Abstract
Therapies for metastatic SDHB-dependent pheochromocytoma and paraganglioma (PPGL) are limited and poorly efficient. New targeted therapies and identification of early non-invasive biomarkers of response are thus urgently needed for these patients. We characterized an in vivo allograft model of spontaneously immortalized murine chromaffin cells (imCC) with inactivation of the Sdhb gene by dynamic contrast-enhanced MRI (DCE-MRI) and 18FDG-PET. We evaluated the response to several therapies: IACS-010759 (mitochondrial respiratory chain complex I inhibitor), sunitinib (tyrosine kinase inhibitor with anti-angiogenic activity), talazoparib (poly ADP ribose polymerase (PARP) inhibitor) combined or not to temozolomide (alkylating agent), pharmacological inhibitors of HIF2a (PT2385 and PT2977 (belzutifan)) and molecular inactivation of HIF2a (imCC Sdhb−/− shHIF2a). Multimodal imaging was performed, including magnetic resonance spectroscopy (1H-MRS) to monitor the level of succinate in vivo. The allografted model of Sdhb−/− imCC reflected SDHB-deficient tumors, with increased angiogenesis and a particular avidity for 18FDG. After 14 days of treatment, IACS-010759, sunitinib and talazoparib at high doses allowed a significant reduction of the tumor volumes. In contrast to the tumor growth inhibition observed in Sdhb−/− shHIF2a imCC tumors, pharmacological inhibitors of HIF2a (PT2385 and belzutifan) showed no antitumor action in this model, alone or in combination with sunitinib. 1H-MRS, but not DCE-MRI, enabled the monitoring response to sunitinib, which was the best treatment in this study, promoting a decrease in succinate levels detected in vivo. This study paves the way for new therapeutic options and reveals a potential new early biomarker of response to treatment in SDHB-dependent PPGL.
Introduction
Pheochromocytoma and paraganglioma (PPGL) are rare neuroendocrine tumors that arise in chromaffin cells of the adrenal medulla or in sympathetic and parasympathetic ganglia, respectively. Around 40% of PPGL patients carry a germline mutation in one of the 20 PPGL susceptibility genes identified so far. Mutations in SDHx (SDHA, SDHB, SDHC, SDHD, and SDHAF2) genes are the most frequently involved, causing approximately half of the genetically determined cases (Favier et al. 2015). They encode the four subunits and assembly factor of succinate dehydrogenase (SDH), a mitochondrial enzyme involved both in the tricarboxylic acid cycle and the complex II of the electron transport chain (ETC). Patients with SDHB mutations have an increased risk of recurrence and a metastatic disease in nearly 50% of cases (Pasini & Stratakis 2009), defined by the occurrence of metastases in non-chromaffin organs (Lloyd et al. 2017). Five-year overall survival is excellent for localized PPGL (above 95%) but declines to 40–77% in case of metastasis (Ayala-Ramirez et al. 2011, Turkova et al. 2016, Hamidi et al. 2017, Hescot et al. 2019). Surgery remains the only curative approach, and adjuvant therapies of metastatic PPGL are limited and poorly efficient (Baudin et al. 2014). Currently, treatment of metastatic PPGL includes the standard chemotherapy cyclophosphamidevincristine–dacarbazine regimen and the oral form of dacarbazine, temozolomide, which seems to have higher response rates in patients with SDHB mutations (Hadoux et al. 2014, Niemeijer et al. 2014). Sunitinib, a tyrosine kinase inhibitor (TKI) with anti-angiogenic properties, was recently evaluated in two phase II trials and seems promising (O’Kane et al. 2019, Baudin et al. 2021). However, knowledge acquired in other cancers shows that although they can stabilize tumor growth, anti-angiogenic agents rarely achieve complete responses, and acquired resistance is common after several months of treatment (Jimenez et al. 2020). Thus, there is an urgent need to develop alternative therapeutic strategies or to combine anti-angiogenic therapies with new treatments.
The understanding of PPGL biology has strikingly progressed with the generation of genomics and metabolomics data on these tumors, making it possible to envision the use of targeted therapies and precision medicine (Moog et al. 2020). Indeed, germline SDHxmutations cause the complete loss of SDH activity and the accumulation of its substrate, succinate, which acts as an oncometabolite, inhibiting iron(II) and 2-oxoglutarate-dependent dioxygenases (Gimenez-Roqueplo et al. 2001, Selak et al. 2005, Morin et al. 2020). It leads to the combination of a pseudohypoxic state and a global epigenetic reprogramming, which act in synergy to promote invasiveness and putatively resistance to treatment (Morin et al. 2020). In particular, stabilization of hypoxia-inducible transcription factor 2α (HIF2a) through the inhibition HIF prolyl-hydroxylases by succinate activates a wide range of target genes involved in tumorigenesis by mediating metabolic adaptation (glycolytic switch), proliferation, angiogenesis and acquisition of mesenchymal hallmarks (Favier & Gimenez-Roqueplo 2010, Toledo 2017, Morin et al. 2020). We have previously explored the in vitro silencing of HIF2a in Sdhb−/− imCC cells, which results in decreased proliferation and migration as well as a reversal of their mesenchymal phenotype (Morin et al. 2020). HIF2a, although a crucial target, was long considered to be pharmacologically inaccessible. Based on the structure of the HIF2a-ARNT/HIF1b dimer, two antagonists of HIF2a (PT2385 and PT2977 (belzutifan)) were generated. These small molecules allosterically block the binding of HIF2a to ARNT/HIF1b, thereby inhibiting its transcriptional activity (Scheuermann et al. 2015) and have shown very promising results in clear cell renal cell carcinoma (ccRCC), in preclinical models and in phase I and II (Chen et al. 2016, Cho et al. 2016, Xu et al. 2019), making them good candidates for the treatment of metastatic PPGLs.
