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

Posted on November 7, 2022 by MaryO

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+Vn−1)2∗(Cn−Cn−1)

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. (a–g) 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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Evaluation of Ketoconazole As a Treatment for Cushing’s Disease in a Retrospective Cohort

Posted on October 26, 2022 by MaryO

Objective: The first-line treatment for Cushing’s disease is transsphenoidal surgery, after which the rates of remission are 60 to 80%, with long-term recurrence of 20 to 30%, even in those with real initial remission. Drug therapies are indicated for patients without initial remission or with surgical contraindications or recurrence, and ketoconazole is one of the main available therapies. The objective of this study was to evaluate the safety profile of and the treatment response to ketoconazole in Cushing’s disease patients followed up at the endocrinology outpatient clinic of a Brazilian university hospital.

Patients and methods: This was a retrospective cohort of Cushing’s disease patients with active hypercortisolism who used ketoconazole at any stage of follow-up. Patients who were followed up for less than 7 days, who did not adhere to treatment, or who were lost to follow-up were excluded.

Results: Of the 172 Cushing’s disease patients who were followed up between 2004 and 2020, 38 received ketoconazole. However, complete data was only available for 33 of these patients. Of these, 26 (78%) underwent transsphenoidal surgery prior to using ketoconazole, five of whom (15%) had also undergone radiotherapy; seven used ketoconazole as a primary treatment. Ketoconazole use ranged from 14 days to 14.5 years. A total of 22 patients had a complete response (66%), three patients had a partial response (9%), and eight patients had no response to treatment (24%), including those who underwent radiotherapy while using ketoconazole. Patients whose hypercortisolism was controlled or partially controlled with ketoconazole had lower baseline 24-h urinary free cortisol levels than the uncontrolled group [times above the upper limit of normal: 0.62 (SD, 0.41) vs. 5.3 (SD, 8.21); p < 0.005, respectively] in addition to more frequent previous transsphenoidal surgery (p < 0.04). The prevalence of uncontrolled patients remained stable over time (approximately 30%) despite ketoconazole dose adjustments or association with other drugs, which had no significant effect. One patient received adjuvant cabergoline from the beginning of the follow-up, and it was prescribed to nine others due to clinical non-response to ketoconazole alone. Ten patients (30%) reported mild adverse effects, such as nausea, vomiting, dizziness, and loss of appetite. Only four patients had serious adverse effects that warranted discontinuation. There were 20 confirmed episodes of hypokalemia among 10/33 patients (30%).

Conclusion: Ketoconazole effectively controlled hypercortisolism in 66% of Cushing’s disease patients, being a relatively safe drug for those without remission after transsphenoidal surgery or whose symptoms must be controlled until a new definitive therapy is carried out. Hypokalemia is a frequent metabolic effect not yet described in other series, which should be monitored during treatment.

Introduction

Cushing’s disease (CD) results from a pituitary tumor that secretes adrenocorticotropic hormone (ACTH), which leads to chronic hypercortisolism. It is a potentially fatal disease with high morbidity and a mortality rate of up to 3.7 times than that of the general population (1–4) associated to several clinical–metabolic disorders caused by excess cortisol and/or loss of circadian rhythm (5). In general, its management is a challenge even in reference centers (6, 7).

Transsphenoidal surgery (TSS), the treatment of choice for CD, results in short-term remission in 60 to 80% of patients (8). However, recurrence rates of 20 to 30% are found in long-term follow-up, even in those with clear initial remission (9). Drug therapies can help control excess cortisol in patients without initial remission, in cases of recurrence, and in those with contraindications or high initial surgical risk (10).

Nevertheless, specific drugs that act on the pituitary adenoma, which could directly treat excess ACTH, have a limited effect, and only pasireotide is approved for this purpose in Brazil (11, 12). In this scenario, adrenal steroidogenesis blockers are important. One such off-label medication is the antifungal drug ketoconazole, a synthetic imidazole derivative that inhibits the enzymes CYP11A1, CYP17, CYP11B2, and CYP11B1. Because of its hepatotoxicity and the availability of other drugs, it has been withdrawn from the market in several countries (13). In Europe, it is still approved for use in CD, although in the United States, it is recommended for off-label use almost in CD (14–16). Due to the potential benefits for hypercortisolism, ketoconazole has been replaced by levoketoconazole, which the European Union has recently approved for CD with a lower expected hepatotoxicity (17).

Thus, when adrenal inhibitors are used as an alternative treatment for CD, information about the outcomes of drugs such as ketoconazole are important. Clinical studies on these effects in CD are scarce, mostly retrospective, multicenter, or from developed countries (14, 18). A recent meta-analysis on the therapeutic modalities for CD included only four studies (246 patients) that evaluated urinary cortisol response as a treatment outcome and eight studies (366 patients) describing the prevalence of some side effects: change in transaminase activity, digestive symptoms, skin rash, and adrenal insufficiency. Hypokalemia was not mentioned in this meta-analysis (19).

The objective of this study was to evaluate the safety profile of and treatment response to ketoconazole in CD patients followed during a long term in the endocrinology outpatient clinic of a Brazilian university hospital.

Patients and methods

Patients

We retrospectively evaluated 38 patients (27 women) diagnosed with CD. These patients, whose treatment included ketoconazole at any time between 2004 and 2020, are part of a prospective cohort series from the Hospital de Clínicas de Porto Alegre neuroendocrinology outpatient clinic.

