Schinzel-Giedion syndrome (SGS) is a rare developmental disorder characterized by multiple malformations, severe neurological alterations and increased risk of malignancy. SGS is caused by de novo germline mutations clustering to a 12bp hotspot in exon 4 of SETBP1. Mutations in this hotspot disrupt a degron, a signal for the regulation of protein degradation, and lead to the accumulation of SETBP1 protein. Overlapping SETBP1 hotspot mutations have been observed recurrently as somatic events in leukemia. We collected clinical information of 47 SGS patients (including 26 novel cases) with germline SETBP1 mutations and of four individuals with a milder phenotype caused by de novo germline mutations adjacent to the SETBP1 hotspot. Different mutations within and around the SETBP1 hotspot have varying effects on SETBP1 stability and protein levels in vitro and in in silico modeling. Substitutions in SETBP1 residue I871 result in a weak increase in protein levels and mutations affecting this residue are significantly more frequent in SGS than in leukemia. On the other hand, substitutions in residue D868 lead to the largest increase in protein levels. Individuals with germline mutations affecting D868 have enhanced cell proliferation in vitro and higher incidence of cancer compared to patients with other germline SETBP1 mutations. Our findings substantiate that, despite their overlap, somatic SETBP1 mutations driving malignancy are more disruptive to the degron than germline SETBP1 mutations causing SGS. Additionally, this suggests that the functional threshold for the development of cancer driven by the disruption of the SETBP1 degron is higher than for the alteration in prenatal development in SGS. Drawing on previous studies of somatic SETBP1 mutations in leukemia, our results reveal a genotype-phenotype correlation in germline SETBP1 mutations spanning a molecular, cellular and clinical phenotype.
Schinzel-Giedion syndrome (SGS; OMIM 269150) is a rare developmental disorder characterized by multiple malformations including midface hypoplasia, cardiac defects, hydronephrosis and skeletal abnormalities [1–3]. This clinically recognizable syndrome was the first dominant disorder for which the underlying genetic cause was identified by whole exome sequencing [4]. In 12 of 13 unrelated individuals with this disorder, we identified germline de novo mutations in SETBP1 clustering to a hotspot of 12 base pairs coding for residues 868 to 871 of the SETBP1 protein [4]. Interestingly, shortly after the identification of germline de novo mutations in SETBP1 as the cause of SGS, overlapping somatic mutations in SETBP1 were reported in several types of myeloid malignancies [5–7]. This dual role in cancer and development is not unique to SETBP1; a growing number of genes in which germline mutations cause developmental disorders, such as HRAS, ASXL1, EZH2 and FGFR2, are also known to harbor overlapping somatic mutations which drive the development of cancer [8]. This genetic overlap is not entirely unexpected; higher rates of childhood cancer have been identified in individuals with birth defects and vice versa [9–11], a finding which is thought to be the consequence of abnormalities in molecular pathways shared between embryogenesis and cancer development [12,13]. The precise function of SETBP1, which encodes the SET-binding protein 1 (OMIM 611060), is yet to be discovered and, as a result, the molecular consequences of SETBP1 mutations remain largely unknown. However, the clustering of all germline SETBP1 mutations identified in SGS to a single region and their overlap with the somatic events identified in myeloid malignancies support a gain-of-function effect on the SETBP1 protein. This recurrently mutated region of the protein is highly conserved and has been identified as a degron signal targeted by the SCF-βTrCP1 E3 ligase [5]. A degron is a peptide sequence that is recognized and bound by a component of the ubiquitin-proteasome pathway, thereby initiating degradation of the protein by ubiquitination [14]. As a result, mutations localizing to the degron in SETBP1 disrupt binding by the βTrCP1 E3 ligase, increase protein stability by interfering with ubiquitination [15] and ultimately lead to accumulation of SETBP1 protein in cells [5]. While the molecular consequences of germline SETBP1 mutations are poorly understood, somatic mutations disrupting the SETBP1 degron lead to increased proliferation in myeloid progenitors [7], possibly mediated by effects on its interaction partner SET, phosphorylation of PP2A and transcriptional activation of HOXA9 and HOXA10 [5,16,17]. Additional clinical and functional investigation is warranted to gain more understanding about the molecular mechanisms of SGS. Here we present the clinical characterization of the largest cohort of individuals with genetically confirmed SGS and establish genotype-phenotype correlations for SGS. Given the occurrence of overlapping germline and somatic SETBP1 mutations, we compare the mutations in SGS and leukemia to identify genetic and functional differences between SETBP1 mutations in both conditions.
