Preprint
Case Report

This version is not peer-reviewed.

Molecular-Genetic and In Silico 3D Characterization of an Adamantinomatous Craniopharyngioma, the ‘Chameleon’ Among Pediatric Brain Tumors

Submitted:

11 July 2026

Posted:

13 July 2026

You are already at the latest version

Abstract
Background: Adamantinomatous craniopharyngiomas (ACPs) are congenital brain tumors that affect children and adults. Due to their location within the brain and their adhesion to surrounding structures they are difficult to treat. They are commonly associated with pituitary and hypothalamic dysfunction. The aim of this report is a detailed phenotypic and genotypic evaluation of a girl with ACP. Methods: Laboratory blood tests and magnetic resonance imaging (MRI) were performed. Histopathological investigations included staining with hematoxylin and eosin (H&E), and various antibodies. Genetics and bioinformatics tests comprised single nucleotide polymorphism (SNP) array, deoxyribonucleic acid (DNA) methylation array, next generation sequencing (NGS) and structural modelling of beta-catenin. Results: An 8.5-year-old girl presented to her general practitioner with gastrointestinal symptoms and was comprehensively investigated by a paediatric gastroenterologist. During the following 1.5 years she showed traits of sensory processing disorder and complained of mild headaches. Brain imaging revealed an adamantinomatous craniopharyngioma which was incompletely resected. Sequencing of the CTNNB1 gene demonstrated a tumorigenic variant, c.98C>G p.(Ser33Cys). Three-dimensional modeling of the Ser33Cys beta-catenin variant indicated a weaker interaction with β‑TrCP1 (β-transducin repeat containing E3 ubiquitin protein ligase 1), due to the impossibility to undergo phosphorylation at Ser33, leading to impaired beta-catenin ubiquitination, a possible cause of protein accumulation and tumorigenic progression. Conclusion: Pediatric ACP patients present with a wide range of symptoms which often results in diagnostic delay. No reliable biomarker exists for this disease, and magnetic resonance brain imaging is the investigation of choice. Next generation sequencing (NGS) is the preferred genetic test to identify the underlying somatic pathogenic variant.
Keywords: 
;  ;  ;  ;  ;  ;  ;  ;  ;  

1. Introduction

Craniopharyngiomas can be divided in adamantinomatous craniopharyngiomas (90%), affecting children between 5 and 15 years and adults between 45 and 60 years; and in papillary craniopharyngiomas (PCPs, 10%), affecting mostly adults between 40 and 55 years (Otte and Müller, 2021; Pfister et al, 2022). ACPs are slow-growing, non-cancerous epithelial tumours (WHO Grade 1) originating from cell remnants of the embryonic craniopharyngeal duct and Rathke’s pouch. They have an incidence of 0.5-2.5 per million population and account for less than 5% of all brain tumors (Karsonovich et al, 2026). Due to their initially non-specific clinical presentation, it can take several years before the diagnosis is made. Their proximity to the pituitary gland and hypothalamus leads to multiple hormone deficiencies which often worsen after treatment with surgery and/or radiotherapy (De Alcubierre et al, 2025; Zhou et al, 2021). In histological sections, tumor tissue typically stains positive for β-catenin, whose overall structure is represented in Figure 1, and negative for BRAF(V600E). By contrast, BRAF(V600E) is positive in PCP. ACP is caused by somatic driver mutations in the CTNNB1 gene on chromosome 3p22.1 (Sekine et al, 2002, Apps et al, 2020). Clinical management requires a multidisciplinary team including general paediatrician, endocrinologist, dietitian, ophthalmologist, neurooncologist, neuroradiologist and clinical psychologist. Patients require long-term follow up and close monitoring for relapse which occurs in 20 – 40% of cases. Overall, prognosis is good with a 30-year survival rate of up to 80% (Gan et al, 2023). Here, we present a young girl with ACP and panhypopituitarism who was investigated with biochemical (data not shown), radiological, histopathological, molecular-genetic and bioinformatics techniques.

2. Methods

1.1. Magnetic Resonance Imaging

Images were obtained on a GE HealthCare SIGNA Voyager 1.5T 70cm wide-bore MRI scanner using AIR Recon DL (AI-based reconstruction) and AIR coils. The following sequences were applied: T1W in coronal plane, T2W PROPPELLER in axial and sagittal planes, FLAIR PROPELLER in axial plane, DWI-ADC and SWAN. Slice thickness was 5 mm for all sequences except for SWAN which was 2.9 mm thick.

1.2. Histopathology and Immunohistochemistry

Standard tissue preparation and staining techniques were used for H&E, β-catenin, BRAF(V600E), CKC (AE1/AE3) and MGMT stains (Kazmi and Schuerch, 2022). Immunohistochemistry was carried out on an automated Roche BenchMark Ultra or Ultra Plus platform.