The diagnostic criteria for hypercortisolism were based on high 24-h urinary free cortisol levels (24-h UFC) in at least two samples, non-suppression of serum cortisol after low-dose dexamethasone testing (>1.8 µg/dl), and/or loss of cortisol rhythm (midnight serum cortisol >7.5 µg/dl or midnight salivary cortisol >0.208 nmol/L). CD was diagnosed by normal or elevated ACTH levels, evidence of pituitary adenoma >0.6 cm on magnetic resonance image (MRI), and ACTH central/periphery gradient on inferior petrosal sinus catheterization when MRI was normal or showed an adenoma <0.6 cm.

CD was considered to be in remission after the improvement of hypercortisolism symptoms or clinical signs of adrenal insufficiency, associated with serum cortisol within reference values, normalization of 24-h UFC and/or serum cortisol <1.8 μg/dl at 8 am after 1 mg dexamethasone overnight, and/or normalization of midnight serum or salivary cortisol. In patients with active disease, to evaluate the ketoconazole treatment response, 24-h UFC was used as a laboratory parameter, as recommended in similar publications (14, 16, 20, 21), but in some cases, we considered elevated late night salivary cortisol and/or 1 mg dexamethasone overnight cortisol (even with normal 24-h UFC), given the greater assessment sensitivity seen through these two methods in the detection of early recurrence when compared with 24-h UFC (22).

Inclusion criteria

We included patients with CD and active hypercortisolism who used ketoconazole either as primary treatment, after TSS without hypercortisolism remission, or after a recurrence.

Exclusion criteria

We excluded patients with CD and active hypercortisolism who used ketoconazole but had <7 days of follow-up, irregular outpatient follow-up, treatment non-adherence, and incomplete medical records or those who were lost to follow-up.

Evaluated parameters

Prior to ketoconazole treatment, all patients underwent an assessment of pituitary function and hypercortisolism, including serum cortisol, ACTH, 24-hour UFC, cortisol suppression after 1 mg dexamethasone overnight, midnight serum cortisol, and/or midnight salivary cortisol. The evaluated parameters were sex, age at diagnosis, weight, height, prevalence and severity of hypertension and DM, pituitary tumor characteristics, prior treatment (surgery, radiotherapy, or other medications), symptoms at disease onset, biochemical tests (renal function, hepatic function, and lipid profile), number of medications used to treat associated comorbidities, data on medication tolerance, and reasons for discontinuation, when necessary.

The clinical parameters observed during treatment were control of blood pressure and hyperglycemia, anthropometric measurements (weight, height, and body mass index), jaundice, and any other symptoms or adverse effects reported by patients.

The biochemical evaluation included fasting glucose, glycated hemoglobin, lipid profile (total cholesterol, high-density lipoprotein, low-density lipoprotein, and triglycerides), markers of liver damage (transaminases, bilirubin, gamma-glutamyl transferase, and alkaline phosphatase), electrolytes (sodium and potassium), and renal function (creatinine and urea). Hypecortisolism was accessed preferentially by 24-h UFC, however, late-night salivary cortisol and cortisol after 1 mg overnight dexamethasone could also be used.

Study design

This retrospective cohort study included patients with CD who were followed up at the Hospital de Clínicas de Porto Alegre Endocrinology Division, with their medical records from the first outpatient visit and throughout clinical follow-up collected. This study was approved by the Hospital de Clínicas de Porto Alegre Research Ethics Committee (number 74555617.0.0000.5327).

Outcomes

Hypercortisolism was considered controlled when the 24-h UFC and/or late-night salivary cortisol (LNSC) and/or overnight 1 mg dexamethasone suppression test (DST) levels were normalized in at least two consecutive assessments. Hypercortisolism was considered partially controlled when there was a 50% over-reduction in 24-h UFC and/or LNSC and/or DST levels but still above normal. A reduction lower than 50% in these parameters was considered as non-response.

We also assessed the ketoconazole doses that resulted in 24-h UFC normalization, maximum dose, medication tolerance, adverse effects, and changes in liver, kidney, and biochemical function. Due to the characteristics of this study, these outcomes were periodically evaluated in all patient consultations, which occurred usually every 2 to 4 months.

Data collection

This retrospective cohort evaluated outpatient medical records and any tests indicated by the attending physician as a pragmatic study. Ketoconazole use followed the department’s care protocol, which is based on national and international guidelines (4), and all patients received a similar care routine: the recommended initial prescription was generally taken in two to six doses at 100 to 300 mg/day. It was then increased by 200 mg every 2 to 4 months until hypercortisolism was controlled or side effects developed, especially those related to liver function. The maximum prescription was 1,200 mg/day. Clinical follow-up of these patients was performed 30 days after starting the medication and every 2–4 months thereafter (23).

Clinical, anthropometric, laboratory, and other exam data were collected through a review of the hospital’s electronic medical records for the entire follow-up period. Data from the first and last consultation were considered in the final analysis of all parameters.

Statistical analysis

Baseline population characteristics were described as mean and standard deviation (SD) or median with interquartile ranges (25–75) for continuous variables. The chi-square test was used to compare qualitative variables, and Student’s t-test or ANOVA was used to compare the quantitative variables. The Mann–Whitney U-test was used for unpaired data. P-values <0.05 were considered significant. Statistical analysis was performed in SPSS 18.0 (SPSS Inc., Chicago, IL, USA) and R package geepack 1.3-1.

Results

Treatment with ketoconazole was indicated for 41 of the 172 CD patients. In 3/41 patients, ketoconazole was unallowed due to concomitant liver disease, and 38 received ketoconazole during CD treatment between 2004 and 2020. Of these, five were excluded due to insufficient data to determine the response to ketoconazole (short treatment time, irregular follow-up, incomplete medical records, or lost to follow-up). The baseline characteristics of every sample are shown in Table 1. Thus, 33/41 patients were included in the final analysis. The patients were predominantly women (84.2%) and white (89.5%); 11 had microadenoma, 15 had macroadenoma, and 11 had no adenoma visualized. In 12/33 patients, pituitary imaging was not performed immediately before starting ketoconazole. Hypertension was observed in 26 patients (78%) and DM in 12 patients (36%). The mean age at CD diagnosis was 31.7 years.