In parallel, succinate has been recently found to suppress the homologous recombination DNA-repair pathway (that repairs double-strand DNA breaks) through the inhibition of the lysine demethylase KDM4B making renal cancer cells and renal tumor xenograft with SDHB-deficiency vulnerable to PARP inhibitors (Sulkowski et al. 2018, 2020). Finally, it has been reported that SDHxmutations induce the reprogramming of cell metabolism through the upregulation of ETC complex I, the consumption of extracellular pyruvate and the activation of pyruvate carboxylation to re-supply the depleted pool of aspartate that is further used to provide amino and nucleic acids to sustain cell growth and survival (Cardaci et al. 2015, Lussey-Lepoutre et al. 2015). All these pathways can potentially be targeted by new drugs that first need to be tested in preclinical models. Recently, IACS-010759 (IACS), a clinical-grade small molecule inhibitor of oxidative phosphorylation through the inhibition of mitochondrial complex I and reduction of aspartate production, has been tested with promising results in mouse models of acute myeloid leukemia and brain cancer, making IACS a potential drug for PPGL (Molina et al. 2018).
The lack of innovative therapy in this disease is in part due to the lack of suitable animal models, in particular, the absence of adequate experimental models of Sdhb-deficient tumors and the high complexity in the establishment of cell lines from primary human metastatic and/or SDHB-deficient PPGL (Lepoutre-Lussey et al. 2016, Bayley & Devilee 2020). We have generated an immortalized mouse chromaffin cell (imCC) line knocked out for the Sdhb gene (Letouzé et al. 2013) that allowed the establishment of an in vivo allograft model that can be used for the evaluation of new therapies but also for the development of new multimodal preclinical imaging approaches (Lussey-Lepoutre et al. 2016, Facchin et al. 2020). Indeed, the development of new therapies in cancers requires optimal imaging techniques allowing early detection, localization of the lesions and evaluation of response to treatment. Follow-up of new targeted therapies by imaging needs to fulfill specific criteria, permitting early identification of tumor escape. Morphologic criteria are not well adapted to predict early response to treatment because targeted therapies have little effect on tumor size (Fournier et al. 2017). In contrast, several reports have shown that imaging of tumor perfusion using dynamic contrast-enhanced MRI (DCE-MRI) is an indicator of treatment efficacy with anti-angiogenic agents (Cuenod & Balvay 2013, Ewing & Bagher-Ebadian 2013, Choi et al. 2016, Hudson et al. 2018, Zhong et al. 2021). PET with 2-deoxy-2-[18F]fluoro-d-glucose (18FDG) also appears as a promising tool to predict early response to treatment in several cancers including PPGL (Ayala-Ramirez et al. 2012). Finally, accumulation of succinate in tumors is a specific biomarker of SDHx mutations that can be measured in vivo and could represent a surrogate marker of early response to treatment (Lussey-Lepoutre et al. 2016, 2020).
In the current study, we report the characterization of the allograft model of Sdhb−/− imCC using multimodal imaging and the preclinical response to several new treatments, including HIF2a inhibitors PT2385 and belzutifan, complex I inhibitor and PARP inhibitor. We also show the monitoring response of sunitinib by 1H-MRS and DCE-MRI.
Materials and methods
In vivo experiments
Cellular and mouse models
This study was approved by the French Ethical committee and registered under APAFIS no. 16922 and performed by certified personal following the French law on animal experimentation. Guidelines for the welfare and use of animals in cancer research were followed (Workman et al. 2010). The allografted mouse model was generated by subcutaneous injection of 2.5 106 imCC on the flank of NMRI nude female mice (6–8 weeks old, weight = 30 g, Janvier Labs, France). Pieces of grown tumors were secondarily propagated into the fat pad of a second series of NMRI mice, as previously described (Lussey-Lepoutre et al. 2016, Facchin et al. 2020). Allografts were generated with either WT, Sdhb−/− (Letouzé et al. 2013) or Sdhb−/− with silencing of HIF2a using a specific shRNA lentiviral vector (Sdhb−/− shHIF2a) cells ( Morin et al. 2020). Mice were maintained at a controlled temperature (24°C) and relative humidity (50%) on a 12 h light:12 h darkness cycle with free access to water and food. Tumor size and body weight were measured twice a week. Tumor volume was calculated by caliper measurements using the formula: ½ × length × (width)2. Toxicity was evaluated by body weight loss from the start of the treatment. A weight loss of more than 20% led to the interruption of the experiment. For imaging, mice were under anesthetic with isoflurane (2–3% in normal air) and placed head-first in prone position in the scanner under respiration monitoring with a window placed between 30 and 50 cycles per min.
Experimental treatments design
When tumors became palpable, mice were randomly divided into treated or vehicle groups for each treatment. Sunitinib (HY-10255A, MedChem) was dissolved in DMSO and PBS solution (stock solution at 56 mM, final solution 28 mM) and administered 5 days a week by oral gavage at 60 mg/kg alone or at 40 mg/kg in combination with IACS-010759. IACS-010759 was kindly provided by Giulio Draetta (MD Anderson, Houston, TX, USA) and dosed in a 0.5% methylcellulose suspension by oral gavage at 10 mg/kg 5 days a week (final solution 2.5 mM). Talazoparib (TLZ) (HY-16106, MedChem) was first dissolved in DMSO at 10 mM and then formulated with 84% PBS, 6% Solutol (Sigma) and 10% DMAc (Sigma) at 0.12 mM. TLZ was administered by oral gavage at 0.3, 0.4 or 0.5 mg/kg, 5 or 7 days a week. Temozolomide (HY-17364, MedChem) was dissolved in DMSO at 50 mM, then formulated in water containing 0.5% methylcellulose at 15 mM and administered by oral gavage at 5 mg/kg for the first 5 days of treatment in combination or not with TLZ. PT2385 and belzutifan (HY-12867 and HY-125840, MedChem) were formulated with 10% absolute ethanol, 30% PEG400, 60% water containing 0.5% methylcellulose and 0.5% Tween 80 (final solution 5.5 mM) and were administered by oral gavage at 10 mg/kg twice daily, 7 days a week. Solutions were prepared every day for sunitinib or twice a week for the others, kept at 4°C and homogenized every day.
