change in gene expression compared to the control, and GAPDH served as an internal control.

2.12. Whole Exome Sequencing

WES was performed by the University of Arizona Center for Applied Genetics and Genomic Medicine. Isolated DNA from patient adenoma tissue will be quantified using the Qubit quantitation system with standard curve, as per the supplier protocol (Thermo Fisher Scientific). All samples were further tested for quality using the Fragment Analyzer (Advanced Analytical), following the manufacturer-recommended protocols. Whole exome sequencing (WES) was performed by array capture and approximately 60 Mb of exome target sequence, using the SureSelectXT Human All Exon V6 enrichment (Agilent) or equivalent (which one was used). All exome library builds were quantified via qPCR and subsequently sequenced to a minimum 20X coverage, using paired-end chemistry on the Illumina NovaSeq platform. Whole exome sequencing (WES) was performed by hybridization capture of approx. 35 Mb of the exome target sequence, using the Swift Exome Hyb Panel (Swift Biosciences 83216). All exome library builds were quantified via qPCR and subsequently sequenced to a minimum 20X coverage, using paired-end chemistry on the Illumina NextSeq500 or NovaSeq platform (Illumina). DNA reads were trimmed, filtered by quality scores and aligned to the human genome (hg38) with Burrows–Wheeler Aligner with default parameters. Picard (http://broadinstitute.github.io/picard (accessed on 22 December 2021)) was used to mark duplicates. Germline single nucleotide variants (SNV) were called using the Genome Analysis Tool Kit (GATK), using the given guidelines. Mutations were annotated using ANNOVAR for coding sequences. Variants that passed the quality filter were further investigated for similarity. Concordance between tissue and organoids was calculated using Jaccard similarity index (Jij = Mij/(Mi + Mj − Mij) where Mi is the number of variants in tissues, Mj is the number of variants in organoids, and Mij is the number of identical variants in both tissue and organoid.

2.13. Single Cell RNA Sequencing (scRNA-Seq)

Cultures were collected on day 15 of the pituitary directed differentiation schedule, and cells were dissociated into a single-cell suspension using Cell Dissociation Buffer (Thermo Fisher Scientific 13151014). Cells (15,000 cells/sample) were resuspended in the sample buffer (BD Biosciences 65000062), filtered using cell strainer (40 microns), and loaded into a BD Rhapsody cartridge (BD Biosciences 400000847) for single-cell transcriptome isolation. Based on the BD Rhapsody system whole-transcriptome analysis for single-cell whole-transcriptome analysis, microbead-captured single-cell transcriptomes were used to prepare a cDNA library. Briefly, double-stranded cDNA was first generated from the microbead-captured single-cell transcriptome in several steps, including reverse transcription, second-strand synthesis, end preparation, adapter ligation, and whole-transcriptome amplification (WTA). Then, the final cDNA library was generated from double-stranded full-length cDNA by random priming amplification using a BD Rhapsody cDNA Kit (BD Biosciences, 633773), as well as the BD Rhapsody Targeted mRNA and WTA Amplification Kit (BD Biosciences, 633801). The library was sequenced in PE150 mode (paired-end with 150-bp reads) on NovaSeq6000 System (Illumina). A total of 80,000 reads were demultiplexed, trimmed, mapped to the GRCh38 annotation, and quantified using the whole transcriptome analysis pipeline (BD Rhapsody™ WTA Analysis Pipeline v1.10 rev6, San Jose, CA, USA) on the Seven Bridges Genomics platform (https://igor.sbgenomics.com (accessed on 4 April 2022)), prior to clustering analysis in Seurat. For QC and filtration, read counting and unique molecular identifier (UMI) counting were the principal gene expression quantification schemes used in this single-cell RNA-sequencing (scRNA-seq) analysis. The low-quality cells, empty droplets, cell doublets, or multiplets were excluded based on unique feature count (less than 200 or larger than 2500), as they may often exhibit either an aberrantly high gene count or very few genes. Additionally, the mitochondrial QC metrics were calculated, and the cells with >5% mitochondrial counts were filtered out, as the percentage of counts originating from a set of low-quality or dying cells often exhibit extensive mitochondrial contamination. After the removal of unwanted cells from the single cell dataset, the global-scaling normalization method LogNormalize was employed. This method normalizes the feature expression measurements for each cell by the total expression, multiplies this by a scale factor (10,000), and log-transforms the result. The molecules per gene per cell, based on RSEC error correction (RSEC_MolsPerCell file) matrix files from iPSCctrl and iPSCCDH23 samples, were imported into Seurat v4, merged, and processed (as stated above) for UMAP reduction, cluster identification, and differential marker assessment using the FindAllMarkers function within Seurat.

2.14. Statistical Analyses

Sample size was based on assessment of power analysis using SigmaStat software. Data collected from each study from at least 4 in vitro technical replicates were analyzed by obtaining the mean ± standard error of the mean (SEM), unless otherwise stated. The significance of the results was then tested using commercially available software (GraphPad Prism, GraphPad software, San Diego, CA, USA).

3. Results

3.1. Generation and Validation of Human PitNET Tissue Derived Organoids

Human PitNET tissue was harvested during endoscopic transsphenoidal pituitary surgery from 35 patients in order to generate organoids. These cultures are referred to as human PitNET tissue derived organoids (hPITOs). Supplementary Table S3 summarizes the neuropathology reports and clinical diagnosis from these cases. In summary, 12 corticotroph (functional, CD), and 3 silent corticotroph tumors (nonfunctional tumors), 9 gonadotroph tumors, 8 lactotroph tumors, and 3 somatotroph tumors (acromegaly) were used to generate hPITOs (Supplementary Table S3).
Bright-field microscopy images of hPITOs that were generated from corticotroph adenomas from patients diagnosed with CD (Figure 1a–e). Silent/nonfunctioning tumors (Figure 1f,g) revealed morphological diversity among the organoid lines between individual patients and amongst subtypes. Confocal microscopy was used to capture a z-stack through the hPITO38, immunofluorescently stained for CAM5.2 (red), ACTH (green), and Hoechst (nuclear staining, blue) and emphasizes the 3D cellular structure of the hPITOs (Supplemental Video S1). Lactotroph, gonadotroph, and somatotroph adenomas were used to generate hPITOs, and showed the same morphological divergence amongst subtypes and between each patient line (Supplemental Figure S2). Proliferation was measured within the cultures using 5-ethynyl-2′-deoxyuridine (EdU) uptake and showed that the percentage of EdU+ve cells/total Hoechst+ve nuclei directly correlated with the pathology MIB-1 (Ki67) score (red, R2 = 0.9256) (Figure 1a–g, Supplemental Figure S2). ACTH concentration, which was measured by ELISA using organoid conditioned culture media collected from each hPITO line, showed the highest expression in the corticotroph adenoma organoids generated from CD patients (Figure 1h).
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Figure 1. Morphology and function of corticotroph hPITOs. (ag) Brightfield images, immunofluorescence staining using antibodies specific for CAM5.2 (red), ACTH (green), and EdU (magenta, inset) of organoid cultures generated from patients with Cushing’s disease (hPITOs 1, 7, 10, 33, 35) or nonfunctional corticotroph adenomas (hPITO8, 12). Quantification of %EdU positive cells/total cell number is shown and compared to the Ki67 score given in the pathology report (Supplemental Table S3). An ELISA was performed using conditioned media collected from (h) corticotroph hPITO cultures and (i) lactotroph, somatotroph, and gonadotroph hPITO cultures for the measurement of ACTH secretion (pg/mL).

3.2. Characterization of Cell Lineages in Pituitary Adenoma-Derived Organoids by Spectral Cytek™ Aurora Analysis

In order to validate the similarity in cell lineages identified between the organoid line and the patient’s tumor, we compared the immunohistochemistry from the neuropathology report (Supplemental Table S3) to the expression pattern of pituitary adenoma-specific markers, which were measured using Cytek™ Aurora spectral flow cytometry (Figure 2). The location of cells that are found in each cluster based on the highly expressed antigens are shown in the representative tSNE (viSNE) maps (Figure 2a). Compared to nonfunctional adenoma-derived hPITOs, organoids derived from corticotroph adenomas of CD patients highly expressed proliferating (Ki67+) T-Pit+ ACTH cells (Figure 2a). Interestingly, there was an increase in SOX2+ cells within the total cell population, associated with Crooke’s cell adenoma hPITOs (Figure 2a). Within the total cell population, cell clusters expressing CD45 and vimentin were also measured (Figure 2a). Data for the analysis of corticotroph hPITOs, derived from CD patients and individuals with nonfunctional adenomas, were summarized in a heatmap for each subtype organoid line based on quantified cell abundance (percent of total cells) using spectral flow cytometry (Figure 2b).
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Figure 2. Cell heterogeneity of corticotroph hPITOs. (a) viSNE maps define spatially distinct cell populations using pituitary specific cell lineage, stem cell, and transcription factor markers. Cell populations were quantified in organoids generated from CD patients with corticotroph adenomas (sparsely granulated and Crooke’s cell adenoma) or patients with nonfunctional corticotroph adenomas. (b) Quantification of the abundance of cells expressing pituitary specific markers as a percent total. viSNE maps define spatially distinct cell populations in organoid cultures generated from CD patient with (c) corticotroph adenoma (hPITO37, Crooke’s cell adenoma) and adjacent normal tissue (hPITO37N), or (d) sparsely granulated corticotroph adenomas (hPITO38) and adjacent normal tissue (hPITO38N).
Organoid cultures derived from pituitary adenomas (hPITO37 and hPITO38) were compared to organoids derived from adjacent normal pituitary tissue (hPITO37N and hPITO38N) (Figure 2c,d). While Pit1 lineages including cells expressing GH and PRL, as well as SF1 lineages expressing FSH and LH, were detected in the hPITO37N and hPITO38N organoid cultures, these cell populations were significantly reduced within the patient’s matched adenoma tissue (Figure 2c,d). Overall, hPITOs derived from CD patients expressed increased stem and progenitor cell markers, including CXCR4, SOX2, and CD133 (Figure 2). Collectively, our findings of the characterization of the hPITO cultures support our prediction that this in vitro model recapitulates much of the patient’s adenoma pathophysiology.