Table 1
www.frontiersin.orgTABLE 1 Baseline clinical data of Cushing’s disease patients treated with ketoconazole.

Of the 33 patients with complete data, 26 (78%) underwent TSS prior to starting ketoconazole, five of whom (15%) had also undergone radiotherapy. Thus, seven patients used ketoconazole as primary treatment since performing a surgical procedure was impossible at that time. Of these, four had no response to ketoconazole, one had a partial response, and two had a complete response. At follow-up, four of these patients underwent their first TSS, and three continued the ketoconazole therapy, achieving full UFC control. Among those who used ketoconazole after TSS (n = 26), 20 had a complete response, two had a partial response, and four had no response. Figure 1 shows the study flow chart and patient distribution throughout the treatment.

Figure 1
www.frontiersin.orgFIGURE 1 Flowchart of ketoconazole treatment in Cushing’s disease patients.

Individual patient data are described in Table 2. The duration of ketoconazole use ranged from 14 days (in one patient who used it pre-TSS) to 14.5 years. The total follow-up time of the 22 patients with controlled CD ranged from 3 months to 14.5 years, with a mean of 5.33 years and a median of 4.8 years.

Table 2
www.frontiersin.orgTABLE 2 Individual data.

Therapeutic response

Relative therapeutic response data are described in Table 3. Patients whose hypercortisolism was controlled or partially controlled with ketoconazole had lower baseline 24-h UFC than the uncontrolled group [times above the upper limit of normal: 0.62 (SD, 0.41) vs. 5.3 (SD, 8.21); p < 0.005, respectively], in addition to more frequent prior TSS (p < 0.04). In some patients (4/33), 24-h UFC was in the normal range at the beginning of ketoconazole therapy, but they were prescribed with the medication due to the clinical recurrence of CD associated to cortisol non-suppression after 1 mg dexamethasone overnight and/or abnormal midnight salivary or serum cortisol.

Table 3
www.frontiersin.orgTABLE 3 Baseline characteristics of Cushing’s disease patients according to therapeutic response to ketoconazole.

Figure 2 shows that the prevalence of uncontrolled patients remained stable over time (approximately 30%) despite dose adjustments or association with other drugs, which led to no differences. When analyzing only the results of the last follow-up visit (eliminating fluctuations during follow-up), 22 patients had a complete response (66%), three patients had a partial response (9%), and eight patients had no response to ketoconazole treatment (24%), which includes patients who underwent radiotherapy during ketoconazole treatment.

Figure 2
www.frontiersin.orgFIGURE 2 Prevalence of controlled hypercortisolism during follow-up of Cushing’s disease patients treatesd with ketoconazole.

During follow-up, no significant differences were found in blood pressure control or in dehydroepiandrosterone sulfate, cortisol, ACTH, or glucose levels. Worsening of hypertension control was observed in association with hypokalemia in some cases, as described in side effects. The ketoconazole doses ranged from 100 to 1,200 mg per day, and there were no significant dose or response differences between the groups (Table 4). Figure 3 shows the patients, their dosages, and 24-h UFC control at the first and last consultation, showing a trend toward hypercortisolism reduction in approximately 70% of the cohort (25 of 33). Only four patients used doses lower than 300 mg at the end of follow-up. One of them used before TSS and suspended its use after surgery. One patient, who has already undergone radiotherapy, discontinued ketoconazole due to intolerance, despite adequate control of hypercortisolism. Another one, who had also undergone radiotherapy, was lost to follow-up when it was controlled using 100 mg daily, and one remained controlled using 200 mg, without previous radiotherapy.

Table 4
www.frontiersin.orgTABLE 4 Final dose of ketoconazole used in patients with Cushing’s disease.

Figure 3
www.frontiersin.orgFIGURE 3 First and last consultation 24çhour UFC results vs. ketoconazole dosage in Cushing’s disease patients.

Side effects

Regarding adverse effects (Table 5), there was no significant difference between the controlled/partially controlled group and the uncontrolled group regarding liver enzyme changes or drug intolerance. Mild adverse effects, including nausea, vomiting, dizziness, and loss of appetite, occurred in 10 patients (30%). Only four patients had serious adverse effects that warranted discontinuing the medication. In two cases, ketoconazole was discontinued due to a significantly acute increase in liver enzymes (drug-induced hepatitis) during the use of 400 and 800 mg of ketoconazole. Non-significant elevation of transaminases (up to three times the normal value) was observed in three cases. A slight increase in gamma-glutamyltransferase occurred in six patients. In these nine patients with elevated liver markers, the daily dose ranged from 400 to 1,200 mg. None of those with mild increases in liver markers needed to discontinue ketoconazole.

Table 5
www.frontiersin.orgTABLE 5 Adverse effects of ketoconazole in Cushing’s disease patients treated with ketoconazole.

One female patient developed pseudotumor cerebri syndrome, which was treated with acetazolamide. She did not need to discontinue ketoconazole, having used it for more than 10 years without new side effects and achieving complete control of hypercortisolism (24). Another patient became pregnant during follow-up while using the medication, but no maternal or fetal complications occurred (25).

Hypokalemia was also observed during follow-up. Twenty episodes of reduced potassium levels occurred in 10 patients over the course of treatment. Of these episodes, six occurred in controlled patients, three in partially controlled patients, and 11 in uncontrolled patients (Table 6). The hypokalemia was managed with spironolactone (25 to 100 mg) and oral potassium supplementation.