Classic SGS is caused by mutations within four residues of the SETBP1 degron (D868, S869, G870 and I871, Fig 1A and 1B), constituting the critical consensus sequence of the degradation signal [18] (from here on, referred to as the canonical degron). Since the initial description of 12 mutation-positive cases [4], we have gathered clinical details of 26 additional individuals with SGS genetically confirmed by the presence of de novo mutations in SETBP1 (see Table 1 and S1 Table). In addition, we present three patients with a milder phenotype variably overlapping with SGS and secondary to novel mutations in SETBP1 affecting highly conserved residues in close proximity to the canonical degron (current cases 27–29, with mutations in residues E862, S867 and T873 shown in green in Fig 1B). We report on the clinical features observed in our cohort in addition to previously published mutation-positive cases to further delineate this disorder (n = 51 individuals). Mutations within the canonical degron of SETBP1 disrupt its interaction with βTrCP1, increasing protein stability and SETBP1 levels [5,15] but the effect of SETBP1 mutations outside the canonical degron on protein stability is unknown. Clear differences in the severity of the phenotype resulting from germline SETBP1 mutations within and outside the canonical degron suggest a difference in the effect of the mutations depending on their localization. Therefore, we performed the functional characterization of the most frequent SETBP1 mutations observed within the canonical degron and causative for classic SGS (D868N, S869N, G870S and I871T) as well as one mutation outside the canonical degron leading to atypical SGS (E862K).
The aims of our study were: to present the phenotype of the largest cohort of individuals with SGS and germline SETBP1 mutations, establish genotype-phenotype correlations for germline SETBP1 mutations and, by using these and previous findings from cancer research, provide insight into the molecular mechanism of SGS. We present the clinical features of 47 individuals with “classic” SGS caused by germline mutations in SETBP1 affecting the canonical degron (D868-I871). All mutations were found de novo in the affected proband, although two individuals in our cohort were siblings carrying the same disease-causing mutation in residue I871. This recurrence suggests parental mosaicism as the origin of the mutation but we were unable to detect the mutation in DNA from parental blood samples by deep sequencing. Interestingly, the first published report of SGS in 1978 described two siblings with the phenotype, which initially led to believe that this disorder was inherited autosomal recessively [1]. SGS is a rare but clinically recognizable developmental disorder consisting of typical facial features, neurological alterations, various congenital anomalies and increased risk of malignancy. Neurological problems often encountered include severe intellectual disability, intractable epilepsy and cerebral blindness and deafness. Individuals with SGS frequently present with congenital anomalies in multiple organ systems including heart defects, kidney and/or genital malformations and bone abnormalities. Most affected individuals do not survive past childhood due to the severity of this disorder. Four additional individuals presented a developmental phenotype with clinical characteristics overlapping classic SGS caused by atypical SETBP1 mutations in close proximity to the canonical degron. SGS is often recognized and diagnosed based on the reminiscent clinical features and, interestingly, the amount of clinical overlap with SGS seems to be related to the position of the mutation in relation to the canonical degron. Both individuals carrying a mutation affecting SETBP1 residue S867 had the characteristic facial features of SGS, genital anomalies and seizures but no hydronephrosis. The absence of hydronephrosis in these cases is remarkable, since it is considered one of the hallmark features of SGS [51]. However, hydronephrosis was also absent in two individuals with mutations within the degron, suggesting that it should not be recognized as an obligatory feature for the diagnosis of SGS. Although both individuals with an atypical SETBP1 mutation in residues E862 and T873 share some features with SGS, they would not have been classified as typical SGS. In both these individuals, the mutations were detected by whole exome sequencing and lead to the diagnosis of atypical SGS a posteriori. Therefore, as Carvalho et al. recently suggested [21], previously proposed clinical diagnostic criteria for SGS may not be applicable for these cases. Due to the limited number of atypical cases, we cannot draw any conclusions on the survival and progress of the disease in these cases. Somatic SETBP1 mutations observed in myeloid malignancies have been shown to have a gain-of-function