3.3. Inherent Patient Differences to Drug Response Is Reflected in the Organoid Culture

Tumor recurrence can occur in as many as 30–50% of CD patients after successful surgical treatment [10,33,34]. Unfortunately, bilateral adrenalectomy is the chosen surgical treatment for patients with persistent CD [35]. Bilateral adrenalectomy leads to the increased risk for development of Nelson’s syndrome (progressive hyperpigmentation due to ACTH secretion and expansion of the residual pituitary tumor). Although the risk of developing Nelson’s syndrome following adrenalectomy can be reduced by 50% with stereotactic radiotherapy [35], there is a need to develop medical therapies that directly target the pituitary adenoma. Thus, we established a high-throughput drug screening assay using patient-derived PitNET organoids. After 72 h of treatment, cell viability was measured using an MTS assay, and data were represented as a heatmap whereby blue indicated higher cell death, and red suggested higher cell viability. The replicates behaved consistently with the drug response, with correlation scores of >0.8 for these samples (Figure 3a). We estimated the variance component for each drug across all organoids. Variation among samples was found to be significant (p ≤ 0.05) for each of the 83 drugs. The drug responses were grouped by variance factor into large, median, and small. The larger the variance, the more variable the drug response was across the organoids. We noted a set of drugs that showed a significant differential response across the functional corticotroph organoids. Unsupervised clustering of drug responses across organoids shows a pattern that relates to our statistically calculated results (Figure 3a,c), and the replicates for each independent organoid cluster together. The drugs with higher variance components across all the functional corticotrophs cluster together as a group (Figure 3a). These drugs show cell viability of 10% to 60% across different organoids. Analyzing the pattern more closely, we observe that, within a pathologically defined group, there was a differential organoid response to drugs as well as inherent patient differences to drugs within this group. Figure 3 demonstrates a variation in drug responsiveness amongst the organoid lines generated from individual patients. Importantly, there was further divergence in drug responsiveness amongst the individual organoid lines within each pathologically defined corticotroph subtype. These data clearly demonstrate that the inherent patient difference to drug response which is often observed among CD patients is reflected in the organoid culture.
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Figure 3. Drug screen using hPITOs generated from CD patients. (a) High-throughput drug screening of hPITOs reveals sensitivities to a range of therapeutic agents. Cell viability with high values (indicating resistance) are depicted in red, and low values (indicating sensitivity) are in blue in the clustered heatmap. (b,c) Clusters showing response to therapeutic agents with the most variance across the organoids. (d) Network of drugs from the clusters b and c and their gene targets, showing their participation in signaling pathways and cellular processes.
Drugs that clustered together and showed correlated responses were investigated further for their mode of action based on target genes (Figure 3d). The genes were analyzed for their associations in cellular pathways and gene ontology functional processes. Identified drug–gene pairs were interconnected by cellular pathways that are known to regulate cell cycle, WNT signaling, hedgehog signaling, and neuroactive ligand-receptor interaction signaling pathways (Figure 3d). These identified genes are also known to be influenced by multiple cellular functions, such as cytokine–cytokine receptor interactions and Notch signaling. Proteosome 20S subunit genes PSMAs/PSMBs and the HDAC gene family are involved in many cellular functions. The ephrin receptors (EPHs), adrenoceptor alpha receptors (ADRs), dopamine receptors (DRDs), and the 5-hydroxytryptamine serotonin receptors (HTRs) gene families influence neuronal functions and are targeted by multiple drugs in our focused cluster. These data reveal potential therapeutic pathways for CD patients.
Divergent half maximal inhibitory concentration (IC50) values, as documented by an MTS cell viability assay, were observed in response to drug treatment among hPITOs lines 28, 33, 34, 35, and 37. Note that a shift of the curve to the right indicates a higher IC50 (i.e., more resistant to that drug). Cell viability assays were normalized to vehicle-treated controls in order to ensure that toxicity was specific to the drug effects (Figure 4). Dose response curves for organoid 33 and organoid 34 showed better responses at lower doses for cabergoline compared to Metyrapone and osilodrostat, but different for organoid 35, where Metyrapone and osilodrostat gave better responses than Cabergoline (Figure 4a–h). For the drugs mifepristone and GANT61, 33 and 34 had the same level of response to both the drugs. However, when the two organoid responses were compared, 34 had a better response than 33 (Figure 4a–h). Similar divergent drug responses were observed in hPITO lines 37 and 38 (Figure 4i,k). However, organoids generated from adjacent normal pituitary tissue from patients 37 and 38 were nonresponsive to the same standard of care of investigational drugs for CD (Figure 4j,l). These data were consistent with observation made in the drug screen (Figure 3a–c), and demonstrate that there was an inherent difference to drug response within the organoid cultures of the same corticotroph subtype.
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Figure 4. Drug dose responses by hPITOs generated from CD patients. Dose responses to mifepristone, GANT61, cabergoline, and osilodrostat. (a,e) hPITO28, (b,f) hPITO33, (c,g) hPITO34, and (d,h) hPITO35. Dose responses to cabergoline, ketoconazole, roscovitine, GANT61, pasireotide, mifepristone, etomidate, mitotane, metyrapone, and osilodrostat in (i) hPITO37, (j) organoids generated from adjacent normal pituitary tissue (hPITO37N), (k) hPITO38, (l) hPITO38N, and (m) hPITO39. (n) IC50 and integrated area under the curve in response to mifepristone, ketoconazole, and pasireotide using hPITO39 cultures. Nuclear morphometric analysis of hPITO39 cultures in response to (o,p) vehicle, (q,r) mifepristone, (s,t) pasireotide, and (u,v) ketoconazole. Morphometric classification of NII was based on the normal (N), small (S), small regular (SR), short irregular (SI), large regular (LR), large irregular (LI), and irregular (I) nuclear morphology. Representative Hoechst staining of organoids in response to drug treatments for the calculation of the nuclear irregularity index (NII) are shown in the insets in (p,r,t,v).
In addition to cell viability, Nuclear Morphometric Analysis (NMA) using treated organoids was performed based on a published protocol that measures cell viability according to the changes in nuclear morphology of the cells, using nuclear stain Hoechst or DAPI [30]. Nuclear Irregularity Index (NII) was measured based on the quantification of the morphometric changes in the nuclei in response to the standard-of-care drugs mifepristone, pasireotide, and ketoconazole in hPITO39 (Figure 4o–v). The area vs. NII of vehicle-treated cells were plotted as a scatter plot using the template, and considered as the normal cell nuclei (Figure 4o). The same plots were generated for mifepristone (Figure 4q), pasireotide (Figure 4s), and ketoconazole (Figure 4u). The NII and area of treated cells were compared to those of the normal nuclei, and classified as one of the following NMA populations: Normal (N; similar area and NII), Mitotic (S; similar area, slightly higher NII), Irregular (I; similar area, high NII), Small Regular (SR; apoptotic, low area and NII), Senescent (LR; high area, low NII), Small Irregular (SI; low area, high NII), or Large Irregular (LI; high area, high NII) (Figure 4p,r,t,v). Cells classified as SR exhibited early stages of apoptosis, and cells classified as either I, SI, or LI exhibited significant nuclear damage. Data showed that mifepristone induced significant apoptosis in hPITO39 cultures (Figure 4r), compared to responses to pasireotide (Figure 4t) and ketoconazole (Figure 4v). These responses were consistent with the IC50 and the total area under the curve in response to drugs (Figure 4m,n). Measurement of NII is an approach which may be used to confirm potential drug targets identified from the drug screen.

3.4. Organoid Responsiveness to Pasireotide Correlates with SSTR2 and SSTR5 Expression

Organoid lines hPITO28, 31, 33, 34, and 35 exhibited divergent IC50 values in response to SSTR agonist pasireotide (Figure 5a). hPITO34 was the most responsive to pasireotide, with a low IC50 value of 6.1 nM (Figure 5a). Organoid lines hPITO33 and hPITO35 were the least responsive, with IC50 values of 1.2 µM and 1 µM, respectively, in response to pasireotide (Figure 5a). The expression of SSTR subtypes 1–5 among the different organoid lines were measured by qRT-PCR and IHC (Figure 5b). One of the least responsive organoid lines, hPITO28, exhibited lower differential expression in SSTR2 and SSTR5 compared to the highly responsive hPITO34 line (Figure 5a,b). Gene expression levels of SSTR2 and SSTR5 within hPITO28 and 34 correlated with protein levels within the patient’s tumor tissue (Figure 5c–f). Given the greater binding affinity for SSTR5 compared to SSTR2 by pasireotide, these data were consistent with greater responsiveness to the drug by hPITO34 in comparison to hPITO28 (Figure 5a,c–f). The expression of SSTR subtypes 2 and 5 within the organoid cultures correlated with the expression patterns of the patient’s tumor tissues (Figure 5a,c–f).
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Figure 5. SSTR1-5 expression in hPITOs and patient’s PitNET tissue. (a) Dose response of hPITO28, 31, 33, 34, and 35 lines to pasireotide. (b) Differential expression of SSTR subtypes 1–5 (SSTR1, SSTR2, SSTR3, SSTR4, SSTR5) in hPITO28, hPITO31, hPITO33, hPITO34, and hPITO35. Immunohistochemistry of (c,e) SSTR2 and (d,f) SSTR5 expression in patient PitNET tissue (Pt28 and Pt34), from which hPITO28 and 34 were generated.