MRI acquisition protocol and images post-processing
MRI was performed in a dedicated small-animal 4.7 Tesla MR system (Biospec 47/40 USR, Bruker, Ettlingen, Germany), using a 1H quadrature transmit/receive body coil with a 3.5-cm inner diameter. An anatomic two-dimensional (2D) steady-state free precession sequence (True FISP) was first acquired in two orthogonal planes to localize and measure tumors and a phase-contrast sequence in the sagittal plane to localize the abdominal aorta. DCE-MRI was performed with a 2D-FLASH sequence (repetition time (TR): 11.4 ms, echo time (TE): 1 ms, matrix: 128 × 103, field of view: 4 × 3.22 cm, slice thickness: 0.7 mm, resolution: 312 μm/pixel, 500 repetitions) in the coronal plane to select two planes of imaging; in a first plane, a region of interest (ROI) was positioned over the suprarenal aorta to determine the arterial input function (AIF), and in a second plane, a ROI was positioned over the largest diameter of the tumor. The temporal resolution of the MRI sequence was 1.1 s and the total duration was 9 min 48 s. A conventional gadolinium chelate-contrast agent (gadoterate meglumine, Dotarem®, Guerbet, 500 mmolGd/L, dilution: 1/15, bolus: 100 µL) was injected after the first 30 s of acquisition through the tail vein in a 24G catheter. To prevent the entry slice artifact, an axial saturation band was placed above the aorta.
DCE-MRI analysis was performed on acquisitions without noise correction using in-house software (PhysioD 3D) developed with Matlab (MathWorks, Natick, MA, USA). Tumors and aorta were manually delimited by a zone of interest and oversegmented using automatic pixel clustering based on the k-means methods. Clusters presenting noisy signals were manually eliminated. The intensity-to-time average signal inside each ROI was computed and modeled with a one-compartmental model to yield the following vascular parameters: (i) relative area under the curve for total acquisition (rAUC10min) representing the global tumor enhancement corrected for AIF; (ii) tissue blood flow (F) in mL/min/100 mL of tissue; (iii) tissue blood volume (Vb) expressed in percent of vascular to tissue volume. Modeling was based on fittings enhancement curves using the Levenberg–Marquard regression method.
The magnetic resonance spectroscopy (1H-MRS) sequence for the detection of succinate in vivo was performed as previously described (Lussey-Lepoutre et al. 2016). In brief, 1H-MRS was carried out using an optimized asymmetric Point REsolved SpectroScopy monovoxel acquisition. Echo signals (TR: 3.000 ms; TE: 144 ms; average: 512, with a VOI size of 5 × 5 × 5 mm3) were acquired during 25 min. The MRS spectrum of succinic acid (HOOC-(CH2)2-COOH) presents a characteristic peak at 2.4 ppm, corresponding to the precession frequency of the CH2 protons. The succinate peak was quantified by measuring the area under the peak using Topspin 2.0 software (Bruker Corporation).
18FDG-PET-CT acquisition protocol and images post-processing
PET-CT images were acquired with a sequential PET/CT scanner dedicated to small-animal imaging (nanoScan PET/CT, Mediso Ltd., Hungary). Ten MBq of 2-deoxy-2-[18F]fluoro-d-glucose (18FDG) was injected in a volume of 0.15 mL saline into the tail vein under gaseous anesthesia. Animal temperatures and respiration rates were monitored during the entire scan. PET data were collected in 3D acquisition mode during 60 min. PET volumes corresponding to 45–60 min post-injection events were reconstructed using a 3D Ordered Subset Expectation Maximization algorithm (Tera-Tomo, Mediso Ltd.) with a final voxel size of 0.4 mm. For attenuation correction, co-registered CT scans were acquired with the following parameters: 520 µAs, 50 keV, pitch: 0.5, binning 1:4, FOV: 283 mm, matrix: 344 × 344.
FDG uptake was quantified in 3D volumes-of-interest (VOI) delineated semi-automatically by iso-contours at a 25% threshold of maximal value for each tumor on PET/CT fusion slices using the PMOD software package (PMOD Technologies Ltd, Zürich, Switzerland). Mean and maximal standardized uptake values (SUV) were calculated for each VOI. The total lesion glycolysis (TLG) was evaluated by multiplicating the SUV mean by the metabolic tumor volume (MTV).
Ex-vivo experiments
Immunohistochemistry
Tumors were resected and fixed in 4% paraformaldehyde, transferred to 70% EtOH before paraffin-embedding. Six-micrometer sections of paraffin-embedded tissues were cut and mounted on Superfrost Plus glass slides. The sections were deparaffinized and rehydrated and immunostained with anti-CD31 (1:100, DIA310, Clinisciences) or anti-Ki67 (1:200, ab15580, Abcam) antibodies at room temperature during 1 h. Antigen retrieval was performed by boiling slides in citrate buffer pH 6 for 20 min. Revelation was performed using Histogreen (E109, Linaris) as a chromogen. Images were acquired with a Leica DM400B microscope with Leica Application Suite software V.2.8.1 and a Leica DFC420C camera with 20× or 40× objective. CD31 positives vessels were counted manually in 10 fields of independent sections at 20× magnification for each sample.
RNA isolation and RT-qPCR
Tumors were resected and snap-frozen in liquid nitrogen. Total mRNA was extracted from tumors using RNeasy Plus Mini Kit (Qiagen). RT was fulfilled using iScript cDNA Synthesis Kit (Bio-Rad) and real-time quantitative PCR (qRT-PCR) was performed on CFX96 Real-Time System C1000 Touch Thermal Cycler (Bio-Rad) using SuperScript SybrGreen (Bio-Rad) and normalization was performed with Ubc, B2m and 18S amplifications, and comparisons were calculated using the ΔΔCt method. Primers’ sequences were as follows:
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Ubc: F, 5’-AGCCCAGTGTTACCACCAAG-3’; R, 5’-ACCCAAGAACAAGCACAAG-3’;
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18 S: F, 5’-CGCGGTTCTATTTTGTTGGT-3’; R, 5-AACCATAAACGATGCCGAC-3’;
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B2m: F, 5’-ATTCACCCCCACTGAGACTG-3’; R, 5-TGCTATTTCTTTCTGCGTGC-3’;
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Mmp9: F, 5’-CGGCACGCTGGAATGATC-3’; R5-TCGAACTTCGACACTGACAAGAA-3’;
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Pai: F, 5’-ACAGCCAACAAGAGCCAATC-3’; R, 5’-GGACCACCTGCTGAAACACT-3’.