1.3. Single Nucleotide Polymorphism Array

DNA was extracted from patient blood leukocytes according to standard techniques and processed with Infinium CytoSNP-850K v1.4 Illumina BeadChip array (Illumina, San Diego, CA). Data were analyzed using the dedicated cytogenetics software BlueFuse Multi v4.5 (GRCh 38).

1.4. DNA Methylation Array

DNA was obtained from formalin-fixed, paraffin-embedded tumor curls (FFPE, tumor content 40-50%) and treated with sodium bisulphite (EZ DNA Methylation Kit, Zymo Research). Somatic DNA was further processed with the Infinium MethylationEPIC v2.0 Kit (Illumia, San Diego, CA). Data were sent for methylation profiling to Heidelberg Epignostix GmbH and analyzed with the CNS Tumor Methylation Classifier v12.8 (Capper et al, 2018).

1.5. Next Generation Sequencing

DNA was extracted from FFPE curls. Roche KAPA HyperCap Custom Probes (IDH1, IDH2, APC, CTNNB1, GNAS, H3-3A, H3-3B, BCOR, SMARCB1) were used for library preparation and Illumina NovaSeq for massive parallel sequencing by synthesis (SBS). DNA reads were interpreted with Mutect2-GATK (Broad Institute, Cambridge, MA) and Pindel (Wellcome Sanger Institute, Hinxton, UK).

1.6. In Silico Bioinformatic Analyses

The Ser33 to cysteine substitution was modeled in silico using both the structure of the Leu31–Thr40 β-catenin peptide fragment within the β-TrCP/Skp1/NRX-2776 ternary complex (PDB entry: 6M90) (Simonetta et al, 2019) and the AlphaFold-predicted model of full-length β-catenin (AF-P35222-F1-v6) (Jumper et al, 2021, Bertoni et al, 2025). The latter model was employed to validate the molecular dynamics results obtained for the short β-catenin peptide based on previously reported crystallographic data (Simonetta et al, 2019) and to avoid overfitting caused by the reduced length of the short peptide present in the X-ray structure. All modeling procedures were carried out in Coot 0.9.8.96 (Emsley et al, 2010). The resulting models were refined by simple molecular dynamics simulations using phenix.dynamics (Burnley et al, 2012) within the Phenix 2.0.5936 suite (Liebschner et al, 2019). Subsequent analyses, including bond distance measurements from the simulation models, rotamer evaluation according to minimal energy criteria, and figure preparation, were performed by PyMOL 2.5 (The PyMOL Molecular Graphics System, 2021).

3. Results

3.1. Case

An 8-year-old girl was referred to paediatric outpatients with a 6-month history of tiredness, nausea, abdominal pain and slow bowel movements. She took iron supplements for mild iron deficiency anaemia. On examination she looked extremely pale and had very fair hair, hypertelorism and diastemas. Weight and height were on the 9th centiles. She was referred to tertiary pediatric gastroenterology where she was extensively investigated with an abdominal MRI scan and endoscopies. Diagnoses of non-specific colitis and small intestinal bacterial overgrowth (SIBO) were made. The girl was referred to the regional genetics service who took detailed photographs and reviewed early childhood images. She was noted to have difficulties with sensory processing prompting involvement of primary mental health services (PMHS). Her school attendance dropped to 50%. One year later, she complained of intermittent headaches and sensitive scalp skin. Magnetic resonance imaging (Figure 2) and computed tomography (CT) of the brain revealed a large mass originating in the sella turcica. She was referred to the regional children’s hospital for further management. Preoperatively she was found to have secondary hypothyroidism and adrenal insufficiency which were treated with Levothyroxine and Hydrocortisone. Ophthalmology review revealed mild optic disc atrophy and restricted peripheral vision bilaterally. At the age of 10 years, she underwent a right pterional craniotomy and debulking of the tumor. Immunohistopathology was consistent with an ACP (Figure 3A-D). Postoperatively, she developed central diabetes insipidus with polyuria and polydipsia which was treated with Desmopressin. She gained weight rapidly (50th centile) caused by her increased appetite (hypothalamic hyperphagia) and steroid replacement therapy. Her post-surgery MRI brain scan demonstrated a high T1-weighted signal in the inferior sella turcica, likely to represent residual tumour tissue. However, a repeat pituitary MRI scan with contrast performed 4 months after surgery showed no significant residual disease. At 11 years of age, her weight gain slowed down, and she was commenced on daily subcutaneous growth hormone injections for growth hormone deficiency. The girl was referred to a dietitian and a clinical psychologist for advice and support.

3.2. SNP Array

SNP analysis detected a normal female profile [arr (X,1-22)] without clinically significant imbalances.

3.3. DNA Methylation Profiling

The copy number variation profile of the patient covering chromosomes 1 - 22, X, showed no evidence of copy number changes. No match was found among 184 tumor classes. The status of the MGMT promotor was unmethylated (Figure 4).