3.5. Organoids Derived from Pituitary Corticotroph Adenomas Retain the Genetic Alterations of the Patient’s Primary Tumor

In order to identify the genetic features of the organoids derived from pituitary adenomas of CD patients, we performed whole-exome sequencing (WES) of hPITOs and the corresponding primary adenoma tissues. We performed WES analysis of each hPITO line, and compared the results with those for the corresponding primary adenoma tissues. We showed the concordance rate of exonic variants between the primary tumor tissues obtained from CD patients and the corresponding organoid line. We identified, on average, approximately 5000 mutations across each of the 14 paired samples of organoids and tissues. For the variants detected, all seven pairs showed a Jaccard index ranging from 0.5 to 0.8. Out of seven pairs, five (hPITO24, 25, 28 and 35) pairs had a Jaccard score of 0.8, while hPITO33 and 34 pairs had 0.7, and hPITO1 had 0.5. In order to investigate the similarity across the SNV (single nucleotide variation) sites, we calculated the Jaccard index of exon sites for synonymous and non-synonymous events, and found scores for all pairs ranging from 0.8 to 0.9. Furthermore, for only non-synonymous events, Jaccard scores also ranged from 0.8 to 0.9, except for hPITO1, which showed overall lower concordance, and had a score of 0.4 to 0.5. Figure 6 shows non-synonymous mutations found in organoid and tissue pairs for some of the key genes that are known to be involved in pituitary adenoma disease. Concordance indices between organoids and the matched patient’s adenoma tissues is reported in Figure 6. Therefore, WES data demonstrated that organoids derived from pituitary corticotroph adenomas retained the genetic alterations of the patient’s primary tumor tissue.
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Figure 6. Genomic landscape of hPITOs recapitulates genetic alterations commonly found PitNETs. Overview of single nucleotide variation events detected in hPITOs in genes commonly altered in PitNETs. The mutation frequency across the organoid population is depicted on the right. Color coding of the figure shows that organoid lines are derived from the same patient tumor tissue. ORG: organoid line, TIS: matched patient’s PitNET tissue.

3.6. IPSC Pituitary Organoids Generated from a CD Patients Expressing Familial Mutations Reveal Corticotroph Adenoma Pathology In Vitro

Extensive research has revealed the role of somatic and germline mutations in the development of CD adenomas [36,37]. Pituitary organoids were developed from iPSCs generated from the PBMCs of CD patients and carrying germline mutations that were identified by WES (Supplemental Figure S4). Chromosomal aberrations were not found when comparing against the reference dataset in the iPSCs generated from the CD patients (Supplemental Figure S3a,b). PBMCs isolated from patients diagnosed with CD were analyzed by WES in order to determine the expression of germline mutations. WES revealed the expression of a more recently identified gene predisposing patients to CD, namely cadherin-related 23 [38] (Supplemental Figure S5).
Pituitary organoids were then developed from iPSCs which were generated from the PBMCs of patients with CD (iPSCCDH23 and iPSCMEN1) and a healthy individual (iPSCctrl). Expression of PIT1 (pituitary-specific positive transcription factor 1), ACTH (adrenocorticotropic hormone), GH (growth hormone), FSH (follicle-stimulating hormone), LH (luteinizing hormone), PRL (prolactin), and synaptophysin (synaptophysin) with co-stain Hoechst (nuclei, blue) was measured by immunofluorescence, using chamber slides collected at 15 of the differentiation schedules (Supplemental Figure S6). While pituitary tissue that was differentiated from iPSCctrl expressed all major hormone-producing cell lineages (Supplemental Figure S6a), there was a significant increase in the expression of ACTH and synaptophysin, with a concomitant loss of PIT1, GH, FSH, LH, and PRL in iPSCsMEN1 (Supplemental Figure S6b,c). Interestingly, iPSCCDH23 cultures exhibited a significant increase in the expression of ACTH, GH, LH, and synaptophysin, with a concomitant loss of PIT1, FSH, and PRL (Supplemental Figure S6b,c). Immunofluorescence of iPSCs collected on the fourth day of the differentiation schedule revealed no expression of PIT1, ACTH, GH, FSH, LH, or PRL in (data not shown). Compared to control lines, iPSC lines expressing mutated CDH23 secreted significantly greater concentrations of ACTH earlier in the differentiation schedule (Supplemental Figure S7a). The upregulated expression of pituitary corticotroph adenoma-specific markers in iPSCCDH23 and iPSCMEN1 demonstrates that the iPSC-derived organoids represented the pathology of corticotroph adenomas in vitro.

3.7. ScRNA-seq Reveals the Existence of Unique Proliferative Cell Populations in iPSCCDH23 Cultures When Compared to iPSCsctrl

Using Seurat to identify cell clusters, as well as Uniform Manifold Approximation and Projection 9UMAP, clustering analysis identified 16 distinct cell populations/clusters consisting of known marker genes. Clusters 1, 5, and 7 of the iPSCsCDH23 were distinct from the iPSCctrl cultures (Figure 7a,b). Pituitary stem cells were characterized in iPSCctrl and iPSCCDH23 cultures (Figure 7b). Clusters 1 and 5 expressed markers consistent with the corticotroph subtype cell lineage (Figure 5c). Markers of dysregulated cell cycles and increased proliferation were identified in cell cluster 7 (Figure 7c). Expression of the E2 factor (E2F) family of transcription factors, which are downstream effectors of the retinoblastoma (RB) protein pathway and play a crucial role in cell division control, were identified in distinct cell cluster 7, which was identified within the iPSCCDH23 cultures (Figure 7c). Stem cell markers were also upregulated in cell cluster 7, and identified within the iPSCCDH23 cultures (Figure 7c). Using Cytobank software to analyze organoids collected 30 days post-differentiation, cells were gated on live CK20 positive singlets, and 9000 events per sample were analyzed by the viSNE algorithm. ViSNE plots are shown in two dimensions with axes identified by tSNE- 1 and tSNE-2, and each dot representing a single cell positioned in the multidimensional space (Figure 7d). Individual flow cytometry standard files were concatenated into single flow cytometry standard files, from which 12 spatially distinct populations were identified (Figure 7e). Overlaying cell populations identified by traditional gating strategies onto viSNE plots identified unique cell populations within the iPSCCDH23 cultures (Figure 7e). There were distinct cell populations between the iPSCctrl and iPSCCDH23 organoids, in addition to expression of hormone and cell lineage markers such as ACTH, TPit, PRL, and PIT1 (Figure 7e). The cell populations that exhibited high expression of Ki67 within the iPSCctrl organoid cultures included SOX2+ and PIT1+ populations (Figure 7f). The highly proliferating cell populations within the iPSCCDH23 organoid cultures included those that expressed CD90+/VIM+/CXCR4+ (mesenchymal stem cells), CXCR4+/SOX2+ (stem cells), TPit+ (corticotroph cell lineage), CD133+/CD31+ (endothelial progenitor cells), and CK20+/VIM+/CXCR4+ (hybrid epithelial-mesenchymal stem cells) (Figure 7f). Overall, the iPSCCDH23 organoids were significantly more proliferative compared to the iPSCctrl cultures (Figure 7f). Immunofluorescence staining of iPSCCDH23 organoids revealed increased mRNA expression of TPit and POMC, which correlated with increased ACTH protein compared to iPSCsctrl (Supplemental Figure S6). As shown in Supplemental Figure S6b,c, iPSCCDH23 cultures also exhibited a significant increase in the expression of GH and LH (Supplemental Figure S6b,c).
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Figure 7. Single cell analysis of iPSCctrl and iPSCCDH23 cultures 15 and 30 days post-directed differentiation. (a) UMAP plots showing identified cell clusters 0–16 in iPSCctrl and iPSCCDH23 cultures 15 days post-directed differentiation. (b) Violin plots of representative identified markers of the corticotroph cell lineage, where 2 subpopulations were observed among iPSCctrl and iPSCCDH23 cultures. Arrows highlight clusters 1, 5, and 7. (c) Violin plots showing expression of genes representative of stem cells, Wnt, NOTCH, Hh and SST signaling, anterior pituitary (corticotroph) cell lineage, and cell cycle in clusters 1, 5, and 7 of iPSCCDH23 cultures. Plot width: cell number, plot height: gene expression. (d) viSNE maps showing concatenated flow cytometry standard files for both samples and iPSCctrl and iPSCCDH23 organoids 30 days post-directed differentiation. (e) Overlay of manually gated cell populations onto viSNE plots. (f) Fluorescent intensity of Ki67 of viSNE maps for both samples and iPSCctrl and iPSCCDH23 organoids. iPSCctrl = 22518 events; iPSCCDH23 = 17542 events.
Collectively, Figure 7 demonstrates that the development of pituitary organoids generated from iPSCs of CD patients may reveal the existence of cell populations which, potentially, contribute to the support of adenoma growth and progression, as well as an expansion of stem and progenitor cells that may be the targets for tumor recurrence.