Statistical analysis
Data are represented as mean ± s.e.m. Data were analyzed by an unpaired Student’s t-test or using two-way ANOVA with Bonferroni’s multiple comparisons test. Statistical tests were carried out using the GraphPad Prism software. All analyses considered a value of P ≤ 0.05 to be statistically significant.
Results
The allograft model of Sdhb−/− imCC mimics SDHB-deficient tumors
WT tumors become macroscopically visible about 1 week before Sdhb−/− tumors and grow faster, in line with the doubling times of cells grown in vitro(Letouzé et al. 2013) (Supplementary Fig. 1A, see section on supplementary materials given at the end of this article). As previously described in human SDHB-mutated PPGL, vessel density was significantly higher in Sdhb−/− tumors than in WT tumors (Fig. 1A and B).
Microcirculation and metabolic characterization of the Sdhb−/− allograft model. (A) Tumor vasculature revealed by CD31 staining. Scale bar: 50 µm. (B) IHC quantification of CD31. (C) Evaluation of tumor microcirculation using DCE-MRI in Sdhb−/− tumors (n = 15) or WT tumors. Global enhancement in tumors on dynamic coronal slices after injection of the contrast agent. (D) Parameter maps obtained after automatic segmentation. Brown-red: highly enhanced zone; blue: poorly enhanced zone. (E) Corresponding AUC curves of the segmented areas. (F) rAUC: relative area under the curve for total acquisition that represents the global tumor enhancement (%). (G) Tissue blood flow in mL/min/100 mL of tissue (F). (H) Tissue blood volume fraction in % (Vb). (I) Evaluation of tumor metabolism using 18FDG-PET (n = 20 Sdhb−/− tumors and n = 15 WT tumors) on sagittal (left part) and coronal (right part) slices at 60 min post-injection (arrows). Quantification of the signal in the tumor: metabolic volume higher than 50% of SUVmax (J) and TLG (K). Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Microcirculation and metabolic characterization of the Sdhb−/− allograft model. (A) Tumor vasculature revealed by CD31 staining. Scale bar: 50 µm. (B) IHC quantification of CD31. (C) Evaluation of tumor microcirculation using DCE-MRI in Sdhb−/− tumors (n = 15) or WT tumors. Global enhancement in tumors on dynamic coronal slices after injection of the contrast agent. (D) Parameter maps obtained after automatic segmentation. Brown-red: highly enhanced zone; blue: poorly enhanced zone. (E) Corresponding AUC curves of the segmented areas. (F) rAUC: relative area under the curve for total acquisition that represents the global tumor enhancement (%). (G) Tissue blood flow in mL/min/100 mL of tissue (F). (H) Tissue blood volume fraction in % (Vb). (I) Evaluation of tumor metabolism using 18FDG-PET (n = 20 Sdhb−/− tumors and n = 15 WT tumors) on sagittal (left part) and coronal (right part) slices at 60 min post-injection (arrows). Quantification of the signal in the tumor: metabolic volume higher than 50% of SUVmax (J) and TLG (K). Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Microcirculation and metabolic characterization of the Sdhb−/− allograft model. (A) Tumor vasculature revealed by CD31 staining. Scale bar: 50 µm. (B) IHC quantification of CD31. (C) Evaluation of tumor microcirculation using DCE-MRI in Sdhb−/− tumors (n = 15) or WT tumors. Global enhancement in tumors on dynamic coronal slices after injection of the contrast agent. (D) Parameter maps obtained after automatic segmentation. Brown-red: highly enhanced zone; blue: poorly enhanced zone. (E) Corresponding AUC curves of the segmented areas. (F) rAUC: relative area under the curve for total acquisition that represents the global tumor enhancement (%). (G) Tissue blood flow in mL/min/100 mL of tissue (F). (H) Tissue blood volume fraction in % (Vb). (I) Evaluation of tumor metabolism using 18FDG-PET (n = 20 Sdhb−/− tumors and n = 15 WT tumors) on sagittal (left part) and coronal (right part) slices at 60 min post-injection (arrows). Quantification of the signal in the tumor: metabolic volume higher than 50% of SUVmax (J) and TLG (K). Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Evaluation of tumor microcirculation using DCE-MRI
DCE-MRI was performed 19 days (±5) after the graft for the WT group (n =15) and 34 days (±8) for the Sdhb−/− group (n =16) on tumors of 1.8 cm3 (±0.2) and 1.3 cm3 (±0.2), respectively. Global enhancement in tumors was strikingly higher in Sdhb−/− than in WTtumors (Fig. 1C). Moreover, after automatic segmentation based on the evolution of the gray scale level along time, the parameter maps showed a binary distribution in WTtumors with a poorly enhanced large core (corresponding histologically to necrotic and hemorrhagic alterations), while Sdhb−/− tumors were homogeneously enhanced (Fig. 1D). The corresponding curves of the four automatic segmented zones illustrate the difference in enhancement between the two types of tumors: the curve corresponding to the most strongly enhanced area in the WT tumor (brown curve) having a lower intensity than the least enhanced area of the Sdhb−/− tumor (blue curve) (Fig. 1E). A high time resolution sequence and mathematical models were used to extract vascular parameters. Correlating the variation of signal intensity in the tumor (AUC) with enhancement in the artery, that is the arterial input function (AIF), allowed a quantitative analysis. A compartmental analysis was used to calculate tumor blood flow (F) and blood volume fraction (Vb). A significantly higher enhancement was observed in the Sdhb−/− group with an AUC of 30.3 ± 2.0% vs 15.3 ± 1.8% for the WT group (P < 0.0001) (Fig. 1F). This high enhancement was consecutive to an increase in blood flow (F: 106.4 ± 16.5 mL/min/100 mL for Sdhb−/− vs 42.9 ± 5.7 mL/min/100 mL for WT tumors, P = 0.0001) and also in blood volume fraction (Vb: 54.4 ± 3.9 % in Sdhb−/− vs 32.8 ± 3.8 % in WT, P = 0.0003) (Fig. 1G and H).