effect on the SETBP1 protein, leading to decreased binding of the βTrCP1 and increased protein levels [5]. This gain-of-function mechanism seems to also pertain to germline SETBP1 mutations, as we observe that cells of individuals with germline SETBP1 mutations have increased levels of SETBP1 protein. Furthermore, recent reports of germline chromosomal deletions and truncating mutations in SETBP1 show that loss-of-function mutations in this gene cause a completely different phenotype from SGS [52]. Clinically, individuals with these genetic lesions present a phenotype characterized by a complete lack of expressive speech with intact receptive language abilities, decreased fine motor skills, subtle dysmorphisms and hyperactivity and autistic traits [53]. The distribution of germline SETBP1 mutations within the canonical degron differs from that of somatic events; mutations affecting residue I871 are significantly more frequent in the germline than somatically. Furthermore, germline SETBP1 mutations are on average less disruptive to the βTrCP1-SETBP1 interaction than somatic mutations. Notably, the isoleucine at position 871 is a variable residue within the SETBP1 degron, which is defined as “DpSGφXpT” where φ (in this case, isoleucine) represents a hydrophobic amino acid and X stands for any residue [18]. Previous studies of the structure of the conserved destruction motif in β-catenin show that the isoleucine residue in the degron has a small role in the interaction with βTrCP1, while the first three residues of the degron and the asparagine in particular are essential for protein-protein binding [18]. Thus, the molecular differences observed between germline and somatic SETBP1 mutations are likely caused by variation in the prevalence of mutations in residue I871 in each condition. As a consequence of the weak role of residue I871 in the interaction of SETBP1 with βTrCP1, mutations in this residue, although disruptive when present in the germline, are functionally milder. The difference in molecular consequences between somatic and germline SETBP1 mutations is in line with findings from previous studies examining somatic and germline mutations in PTPN11, involved in juvenile myelomonocytic leukemia and in Noonan syndrome, respectively [54,55]. In contrast with SETBP1 mutations, germline PTPN11 mutations causative for Noonan syndrome rarely overlap with somatic mutations observed in leukemia. This mutual exclusivity between germline and somatic PTPN11 mutations has been proposed to result from the existence of distinct thresholds for gain-of-function mutations in developmental phenotypes and tumorigenesis [55]. Despite their overlap, our analysis of germline and somatic SETBP1 mutations supports this model. Malignant cell behavior in cancer can only be driven by somatic mutations with intense activation, while germline mutations with mild activation are sufficient to disrupt normal development. Consequently, gain-of-function mutations usually found somatically may lead to prenatal lethality or severe developmental alterations when present in the germline, as a result of intense activation [56]. Likewise, mild hypermorphic mutations associated with developmental disorders may be less likely to drive malignancy and are encountered less frequently as somatic events in cancer. In line with this, functional analysis of D868N, the SETBP1 mutation most commonly found in cancer, shows that it leads to the highest increase in SETBP1 protein levels and cell proliferation, suggesting it has the strongest effect at the biochemical and cellular level. Remarkably, individuals with SGS caused by mutations in residue D868 have higher incidence of tumorigenesis with odds ratio above 9 when compared to individuals with SGS caused by other mutations. Our findings suggest that individuals with strongly activating germline mutations in SETBP1 are at increased risk of malignancy. Due to the extremely low prevalence of SGS and the fact that malignancy is still a relatively infrequent complication of SGS, our study is limited by the small number of individuals with SGS who developed a malignancy. The correlation between strongly activating germline SETBP1 mutations and risk of malignancy should be reproduced in a larger cohort, in order to provide accurate prognosis and personalized follow up for individuals with germline SETBP1 mutations. Despite the increased risk for tumorigenesis, most individuals with SGS do not develop cancer. This observation that can be extended to individuals with developmental disorders resulting from germline mutations in genes involved in cancer when mutated somatically such as ASXL1, EZH2 or ARID1A [57–59]. As mentioned previously, this observation may be in part due to the effect of germline mutations not reaching the threshold of functional activation required to drive cancer. Furthermore, early