4. Discussion

Our studies demonstrate the development of organoids generated from human PitNETs (hPITOs) can potentially be used to screen for the sensitivity and efficacy of responses to targeted therapies for CD patients that either fail to achieve remission or exhibit recurrence of disease after surgery. In addition, we have documented that induced pluripotent stem cells (iPSCs) generated from a CD patient expressing germline mutation CDH23 (iPSCCDH23) reveals the disease pathogenesis under directed differentiation. Many early in vitro experiments have used pituitary cell lines, spheroids, aggregates, and/or tumoroids that do not replicate the primary PitNET microenvironment [19,20,21], and lack a multicellular identity [39,40]. The development of PitNET tissue-generated organoids is limited to the use of transgenic mouse models as the source [22,23,41]. The recent organoid cultures reported by Nys et al. [42] have been generated from single stem cells isolated from PitNET tissue, and are claimed to be true organoids due to their clonality. However, multicellular complexity was not validated by the protein expression or hormone secretion from pituitary cell lineages in these cultures [42]. According to the National Cancer Institute (NCI, NIH), an ‘organoid’ is defined as “a tiny, 3-dimensional mass of tissue that is made by growing stem cells (cells from which other types of cells develop) in the laboratory” [43]. The hPITOs reported here begin from single and/or 3–4 cell clusters dissociated from the PitNET tissue that harbors the stem cells. Supplemental Video S2 demonstrates a process of ‘budding,’ as well as lumen formation as organoids grow and differentiate. We document differentiation and function by comprehensive spectral flow cytometry, ELISA, and response to standard of care drugs. The growth of PitNET organoids reported in the current study is consistent with that of gastrointestinal tissue derived cultures that begin from cell clusters, crypts, or glands [27,44,45].
Our studies report a PitNET tissue organoid culture with a multicellular identity consisting of differentiated cell lineages, stem/progenitor cells, and immune and stromal cell compartments, which replicates much of the patient’s own adenoma pathology, functionality, and complexity. We have also demonstrated that iPSCs, derived from the blood of a CD patient, can be directly differentiated into pituitary organoids that resemble similar characteristics to the tumor tissue. Many investigators have proposed the use of organoids in personalized medicine, but have focused these efforts on targeted treatment of cancers [27,46,47,48]. The findings reported in these studies are the first to implement this approach for the potential treatment of PitNETs. Collectively, we have developed a relevant human in vitro approach to potentially advance our knowledge as well as our approach to studies in the field of pituitary tumor research. Both the hPITOs and the iPSCCDH23 may be implemented in studies that strive to (1) define the molecular and cellular events that are crucial for the development of PitNETs leading to CD, and (2) accelerate the identification of effective targeted therapies for patients with CD.
While published studies have advanced our understanding of the molecular mechanisms of the pathogenesis of corticotroph adenomas and elucidated candidate therapeutic targets for CD, these reports fall short of directly informing clinical decisions for patient treatment. Using organoids to screen potential drugs and compounds can potentially improve therapeutic accuracy. Figure 3 demonstrated a variation in drug responsiveness amongst the organoid lines generated from individual patients. Importantly, there was further divergence in drug responsiveness amongst the individual organoid lines within each pathologically defined corticotroph subtype. For example, hPITOs generated from patients with sparsely granulated corticotroph adenomas (hPIT0s 10, 25, 34, 35) and Crooke’s cell adenomas (hPITOs 7, 33) showed variable responses regardless of similar pathologically defined subtypes. In addition, the response of the tumor cells within the organoids to the standard of care drugs that directly target the pituitary in the body, including mifepristone and cabergoline, was only 50% in hPITO34 and hPITO35, and almost 0% in the other lines, including hPITO7, 10, and 25. These data clearly demonstrate that the inherent patient difference to drug response that is often observed among CD patients is reflected in the organoid culture. This culture system may be an approach that will provide functional data revealing actionable treatment options for each patient. Patient-derived organoids from several tumors have served as a platform for testing the efficacy of anticancer drugs and predicting responses to targeted therapies in individual patients [27,46,48,49,50]. An example of the use of organoids in identifying drug responsiveness within an endocrine gland is that of papillary thyroid cancer [51]. Organoids developed from PTC patients were used as a preclinical model for studying responsiveness to anticancer drugs in a personalized approach [51]. However, our study is the first report of the use of hPITOs for drug screening. Connecting genetic and drug sensitivity data will further categorize corticotroph subtypes associated with CD. WES analysis of each hPITO line was compared to the results for the corresponding primary adenoma tissues. We showed the concordance rate of exonic variants between the primary tumor tissues obtained from CD patients and the corresponding organoid line. On average, approximately 80% of the variants observed in the CD patients’ adenoma tissues were retained in the corresponding hPITOs.
Pituitary organoids were also developed from iPSCs generated from PBMCs of a CD patient expressing a germline genetic alteration in cadherin-related 23 CDH23 (iPSCCDH23), a CD patient expressing an MEN1 mutation (iPSCMEN1), and a healthy individual (iPSCctrl). Foundational studies performed by investigators at the genome level have revealed significant knowledge regarding the pathophysiology of CD [36,37,52,53]. In some instances, CD is a manifestation of genetic mutation syndromes that include multiple endocrine neoplasia type 1 (MEN1), familial isolated pituitary adenoma (FIPA), and Carney complex [54,55]. CDH23 syndrome is clinically associated with the development of Usher syndrome, deafness, and vestibular dysfunction [56]. Several mutations in CDH23 are associated with inherited hearing loss and blindness [57]. However, none of the variants found in this study were linked to any symptoms of deafness or blindness. A possible explanation is that deafness-related CDH23 mutations are caused by either homozygous or compound heterozygous mutations [57]. In a study that linked mutations in CDH23 with familial and sporadic pituitary adenomas, it was suggested that these genetic alterations could play important roles in the pathogenesis of CD [38]. Genomic screening in a total of 12 families with familial PitNETs, 125 individuals with sporadic pituitary tumors, and 260 control individuals showed that 33% of the families with familial pituitary tumors and 12% of individuals with sporadic pituitary tumors expressed functional or pathogenic CDH23 variants [38]. Consistent with the expected pathology and function of a PitNET from a patient with CD, iPSCCDH23 organoids exhibited hypersecretion of ACTH, and expression of transcription factors and cell markers were reported in the pathology report for corticotroph PitNETs. Collectively, these findings warrant further investigation to determine whether carriers of CDH23 mutations are at a high risk of developing CD and/or hearing loss. Specifically, clinical investigation is required to determine whether pituitary MRI scans should be adopted in the screening of CDH23-related diseases, including Usher syndrome and age-related hearing loss.
Pituitary organoids generated from iPSCs of a CD patient revealed the existence of cell populations that potentially contribute to the support of PitNET growth and disease progression, as well as an expansion of stem and progenitor cells that may be the targets for tumor recurrence. Organoids derived from both pituitary adenomas and iPSCs exhibited increased expression of stem cell and progenitor markers at both the protein and transcriptomic levels. Unique clusters that were proliferative in the iPSCCDH23 organoids expressed a hybrid pituitary cell population which was in an epithelial/mesenchymal state (CK20+/VIM+/CXCR4+/Ki67+). In support of our findings, a similar report of a hybrid epithelial/mesenchymal pituitary cell has been made as part of the normal developmental stages of the human fetal pituitary [58]. Previous studies have suggested that pituitary stem cells undergo an EMT-like process during cell migration and differentiation [59,60,61]. Consistent with our findings are extensive studies using single cells isolated from human pituitary adenomas to show increased expression of stem cell markers SOX2 and CXCR4 [22,23,41,62,63]. Within the clusters identified in the iPSCCDH23 culture were cell populations expressing stem cell markers, including SOX2, NESTIN, CXCR4, KLF4, and CD34. The same iPSCCDH23 cell clusters, 4, 8, 9, and 11, co-expressed upregulated genes of NOTCH, Hedgehog, WNT, and TGFβ signaling, which are pivotal not only in pituitary tumorigenesis and pituitary embryonic development, but also in ‘tumor stemness’ [22,23,41,62,63,64]. We also noted that clusters of cell populations 5 and 14 unique within the iPSCCDH23 cultures expressed upregulated genes which were indicative of high proliferation. We observed upregulated expression of the E2F family of transcription factors (E2Fs) E2F1 and E2F7. These findings are of significance, given that there is evidence to show that upregulation of E2Fs is fundamental for tumorigenesis, metastasis, drug resistance, and recurrence [65]. Within the pituitary adenoma microenvironment, whether these stem cells directly differentiate into pituitary tumors or support the growth of the adenoma is largely unknown. In addition, whether pituitary stem cell populations become activated in response to injury is also understudied. Although the role of stem cells has been identified using a mouse model through implantation of the cells within the right forebrain [66], the identification of pituitary tumor-initiating stem cells using in vivo orthotopic transplantation models is impossible in mice. Pituitary tumors harboring the stem cells may require engraftment within the environment from which the cells are derived in order to enable growth and differentiation of the tumor. However, it is technically impossible to implant cells orthotopically in the murine pituitary. The pituitary tumor organoid cultures presented in these studies may offer an approach by which isolation, identification, and characterization of this stem cell population is possible. Therefore, we would gain knowledge on the mechanisms of pituitary tumor pathogenesis and reveal potential novel targets for therapeutic interventions by using the iPSC generated pituitary organoid culture.
PitNETs associated with the development of CD cause serious morbidity due to chronic cortisol exposure that dysregulates almost every organ system in the body. Overall, existing medical therapies remain suboptimal, with negative impact on health and quality of life, including considerable risk of therapy resistance and tumor recurrence. To date, little is known about the pathogenesis of PitNETs. Here, we present a human organoid-based approach that will allow us to acquire knowledge of the mechanisms underlying pituitary tumorigenesis. Such an approach is essential to identify targeted treatments and improve clinical management of patients with CD.

5. Conclusions

Cushing’s disease (CD) is a serious endocrine disorder caused by an adrenocorticotropic hormone (ACTH)-secreting pituitary neuroendocrine tumor (PitNET), which stimulates the adrenal glands to overproduce cortisol. The absence of preclinical models that replicate the PitNET microenvironment has prevented us from acquiring the knowledge to identify therapies that can be targeted to the tumor with a higher efficacy and tolerability for patients. Our studies demonstrate the development of organoids generated from human PitNETs or induced pluripotent stem cells as an essential approach to identifying targeted therapy methods for CD patients.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cells11213344/s1, Figure S1: Antibodies used and Cytek® Full Spectrum Viewer showing calculated similarity indices; Figure S2: Morphology and proliferation of lactotroph, somatotroph, and gonadotroph hPITOs; Table S1: Pituitary Growth Media; Table S2: Components used for pituitary organoids generated from iPSCs; Table S3: clinical characteristics of pituitary adenoma samples used for the generation of organoids; Table S4: Average correlation of replicates reported in Figure 3; Table S5: pituitary cell lineage or stem cell markers used in the scRNA-seq analysis; Video S1: hPITO38 EdU ACTH 3.

Author Contributions

Conceptualization, Y.Z.; methodology, J.C., Y.Z., J.M.C., B.N.S., S.M. and K.W.P.; software, J.C., Y.Z., J.M.C., S.M., Y.C., P.M. and R.P.; validation, Y.Z., J.C., J.M.C., A.S.L., K.C.J.Y. and R.P.; formal analysis, J.C., Y.Z., J.M.C., R.P., Y.C., S.M. and P.M.; investigation, Y.Z.; resources, Y.Z., J.C., J.E., C.A.T., B.H. and A.S.L.; data curation, J.C., Y.Z., J.M.C., R.P. and S.M.; writing—original draft preparation, Y.Z., J.C, S.M., J.M.C., Y.C., B.H. and R.P.; writing—review and editing, Y.Z., J.C., J.M.C., A.S.L., K.C.J.Y., S.M., J.E., C.A.T., K.W.P., B.H., Y.C., P.M., B.N.S. and R.P.; visualization, Y.Z., J.C., J.M.C., A.S.L., K.C.J.Y. and R.P.; supervision, Y.Z.; project administration, Y.Z.; funding acquisition, Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Department of Cellular and Molecular Medicine (University of Arizona College of Medicine) startup funds (Zavros). This research study was also partly supported by the National Cancer Institute of the National Institutes of Health under award number P30 CA023074 (Sweasy).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of St. Joseph’s Hospital and Barrow Neurological Institute Biobank collection protocol PHXA-05TS038, and collection of outcomes data protocol PHXA-0004-72-29, and patient consent (protocol date of approval).