Evaluation of glucose uptake by 18FDG-PET
Results of metabolic imaging with 18FDG-PET performed on 35 mice (20 Sdhb−/− and 15 WT at an average tumor volume of 1.9 ± 0.2 and 1.4 ± 0.2 cm3, respectively; P = 0.23) were consistent with vascular imaging, showing a homogeneous uptake in Sdhb −/− tumors while WT tumors displayed a large central core with no 18FDG uptake (Fig. 1I). After quantification of the signal in the tumor, the maximum uptake value (SUVmax) was not significantly different between the two types of tumors, with a mean SUVmax of 6.7 ± 0.4 for the Sdhb−/− vs 7.5 ± 0.4 for the WT group (P = 0.18) (Supplementary Fig. 1B). However, we observed a significant difference between the mean volume fraction of tumor with an uptake equivalent or superior to 50% of SUVmax (39.2 ± 1.7% for Sdhb−/−vs 16.4 ± 3.1% for the WT, P < 0.0001) (Fig. 1J). TLG was also increased in Sdhb−/− tumorsvs WT tumors (6.7 ± 0.9% for Sdhb−/− vs 3.7 ± 0.4% for WT, P = 0.01) (Fig. 1K), reflecting a high avidity for 18FDG.
Altogether, the characterization of Sdhb-deficient tumors by multimodality imaging showed, as in human PPGL, a highly vascularized pattern and a particular avidity for 18FDG, validating this SDHB-deficient preclinical model for the evaluation of therapeutic responses.
Antitumoral effect of IACS, talazoparib and sunitinib
We evaluated the complex I inhibitor IACS and the PARP inhibitor talazoparib, in comparison to the TKI sunitinib. When tumors became palpable, mice were randomly administered the different treatments by oral gavage. IACS and sunitinib significantly slowed down tumor growth, with, at day 13, a 49 and 42% decrease in tumor volume, respectively, compared to vehicle-treated mice, and without toxicity (P < 0.001) (Fig. 2A and B). For talazoparib treatment, we tested two doses (0.4 and 0.5 mg/kg) for 5 or 7 days per week. The toxicity-effectiveness correlation was striking with a maximum potency at 0.4 and 0.5 mg/kg 7 days per week (67 and 66% of tumor growth decrease at day 14, respectively, P < 0.0001) (Fig. 2C and E) associated with significant weight loss (Fig. 2D and F). Reducing the schedule to 5 days per week resulted in a significant decrease in both efficacy and weight loss (Fig. 2G and H). Ki67 immunohistochemistry, performed as a biomarker of proliferation, showed lower levels of nuclear staining in all treated tumors compared to vehicle, whereas CD31 staining, a biomarker of angiogenesis, showed no difference between treatment subgroups (Supplementary Fig. 2).
Antitumoral effect of IACS, talazoparib and sunitinib in the Sdhb−/− allograft model. Tumor size (A, C, E and G) and body weight (B, C, F and H) were measured twice a week. (A and B) 10 mg/kg IACS (n = 17), 60 mg/kg Sunitinib (n = 5), or vehicle (n = 16) were given 5 days a week. (C and D) 0.5 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 7 days a week. (E and F) 0.4 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 7 days a week. (G and H) 0.4 mg/kg talazoparib (n = 5), 0.5 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 5 days a week. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001. Arrow: beginning of the treatment. Cross: dead mouse.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Antitumoral effect of IACS, talazoparib and sunitinib in the Sdhb−/− allograft model. Tumor size (A, C, E and G) and body weight (B, C, F and H) were measured twice a week. (A and B) 10 mg/kg IACS (n = 17), 60 mg/kg Sunitinib (n = 5), or vehicle (n = 16) were given 5 days a week. (C and D) 0.5 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 7 days a week. (E and F) 0.4 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 7 days a week. (G and H) 0.4 mg/kg talazoparib (n = 5), 0.5 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 5 days a week. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001. Arrow: beginning of the treatment. Cross: dead mouse.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Antitumoral effect of IACS, talazoparib and sunitinib in the Sdhb−/− allograft model. Tumor size (A, C, E and G) and body weight (B, C, F and H) were measured twice a week. (A and B) 10 mg/kg IACS (n = 17), 60 mg/kg Sunitinib (n = 5), or vehicle (n = 16) were given 5 days a week. (C and D) 0.5 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 7 days a week. (E and F) 0.4 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 7 days a week. (G and H) 0.4 mg/kg talazoparib (n = 5), 0.5 mg/kg talazoparib (n = 5) or vehicle (n = 5) were given 5 days a week. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001. Arrow: beginning of the treatment. Cross: dead mouse.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Increased antitumoral effects and toxicities by combining therapies
We then combined IACS with sunitinib and talazoparib with the alkylating agent temozolomide at different dosages. IACS at 10 or 5 mg/kg with sunitinib at a high dose resulted in a striking antitumoral efficacy but also side effects such as weight loss causing premature death (Fig. 3A and B). Half-dose treatment with both IACS and sunitinib was well tolerated but did not show superior efficacy to sunitinib alone (Fig. 3A). Similarly, the combined treatment of talazoparib and temozolomide, despite a drastic dose decreased, resulted in a significant reduction in tumor growth but with major side effects (Fig. 3C and D).