Table 6
www.frontiersin.orgTABLE 6 Characteristics of Cushing’s disease patients who developed hypokalemia during ketoconazole treatment.

Ketoconazole and associations

Of the patients who used an association of cabergoline and ketoconazole, one did so since the beginning of follow-up, while another nine were prescribed cabergoline during follow-up due to non-response to ketoconazole alone. Of these 10 patients, two did not start the medication due to problems in obtaining the drug. Thus, in two of the nine patients on the maximum tolerated dose of ketoconazole or who could not tolerate a higher dose due to hepatic enzymatic changes, 1.5–4.5 mg of cabergoline per week was associated. In patients not controlled with ketoconazole plus cabergoline, mitotane (two patients) or pasireotide (two patients) was added. Only two of nine patients responded to the combination of cabergoline and ketoconazole. Data on these associations are shown in Table 7.

Table 7
www.frontiersin.orgTABLE 7 Effects of associating cabergoline with ketoconazole in Cushing’s disease patients.

Considering that one of the indications for the treatment of hypercortisolism may be complementary to radiotherapy, we analyzed the eight patients who underwent radiotherapy after transsphenoidal surgery. In these patients, doses of ketoconazole from 200 to 1,200 mg were used, and in six patients there was a normalization of the UFC in 1 to 60 months of treatment. Thus, the association of ketoconazole with radiotherapy was effective in normalizing the 24-h UFC in 75% of cases.

Clinical follow-up

New therapeutic approaches were attempted in some patients during follow-up: radiotherapy (eight patients), new TSS (five patients), and bilateral adrenalectomy (four patients). At the end of this analysis, 11 patients remained on ketoconazole, all with controlled hypercortisolism. Among the 11 patients who were not fully controlled by the last visit, five were using ketoconazole as pre-TSS therapy and underwent TSS as soon as possible, while three others underwent radiotherapy and two underwent bilateral adrenalectomy. One patient was lost to follow-up.

Discussion

According to the current consensus about CD, drug treatment should be reserved for patients without remission after TSS, those who cannot undergo surgical treatment, or those awaiting the effects of radiotherapy (4, 16). Drugs available in this context may act as adrenal steroidogenesis blockers (ketoconazole, osilodrostat, metyrapone, mitotane, levoketoconazole, and etomidate), in pituitary adenoma (somatostatinergic receptor ligands—pasireotide), dopamine receptor agonists (cabergoline), or glucocorticoid receptor blockers (mifepristone) (16, 26). Among these alternatives, the drug of choice still cannot be determined. Thus, the best option must be established individually, considering aspects such as remission potential, safety profile, availability, cost, etc. (16, 27, 28).

For over 30 years, ketoconazole has been prescribed off-label for CD patients with varied rates of remission of hypercortisolism, and it can be used in monotherapy or associated with other drugs (29, 30). The Brazilian public health system does not provide drugs for the treatment of CD, and among medications with a better profile for controlling hypercortisolism, such as osilodrostat, levoketoconazole, and pasireotide, only pasireotide has been approved by the national regulatory authority (ANVISA). Due to such pragmatic considerations, ketoconazole is among the most commonly used drugs in our health system, whether recently associated or not with cabergoline (7).

In this cohort, the most prevalent response type was complete (66%). Since 75% of the CD patients who used ketoconazole had a complete or partial response, there was a clear trend towards improvement in hypercortisolism. When only those who used ketoconazole post-TSS were evaluated, the rate of control increased to 76%. We found that patients with a higher initial 24-h UFC tended to have less control of excess cortisol, a difference that was not observed when analyzing ketoconazole dose or follow-up time.

In our series and at the prescribed doses, the combination of cabergoline and ketoconazole was not effective in the management of hypercortisolism since only two of nine patients (22%) had their 24-hour UFC normalized. However, it should be observed that this association was used in patients who had more severe CD and, consequently, were less likely to have a favorable response. The effects of cabergoline in CD patients remain controversial, although some studies have shown promising responses (31, 32).

Previous reviews found that the efficacy of ketoconazole for hypercortisolism control was quite heterogeneous, ranging from 14 to 100% in 99 patients (33, 34). Our cohort’s response rate was lower than that of Sonino et al. (89%) (20) but higher than that of a multicenter cohort by Castinetti et al. (approximately 50%) (14). Regarding other smaller series (35–37) our results reinforce some findings that demonstrate a percentage of control greater than 50% of the cases.

Our analyses showed a trend toward a response that continued, with some oscillations, over time. The rate of uncontrolled patients remained stable over time (approximately 30%), regardless of association with other drugs (cabergoline, mitotane, or pasireotide) or dose adjustments. Speculatively, it would appear that patients who respond to ketoconazole treatment would show some type of response as soon as therapy begins.

Our cohort has the longest follow-up time of any study on ketoconazole use in CD, nearly 15 years. Our results demonstrate that patients who benefit from ketoconazole (i.e., control of hypercortisolism and associated comorbidities) can safely use it for a long term since those who did not experience liver enzyme changes at the beginning of treatment also had no long-term changes.

Another relevant information for clinical practice is the result of treatment with ketoconazole associated with radiotherapy, which demonstrated normalizing the 24-h UFC in 75% of cases, a finding that reinforces the use of this therapeutic combination, especially in cases that are more resistant to different treatment modalities.