lethality could also explain why most individuals with developmental disorders caused by germline mutations in genes involved in cancer do not develop malignancies. For instance, somatic SETBP1 mutations have been associated mainly with chronic myeloid leukemia, a disease occurring generally in individuals above the age of 60 [5,31]. Individuals with SGS have a short life span, which may not allow for the accumulation of additional somatic mutations required for tumorigenesis. Additionally, the cellular context is also important for the expression of a mutation: certain cancer-driving mutations can only do so in the context of “aged” hematopoietic stem cells [60–62]. This combination of factors may explain why myeloid malignancy is a rare malignancy in SGS, while embryonic cancers are observed more frequently. Finally, the presence of mutations in all cells of the organism instead of a subset may eliminate cellular advantage in a single cell which would allow for clonal expansion and, eventually, malignancy. Cell lines derived from individuals with SGS recapitulate some of the features identified in myeloid cells with SETBP1 mutations, including increased SETBP1 and SET protein levels and enhanced cell proliferation [5,7]. Although we observed a SETBP1 mutation-specific effect on cell proliferation, we did not detect visible differences in SET protein levels between individuals with different SETBP1 mutations. It is possible that different SETBP1 mutations have a subtle but distinct effect on SET protein levels that are not detectable by Western blot. However, we cannot rule out the absence of a mutation-specific effect of SETBP1 mutations on SET protein levels with additional mutation-specific downstream alterations resulting from pathways that do not involve SET protein. In light of our findings, cell lines derived from patients with developmental disorders caused by germline mutations in genes implicated in tumorigenesis may be a valuable model for the study of downstream consequences of cancer mutations at the molecular level. Furthermore, the similarities observed in the molecular consequences of germline and somatic SETBP1 mutations support the rationale behind recent studies which have elegantly repurposed drugs used in cancer therapy for the treatment of developmental disorders in mouse models [63]. An increase in SETBP1 protein as a result of mutations or overexpression leads to an increase in SET protein which results in the inactivation of PP2A. Although currently there are no known SETBP1 antagonists, several compounds have been described to antagonize SET protein or to lead to PP2A activation [64]. For example, OP449 is a synthetic peptide that binds to SET protein, activates PP2A and selectively inhibits cell growth in leukemia cell lines and primary patient cells [65]. Other compounds that directly activate PP2A, such as FTY720, have also been described [66]. While promising, it is yet unclear whether compounds targeting SET or PP2A may prove useful in the treatment of individuals with germline SETBP1 mutations. For one, the window of time between diagnosis and potential therapeutic interventions for early developmental phenotypes may be minimal. However, although this is still a speculative point, future therapeutic interventions may be useful to prevent progression of certain features of SGS, such as neurodegeneration [28]. Finally, it is still possible that individuals with SGS present alterations in other proteins downstream of SETBP1. In summary, we describe the largest cohort of SETBP1 mutation-positive SGS patients to date. Our results support that typical SGS is caused by gain-of-function mutations of SETBP1 affecting a degron involved in SETBP1 protein stability, while novel mutations outside the canonical degron cause an atypical form of SGS characterized by a milder phenotype. We observe variability in the magnitude of effect of germline mutations within the canonical degron of SETBP1 with consequences at the biochemical level and influencing the cellular and clinical phenotype. Furthermore, our results highlight that, despite the identification of overlapping SETBP1 mutations in SGS and myeloid malignancies, the mutation spectrum is significantly different in both conditions with functionally weaker mutations appearing predominantly as germline mutations in SGS. The parallelisms between the functional consequences of germline and somatic SETBP1 mutations is relevant for the better understanding of SGS but could also deliver insight into the role of SETBP1 as a cancer driver. Finally, our findings highlight that the convergence of the fields of cancer and developmental disorders uncovers common molecular mechanisms of disease for overlapping germline and somatic pathogenic mutations and may support the development of drugs with a dual therapeutic role in developmental disorders and cancer.