Increased antitumoral effects and toxicities by combining therapies. Tumor size (A, C) and body weight (B, D) were measured twice a week. (A and B) Sunitinib 40 mg/kg with IACS 5 mg/kg (n = 4), sunitinib 60 mg/kg with IACS 5 mg/kg (n = 4), sunitinib 60 mg/kg with IACS 10 mg/kg (n = 4) or vehicle (n = 4) were given 5 days a week. (C and D) Talazoparib 0.3 mg/kg 5 days a week and temozolomide 5 mg/kg 5 days were given individually (n = 5 and n = 5, respectively) or in combination (n = 5) compared to vehicle (n = 5). Data are represented as mean ± s.e.m.. *P < 0.05; **P < 0.01; ***P < 0.001. Arrow: beginning of the treatment. Cross: dead mouse.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Increased antitumoral effects and toxicities by combining therapies. Tumor size (A, C) and body weight (B, D) were measured twice a week. (A and B) Sunitinib 40 mg/kg with IACS 5 mg/kg (n = 4), sunitinib 60 mg/kg with IACS 5 mg/kg (n = 4), sunitinib 60 mg/kg with IACS 10 mg/kg (n = 4) or vehicle (n = 4) were given 5 days a week. (C and D) Talazoparib 0.3 mg/kg 5 days a week and temozolomide 5 mg/kg 5 days were given individually (n = 5 and n = 5, respectively) or in combination (n = 5) compared to vehicle (n = 5). Data are represented as mean ± s.e.m.. *P < 0.05; **P < 0.01; ***P < 0.001. Arrow: beginning of the treatment. Cross: dead mouse.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Increased antitumoral effects and toxicities by combining therapies. Tumor size (A, C) and body weight (B, D) were measured twice a week. (A and B) Sunitinib 40 mg/kg with IACS 5 mg/kg (n = 4), sunitinib 60 mg/kg with IACS 5 mg/kg (n = 4), sunitinib 60 mg/kg with IACS 10 mg/kg (n = 4) or vehicle (n = 4) were given 5 days a week. (C and D) Talazoparib 0.3 mg/kg 5 days a week and temozolomide 5 mg/kg 5 days were given individually (n = 5 and n = 5, respectively) or in combination (n = 5) compared to vehicle (n = 5). Data are represented as mean ± s.e.m.. *P < 0.05; **P < 0.01; ***P < 0.001. Arrow: beginning of the treatment. Cross: dead mouse.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Discrepancies between HIF2a inhibition by knockdown and pharmacological antagonists
We then explored the impact of HIF2a inhibition on the growth of Sdhb−/− cells in vivo. HIF2a silencing drastically decreased the growth of subcutaneous Sdhb−/− tumors in the flank of nude mice compared to the Sdhb−/− cells (366 ± 33 vs 80 ± 6 days, P < 0.0001) (Fig. 4A). Furthermore, after engraftment of these subcutaneous tumors in the fat pad, HIF2a silenced Sdhb−/− cells showed a strikingly decreased growth rate as compared to Sdhb−/− tumors (Fig. 4B). CD31 immunostaining quantification showed a decrease in vascularization which may account for this antitumoral effect (P < 0.0001) (Fig. 4C and D). We then explored the efficacy of the two HIF2a pharmacological inhibitors in the Sdhb−/− imCC allograft model. Surprisingly, neither PT2385 nor belzutifan showed any efficacy in reducing tumor growth (P = 0.5) despite weak inhibition of MMP9 and PAI transcription, two HIF2a target genes (P = 0.05 and P = 0.0006) (Fig. 4E, F and Supplementary Fig. 3). No impact on proliferation or angiogenesis was observed (Supplementary Fig. 2).
Discrepancies between HIF2a inhibition by knockdown and by pharmacological antagonists. (A) 2.5 106 imCC carrying a homozygous knockout of the Sdhb gene (Sdhb−/−) with or without silencing of HIF2a using specific shRNA lentiviral vector (Sdhb−/− shHIF2a) were subcutaneously injected into nude mice (n = 5 tumors per group). Time of growth until a palpable tumor was obtained. (B) Tumors were secondarily propagated in the back of the neck fat pad and tumor volume was measured twice a week. The tumor vasculature was detected by immunostaining for CD31. (C) IHC quantification of CD31. (D) Representative images of CD31 staining. Scale bar: 100 µm. (E) When Sdhb−/− tumors became palpable, nude mice were randomly assigned to administration by oral gavage to PT2385 10 mg/kg (n = 5), PT2977 (belzutifan) 10 mg/kg (n = 5) or with the vehicle solution (n = 5) (arrow: start of treatment). Tumor size was measured twice a week. (F) qRT-PCR analysis of two HIF2a target genes of Sdhb−/− tumors treated with PT2385 10 mg/kg or vehicle. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Discrepancies between HIF2a inhibition by knockdown and by pharmacological antagonists. (A) 2.5 106 imCC carrying a homozygous knockout of the Sdhb gene (Sdhb−/−) with or without silencing of HIF2a using specific shRNA lentiviral vector (Sdhb−/− shHIF2a) were subcutaneously injected into nude mice (n = 5 tumors per group). Time of growth until a palpable tumor was obtained. (B) Tumors were secondarily propagated in the back of the neck fat pad and tumor volume was measured twice a week. The tumor vasculature was detected by immunostaining for CD31. (C) IHC quantification of CD31. (D) Representative images of CD31 staining. Scale bar: 100 µm. (E) When Sdhb−/− tumors became palpable, nude mice were randomly assigned to administration by oral gavage to PT2385 10 mg/kg (n = 5), PT2977 (belzutifan) 10 mg/kg (n = 5) or with the vehicle solution (n = 5) (arrow: start of treatment). Tumor size was measured twice a week. (F) qRT-PCR analysis of two HIF2a target genes of Sdhb−/− tumors treated with PT2385 10 mg/kg or vehicle. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Discrepancies between HIF2a inhibition by knockdown and by pharmacological antagonists. (A) 2.5 106 imCC carrying a homozygous knockout of the Sdhb gene (Sdhb−/−) with or without silencing of HIF2a using specific shRNA lentiviral vector (Sdhb−/− shHIF2a) were subcutaneously injected into nude mice (n = 5 tumors per group). Time of growth until a palpable tumor was obtained. (B) Tumors were secondarily propagated in the back of the neck fat pad and tumor volume was measured twice a week. The tumor vasculature was detected by immunostaining for CD31. (C) IHC quantification of CD31. (D) Representative images of CD31 staining. Scale bar: 100 µm. (E) When Sdhb−/− tumors became palpable, nude mice were randomly assigned to administration by oral gavage to PT2385 10 mg/kg (n = 5), PT2977 (belzutifan) 10 mg/kg (n = 5) or with the vehicle solution (n = 5) (arrow: start of treatment). Tumor size was measured twice a week. (F) qRT-PCR analysis of two HIF2a target genes of Sdhb−/− tumors treated with PT2385 10 mg/kg or vehicle. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
1H-MRS but not DCE-MRI enables monitoring response to sunitinib
In this study, sunitinib appears to be one of the most effective treatments in the Sdhb-deficient tumor model, with good tolerance. Thus, we then monitored the response to this treatment using several imaging techniques. After the tumors had grown to an approximative size of 800 mm3, mice were randomly divided into two subgroups: treated with sunitinib 60 mg/kg (n = 19) or vehicle (n = 21) and evaluated weekly by 1H-MRS during the 3 weeks of treatment. Among these mice, 13 (n = 8 in the sunitinib group and n = 7 in the vehicle group) were also evaluated by DCE-MRI.