As described in the literature, adverse effects, such as nausea, vomiting, dizziness, headache, loss of appetite, and elevated transaminases, are relatively frequent (38). In our cohort, 10 patients (30%) had mild adverse effects, and four (12%) had more serious adverse effects requiring discontinuation. In other studies, up to 20% of patients required discontinuation due to side effects (14). We documented 20 episodes of hypokalemia during ketoconazole treatment, some with worsening blood pressure control. In most cases, hypokalemia has occurred in association with the use of diuretic drugs, which may have potentiated potassium spoliation, reinforcing the need of stringent surveillance in hypertensive Cushing’s disease patients using this combination. It can also result from the enzymatic blockade that could lead to the elevation of adrenal mineralocorticoid precursors (pex. deoxycorticosterone), with consequent sodium retention and worsening hypertension. Although it has not been analyzed in other series with ketoconazole, this side effect has been observed in patients who received other adrenal-blocking drugs, such as osilodrostat and metyrapone (16). This alteration seems to be transient in some patients; in our series, it was managed by suspending drugs that could worsen hypokalemia and introducing spironolactone and/or potassium supplementation. Hypokalemia may also result from continuing intense adrenal stimulation by ACTH and changes in the activity of the 11-beta-hydroxysteroid dehydrogenase enzyme, which increase the mineralocorticoid activity of cortisol, as observed in patients with severe hypercortisolism in uncontrolled CD (39). Hypogonadism occurred in one male patient. In two adolescent patients (one female and one male), hypercortisolism was effectively controlled without altering the progression of puberty. As described in other cohorts, this effect was expected due to the high doses, which block adrenal and testicular androgen production (20).

Thus, our findings confirm previous reports in the literature and add important information about the side effects and safety of long-term ketoconazole use in CD treatment. Our data reinforce the current recommendations about ketoconazole for recurrent cases or those refractory to surgery, including proper follow-up by an experienced team specializing in evaluating clinical and biochemical responses and potential adverse effects (7, 18, 40). Despite the severity of many of our CD patients, no ketoconazole-related death occurred during follow-up, including long-term observation. On the other hand, no patient progressed to definitive remission of hypercortisolism, even after many years of treatment with ketoconazole.

Conclusions

In our cohort of patients, ketoconazole proved to be an effective and safe alternative for CD treatment, although it can produce side effects that require proper identification and management, allowing effective long-term treatment. We found side effects that have been rarely described in the literature, including hypokalemia and worsening hypertension, which require specific care and management. Thus, ketoconazole is an effective alternative for CD patients who cannot undergo surgery, who do not achieve remission after pituitary surgery, or who have recurrent hypercortisolism.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors without undue reservation.

Ethics statement

The studies involving human participants were reviewed and approved by the Hospital de Clínicas de Porto Alegre Research Ethics Committee. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Author contributions

CV and MAC created the research format. CV, RBM, and MCBC realized the search on medical records. CV performed the statistical analysis. MAC, ACVM, and TCR participated in the final data review and discussion. ACVM participated in the final data review and discussion as volunteer collaborator. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by the “Coordenação de Aperfeiçoamento de Pessoal de Nı́vel Superior” (CAPES), Ministry of Health – Brazil, through a PhD scholarship; and the Research Incentive Fund (FIPE) of Hospital de Clı́nicas de Porto Alegre.

Acknowledgments

The authors would like to thank the HCPA Research and Graduate Studies Group (GPPG) for the statistical technical support provided by Rogério Borges. We also thank the Research Incentive Fund of Hospital de Clínicas de Porto Alegre and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), by funds applied. We also thank the Graduate Program in Endocrinology and Metabolism (PPGEndo UFRGS) for all the support in the preparation of this research.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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40. Varlamov EV, Han AJ, Fleseriu M. “Updates in adrenal steroidogenesis inhibitors for cushing’s syndrome – a practical guide,”. Best Pract Res Clin Endocrinol Metab (2021) 35(1):101490. doi: 10.1016/j.beem.2021.101490

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Keywords: Cushing’s disease, Cushing’s syndrome, hypercortisolism, treatment, ketoconazole

Citation: Viecceli C, Mattos ACV, Costa MCB, Melo RBd, Rodrigues TdC and Czepielewski MA (2022) Evaluation of ketoconazole as a treatment for Cushing’s disease in a retrospective cohort. Front. Endocrinol. 13:1017331. doi: 10.3389/fendo.2022.1017331

Received: 11 August 2022; Accepted: 06 September 2022;
Published: 07 October 2022.

Edited by:

Luiz Augusto Casulari, University of Brasilia, Brazil

Reviewed by:

Juliana Drummond, Federal University of Minas Gerais, Brazil
Monalisa Azevedo, University of Brasilia, Brazil

Copyright © 2022 Viecceli, Mattos, Costa, Melo, Rodrigues and Czepielewski. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Mauro Antonio Czepielewski, maurocze@terra.com.br

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

From https://www.frontiersin.org/articles/10.3389/fendo.2022.1017331/full

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Medications Used to Treat Cushing’s

Posted on June 13, 2022 by MaryO

Dr. Friedman uses several medications to treat Cushing’s syndrome that are summarized in this table. Dr. Friedman especially recommends ketoconazole. An in-depth article on ketoconazole can be found on goodhormonehealth.com.