Informed Consent Statement

Written informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated during the analysis of the present study are available in the ReDATA repository, https://doi.org/10.25422/azu.data.19755244.v1. The datasets generated in the current study are also available from the corresponding author on reasonable request. All data generated or analyzed during this study are included in this published article (and its Supplementary Information Files).

Acknowledgments

We acknowledge the technical support of Maga Sanchez in the Tissue Acquisition and Cellular/Molecular Analysis Shared Resource (TACMASR University of Arizona Cancer Center) for assistance with embedding and sectioning of organoids. We would also like to acknowledge Patty Jansma (Marley Imaging Core, University Arizona) and, Douglas W Cromey (TACMASR imaging, University of Arizona Cancer Center) for assistance in microscopy. The authors thank the patients who consented to donate pituitary tumor tissues and blood for the development of the organoids. Without their willingness to participate in the study, this work would not be possible.

Conflicts of Interest

The authors declare no conflict of interest.

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Characterization of Adrenal miRNA-Based Dysregulations in Cushing’s Syndrome

Abstract

MiRNAs are important epigenetic players with tissue- and disease-specific effects. In this study, our aim was to investigate the putative differential expression of miRNAs in adrenal tissues from different forms of Cushing’s syndrome (CS). For this, miRNA-based next-generation sequencing was performed in adrenal tissues taken from patients with ACTH-independent cortisol-producing adrenocortical adenomas (CPA), from patients with ACTH-dependent pituitary Cushing’s disease (CD) after bilateral adrenalectomy, and from control subjects. A confirmatory QPCR was also performed in adrenals from patients with other CS subtypes, such as primary bilateral macronodular hyperplasia and ectopic CS. Sequencing revealed significant differences in the miRNA profiles of CD and CPA. QPCR revealed the upregulated expression of miR-1247-5p in CPA and PBMAH (log2 fold change > 2.5, p < 0.05). MiR-379-5p was found to be upregulated in PBMAH and CD (log2 fold change > 1.8, p < 0.05). Analyses of miR-1247-5p and miR-379-5p expression in the adrenals of mice which had been exposed to short-term ACTH stimulation showed no influence on the adrenal miRNA expression profiles. For miRNA-specific target prediction, RNA-seq data from the adrenals of CPA, PBMAH, and control samples were analyzed with different bioinformatic platforms. The analyses revealed that both miR-1247-5p and miR-379-5p target specific genes in the WNT signaling pathway. In conclusion, this study identified distinct adrenal miRNAs as being associated with CS subtypes.

1. Introduction

Cushing’s syndrome (CS) results from the excessive secretion of cortisol, leading to visceral obesity, resistance to insulin, osteoporosis, and altered lipid and glucose metabolism [1,2]. Excessive production of cortisol by the adrenal glands can be either ACTH-dependent or -independent. In the majority of patients, hypercortisolism is due to ACTH secretion by corticotroph adenomas of the pituitary gland (Cushing’s disease, CD) or by ectopic tumors [3]. Approximately 20% of cases are ACTH-independent, where cortisol is secreted autonomously by the adrenal cortex. The pathology of ACTH-independent cases is diverse; they are most often caused by unilateral cortisol-producing adrenocortical adenomas (CPA). Rare causes are cortisol-secreting adrenocortical carcinomas (ACC), primary bilateral macronodular adrenocortical hyperplasia (PBMAH), bilateral CPAs, and primary pigmented nodular adrenal disease (PPNAD) [4,5]. Irrespective of the subtype, prolonged exposure to cortisol in CS is associated with increased mortality and cardiovascular morbidity in its patients [6]. Treatment is based on the underlying cause of hypercortisolism, with pituitary surgery or adrenalectomy being the preferred choice. Medical therapy options in CS are few and consist of pituitary-directed drugs, steroid synthesis inhibitors, and glucocorticoid receptor antagonists [7]. For the timely diagnosis and targeted management of CS and its subtypes, a comprehensive understanding of cortisol secretion, in terms of canonical signaling pathways as well as upstream epigenetic factors, is needed.
MiRNA molecules have emerged as key epigenetic players in the transcriptional regulation of cortisol production. Briefly, the deletion of Dicer in adrenals, a key miRNA processing enzyme, revealed diverse expression changes in miRNAs along with related changes in steroidogenic enzymes such as Cyp11b1 [8]. Furthermore, key enzymes in the cortisol biosynthesis pathway, namely Cyp11a1, Cyp21a1, Cyp17a1, Cyp11b1, and Cyp11b2, were also found to be regulated by various miRNAs (miRNA-24, miRNA-125a-5p, miRNA-125b-5p, and miRNA-320a-3p) in in vitro studies [9]. Consequently, various studies have also characterized miRNA expression profiles in CS subtypes. Importantly, miRNA expression in the corticotropinomas of CD patients was found to vary according to USP8 mutation status [10]. Other studies have also identified specific miRNA candidates and associated target genes in the adrenals of patients with PPNAD [11], PBMAH [12,13], and massive macronodular adrenocortical disease [14]. Interestingly, no common miRNA candidates were found among these studies, indicating the specificity of miRNAs to the different underlying pathologies in CS.
There are limited studies directly comparing miRNA expression profiles of ACTH-dependent and ACTH-independent CS patients. Consequently, in our previous study, we found differences in expression profiles when comparing circulating miRNAs in CD and CPA patients [15]. We hypothesized that the presence of ACTH possibly influences the miRNA profile in serum due to the upstream differential expression in the origin tissues. In this study, we aim to further explore this hypothesis by comparing the miRNA expression profile of adrenal tissues in ACTH-dependent and ACTH-independent CS. In brief, miRNA specific sequencing was performed in two prevalent subtypes of CS: in CD, the most prevalent ACTH-dependent form; and in CPA, the most prevalent ACTH-independent form. Specific miRNA candidates related to each subtype were further validated in other forms of CS. To further investigate our hypothesis, the response of miRNA candidates following ACTH stimulation was assessed in mice, and the expression of miRNAs in murine adrenals was subsequently investigated. Finally, an extensive targeted gene analysis was performed based on in silico predictions, RNA-seq data, and luciferase assays.

2. Results

2.1. Differentially Expressed miRNAs

NGS revealed differentially expressed miRNAs between the different groups analyzed (Figure 1). CD and CPA taken together as CS showed a differentially expressed profile (42 significant miRNAs) in comparison to controls. Moreover, individually, CPA and CD were found to show a significantly different expression profile in comparison to controls (n = 38 and n = 17 miRNAs, respectively). Interestingly, there were no significantly upregulated genes in the adrenals of patients with CD in comparison to the control adrenals. A comparative analysis of the top significant miRNAs (log2 fold change (log2 FC) > 1.25 & p < 0.005) between the two groups was performed and the representative Venn diagrams are given in Figure 2. Briefly, miR-1247-5p, miR-139-3p, and miR-503-5p were significantly upregulated in CPA, in comparison to both CD and controls. Furthermore, miR-150-5p was specifically upregulated in CPA as compared to CD. Several miRNAs (miR-486-5p, miR-551b-3p, miR-144-5p, miR-144-3p, and miR-363-3p) were found to be significantly downregulated in the groups of CPA and CD in comparison to controls. MiR-19a-3p and miR-873-5p were found to be commonly downregulated in CPA in comparison to both CD and controls. Principal component analyses based on miRNA sequencing did not identify any major clusters among the samples. Furthermore, the miRNA profile was not different among the CPA samples based on the mutation status of PRKACA (Supplementary Materials Figure S1).
Ijms 23 07676 g001 550
Figure 1. Differentially expressed miRNAs from sequencing. Volcano plot showing the relationship between fold change (log2 fold change) and statistical significance (−log10 p value). The red points in the plot represent significantly upregulated miRNAs, while blue points represent significantly downregulated miRNAs. CPA, cortisol producing adenoma; CD, Cushing’s disease; Cushing’s syndrome represents CPA and CD, taken together.
Ijms 23 07676 g002 550
Figure 2. Venn analyses of the common significant miRNAs from each group. The significantly expressed miRNAs from each sequencing analysis were shortlisted and compared between the groups. CPA, cortisol producing adenoma; CD, Cushing’s disease.

2.2. Validation and Selection of Candidate miRNAs

For validation by QPCR, the most significant differentially expressed miRNAs (log2 FC > 1.25 & p < 0.005) among the groups were chosen (Table S1). According to the current knowledge, upregulated miRNAs are known to contribute more to pathology than downregulated miRNAs [16]. Since the total number of significantly upregulated miRNAs was six, all these miRNAs were chosen for validation. Contrarily, 25 miRNAs were significantly downregulated among the groups. In particular, miR-486-5p, miR-551b-3p, miR-144-5p, miR-144-3p, and miR-363-3p were found to be commonly downregulated in the CS group in comparison to controls; therefore, these miRNAs were chosen for validation.
Among the upregulated miRNA candidates, miR-1247-5p QPCR expression confirmed the NGS data (Figure 3A, Table S1). Moreover, miR-150-5p and miR-139-3p were upregulated in CPA specifically in comparison to CD, and miR-379-5p was upregulated in CD in comparison to controls by QPCR. In the case of downregulated genes, none of the selected miRNAs could be confirmed by QPCR (Figure 3B). Thus, analysis of the six upregulated and five downregulated miRNAs from NGS yielded two significantly upregulated miRNA candidates, miR-1247-5p in CPA and miR-379-5p in CD, when compared to controls. These miRNA candidates were taken up for further QPCR validation in an independent cohort of other subtypes of CS (Figure 4), namely ACTH-dependent ectopic CS (n = 3) and ACTH-independent PBMAH (n = 10). The QPCR analysis in the other subtypes revealed miR-1247-5p to be consistently upregulated in ACTH-independent CS (PBMAH and CPA) in comparison to ACTH-dependent CS (CD and ectopic CS) and controls. On the other hand, miR-379-5p was upregulated in CD and PBMAH in comparison to controls.
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Figure 3. QPCR analyses of significant miRNAs from sequencing analyses. Data are represented as mean ± standard deviation (SD) of −dCT values: (A) Expression analysis of significantly upregulated miRNAs; (B) Expression analysis of common significantly downregulated miRNAs. Housekeeping gene: miR-16-5p. Statistics: ANOVA test with Bonferroni correction to detect significant differences between patient groups with at least a significance of p-value < 0.05 (*).
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Figure 4. QPCR analyses of significantly upregulated miRNAs from validation QPCR. Data are represented as mean ± standard deviation (SD) of −dCT values. Housekeeping gene: miR-16-5p. Statistics: ANOVA test with Bonferroni correction to detect significant differences between patient groups with at least a significance of p-value < 0.05 (*).