Despite a significant reduction in tumor growth, no difference was observed in global vascular enhancement (AUC: 42.4 ± 8.7% at day 21 for the sunitinib-treated group vs 30.3 ± 5.4% for the vehicle-treated group; P = 0.25), in blood flow (F: 80.3 ± 16.4 mL/min/100 mL at day 21 for the sunitinib-treated group vs 92.0 ± 21.5 mL/min/100 mL for the vehicle-treated group; P = 0.46) nor in the blood volume fraction (Vb: 72.8 ± 8.2% at day 21 for the sunitinib-treated group vs 56.8 ± 4.8% for the vehicle-treated group; P = 0.24) (Fig. 5A and Supplementary Fig. 4A, B and C).
1H-MRS enables monitoring response to sunitinib. After the tumors had grown to an approximative size of 800 mm3, mice were randomly divided into two subgroups: treated with sunitinib (n = 19) or vehicle (n = 21) and evaluated weekly by 1H-MRS during the 3 weeks of treatment. (A) Tumor size was measured twice a week. (B) Area under the peak of succinate was measured by 1H-MRS on days 0, 7, 14 and 21 in the two subgroups. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
1H-MRS enables monitoring response to sunitinib. After the tumors had grown to an approximative size of 800 mm3, mice were randomly divided into two subgroups: treated with sunitinib (n = 19) or vehicle (n = 21) and evaluated weekly by 1H-MRS during the 3 weeks of treatment. (A) Tumor size was measured twice a week. (B) Area under the peak of succinate was measured by 1H-MRS on days 0, 7, 14 and 21 in the two subgroups. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
1H-MRS enables monitoring response to sunitinib. After the tumors had grown to an approximative size of 800 mm3, mice were randomly divided into two subgroups: treated with sunitinib (n = 19) or vehicle (n = 21) and evaluated weekly by 1H-MRS during the 3 weeks of treatment. (A) Tumor size was measured twice a week. (B) Area under the peak of succinate was measured by 1H-MRS on days 0, 7, 14 and 21 in the two subgroups. Data are represented as mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-22-0030
Succinate levels decreased significantly after the first week of treatment (27% (95% CI 0.02; 0.52) decrease in the sunitinib-treated group vs 14% (95% CI −0.09; 0.38) decrease in the vehicle-treated group), predicting response to sunitinib treatment earlier than tumor size measurement by caliper (P = 0.02).
Decrease in tumor volume became significant at day 11 and showed escape right after, in correlation with stabilization of succinate levels between day 7 and day 14 (Fig. 5B). No significant variation in succinate levels was observed in the vehicle-treated group. No decrease in succinate levels was observed in the talazoparib group nor in the PT2385 group after 3 weeks of treatment (Supplementary Fig. 4D).
Discussion
Metastatic pheochromocytomas and paragangliomas suffer from a lack of new therapies in part because of the limitation in suitable animal models of Sdhb-deficient tumors, human PPGL tissues showing no growth when xenografted in mice (Lepoutre-Lussey et al. 2016, Powers et al. 2017). Here, we present the imaging characteristics of an allograft model of Sdhb-deficient immortalized mouse chromaffin cells that recapitulate SDHBhuman PPGLs. This model shows increased angiogenesis and increased blood flow and blood volume fraction. Increased angiogenesis is indeed a hallmark of SDHB-mutated PPGLs, with a vascular density 2.5- to 3.5-fold higher than in RETand NF1-related tumors (Favier et al. 2009). In addition, this Sdhb-allograft shows a strong avidity for 18FDG, also a well-established feature in SDHB-PPGLs. 18FDG uptake was shown to be particularly sensitive for the evaluation of metastases in patients harboring SDHB mutations (Timmers et al. 2007, 2012) and the last recommendations of the European Association of Nuclear Medicine include 18FDG-PET for the diagnosis and follow-up of these patients (Taïeb et al. 2019).
Here, we used our well-established preclinical model to test several innovative therapies based on the recent advances in the understanding of oncogenic pathways occurring in these tumors. We first evaluated targeted therapies currently tested in other tumors, such as acute myeloid leukemia (IACS) or ccRCC (HIF2a antagonists) (Courtney et al. 2018, Molina et al. 2018). The rationale for testing IACS in SDHB-deficient tumors is based on its ability to inhibit the mitochondrial complex I and to reduce aspartate production, two pathways known to be essential to sustain cell proliferation following SDH loss of function (Lussey-Lepoutre et al. 2015, Molina et al. 2018). IACS has never been tested in a preclinical model of PPGL, unlike the most common type I complex inhibitor, metformin (Wheaton et al. 2014). Indeed, two in vitrostudies performed on cell lines derived from pheochromocytomas, mostly rat-derived cells (PC12 cells), suggested an anti-proliferative potential of metformin (Li et al. 2017, Thakur et al. 2019). IACS treatment did lead to a reduction in tumor growth associated with a reduction in proliferation rate, while its combination with sunitinib was toxic at high doses and not efficient at lower doses. Altogether, these results suggest that targeting this pathway is promising and should be further investigated.
We then focused on talazoparib, a highly potent PARP1/2 inhibitor that exhibits selective antitumor cytotoxicity and elicits DNA damage at much lower concentrations than earlier generation PARP1/2 inhibitors (such as olaparib, rucaparib and veliparib) (Shen et al. 2013). It has previously been reported that SDHB loss is associated with increased DNA damage in kidney cell lines and sensitivity to inhibitors of PARP (Pang et al. 2018, Sulkowski et al. 2018, 2020). Although we have reported no difference in DNA damage between Sdhb−/− and WT imCCs (Goncalves et al. 2021), talazoparib decreased tumor growth in the SDHB-deficient allograft model, with an antitumor efficacy highly correlated with its toxicity. The combination of PARP inhibitors and temozolomide has already entered clinical trials in aggressive cancers such as Ewing Sarcoma, gliobastoma, small cells lung cancer or AML with varied results and significant toxicities (Gojo et al. 2017, Pietanza et al. 2018, Schafer et al. 2020, Sim et al. 2021). Here, despite striking results on growth inhibition, we were unable to pursue these combinations of treatments because of the associated toxicity (Smith et al. 2015). Adaptation of these treatments will need to be tested in order to limit such toxicities. For example, nanoparticles have been widely studied as drug delivery systems due to their inherent ability to reduce toxicity while maintaining therapeutic efficacy. A nanoformulation of the PARP inhibitor talazoparib has been developed and shown to be more effective and tolerated than the oral form, allowing combination with higher doses of temozolomide (Baldwin et al. 2019a, b). PARP inhibitors may also be combined with others therapies that are particularly interesting in this pathology, such as demethylating agents or even 177Lu-DOTA-octreotate radionuclide therapy (Muvarak et al. 2016, Cullinane et al. 2020). Noteworthily, the first therapeutic trial combining olaparib with temozolomide is about to start in PPGL (NCT04394858).