3.4. CTNNB1 Gene Sequencing

Sequencing of the CTNNB1 gene (NM_001904.4) identified an oncogenic variant, c.98C>G p.(Ser33Cys), with a variant allele frequency (VAF) of 6%. This variant is the cause of the excessive cell growth in this patient (ACP, ICD-O 9351/1).

3.5. In Silico Bioinformatic Analyses

Ser33 is located within the N-terminal domain of β-catenin (Figure 1), a highly flexible region that has not been fully structurally resolved in previous studies, including those of the full-length protein. Nevertheless, the serine residue at this position appears to play a key role in targeting the protein for proteasomal degradation, as Ser33, together with Ser37 and Thr41, is a phosphorylation site required for recognition by the SCF (Skp1–Cullin1–F-box) complex (Wu et al., 2003). The SCF complex is a multi-protein E3 ubiquitin ligase that mediates the ubiquitination of phosphorylated substrates, marking them for degradation by the 26S proteasome. In this complex, the F-box protein β-TrCP1 acts as the substrate recognition subunit, specifically binding phosphorylated degron motifs present in target proteins such as β-catenin (Bi et al., 2020; Baek et al., 2023; Colding-Christensen et al., 2023).
Figure 5A displays the complex structure of the solved Leu31–Thr40 β-catenin peptide fragment with the β-TrCP/Skp1/NRX-2776 ternary complex (PDB entry: 6M90) (Simonetta et al., 2019), where the location of Ser33 could be appreciated. Notably, NRX-2776 is a synthetic stabilizing ligand enhancing complex formation and facilitating structural characterization.
A focus on the interaction between the Leu31–Thr40 β-catenin peptide with β-TrCP (Figure 5B) shows that Ser33 is phosphorylated (pSer33) and, through this post-translational modification, it establishes a well-defined interaction network within the β-TrCP binding pocket, characterized by multiple hydrogen bonds with key residues such as Arg285, Tyr271, and Ser309. These residues directly participate in substrate binding and are conserved within the β-TrCP substrate recognition interface (Wu et al., 2003). In addition, they contribute to phospho-degron recognition by forming specific contacts with the negatively charged phosphate group, as the adjacent Asp 32. Thus, the phosphorylated serine 33 plays a central role in stabilizing the complex by promoting electrostatic and hydrogen-bonding interactions that ensure high-affinity and specific recognition, as already mentioned in literature (Wu et al., 2003).
The p.Ser33Cys variant was modeled in silico, as reported in the Methods section, based on the pSer33 b-catenin peptide complexed with β-TrCP (Figure 5C) and shows an altered binding mode to β-TrCP1 (Figure 5D). In detail, the substitution of Ser33 with cysteine disrupts the canonical interaction pattern, leading to increased distances between the peptide and the critical binding residues of β-TrCP1 (approximately 4.0 Å) and a significant reduction in stabilizing contacts as well as to a more relaxed relationship with the ubiquitination complex if compared to the phospho-Ser33 containing peptide. The Ser33Cys variant peptide behaviour was confirmed also for the structure modeled starting from the AlphaFold prediction of the full-length protein. The structural rearrangement highlights how the absence of phosphorylation at position 33 could compromise the molecular recognition by β-TrCP, ultimately affecting the stability and efficiency of the interaction. Namely, the destruction motif (also known as the DSGXXS phospho-degron sequence) of β-catenin is no longer able to be recognized and be bound by the β propeller of β-TrCP1 (Winston al., 1999), possibly leading to the accumulation of β-catenin and the failure of its ubiquitination.