 

 

 Drug How it works Dosing Side effects
Ketoconazole  (Generic, not FDA approved in US) blocks several steps in cortisol biosynthesis Start 200 mg at 8 and 10 PM, can up titrate to 1200 mg/day • Transient increase in LFTs
• Decreased testosterone levels
• Adrenal insufficiency
Levoketoconazole (Recorlev) L-isomer of Ketoconazole Start at 150 mg at 8 and 10 PM, can uptitrate up to 1200 mg nausea, vomiting, increased blood pressure, low potassium, fatigue, headache, abdominal pain, and unusual bleeding
Isturisa (osilodrostat) blocks 11-hydroxylase 2 mg at bedtime, then go up to 2 mg at 8 and 10 pm, can go up to 30 mg  Dr. Friedman often gives with spironolactone or ketoconazole. • high testosterone (extra facial hair, acne, hair loss, irregular periods)  • low potassium
• hypertension
Cabergoline (generic, not FDA approved) D2-receptor agonist 0.5 to 7 mg • nausea,  • headache  • dizziness
Korlym (Mifepristone) glucocorticoid receptor antagonist 300-1200 mg per day • cortisol insufficiency (fatigue, nausea, vomiting, arthralgias, and headache)
• increased mineralocorticoid effects (hypertension, hypokalemia, and edema
• antiprogesterone effects (endometrial thickening)
Pasireotide (Signafor) somatostatin receptor ligand 600 μg or 900 μg twice a day Diabetes, hyperglycemia, gallbladder issues

For more information or to schedule an appointment with Dr. Friedman, go to goodhormonehealth.com

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Synergistic Cortisol Suppression by Ketoconazole–Osilodrostat Combination Therapy

Posted on January 31, 2022 by MaryO

Abstract

Summary

Here, we describe a case of a patient presenting with adrenocorticotrophic hormone-independent Cushing’s syndrome in a context of primary bilateral macronodular adrenocortical hyperplasia. While initial levels of cortisol were not very high, we could not manage to control hypercortisolism with ketoconazole monotherapy, and could not increase the dose due to side effects. The same result was observed with another steroidogenesis inhibitor, osilodrostat. The patient was finally successfully treated with a well-tolerated synergitic combination of ketoconazole and osilodrostat. We believe this case provides timely and original insights to physicians, who should be aware that this strategy could be considered for any patients with uncontrolled hypercortisolism and delayed or unsuccessful surgery, especially in the context of the COVID-19 pandemic.

Learning points

  • Ketoconazole–osilodrostat combination therapy appears to be a safe, efficient and well-tolerated strategy to supress cortisol levels in Cushing syndrome.
  • Ketoconazole and osilodrostat appear to act in a synergistic manner.
  • This strategy could be considered for any patient with uncontrolled hypercortisolism and delayed or unsuccessful surgery, especially in the context of the COVID-19 pandemic.
  • Considering the current cost of newly-released drugs, such a strategy could lower the financial costs for patients and/or society.

Background

Untreated or inadequately treated Cushing’s syndrome (CS) is a morbid condition leading to numerous complications. The latter ultimately results in an increased mortality that is mainly due to cardiovascular events and infections. The goal of the treatment with steroidogenesis inhibitors is normalization of cortisol production allowing the improvement of comorbidities (1). Most studies dealing with currently available steroidogenesis inhibitors used as monotherapy reported an overall antisecretory efficacy of roughly 50% in CS. Steroidogenesis inhibitors can be combined to better control hypercortisolism. To the best of our knowledge, we report here for the first time a patient treated with a ketoconazole–osilodrostat combination therapy.

Case presentation

Here, we report the case of Mr D.M., 53-years old, diagnosed with adrenocorticotrophic hormone (ACTH)-independent CS 6 months earlier. At diagnosis, he presented with resistant hypertension, hypokalemia, diabetes mellitus, easy bruising, purple abdominal striae and major oedema of the lower limbs.

Investigations

A biological assessment was performed, and the serum cortisol levels are depicted in Table 1. ACTH levels were suppressed (mean levels 1 pg/mL). Mean late-night salivary cortisol showed a four-fold increase (Table 2), and mean 24 h-urinary cortisol showed a two-fold increase. Serum cortisol was 1000 nmol/L at 08:00 h after 1 mg dexamethasone dose at 23:00 h. The rest of the adrenal hormonal workup was within normal ranges (aldosterone: 275 pmol/L and renin: 15 mIU/L). An adrenal CT was performed (Fig. 1) and exhibited a 70-mm left adrenal mass (spontaneous density: 5 HU and relative washout: 65%) and a 45-mm right adrenal mass (spontaneous density: −2 HU and relative washout: 75%). The case was discussed in a multidisciplinary team meeting, which advised to perform 18F-FDG PET-CT and 123I-Iodocholesterol scintigraphy before considering surgery. A genetic screening was performed, testing for ARMC5 and PRKAR1A pathogenic variants.

Figure 1View Full Size
Figure 1
Adrenal CT depicting the bilateral macronodular adrenocortical hyperplasia.

Citation: Endocrinology, Diabetes & Metabolism Case Reports 2021, 1; 10.1530/EDM-21-0071

Table 1Serum cortisol levels at diagnosis (A), using ketoconazole monotherapy (B), using osilodrostat monotherapy (C) and using osilodrostat–ketoconazole combination therapy (D).

Serum cortisol (nmol/L) 08:00 h 24:00 h 16:00 h 20:00 h 12:00 h 16:00 h
A. At diagnosis 660 615 716 566 541 561
B. Ketoconazole monotherapy 741 545 502 224 242 508
C. Osilodrostat monotherapy 658 637 588 672 486 692
D. Osilodrostat–ketoconazole combination 436 172 154 103 135 274
Table 2Salivary cortisol levels at diagnosis (A), using ketoconazole monotherapy (B), using osilodrostat monotherapy (C) and using osilodrostat-ketoconazole combination therapy (D).

Salivary cortisol (nmol/L) 23:00 h 12:00 h 13:00 h Mean
A. At diagnosis 47 62 38 49
B. Ketoconazole monotherapy 20 15 21 18
C. Osilodrostat monotherapy 85 90 56 77
D. Osilodrostat–ketoconazole combination 10 14 9 11

Treatment

As this condition occurred during the COVID-19 pandemic, it was decided to first initiate steroidogenesis inhibitors to lower the patient’s cortisol levels. Initially, ketoconazole was initiated and uptitrated up to 1000 mg per day based on close serum cortisol monitoring, with a three-fold increase of liver enzymes and poor control of cortisol levels (Table 1). In the absence of biological efficacy, ketoconazole was replaced by osilodrostat, which was gradually increased up to 30 mg per day (10 mg at 08:00 h and 20 mg at 20:00 h) without reaching normal cortisol levels (Table 1) and with slightly increased blood pressure levels. Considering the lack of efficacy of anticortisolic drugs used as monotherapy, we combined osilodrostat (30 mg per day) to ketoconazole (600 mg per day), that is, at the last maximal tolerated dose as monotherapy of each drug.