Following the in vitrodemonstration of the role of HIF2a in PPGLs tumorigenesis (Favier et al. 2009, Toledo et al. 2013, Morin et al. 2020), the massive effect of HIF2a shRNA on tumor growth confirms its importance in Sdhb-mutated chromaffin cells in vivo. However, in this study, we were not able to show any effect of the two pharmacological HIF2a antagonists (PT2385 and belzutifan). Both antagonists are validated in preclinical models of ccRCC xenografts and a phase II study with belzutifan recently showed very promising results in patients having previously received several lines of treatment, (Choueiri et al. 2021). In addition, Kamihara et alrecently reported a significant antitumor efficacy of belzutifan in a patient with polycythemia and multiple paragangliomas (Pacak–Zhuang syndrome) caused by somatic mosaicism for an activating mutation in EPAS1(Kamihara et al. 2021). The absence of belzutifan efficacy in our model is thus puzzling. Actually, our study is, to the best of our knowledge, the first one that used a preclinical tumor model where tumor cells were of mouse origin. All previous studies used human cells or patient-derived xenografts (PDX). Hence, one hypothesis would be that the efficacy of PT2385 and belzutifan could be reduced on the murine HIF2a protein. This, however, would be very surprising as the PAS-B domains of the human and murine HIF2a proteins show 98% identity. Moreover, PT2385 has already shown some efficacy in other types of mouse models. Cheng et al. showed that HIF2a inhibitors are active in mice and rapidly impaired ventilatory responses to hypoxia, abrogating both ventilatory acclimatization and carotid body cell proliferative responses to sustained hypoxia (Cheng et al. 2020). Similarly, administration of a HIF-2-specific inhibitor inhibited neovascularization in an oxygen-induced retinopathy mouse model (Zhang et al. 2021). However, it is worth noting that the Sdhb−/− imCC display massive HIF2a accumulation which might limit the efficacy of its pharmacological inhibition. In agreement with our results, a recent in vitrostudy on a model of neuroblastoma PDX that also shows overexpression of HIF2a, found no effect on HIF2a target genes expression and no major impact on cell survival in vitroor tumor growth in vivoupon treatment with PT2385 (Persson et al. 2020). However, combining HIF1a downregulation by short hairpin and PT2385 treatment resulted in an enhanced effect of the drug, highlighting a potential compensatory mechanism by HIF1a. This mechanism also appears to be potentially involved in the resistance of glioblastoma cells treated with PT2385 (Renfrow et al. 2020). Importantly, HIF2a may possess unexplored ARNT-independent functions that could explain these discrepancies: for example, the c-Myc/Max complex is stabilized by HIF2a independently of the aryl hydrocarbon receptor nuclear translocator (ARNT), and contributes to HIF2a-mediated neoplastic progression (Gordan et al. 2007).
Nevertheless, preclinical data remain limited and a phase II study testing the efficacy and safety of belzutifan will soon be opened for patients with PPGLs of any genotype and hopefully provide some answers (NCT04924075).
So far, sunitinib appears to be the most effective treatment for reducing tumor growth in our model. These results are consistent with the promising preliminary data from the first randomized phase II FIRSTMAPP trial (Baudin et al. 2021). This trial included 78 patients, of whom 32% were SDHxmutated, and demonstrated an increased PFS of 8.9 months in the sunitinib (37.5 mg daily) group vs 3.6 months in the placebo group. Reasons for discontinuation were adverse events or tumor progression in respectively 14 and 64% of sunitinib-treated patients and 0 and 86% of patients treated with placebo. As a result, sunitinib, will probably become one of the first lines of treatment for metastatic PPGLs. Sunitinib has more a cytostatic than a cytotoxic action. Hence, tumor response or resistance may not be anticipated by conventional imaging prior to tumor shrinkage (Fournier et al. 2017).
We therefore focused on characterizing the antitumor response to sunitinib in our preclinical model. We observed a decrease in succinate levels measured by 1H-MRS following sunitinib treatment, which was detected prior to changes in tumor growth. These data may be put in perspectives with those published very recently on the decrease of 2-hydroxyglutarate in mice xenograft with IDH mutated glioma cells treated with several IDH1 inhibitors (Molloy et al. 2020, Wenger et al. 2020). Succinate measurement in vivo is particularly interesting and could directly be translated to evaluate the post-therapeutic tumor response in patients before tumor shrinkage, for example after cervical radiotherapy.
Like many preclinical models of PPGLs, our model has some undeniable limitations, which are rapid growth, lack of metastasis and the use of immunodeficient mice, reinforcing the need for further research in this area to improve it (Bayley & Devilee 2020). Despite these limitations, this study paves the way for future-targeted therapies in metastatic PPGL and suggests that sunitinib is the most beneficial therapy in this model, with succinate detection by 1H-MRS as a potential early metabolic biomarker of tumor response.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/ERC-22-0030.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
Funding
This work has received funding from the Cancer Research for Personalized Medicine – CARPEM project (Site de Recherche Intégré sur le Cancer – SIRIC), The Plan Cancer, Epigénétique et Cancer (EPIG201303 METABEPIC), The Paradifference Foundation and la Ligue Contre le Cancer (Equipe Labellisée). Sophie Moog is the recipient of a fellowship from la Fondation pour la Recherche Médicale FDM201806005916.
Author contribution statement
C Lussey-Lepoutre and J Favier jointly directed this work.
Acknowledgements
IACS-010759 was kindly provided by Dr Giulio Draetta from the Therapeutics Discovery Division at The University of Texas MD Anderson Cancer Center under an MTA.
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