4. Discussion

Headaches and vomiting caused by raised intracranial pressure, and visual impairment are the commonest symptoms of children with ACP. Our patient was atypical as she complained of abdominal pain, nausea and delayed defecation which triggered the referral to a paediatric gastroenterologist. Her tiredness was attributed to mild iron deficiency anaemia. Other signs and symptoms observed in this group of patients include unexplained variations in weight, height or appetite, early or delayed onset of puberty, polydipsia, polyuria, sleep disturbance, intolerance to low temperatures, behaviour difficulties, hypotension, muscle weakness and seizures (Child Growth Foundation, 2000). The time from onset of symptoms to diagnosis of ACP can vary from 8 months to 8 years (Children’s Cancer and Leukaemia Group, 2021). Gross total resection (GTR) of the tumor is the preferred therapeutic option. However, this goal is frequently unachievable due to its sticky, oily nature and proximity to vital neurovascular structures. Instead, subtotal resection (STR), which was performed in this patient, can be combined with radiation therapy if deemed necessary. In children proton beam therapy is superior to radiotherapy as the brain tumor can be targeted more precisely, and there is no associated exit dose that damages healthy tissue (Bidur and Prasad, 2015; Graffeo et al, 2018). During a psychological assessment three months post-surgery our patient described her quality of life (QoL) as improved compared to pre-surgery. Steinbok (2015) reports long-term QoL based on questionnaire survey results as good in 50% of patients. ACP is considered a chronic disease, and survivors require annual MRI brains scans for at least 10 years (European Society for Paediatric Oncology, 2021).
Different state-of-the-art genetics and bioinformatics methods were applied in this case. DNA methylation is an epigenetic process that impacts on gene expression. Through addition of a methyl group to the cytosine ring at a cytosine-phosphate-guanine (CpG) island, transcription factors (TFs) can no longer bind to DNA, and the respective gene is inactivated (‘silenced’). Genome-wide methylation profiles, specifically hypomethylation, and the methylation status of tumor-specific genes are important for cancer diagnostics (Ibrahim et al, 2022; Marrero-Gutiérrez et al, 2025). Methylated MGMT and/or low expression of MGMT (O-6-methylguanine-methyltransferase) make ACPs more sensitive to treatment with the alkylating prodrug Temozolomide (Zuhur et al, 2011). Cavalheiro and co-workers (2026) reported a teenage boy with recurrent ACP who underwent treatment with monthly 7-day courses of oral Temozolomide for 1 year during which his large tumor shrank by 50%. It is noteworthy that Temozolomide has significant side effects. Therefore, it cannot be considered as first-line treatment for patients with ACP. Our patient’s MGMT promotor was unmethylated. Using FFPE curls instead of flash-frozen tumor tissue can lead to a falsely negative genome wide methylation profiling result.
The human CTNNB1 gene has 16 exons and spans ca. 65kb (3:41194741-41260096, GRCh38). Exons 1 and 16 contain untranslated regions (UTRs). Germline loss of function mutations of this gene cause autosomal dominant exudative vitreoretinopathy type 7 (OMIM 617572) and neurodevelopmental disorder with spastic diplegia and visual defects (OMIM 615075). Somatic, de novo missense mutations of CTNNB1 cause ACP, colorectal cancer, hepatocellular carcinoma, medulloblastoma, ovarian cancer and pilomatricoma (Foreman et al, 2023; Gao et al, 2017). The pathogenic single nucleotide variant identified in this patient (Chr3: 41224610, GRCh38) has been described before in different cancerous and non-cancerous tumors (Koch et al, 2001; Campanini et al, 2010; Cani et al, 2011; Ohata et al, 2018; Seki-Soda et al, 2022; Fonseca YG et al, 2026; Rheki et al, 2026). It resides in exon 3 of CTNNB1 which is a hotspot for tumor-inducing variants (Landrum et al, 2016; Kim and Jeong, 2019).The CTNNB1 protein (catenin beta 1, beta-catenin, β-catenin) belongs to the armadillo family of proteins which have important structural as well as functional roles. The name stems from the armadillo (ARM) repeat domains which consist of 40-45 amino acids that form 3 alpha helices arranged in a hairpin structure. They have been likened to the flexible armor of the placental mammal armadillo and facilitate intercellular adhesion (Hatzfeld, 1999). Catenin beta 1 is 781 amino acids (aa) long and has a molecular mass of 85.5 kDa. It can be divided in 3 segments (Figure 1): an N-terminal domain of ca. 150 aa which contains phosphorylation sites, a core domain with 12 ARM repeats (524 aa) and a C-terminal domain of ca. 100 aa which acts as a transcription transactivation domain (TAD). The serin to cysteine conversion observed in our patient is located within the N-terminal domain of β-catenin (Seal et al, 2026; Stelzer et al, 2016).
Beta-catenin is a subunit of the cadherin protein complex and plays an important role in the Wnt (wingless/int-1) signalling pathway which regulates embryonic development, cell determination and cell migration. In the absence of a Wnt ligand, β-catenin binds to the destruction complex and is degraded. The degradation can be triggered by β-TrCP binding to a phosphorylated form of b-catenin, ubiquitination and proteosome targeting. In silico modeling and molecular dynamics simulations highlight that the Ser33-to-Cys substitution markedly disrupts the canonical binding geometry within the β-TrCP pocket, resulting in suboptimal positioning of the b-catenin moiety, increased intermolecular distances (~4.0 Å), and a substantial loss of stabilizing interactions, thereby emphasizing how the absence of pSer33 severely compromises β-TrCP recognition and binding efficiency, thereby its degradation.
In the presence of a Wnt ligand or in the absence of a phosphorylation reaction, β-catenin accumulates in the cytosol and translocates to the nucleus where it activates the transcription of various genes. If β-catenin is defective, it becomes resistant to degradation and switches on nuclear genes in an unregulated, tumorigenic fashion (Campanini et al, 2023; Lainšček et al, 2025). Based on a multi-omics analysis Wang et al. (2023) distinguish 3 molecular ACP subgroups (Wnt, ImA and ImB) where the Wnt group has longer event-free survival and where the ImA/ImB groups show a better response to immune checkpoint blockade (Gonzalez-Meljem et al, 2025; Cacciotti et al, 2020).
To our knowledge, this is the first detailed case report of a child with ACP and c.98C>G p.(Ser33Cys). The patient presented with atypical, chronic symptoms providing further evidence for the ‘chameleon-like’ nature of this rare brain tumor. Every ACP should be genetically confirmed by NGS, in addition to immunohistochemical staining. 3D modeling suggests that the variant determines a failure of b-catenin degradation with the consequence of its possible accumulation and translocation to the nucleus for activation of Wnt genes. Novel treatment with immune checkpoint inhibitors (ICI) may become available in future for patients with ACP.