2.3. In Vivo Assessment of ACTH-Independent miR-1247-5p

To analyze the influence of ACTH on miRNA expression, the expression of miR-1247-5p and miR-379-5p were assessed in the adrenal tissues of ACTH stimulated mice at different time points. For this analysis, miR-96-5p was taken as a positive control, as it has previously been reported to be differentially expressed in ACTH stimulated mice [17]. The analyses revealed that the expression of miR-1247-5p and miR-379-5p did not change at different timepoints of the ACTH stimulation (Figure 5). Meanwhile, the positive control of mir-96-5p showed a dynamic expression pattern with upregulation after 10 min, followed by downregulation at the subsequent 30 and 60 min time points, in concordance with previously reported findings [18].
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Figure 5. Analysis of miRNA expression in ACTH stimulated mice tissue. QPCR analyses of positive controls, miR-96-5p, and candidates miR-379-5p and miR-1247-5p. Mice were injected with ACTH, and adrenals were collected at different timepoints to assess the impact of ACTH on miRNA expression. Data are represented as mean ± standard deviation (SD) of −dCT values. Housekeeping gene: miR-26a-5p. Statistics: ANOVA test with Bonferroni correction to detect significant differences between patient groups with at least a significance of p-value < 0.05 (*).

2.4. In Silico Analyses of miRNA Targets

Two diverse approaches were employed for a comprehensive in silico analysis of the miRNA targets. First, the predicted targets of miR-1247-5p and miR-379-5p were taken from the TargetScan database, which identified miRNA–mRNA target pairs based on sequence analyses [19]. The expression status of these targets was then checked in the RNA sequencing data from CPA vs. controls (miR-1247-5p) and PBMAH vs. controls (miR-379-5p). Targets that showed significant expression changes in the sequencing data were shortlisted (Figure 6A). Among the 1061 predicted miR-1247-5p targets, 28 genes were found to show significant expression changes in CPA (20 upregulated, 8 downregulated). On the other hand, for 124 predicted miR-379-5p targets, 23 genes were found to show significant expression changes in PBMAH (20 upregulated, 3 downregulated). Interestingly, the selected targets were found to be unique for each miRNA, except for FICD (FIC domain protein adenylyltransferase) (Figure 6B).
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Figure 6. (A) Differentially expressed target genes of miRNAs from sequencing. Data are represented as log2 fold change in comparison to the controls. Statistics: ANOVA test with Bonferroni correction to detect significant differences between patient groups with at least a significance of p-value < 0.05. (B) Venn analyses of common significant miRNA target genes and related pathways. The significantly expressed targets from each sequencing analysis were shortlisted and compared between the groups. Predicted pathways of the targets from the Panther database were shortlisted and compared between the groups.

2.5. In Vitro Analyses of miR-1247-5p Targets

For in vitro analyses, we focused on downregulated targets, as we expect our upregulated miRNA candidates to cause a downregulation of the target mRNAs. For our downregulated mRNAs, only targets of miR-1247-5p were found to have published links to CS, namely Cyb5a, Gabbr2, and Gnaq (Table 1). Therefore, these three targets were then verified by QPCR in the groups of CPA, CD, PBMAH, ectopic CS, and controls (Figure 6). Only Cyb5A was found to be significantly downregulated in ACTH-dependent forms (ectopic CS and CD) as well as in ACTH-independent CS (PBMAH and CPA) in comparison to controls. Consequently, to assess whether Cyb5a is indeed regulated by miR-1247-5p, a dual luciferase assay was performed. To prove our hypothesis, treatment of Cyb5a-WT cells with miR-1247-5p mimic was expected to lead to a reduced luminescence, whereas no effects were expected in cells treated with the miR-1247-5p inhibitor or the Cyb5a-mutant (with a mutation in the miR-1247-5p binding site). As shown in Figure 7, transfection of miR-1247-5p significantly reduced luminescence from Cyb5a-WT in comparison to cells transfected with Cyb5a-WT and miR-1247-5p inhibitors. However, these predicted binding results were not found to be specific, as there were no significant differences when compared to wells transfected with Cyb5a-WT alone (Figure 8). Consecutively, when the mutated Cyb5a-Mut were transfected along with the mimics and inhibitors, no significant differences in luminescence were observed in the transfected population. Thus, direct interaction between miR-1247-5p and its predicted target gene Cyb5A could not be conclusively proven using this luciferase assay.
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Figure 7. QPCR analyses of the top predicted targets of miR-1247-5p. Data are represented as mean ± standard deviation (SD) of −dCT values. Housekeeping gene: PPIA. Statistics: ANOVA test with Bonferroni correction to detect significant differences between patient groups with at least a significance of p-value < 0.05 (*).
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Figure 8. Results of dual luminescence assay on cells transfected with miR-1247-5p mimics and related controls. Cells were transfected with plasmids containing either the WT or Mut miRNA binding sequence in Cyb5a. Either miR-1247-5p mimics or miR-1247-5p inhibitors were transfected together with the respective plasmids. Data are represented as mean ± standard error of mean (SEM) of relative luminescence unit values. Statistics: ANOVA test with Bonferroni correction to detect significant differences between patient groups with at least a significance of p value < 0.05 (*).
Table 1. Analysis of the predicted targets of miR-1247-5p and their expression levels in comparison to controls (log2 fold change). Published literature on target genes in reference to CS is highlighted in bold.
Table

2.6. Pathway Analyses of miRNA Targets

For the pathway analysis (Reactome) we used the 28 predicted miRNA-1247-5p targets and the 23 predicted miRNA-379-5p targets from TargetScan, which were significantly differently expressed in the RNA-seq (Figure 6). Concurrently, the pathways commonly enriched by both miRNAs included the WNT signaling pathway and N-acetyl-glucosamine synthesis (Figure 9A). As a complementary approach, in silico analyses were also performed based on the targets from miRTarBase. In this database, targets are shortlisted based on published experimental results. In this analysis, miR-1247-5p (n = 21) and miR-379-5p targets (n = 85) were unique. While the validated targets of miR-379-5p were found to show significant changes in expression in the RNA-seq data from PBMAH (n = 12), none of the validated miR-1247-5p targets were found to show significant expression changes in the RNA-seq data from CPA. Therefore, all the validated targets of the miRNAs were subjected to pathway analyses (Panther). Interestingly, the WNT signaling pathway was also found to be commonly regulated by both miRNAs using this approach (Figure 9B). Finally, the expression status of target genes related to WNT signaling pathways were checked in our RNA-seq data (Figure S2). Given the upregulated status of the miRNAs, a downregulated expression of its target genes was expected. However, a significantly upregulated expression was observed for DVL1 in CPA in comparison to controls and for ROR1 in PBMAH in comparison to controls.
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Figure 9. Pathway analyses of miRNA target genes. (A) The predicted targets were matched with the RNA-seq expression data. For miR-1247-5p, CPA vs. controls expression data; and for miR-379-5p, PBMAH vs. controls expression data. The significantly expressed target genes were then subjected to pathway analyses by Reactome. The significantly enriched pathway networks (p < 0.05) and their related genes are given. (B) The experimentally validated target genes from miRTarBase were analyzed for their role in pathways by the Panther database. The target genes and their related pathways are given. The commonly represented pathways are marked in bold.

3. Discussion

MiRNAs are fine regulators of both physiology and pathology and have diverse roles as diagnostic biomarkers as well as therapeutic targets. While circulating miRNAs have been investigated as potential biomarkers for hypercortisolism in CS subtypes (36), comprehensive analyses of their pathological role in CS subtypes have not yet been performed. This study hoped to uncover the pathological role of miRNAs in different CS subtypes as well as identify unique epigenetic targets contributing to hypercortisolism in these subtypes. As such, miRNA sequencing was performed in the ACTH-independent CPA and ACTH-dependent CD, with additional QPCR validation in PBMAH and ectopic CS. As expected, miRNA expression profiles in CD and CPA were very different.

3.1. ACTH-Independent Upregulated miRNAs in CS

Among the analyzed miRNAs, only miR-1247-5p and miR-379-5p showed the most prominent changes in expression levels. Briefly, miR-1247-5p was significantly upregulated in ACTH-independent forms of CS, CPA, and PBMAH (Figure 1 and Figure 3) while miR-379-5p was found to be upregulated in CD and PBMAH, in comparison to controls. Even though CD and PBMAH represent CS subtypes with different ACTH dependence, albeit both with hyperplastic tissue, it is interesting to find a shared miRNA expression status. Concurrently, miRNAs have been identified as dynamic players in regulating the acute effect of ACTH on adrenal steroidogenesis in in vivo murine studies [20,21]. Further diverse miRNAs have been characterized to regulate steroidogenesis in ACTH and dexamethasone treated rats [22] (suppressed ACTH) as well as in in vitro studies [20]. It is possible that miR-379-5p contributes to the adrenal hyperplasia present in both PBMAH and CD by targeting specific genes related to hyperplasia, and miR-1247-5p by contributing to cortisol production independent of ACTH regulation in CPA and PBMAH.
Interestingly, the miRNA candidates (mir-1247-5p and miR-379-5p) in our study have not been previously characterized in any of these studies. Furthermore, the expression of mir-1247-5p and miR-379-5p were found to be independent of ACTH stimulation, underlying their role in CS independently of the HPA axis control and postulating specific regulatory processes.

3.2. Target Genes of miRNAs in CS

Initially, we focused on the selection of known CS specific target genes that could be directly repressed by miRNAs, thereby contributing to pathology. The predicted target genes of miR-1247-5p and miR-379-5p were assessed for their downregulated expression status in the RNA-seq data. Among the selected target genes, only Cyb5a was found to be significantly downregulated in all forms of CS (Figure 6). Cytochrome b5 (CYB5A) is a marker of the zona reticularis and is an important regulator of androstenedione production [23,24]. Based on its role in adrenal steroidogenesis, it is possible that Cyb5a is downregulated by miR1247-5p. To prove our hypothesis, a dual luciferase assay was performed in HELA cell line to identify a direct interaction between Cyb5a and miR-1247-5p (Figure 7). Unfortunately, a direct interaction could not be proven, indicating that miR-1247-5p perhaps regulates its target genes in different ways.