Outcome

This combination of steroidogenesis inhibitors achieved a good control in cortisol levels, mimicking a physiological circadian rhythm (Table 1D). The patient did not exhibit any side effect and the control of cortisol levels resulted in a rapid improvement of hypertension, kalemia, diabetes control and disappearance of lower limbs oedema. The patient underwent a 18F-FDG PET-CT that did not exhibit any increased uptake in both adrenal masses and a 123I-Iodocholesterol scintigraphy exhibiting a highly increased uptake in both adrenal masses, predominating in the left adrenal mass (70 mm). Unilateral adrenalectomy of the larger mass was then performed, and as the immediate post-operative serum cortisol level was 50 nmol/L, hydrocortisone was administered at a dose of 30 mg per day, with a stepwise decrease to 10 mg per day over 3 months. Pathological examination exhibited macronodular adrenal hyperplasia with a 70-mm adreno cortical adenoma (WEISS score: 1 and Ki67: 1%). The genetic screening exhibited a c.1908del p.(Phe637Leufs*6) variant of ARMC5 (pathogenic), located in exon 5. The patient has no offspring and is no longer in contact with the rest of his family.

Discussion

The goal of the treatment with steroidogenesis inhibitors is normalization of cortisol production allowing the improvement of comorbidities (1). Most studies dealing with currently available steroidogenesis inhibitors used as monotherapy reported an overall antisecretory efficacy of roughly 50% in CS. This rate of efficacy was probably underestimated in retrospective studies due to the lack of adequate uptitration of the dose; For example, the median dose reported in the French retrospective study on ketoconazole was only 800 mg/day, while 50% of the patients were uncontrolled at the last follow-up (2).

Steroidogenesis inhibitors can be combined to better control hypercortisolism. Up to now, such combinations, mainly ketoconazole and metyrapone, were mainly reported in patients with severe CS (median urinary-free Cortisol (UFC) 30- to 40-fold upper-limit norm (ULN)) and life-threatening comorbidities (3, 4). Normal UFC was reported in up to 86% of these patients treated with high doses of ketoconazole and metyrapone. Expected side effects (such as increased liver enzymes for ketoconazole or worsened hypertension and hypokalemia for metyrapone) were reported in the majority of the patients. The fear of these side effects probably explains the lack of uptitration in previous reports. Combination of steroidogenesis inhibitors has previously been described by Daniel et al. in the largest study reported on the use of metyrapone in CS; 29 patients were treated with metyrapone and ketoconazole or mitotane, including 22 in whom the second drug was added to metyrapone monotherapy because of partial efficacy or adverse effects. The final median metyrapone dose in patients controlled with combination therapy was 1500 mg per day (5).

Combination of adrenal steroidogenesis inhibitors should not be reserved to patients with severe hypercortisolism. In the case shown here, the association was highly effective in terms of secretion, using lower doses than those applied as a single treatment, but without the side effects previously observed with higher doses of each treatment used as a monotherapy. To our knowledge, the association of ketoconazole and osilodrostat had never been reported. Ketoconazole blocks several enzymes of the adrenal steroidogenesis such as CYP11A1, CYP17, CYP11B2 (aldosterone synthase) and CYP11B1 (11-hydroxylase), leading to decreased cortisol and occasionally testosterone concentrations. Though liver enzymes increase is not dose-dependent, it usually happens at doses exceeding 400–600 mg per day (2). Osilodrostat blocks CYP11B1 and CYP11B2; a combination should thus allow for a complete blockade of these enzymes that are necessary for cortisol secretion. Short-term side effects such as hypokalemia and hypertension are similar to those observed with metyrapone, due to increased levels of the precursor deoxycorticosterone, correlated with the dose of osilodrostat (6). As for our patient, the occurrence of side effects should not lead to immediately switch to another drug, but rather to decrease the dose and add another cortisol-lowering drug. Moreover, considering the current cost of newly-released drugs such a strategy could lower financial costs for patients and/or society.

Another point to take into account is the current COVID-19 pandemic, for which, as recently detailed in experts’ opinion (7), the main aim is to reach eucortisolism, whatever the way. Indeed patients presenting with CS usually also present with comorbidities such as obesity, hypertension, diabetes mellitus and immunodeficiency (8). Surgery, which represents the gold standard strategy in the management of CS (1, 9), might be delayed to reduce the hospital-associated risk of COVID-19, with post-surgical immunodepression and thromboembolic risks (7). Because immunosuppression and thromboembolic diathesis are common CS features (9, 10), during the COVID-19 pandemic, the use of steroidogenesis inhibitors appears of great interest. In these patients, combing steroidogenesis inhibitors at intermediate doses might allow for a rapid control of hypercortisolism without risks of major side effects if a single uptitrated treatment is not sufficient. Obviously, the management of associated comorbidities would also be crucial in this situation (11).

To conclude, we report for the first time a case of CS, in the context of primary bilateral macronodular adrenocortical hyperplasia successfully treated with a well-tolerated combination of ketoconazole and osilodrostat. While initial levels of cortisol were not very high, we could not manage to control hypercortisolism with ketoconazole monotherapy, and could not increase the dose due to side effects. The same result was observed with another steroidogenesis inhibitor, osilodrostat. This strategy could be considered for any patient with uncontrolled hypercortisolism and delayed or unsuccessful surgery, especially in the context of the COVID-19 pandemic.