Ethics Approval

Not required.

Conflicts of Interest

None declared.

Funding

None received.

Authors’ contributions

Conceptualization: E.-M.S. Investigation: B.F., C.S., M.Pi., N.H., J.R., R.B., M.P., G.B. and M.B. Writing – original draft preparation: E.-M.S. (lead), C.S., M.P., and M.B. Writing – review and editing: all authors.

Acknowledgments

We would like to thank the patient and her parents for consenting to this publication. We are grateful to the following healthcare professionals and scientists: Kasim Ahmad, John Apps, Chamila Balagamalage, Paul Bellis, Simon Bomken, David Butteriss, David Campbell, Timothy Cheetham, Alan Connor, Fiona Court, Gavin Cuthbert, Gail Dovey-Pearce, Jessie Ghansah, Angharad Goodman, Shaun Haigh, Karen Halsey, Fiona Harding, Rebecca Hill, Laura Ions, Lisa Irving, Marcin Kornatowski, Julia Mason, Carter McClurg, Thomas McDonald, Rebecca Mcdonnell, Dipayan Mitra, Anirban Mukhopadhyay, Aamir Munir, Stephanie Needham, Julie Norris, Emily Parsons, Emma Riley, Stephen Talks, Wan Norshuhada Wan Montil, Laura Weir, Philip White.

Figure Legends

Figure 1.Overall Structure of β-catenin, showing both the two disordered N and C-terminal domains (blue and cyan, respectively), and the intermediate domain, also known as armadillo repeat domain (yellow). Ser33 is represented by sticks and indicated by the arrow. Image rendered with PyMOL 2.5 (Schrödinger Inc, New York, NY, USA) using the atomic coordinates provided by the AlphaFold prediction of the full-length β-catenin (AF-P35222-F1-v6).
Figure 2. T2-weighted sagittal MRI brain scan shows a large sellar (se) and suprasellar (su) mass lesion with predominant cystic appearance measuring ca. 4.5 cm in maximum dimension. The sellar component is slightly heterogeneous and contains thin septations internally. There are areas of calcification in the periphery. The lesion causes significant mass effect on optic tracts, optic chiasm, genu of corpus callosum, right side of hypothalamus and fornix. The cavernous internal carotid arteries are displaced laterally. Mass effect is also noted on bifurcation of internal carotid arteries and on middle cerebral arteries. The neoplasm is projecting into the frontal lobes in the midline and causing effacement of the suprasellar cistern.
Figure 3. Composite photograph showing microscopic slices of resected tumor tissue with features characteristic of ACP: A – H&E stain 40x magnified; B – H&E stain 400x; C - β-catenin stain 400x; D - BRAF(V600E) 400x. Cytokeratin stain (CKC, A1/A3) was positive for epithelial cells (not shown).
Figure 4. Result of patient’s MGMT promotor status (courtesy of Heidelberg Epignostix GmbH, see Discussion)
Figure 5. Structural effect of Ser33Cys variant on β-Catenin binding to β-TrCP1. A) Complex between Ser33 β-catenin peptide (colored purple, with pSer33 shown as sticks), ubiquitin ligase β-TrCP1 β-propeller (shown as surface and colored magenta), and binding enhancer molecule NRX-2776 (white sticks) (pdb: 6M90). B) β-Catenin-β-TrCP1 interaction shows a hydrogen bond network stabilizing pSer33 and adjacent Asp32. C) Superposition of pSer33 β-Catenin peptide crystal structure with the Ser33Cys models obtained by 3D modelling of the Leu31–Thr40 peptide from the β-TrCP/Skp1/NRX-2776 ternary complex (PDB entry: 6M90) and by AlphaFold predicted model (full-length β-catenin - AF-P35222-F1-v6). D) Structural rearrangement of the interaction network between the modelled Cys33 β-Catenin peptide and β-TrCP1. Images were rendered with PYMOL 2.5 (Schrödinger Inc, New York, NY, USA).