3.3. Pathway Analyses of miRNA Targets

To identify miRNA specific regulatory processes, comprehensive target and pathway analyses were performed. Independent pathway analyses of the respective targets with two different databases of Reactome and Panther showed the WNT signaling pathway as a common targeted pathway of both mir-1247-5p and miR-379-5p (Figure 8). The WNT signaling pathway represents a crucial regulator in diverse developmental as well as pathological processes with tissue-specific effects [25,26]. Consequently, the WNT pathway has been largely characterized as one of the dysregulated pathophysiological mechanisms in CPA. Mutations in PRKACA, one of the WNT signaling proteins, are present in approximately 40% of CPA [27]. In the case of CD, dysregulated WNT signaling has been characterized as promoting proliferation in ACTH-secreting pituitary adenomas [28]. Moreover, activating mutations in beta catenin, one of the WNT signaling pathways, has been characterized as driving adrenal hyperplasia through both proliferation-dependent and -independent mechanisms [29]. Thus, it could be hypothesized that by targeting specific genes in the pathway, miRNAs drive specific pathophysiological processes in diverse CS subtypes.

3.4. MiRNA Target Genes in WNT Signaling

DVL1 (TargetScan) and DVL3 (miRTar) are the shortlisted target genes of miR-1247-5p in the WNT signaling pathway. These genes are members of canonical WNT pathways and, importantly, activation of the cytoplasmic effector Dishevelled (Dvl) is a critical step in WNT/β-catenin signaling initiation [30,31]. Interestingly, no difference in DVL1 and DVL3 gene expression was found in the analyses of ACTH-secreting pituitary adenomas [32]. Therefore, it could be possible that DVL1 and DVL3 are only targeted by miR-1247-5p specifically in the adrenal of CPA and PBMAH patients, leading to its characterized tumor progression. EDN1, TGFBR1 (TargetScan), and ROR1 (miRTar) were the target genes of miR-379-5p related to the WNT pathway. In epithelial ovarian cancer, Endothelin-1 (EDN-1) was found to regulate the epithelial–mesenchymal transition (EMT) and a chemoresistant phenotype [33]. In the case of receptor tyrosine kinase-like orphan receptor 1 (ROR1), higher expression of the gene was associated with a poor prognosis in ovarian cancer [34]. Concurrently, suppression of TGFBR1-mediated signaling by conditional knockout in mice was found to drive the pathogenesis of endometrial hyperplasia, independent of the influence of ovarian hormones [35]. Therefore, it could be hypothesized that the dysregulated expression of these factors in adrenals could trigger similar hyperplastic effects mediated by these factors, as in ovarian tissues.

3.5. Bottlenecks and Future Outlook

Interestingly, among these genes, only DVL1 and ROR1 were found to be significantly upregulated in the RNA-seq data (Figure S2). The major regulatory role of miRNAs in gene expression come from their ability to repress gene expression at the level of transcription and translation. There are also reports of miRNA-mediated gene upregulation; however, the physiological evidence of the role is still unresolved [36]. Therefore, it is interesting to see the selected targets of miR-1247-5p and miR-379-5p upregulated. Moreover, it should be noted that most of the experimentally validated miRNA targets were identified by CLIP methods [37]. Crosslinking immunoprecipitation (CLIP) are binding assays that provide genome-wide maps of potential miRNA-target gene interactions based on sequencing. Moreover, these assays do not make functional predictions on the outcome of miRNA binding, and neither do upregulation or downregulation [38,39]. Therefore, in our current experimental setting, we could only identify potential miRNA target genes and speculate on their pathological role based on the published literature and in silico analyses. Furthermore, extensive mechanistic analyses based on these potential targets could help in elaborating the specific epigenetic pathways that fine-tune CS pathology in different subtypes.

4. Materials and Methods

4.1. Sample Collection and Ethics Approval

All patients were registered in the German Cushing’s Registry, the ENS@T or/and NeoExNET databases (project number protocol code 379-10 and 152-10). The study was approved by the Ethics Committee of the University of Munich. All experiments were performed according to relevant guidelines and protocols, and written informed consent was obtained from all patients involved. The adrenal samples used in the sequencing (miRNA and RNA) belong to the same patient.
For miRNA-specific next-generation sequencing (NGS), a total of 19 adrenocortical tissue samples were used. The cohort consisted of the following patient groups: ACTH-independent CPA, n = 7; ACTH-dependent hypertrophic adrenals of CD patients after bilateral adrenalectomy, n = 8; normal adjacent adrenal tissue from patients with pheochromocytoma as controls, n = 8. For QPCR validation, the patient groups included adrenal tissue from ACTH-independent PBMAH, n = 10, and ACTH-dependent ectopic CS, n = 3.
In the case of mRNA sequencing, a total of 23 adrenocortical tissue samples were used. This includes the following patient groups: CPA, n = 7; PBMAH, n = 8; normal adjacent adrenal tissue from patients with pheochromocytoma as controls, n = 8.
The clinical characteristics of the patients are given in Table 2. Furthermore, of the eight CPA samples in the study, three of them carried known somatic driver mutations in the PRKACA gene and in the ten PBMAH samples, two carried germline mutations in the ARMC5 gene.
Table 2. Clinical characteristics of the patient groups. Data are given as median with 25th and 75th percentiles in brackets. CPA, cortisol producing adenoma; CD, Cushing’s disease.
Table
The adrenal tissues were stored at −80 °C. Total RNA isolation was carried out from all adrenal cortex samples by an RNeasy Tissue Kit (Qiagen, Hilden, Germany). The isolated RNA was kept frozen at −80 °C until further use.

4.2. MiRNA and RNA Sequencing

RNA integrity and the absence of contaminating DNA were confirmed by Bioanalyzer RNA Nano (Agilent Technologies, Santa Clara, CA, USA) and by Qubit DNA High sensitivity kits, respectively. Sequencing libraries were prepared using the Illumina TruSeq Small RNA Library Preparation Kit. NGS was performed on 2 lanes of an Illumina HiSeq2500 (Illumina, CA, USA) multiplexing all samples (paired end read, 50 bp). The quality of sequencing reads was verified using FastQC0.11.5 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc, date last accessed: 13 March 2020) before and after trimming. Adapters were trimmed using cutadapt [40]. Reads with <15 bp and >40 bp insert sequences were discarded. An alignment of reads was performed using miRBase V21 [41,42] with sRNAbench [43]. EdgeR and DeSeq in R were used for further analyses [44,45]. MiRNAs with at least 5 raw counts per library were included. RNA-seq was performed by Qiagen, Hilden, Germany. For mRNA, sequencing was performed on Illumina NextSeq (single end read, 75 bp). Adapter and quality trimming were performed by the “Trim Reads” tool from CLC Genomics Workbench. Furthermore, reads were trimmed based on quality scores. The QC reports were generated by the “QC for Sequencing Reads” tool from CLC Genomics Workbench. Read mapping and gene quantification were performed by the “RNA-seq Analysis” tool from CLC Genomics Workbench [46]. The miRNA-seq data generated in this study have been submitted to the NCBI (PRJNA847385).

4.3. Validation of Individual miRNAs

MiRNAs and genes significantly differentially expressed by NGS were validated by QPCR. Reverse transcription of miRNA-specific cDNA was performed by using the TaqMan MicroRNA Reverse Transcription Kit (Thermo Fisher Scientific, Munich, Germany), and the reverse transcription of RNA genes was done by using the Superscript VILO cDNA synthesis Kit (Thermo Fisher Scientific, Munich, Germany). 50 ng of RNA was used for each of the reverse transcription reactions. Quantitative real-time PCR was performed using the TaqMan Fast Universal PCR Master Mix (2×) (Thermo Fisher Scientific, Munich, Germany) on a Quantstudio 7 Flex Real-Time PCR System (Thermo Fisher Scientific, Munich, Germany) in accordance with the manufacturer’s protocol. All QPCR reactions were performed in a final reaction volume of 20 μL and with 1 μL of 1:5 diluted cDNA. Negative control reactions contained no cDNA templates. Gene expression was quantified using the relative quantification method by normalization with reference gene [47]. Statistical analysis using the bestkeeper tool was used to compare and select the best reference gene with stable expression across the human adrenal samples [48]. Reference genes with significantly different Ct values (p-value < 0.01) between the samples were excluded. Furthermore, primer efficiency and the associated correlation coefficient R2 of the selected reference gene were determined by the standard curve method in serially diluted cDNA samples [49]. In the case of miRNA reference genes, miR-16-5p [48,50,51] and RNU6B [52] previously used in similar studies were compared. MiR-16-5p was found to show the most stable expression levels across the samples with a p-value of 0.452 in comparison to RNU6B which had a p-value of 0.001. In the case of RNA reference genes, PPIA [53] and GAPDH [54] were compared. Here, PPIA was found to show the most stable expression levels across the samples with a p-value of 0.019 in comparison to GAPDH which had a p-value of 0.003. Therefore, these genes were used for the normalization of miRNA and RNA expression in human adrenal samples.

4.4. Target Screening

In silico prediction of the possible miRNA targets was performed using the miRNA target database, TargetScan, and miRTarBase [19,37]. The top predicted targets were further screened based on their expression status in the RNA-seq data from the adrenocortical tissues of CPA, PBMAH, and controls (unpublished data). Pathway analyses of the targets were performed using Reactome [55] and Panther [56] online platforms. The selected downregulated targets were analyzed by QPCR in the adrenocortical samples to confirm their expression status. The successfully validated candidates were then analyzed for regulation by the miRNA using a dual luciferase assay [57].