Declaration of interest

F C and T B received research grants from Recordati Rare Disease and HRA Pharma Rare Diseases. Frederic Castinetti is on the editorial board of Endocrinology, Diabetes and Metabolism case reports. Frederic Castinetti was not involved in the review or editorial process for this paper, on which he is listed as an author.

Funding

This work did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.

Patient consent

Informed written consent has been obtained from the patient for publication of the case report.

Author contribution statement

V A was the patient’s physician involved in the clinical care and collected the data. T B and F C supervised the management of the patient. F C proposed the original idea of this case report. V A drafted the manuscript. F C critically reviewed the manuscript. T B revised the manuscript into its final version.

References

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The Cushings Disease Treatment Market To Be Consistent In The Next 10 Years

Posted on August 26, 2021 by MaryO

Cushing disease is caused by tumour in the pituitary gland which leads to excessive secretion of a hormone called adrenocorticotrophic (ACTH), which in turn leads to increasing levels of cortisol in the body. Cortisol is a steroid hormone released by the adrenal glands and helps the body to deal with injury or infection.

Increasing levels of cortisol increases the blood sugar and can even cause diabetes mellitus. However the disease is also caused due to excess production of hypothalamus corticotropin releasing hormone (CRH) which stimulates the synthesis of cortisol by the adrenal glands. The condition is named after Harvey Cushing, the doctor who first identified the disease in 1912. Cushing disease results in Cushing syndrome.

Cushing syndrome is a group of signs and symptoms developed due to prolonged exposure to cortisol. Signs and symptoms of Cushing syndrome includes hypertension, abdominal obesity, muscle weakness, headache, fragile skin, acne, thin arms and legs, red stretch marks on stomach, fluid retention or swelling, excess body and facial hair, weight gain, acne, buffalo hump, tiredness, fatigue, brittle bones, low back pain, moon shaped face etc. Symptoms vary from individual to individual depending upon the disease duration, age and gender of the patient.

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Disease diagnosis is done by measuring levels of cortisol in patient’s urine, saliva or blood. For confirming the diagnosis, a blood test for ACTH is performed. The first-line treatment of the disease is through surgical resection of ACTH-secreting pituitary adenoma, however disease management is also done through medications, Cushing disease treatment market comprises of the drugs designed for lowering the level of cortisol in the body. Thus patients suffering from Cushing disease are prescribed medications such as ketoconazole, mitotane, aminoglutethimide metyrapone, mifepristone, etomidate and pasireotide.

Cushing’s disease treatment market revenue is growing with a stable growth rate, this is attributed to increasing number of pipeline drugs. Also increasing interest of pharmaceutical companies to develop Cushing disease drugs is a major factor contributing to the revenue growth of Cushing disease treatment market over the forecast period.

Current and emerging players’ focuses on physician education and awareness regarding availability of different drugs for curing Cushing disease, thus increasing the referral speeds, time to diagnosis and volume of diagnosed Cushing disease individuals.

Growing healthcare expenditure and increasing awareness regarding Cushing syndrome aids in the revenue growth of Cushing’s disease treatment market. Increasing number of new product launches also drives the market for Cushing’s disease Treatment devices. However availability of alternative therapies for curing Cushing syndrome is expected to hamper the growth of the Cushing’s disease treatment market over the forecast period.

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The Cushing’s disease Treatment market is segment based on the product type, technology type and end user

Cushing’s disease Treatment market is segmented into following types:

By Drug Type
  • Ketoconazole
  • Mitotane
  • Aminoglutethimide
  • Metyrapone
  • Mifepristone
  • Etomidate
  • Pasireotide
By End User
  • Hospital Pharmacies
  • Retail Pharmacies
  • Drug Stores
  • Clinics
  • e-Commerce/Online Pharmacies

Cushing’s disease treatment market revenue is expected to grow at a good growth rate, over the forecast period. The market is anticipated to perform well in the near future due to increasing awareness regarding the condition. Also the market is anticipated to grow with a fastest CAGR over the forecast period, attributed to increasing investment in R&D and increasing number of new product launches which is estimated to drive the revenue growth of Cushing’s disease treatment market over the forecast period.

Depending on geographic region, the Cushing’s disease treatment market is segmented into five key regions: North America, Latin America, Europe, Asia Pacific (APAC) and Middle East & Africa (MEA).

North America is occupying the largest regional market share in the global Cushing’s disease treatment market owing to the presence of more number of market players, high awareness levels regarding Cushing syndrome. Healthcare expenditure and relatively larger number of R&D exercises pertaining to drug manufacturing and marketing activities in the region. Also Europe is expected to perform well in the near future due to increasing prevalence of the condition in the region.

Asia Pacific is expected to grow at the fastest CAGR because of increase in the number of people showing the symptoms of Cushing syndrome, thus boosting the market growth of Cushing’s disease treatment market throughout the forecast period.

Some players of Cushing’s disease Treatment market includes CORCEPT THERAPEUTICS, HRA Pharma, Strongbridge Biopharma plc, Novartis AG, etc. However there are numerous companies producing branded generics for Cushing disease. The companies in Cushing’s disease treatment market are increasingly engaged in strategic partnerships, collaborations and promotional activities to capture a greater pie of market share.

The research report presents a comprehensive assessment of the market and contains thoughtful insights, facts, historical data, and statistically supported and industry-validated market data. It also contains projections using a suitable set of assumptions and methodologies. The research report provides analysis and information according to categories such as market segments, geographies, types, technology and applications.

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