References

  1. Apps, J.R.; Stache, C.; Gonzalez-Meljem, J.M.; et al. CTNNB1 mutations are clonal in adamantinomatous craniopharyngioma. Neuropathol. Appl. Neurobiol. 2020, 46(5), 510–514. [Google Scholar] [CrossRef] [PubMed]
  2. Baek, K.; Scott, D.C.; Henneberg, L.T.; King, M.T.; Mann, M.; Schulman, B.A. Systemwide disassembly and assembly of SCF ubiquitin ligase complexes. Cell 2023, 186(9), 1895–1911.e21. [Google Scholar] [CrossRef] [PubMed]
  3. Bertoni, D.; Tsenkov, M.; Magana, P.; Nair, S.; Pidruchna, I.; Lima Afonso, M.Q.; Midlik, A.; Paramval, U.; Lawal, D.; Tanweer, A.; Last, M.; Patel, R.; Laydon, A.; Lasecki, D.; Dietrich, N.; Tomlinson, H.; Žídek, A.; Green, T.; Kovalevskiy, O.; Lau, A.; Kandathil, S.; Bordin, N.; Sillitoe, I.; Mirdita, M.; Jones, D.; Orengo, C.; Steinegger, M.; Fleming, J.R.; Velankar, S. AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage. Nucleic Acids Res. 2026, 54(D1), D358–D362. [Google Scholar] [PubMed]
  4. Bi, Y.; Cui, D.; Xiong, X.; Zhao, Y. The characteristics and roles of β-TrCP1/2 in carcinogenesis. FEBS J. 2021, 288(11), 3351–3374. [Google Scholar] [PubMed]
  5. Bidur, K.C.; Prasad, D.U. Outcome following surgical resection of craniopharyngiomas: A case series. Asian J. Neurosurg. 2017, 12(3), 514–518. [Google Scholar] [CrossRef] [PubMed]
  6. Burnley, B.T.; Afonine, P.V.; Adams, P.D.; et al. Modelling dynamics in protein crystal structures by ensemble refinement. Elife 2012, 1, e00311. [Google Scholar] [CrossRef] [PubMed]
  7. Cacciotti, C.; Choi, J.; Alexandrescu, S.; et al. Immune checkpoint inhibition for pediatric patients with recurrent/refractory CNS tumors: a single institution experience. J. Neurooncol 2020, 149(1), 113–122. [Google Scholar] [CrossRef] [PubMed]
  8. Campanini, M.L.; Colli, L.M.; Paixao, B.M.; et al. CTNNB1 gene mutations, pituitary transcription factors, and MicroRNA expression involvement in the pathogenesis of adamantinomatous craniopharyngiomas. Horm. Cancer 2010, 1(4), 187–196. [Google Scholar] [CrossRef] [PubMed]
  9. Campanini, M.L.; Almeida, J.P.; Martins, C.S.; et al. The molecular basis of craniopharyngiomas. Arch. Endocrinol. Metab. 2023, 67(2), 266–275. [Google Scholar] [PubMed]
  10. Cani, C.M.; Matushita, H.; Carvalho, L.R.; et al. PROP1 and CTNNB1 expression in adamantinomatous craniopharyngioma with or without β-catenin mutations. Clinics (Sao Paulo) 2011, 66(11), 1849–1854. [Google Scholar] [CrossRef] [PubMed]
  11. Capper, D.; Jones, D.T.; Sill, M.; et al. DNA methylation-based classification of central nervous system tumours. Nature 2018, 555(7697), 469–474. [Google Scholar] [CrossRef] [PubMed]
  12. Cavalheiro, S.; Pavon, L.F.; de Farias, C.B.; et al. Evaluating temozolomide for pediatric adamantinomatous craniopharyngiomas using microspheroid-based drug screening. Child’s Nerv. Syst. 2026, 42(1), 89. [Google Scholar] [CrossRef]
  13. Child Growth Foundation. Series No. 13: Craniopharyngioma - A Guide for Parents and Patients (September 2000). Available online: https://childgrowthfoundation.org/wp-content/uploads/2018/07/13_Craniopharyngioma_-_A_Guide.pdf (accessed on 14/07/2026).
  14. Children’s Cancer and Leukaemia Group (CCLG). Management of children and young people with craniopharyngioma: summary guideline (October 2021). Available online: https://www.cclg.org.uk/sites/default/files/2025-03/craniopharyngioma-guidelines_summary_version.pdf (accessed on 14/07/2026).
  15. Colding-Christensen, C.S.; Kakulidis, E.S.; Arroyo-Gomez, J.; Hendriks, I.A.; Arkinson, C.; Fábián, Z.; Gambus, A.; Mailand, N.; Duxin, J.P.; Nielsen, M.L. Profiling ubiquitin signalling with UBIMAX reveals DNA damage- and SCFβ-Trcp1-dependent ubiquitylation of the actin-organizing protein Dbn1. Nat. Commun. 2023, 14(1), 8293. [Google Scholar] [CrossRef] [PubMed]