4.5. Dual Luciferase Assay

The interaction between the predicted 3′-UTR region of Cyb5a and miR-1247-5p was detected using a luciferase activity assay. The 3′UTR sequences of Cyb5a (129 bp) containing the predicted miR-1247-5p binding sites (psiCHECK-2 Cyb5a 3′UTR WT) were cloned into the psiCHECK-2 vector (Promega, Fitchburg, WI, USA). A QuikChange Site-Directed Mutagenesis kit (Agilent Technologies, CA, USA) was used to mutate the miR-1247-5p binding site (psiCHECK-2 Cyb5a 3′UTR mutant) according to the manufacturer’s protocol. All the sequences were verified by Sanger sequencing. Then, 200 ng of the plasmid was used for each transfection. Synthetic miR-1247-5p mimics and specific oligonucleotides that inhibit endogenous miR-1247-5p (miR-1247-5p inhibitors) were purchased from Promega and 100 nmol of the molecules were used for each transfection according to the manufacturer’s protocol. For the assay, HeLa cells were seeded in 96-well plates and incubated for 24 h. The following day, cells were transfected using the following different conditions: (1) psiCHECK-2 Cyb5a 3′UTR WT + miR-1247-5p mimic; (2) psiCHECK-2 Cyb5a 3′UTR WT + miR-1247-5p inhibitor; (3) psiCHECK-2 Cyb5a 3′UTR WT + water; (4) psiCHECK-2 Cyb5a 3′UTR mutant + miR-1247-5p mimic; (5) psiCHECK-2 Cyb5a 3′UTR mutant + miR-1247-5p inhibitor; (6) psiCHECK-2 Cyb5a 3′UTR mutant + water. Forty-eight hours later, luciferase activity in the cells was measured using the dual luciferase assay system (Promega, Fitchburg, WI, USA) in accordance with the manufacturer’s instructions. Renilla luciferase activity was normalized to firefly luciferase activity. Each treatment was performed in triplicate. Any interaction between the cloned gene, Cyb5a (WT and mutant), and miR-1247-5p mimic is accompanied by a decrease in luminescence. This decrease in luminescence would not be observed when the plasmids are transfected with the miR-1247-5p inhibitor, indicating that observed luminescence differences are caused by specific interactions between the plasmid and the miR-1247-5p mimic. Transfection of the plasmid with water corrects any background interactions between the cloned gene and endogenous miRNAs in the culture.

4.6. In Vivo ACTH Stimulation

Experiments were performed on 13-week-old C57BL/6 J female mice (Janvier, Le Genest-Saint-Isle, France). Mice were intraperitoneally injected with 1 mg/kg of ACTH (Sigma Aldrich, Munich, Germany) and adrenals were collected after 10, 30, and 60 min of injections. In addition, control adrenals were collected from mice at baseline conditions (0 min). Mice were killed by cervical dislocation and adrenals were isolated, snap-frozen in liquid nitrogen, and stored at −80 °C for later RNA extraction. MiR-26a was taken as a housekeeping gene in the QPCR [58]. All mice were maintained in accordance with facility guidelines on animal welfare and approved by Landesdirektion Sachsen, Chemnitz, Germany.

4.7. Statistical Analysis and Software

R version 3.6.1 was used for the statistical analyses. To identify RNAs differentially expressed, a generalized linear model (GLM, a flexible generalization of ordinary linear regression that allows for variables that have distribution patterns other than a normal distribution) in the software package edgeR (Empirical Analysis of DGE in R) was employed to calculate p-values [45,59]. p-values were adjusted using the Benjamin–Hochberg false discovery rate (FDR) procedure [60]. Disease groups were compared using the unpaired Mann–Whitney test, and to decrease the false discovery rate a corrected p-value was calculated using the Benjamin–Hochberg method. p adjusted < 0.05 and log2 fold change >1.25 was applied as the cut-off for significance for NGS data. GraphPad Prism Version 8 was used for the statistical analysis of QPCR. To calculate differential gene expression, the dCt method (delta Ct (cycle threshold) value equals target miRNA’s Ct minus housekeeping miRNA’s Ct) was used (Microsoft Excel 2016, Microsoft, Redmond, WA, USA). For QPCR, an ANOVA test with Bonferroni correction was used [61] to assess significance; p-values < 0.05 were considered significant.

5. Conclusions

In conclusion, while comprehensive information regarding the role of miRNAs in acute and chronic phases of steroidogenesis is available, there is little known about the pathological independent role of miRNAs in the pathology of CS. In our study, we have described ACTH-independent miR-1247-5p and miR-379-5p expression in CS for the first time. Thus, by regulating different genes in the WNT signaling pathway, the miRNAs may individually contribute to the Cushing’s pathology in specific subtypes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23147676/s1.

Author Contributions

Conceptualization, S.V., A.C. and A.R.; methodology, S.V., R.Z. and M.E.; software, S.V. and M.E.; validation, R.Z., A.O., D.W. and B.W.; formal analysis, S.V.; investigation, S.V., R.Z., M.E., A.O. and D.W.; resources, A.C., B.W., M.R. and A.R.; data curation, S.V. and R.Z.; writing—original draft preparation, S.V., R.Z. and A.R.; writing—review and editing, S.S., M.R. and A.R.; visualization, S.V.; supervision, A.R.; project administration, A.R.; funding acquisition, A.C., S.S., M.R. and A.R. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by a grant from the Deutsche Forschungsgemeinschaft (DFG) (within the CRC/Transregio 205/1 “The Adrenal: Central Relay in Health and Disease”) to A.C., B.W., S.S., M.R. and A.R., and individual grant SB 52/1-1 to S.S. This work is part of the German Cushing’s Registry CUSTODES and has been supported by a grant from the Else Kröner-Fresenius Stiftung to MR (2012_A103 and 2015_A228). A.R. was supported by the FöFoLe Program of the Ludwig Maximilian University, Munich. We thank I. Shapiro, A. Parl, C. Kühne, and S. Zopp for their technical support.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Ludwig Maximilian University, Munich (protocol code 379-10, 152-10 and 20 July2021).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The miRNA-seq data generated in this study have been submitted to the NCBI (PRJNA847385).

Conflicts of Interest

The authors declare no conflict of interest.

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Hypercortisolemic Cushing’s Patients Possess a Distinct Class of Hematopoietic Progenitor Cells Leading to Erythrocytosis

Abstract

Although human cultures stimulated with dexamethasone suggest that the glucocorticoid receptor (GR) activates stress erythropoiesis, the effects of GR activation on erythropoiesis in vivo remains poorly understood.

We characterized the phenotype of a large cohort of patients with Cushing’s Disease, a rare condition associated with elevated cortisol levels. Results from hypercortisolemic patients with active Cushing’s were compared with those obtained from eucortisolemic patients after remission and from non-diseased volunteers. Active Cushing’s patients exhibit erythrocytosis associated with normal hemoglobin F levels. In addition, their blood contained elevated numbers of the GR-induced CD163+ monocytes and a unique class of CD34+ cells expressing CD110, CD36, CD133 and the GR-target gene CXCR4.

When cultured, these CD34+ cells generated similarly large numbers of immature erythroid cells in the presence and absence of dexamethasone, with raised expression of the GR-target gene GILZ. Of interest, blood from Cushing’s patients in remission maintained high numbers of CD163+ monocytes and, although their CD34+ cells had a normal phenotype, these cells were unresponsive to added dexamethasone.

Collectively, these results indicate that chronic exposure to excess glucocorticoids in vivo leads to erythrocytosis by generating erythroid progenitor cells with a constitutively active GR.

Although remission rescues the erythrocytosis and the phenotype of the circulating CD34+ cells, a memory of other prior changes is maintained in remission.

From https://haematologica.org/article/view/haematol.2021.280542

Sparrow Pharmaceuticals Presents New Clinical Trial Data Analyses on HSD-1 Inhibitor SPI-62 at the 24th European Congress of Endocrinology

Clinical trial analyses focus on the human body’s homeostatic response to potent HSD-1 inhibition by SPI-62

Results highlight that urinary free cortisol is distinct from intracellular cortisol that causes symptoms in patients with Cushing’s syndrome or autonomous cortisol secretion

PORTLAND, Ore.–(BUSINESS WIRE)–Sparrow Pharmaceuticals, an emerging, clinical-stage biopharmaceutical company developing novel, targeted therapies for disorders of glucocorticoid excess, today presented new pharmacological data during a poster session and a Rapid Communications session titled, “HPA axis modulation by a potent inhibitor indicates 11β-hydroxysteroid dehydrogenase type 1 (HSD-1) is a main source of cortisol that can bind intracellular receptors” at the 24th European Congress of Endocrinology (ECE 2022). Sparrow scientists examined the steroid hormone changes after administration of its lead therapeutic candidate, SPI-62, an HSD-1 inhibitor, to healthy adults.

“Normalized urinary free cortisol, or UFC, is a standard therapeutic target for patients with Cushing’s syndrome,” said David A. Katz, Ph.D., CSO at Sparrow Pharmaceuticals, “But that biomarker doesn’t measure the cortisol that can access intracellular receptors and cause symptoms. UFC normalization has been shown not to correlate with clinical endpoints in patients with Cushing’s syndrome. Many patients with autonomous cortisol secretion have normal UFC, yet substantial cortisol morbidity. As we conduct clinical trials for patients with those diseases, we’re in search of better ways to measure the cortisol that makes patients ill.”

The study analyzed historical clinical trial data to better characterize how SPI-62 impacts cortisol levels and the body’s homeostatic response to those changes.

Conclusions of the study include:

  • Half of hepatocellular cortisol with access to intracellular receptors is generated in healthy adults by HSD-1.
  • ACTH increase compensates for the effect of HSD-1 inhibition on systemic cortisol levels.
  • Secondary increases of androgen levels have not been associated to date with clinical consequences.
  • Large changes of the amount of cortisol that can bind intracellular receptors, and thus cause cortisol-related morbidity, can occur independently of urinary free cortisol levels.

HSD-1 converts cortisone to cortisol in tissues in which cortisol excess is associated with morbidity including liver, adipose, bone, and brain. SPI-62 is a potent HSD-1 inhibitor in clinical development for treatment of Cushing’s syndrome and autonomous cortisol secretion, and as adjunctive therapy to prednisolone in polymyalgia rheumatica. In Phase 1 clinical trials SPI-62 was generally well tolerated and associated with maximal liver and brain HSD-1 inhibition.

To register and view the abstracts, visit ECE’s website here.

From https://www.businesswire.com/news/home/20220524005465/en/Sparrow-Pharmaceuticals-Presents-New-Clinical-Trial-Data-Analyses-on-HSD-1-Inhibitor-SPI-62-at-the-24th-European-Congress-of-Endocrinology

 

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