  16. De Alcubierre, D.; Feola, T.; Puliani, G.; et al. Endocrine and metabolic consequences of childhood-onset craniopharyngioma during the transition age: A literature review by the TALENT study group. Rev. Endocr. Metab. Disord. 2025, 26(6), 989–1008. [Google Scholar] [CrossRef] [PubMed]
  17. Emsley, P.; Lohkamp, B.; Scott, W.G.; et al. Features and development of Coot. Acta Crystallogr. D. Biol. Crystallogr. 2010, 66 Pt 4, 486–501. [Google Scholar] [CrossRef] [PubMed]
  18. European Society for Paediatric Oncology (SIOP Europe); Brain Tumour Group. Craniopharyngioma: Standard Clinical Practice Recommendations (13/11/21). Available online: https://siope.eu/media/documents/escp-craniopharyngioma.pdf (accessed on 14/07/2026).
  19. Fonseca, Y.G.; Bastos, V.C.; Moreira, R.G.; et al. Expanding the molecular characterization of adenoid ameloblastoma by assessing a panel of oncogenes and tumor suppressor genes. Mod. Pathol. 2026, 39(1), 100920. [Google Scholar] [CrossRef] [PubMed]
  20. Foreman, J.; Perrett, D.; Mazaika, E.; et al. DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data. Annu Rev. Genom. Hum. Genet 2023, 24, 151–176. [Google Scholar] [CrossRef]
  21. Gan, H.W.; Morillon, P.; Albanese, A.; et al. National UK guidelines for the management of paediatric craniopharyngioma. Lancet Diabetes Endocrinol. 2023, 11(9), 694–706. [Google Scholar] [CrossRef] [PubMed]
  22. Gao, C.; Wang, Y.; Broaddus, R.; et al. Exon 3 mutations of CTNNB1 drive tumorigenesis. Oncotarget 2017, 9(4), 3492–5508. [Google Scholar] [CrossRef]
  23. Gonzalez-Meljem, J.M.; Cao, L.; Apps, J.R.; et al. Decoding craniopharyngioma: From mechanisms to therapy. Best Pract. Res. Clin. Endocrinol. Metab. 2025, 39(5), 102051. [Google Scholar] [CrossRef] [PubMed]
  24. Graffeo, C.S.; Perry, A.; Link, M.J.; et al. Pediatric Craniopharyngiomas: A Primer for the Skull Base Surgeon. J. Neurol. Surg. B Skull Base 2018, 79(1), 65–80. [Google Scholar] [CrossRef] [PubMed]
  25. Hatzfeld, M. The armadillo family of structural proteins. Int. Rev. Cytol. 1999, 186, 179–224. [Google Scholar] [PubMed]
  26. Ibrahim, J.; Op de Beeck, K.; Fransen, E.; et al. Genome-wide DNA methylation profiling and identification of potential pan-cancer and tumor-specific biomarkers. Mol. Oncol. 2022, 16(12), 2432–2447. [Google Scholar] [CrossRef] [PubMed]
  27. Jumper, J.; Evans, R.; Pritzel, A.; et al. Highly accurate protein structure prediction with AlphaFold. Nature 2021, 596, 583–589. [Google Scholar] [CrossRef] [PubMed]
  28. Karsonovich, T.; Shafiq, I.; Mesfin, F.B. Craniopharyngioma. In StatPearls [Internet]; StatPearls Publishing: Treasure Island (FL), 2026 Jan. 2025 Feb 15. [Google Scholar]
  29. Kazmi, A.J.; Schuerch, C. Central Nerve System. In Handbook of Practical Immunohistochemistry; Lin, F., Prichard, J.W., Liu, H., Wilkerson, M.L., Eds.; Springer: Cham, 2022. [Google Scholar]
  30. Kim, S.; Jeong, S. Mutation Hotspots in the β-Catenin Gene: Lessons from the Human Cancer Genome Databases. Mol. Cells 2019, 42(1), 8–16. [Google Scholar] [CrossRef] [PubMed]
  31. Koch, A.; Waha, A.; Tonn, J.C.; et al. Somatic mutations of WNT/wingless signalling pathway components in primitive neuroectodermal tumors. Int. J. Cancer 2001, 93(3), 445–449. [Google Scholar] [CrossRef] [PubMed]
  32. Lainšček, D.; Forstnerič, V.; Miroševič, S. CTNNB1 syndrome mouse models. Mamm. Genome 2025, 36(2), 390–402. [Google Scholar] [CrossRef] [PubMed]
  33. Landrum, M.J.; Lee, J.M.; Benson, M.; et al. ClinVar: public archive of interpretation of clinically relevant variants. Nucleic Acids Res. 2016, 44(D1), D862–868. [Google Scholar] [PubMed]
  34. Liebschner, D.; Afonine, P.V.; Baker, M.L.; Bunkóczi, G.; Chen, V.B.; Croll, T.I.; Hintze, B.; Hung, L.W.; Jain, S.; McCoy, A.J.; Moriarty, N.W.; Oeffner, R.D.; Poon, B.K.; Prisant, M.G.; Read, R.J.; Richardson, J.S.; Richardson, D.C.; Sammito, M.D.; Sobolev, O.V.; Stockwell, D.H.; Terwilliger, T.C.; Urzhumtsev, A.G.; Videau, L.L.; Williams, C.J.; Adams, P.D. Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix. Acta Cryst. D. 2019, 75, 861–877. [Google Scholar] [CrossRef]
  35. Marrero-Gutiérrez, J.; Bueno, A.C.; Martins, C.S.; et al. Methylation and gene expression patterns in adamantinomatous craniopharyngioma highlight a panel of genes associated with disease progression-free survival. Front Endocrinol. 2025, 16, 1585618. [Google Scholar] [CrossRef]
  36. Ohata, Y.; Kayamori, K.; Yukimori, A.; et al. A lesion categorized ghost cell odontogenic carcinoma and dentinogenic ghost cell tumor with CTNNB1 mutation. Pathol. Int. 2018, 68(5), 307–312. [Google Scholar] [CrossRef] [PubMed]
  37. Otte, A.; Müller, H.L. Childhood-onset craniopharyngioma. J. Clin. Endocrinol. Metab. 2021, 106(10), e3820–e3836. [Google Scholar] [CrossRef] [PubMed]
  38. Pfister, S.M.; Reyes-Múgica, M.; Chan, J.K.; et al. A Summary of the Inaugural WHO Classification of Pediatric Tumors: Transitioning from the Optical into the Molecular Era. Cancer Discov. 2022, 12(2), 331–355. [Google Scholar] [PubMed]
  39. Rekhi, B.; Misra, B.K.; Madiwale, C.; et al. A suboccipital pseudoendocrine sarcoma showing CTNNB1 exon 3 c.98C>G, CTNNB1 p.S33C mutation in an adult male patient treated for olfactory meningioma: an uncommon report of a provisional soft tissue neoplasm. Patholgy 2026, 58(1), 113–116. [Google Scholar] [CrossRef]
  40. Seal, R.L.; Braschi, B.; Gray, K.; et al. Genenames.org: the HGNC and PGNC resources in 2026. Nucleic Acids Res. 2026, 54(D1), D1098–1107. [Google Scholar] [PubMed]
  41. Sekine, S.; Shibata, T.; Kokubu, A.; et al. Craniopharyngiomas of adamantinomatous type harbor beta-catenin gene mutations. Am. J. Pathol. 2002, 161(6), 1997–2001. [Google Scholar] [CrossRef] [PubMed]
  42. Seki-Soda, M.; Sano, T.; Matsumura, N.; et al. Ghost cell odontogenic carcinoma arising in dentinogenic ghost cell tumor with next-generation sequencing cancer panel analysis: A case report. Oral Surg. Oral Med. Oral Pathol. Oral Radiol. 2022, 134(3), e58–e65. [Google Scholar] [CrossRef] [PubMed]
  43. Simonetta, K.R.; Taygerly, J.; Boyle, K.; et al. Prospective discovery of small molecule enhancers of an E3 ligase-substrate interaction. Nat. Commun. 2019, 10, 1402. [Google Scholar] [CrossRef] [PubMed]
  44. Steinbok, P. Craniopharyngioma in children: Long-term Outcomes. Neurol. Med. Chir. 2015, 55(9), 722–726. [Google Scholar] [CrossRef]
  45. Stelzer, G.; Rosen, N.; Plaschkes, I.; et al. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. Curr. Protoc. Bioinform. 2016, 54, 1.30.1–1.30.33. [Google Scholar] [CrossRef]
  46. Wang, X.; Zhao, C.; Lin, J.; et al. Multi-omics analysis of adamantinomatous craniopharyngiomas reveals distinct molecular subgroups with prognostic and treatment response significance. Chin. Med. J. (Engl) 2024, 137(7), 859–870. [Google Scholar] [PubMed]
  47. Winston, J.T.; Strack, P.; Beer-Romero, P.; Chu, C.Y.; Elledge, S.J.; Harper, J.W. The SCFbeta-TRCP-ubiquitin ligase complex associates specifically with phosphorylated destruction motifs in IkappaBalpha and beta-catenin and stimulates IkappaBalpha ubiquitination in vitro. Genes Dev. 1999, 13(3), 270–83. [Google Scholar] [CrossRef] [PubMed]
  48. Wu, G.; Xu, G.; Schulman, B.A.; Jeffrey, P.D.; Harper, J.W.; Pavletich, N.P. Structure of a beta-TrCP1-Skp1-beta-catenin complex: destruction motif binding and lysine specificity of the SCF(beta-TrCP1) ubiquitin ligase. Mol. Cell 2003, 11(6), 1445–56. [Google Scholar] [CrossRef] [PubMed]
  49. Zhou, Z.; Zhang, S.; Hu, F. Endocrine disorders in patients with craniopharyngioma. Front Neurol. 2021, 12, 737743. [Google Scholar] [CrossRef] [PubMed]
  50. Zuhur, S.S.; Müslüman, A.M.; Tanik, C.; et al. MGMT immunoexpression in adamantinomatous craniopharyngioma. Pituitary 2011, 14(4), 323–327. [Google Scholar] [CrossRef] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2026 MDPI (Basel, Switzerland) unless otherwise stated

Accessibility

Disclaimer

Terms of Use

Privacy Policy

Privacy Settings