This study was approved by the institutional review board" Commissie Mensgebonden Onderzoek Regio Arnhem-Nijmegen" NL36191. 091. 11. Parents of all patients provided their written consent. Genomic DNA was extracted from saliva or blood using the QIAamp DNA Mini kit (QIAGEN). The hotspot region of SETBP1 was amplified by PCR and Sanger sequenced. Primer sequences are listed in S6 Table. Clinical features of participants were initially evaluated by clinicians from various countries. Photographs and medical information of all individuals were further assessed by a single clinical geneticist (BWvB). Separate informed consent was obtained for publication of photographs. The full-length SETBP1 construct fused to a C-terminal Myc-FLAG tag was purchased from Origene (RC229443). SETBP1 variant constructs were generated using the Quikchange II Site-Directed Mutagenesis kit (Agilent). Primer sequences are listed in S5 Table. SETBP1 cDNAs were subcloned using EcoRI/XhoI restriction sites into a modified pEGFP-C2 vector (Clontech) where the N-terminal EGFP tag was replaced with a YFP tag. All constructs were verified by Sanger sequencing. Fibroblast cell lines were established from skin biopsies of SGS cases and controls. HEK293 cells and fibroblasts were cultured in DMEM supplemented with 10% fetal bovine serum (all from Invitrogen). LCLs were established by Epstein-Barr virus transformation of peripheral lymphocytes from blood samples of SGS patients and controls. LCLs were cultured in RPMI medium (Lonza) with 10% fetal bovine serum and 5% HEPES. Transfections were performed using the GeneJuice transfection reagent following the manufacturer’s instructions (Merck Millipore). Whole-cell lysates were prepared as described previously [67]. Total protein was quantified using the Pierce BCA protein assay kit (ThermoFisher Scientific). Proteins were resolved on 4–15% Tris-Glycine gels and transferred to PDVF membranes (Bio-Rad). After blotting, membranes were incubated overnight at 4°C with the appropriate primary antibodies: rabbit anti-SETBP1 (Santa Cruz, sc-85148,1: 100), rabbit anti-SET (Abcam, ab1183,1: 4000), mouse anti-β-actin (Sigma, AC-15,1: 10000) and mouse anti-FLAG (Sigma, F1804; 1: 1000). Membranes were then incubated with HRP-conjugated donkey anti-rabbit (Abcam) or goat anti-mouse (Bio-Rad) secondary antibodies. Proteins were visualized using the Novex ECL Chemiluminescent Substrate Reagent kit (Invitrogen) and the ChemiDoc XRS+ System (Bio-Rad). Cells were transfected in clear-bottomed black 96-well plates in hexaplicate with YFP-SETBP1 expression plasmids together with a modified pmCherry-C1 plasmid to normalize for transfection efficiency. Fourteen hours post-transfection, YFP and mCherry fluorescence intensities were measured for 24h in live cells in a TECAN M200PRO microplate reader at 37°C and 5% CO2. In the case of stability assays with proteasome inhibitor, MG132 (Sigma) was added to the culture medium (10uM final concentration) 48 hours post-transfection and fluorescence intensities were measured at 0,3 and 12 hours. Cells were grown on poly-L-lysine (Sigma) coated coverslips and were fixed 48 hours post-transfection with 4% paraformaldehyde (Electron Microscopy Sciences) for 10 minutes at room temperature. YFP was visualized by direct fluorescence. Nuclei were visualized with DAPI (Vectorlabs). Fluorescence images were obtained using an Axio Imager Z1 fluorescence microscope (Zeiss). Lymphoblastoid cell lines were synchronized by overnight serum starvation, after which they were seeded in 24-well plates at a concentration of 160,000 cells/mL (three replicates per cell line). A measurement was performed every 24 hours, in which the cells were mixed with Trypan blue and counted. The SETBP1 degron variants observed in SGS and in leukemia were manually curated from previously published reports) [4–7,23–27,30–48]. Mutations were modeled using the YASARA structural simulation software (http: //www. yasara. org/). The protein model for βTrCP1 and degron sequence from β-catenin was obtained from the RCSB protein bank (1p22) [18]. The FoldX plugin for YASARA was used to calculate ΔΔG values [68]. LCLs from individuals with SGS were derived from blood samples of individuals with germline SETBP1 mutations D868N or I871T (n = 2 for each). LCLs from controls (n = 8) were derived from blood samples of individuals with different forms of intellectual disability [69]. RNA was purified from cell cultures using RNeasy mini kit from QIAGEN. RNAseq libraries were prepared using the TruSeq Stranded mRNA kit (Illumina) and sequenced on a Nextseq platform using 2x75bp paired end sequencing. RNA-seq samples were mapped using Kallisto (version 0. 42. 4) to the human genome (hg19. 75). At least 70% of the reads for each sample were mapped to the human genome entailing at least 39. 6 million reads in the sample with the lowest sequencing depth. Differential gene expression was performed using DESeq2 [49]. Gene set enrichment analysis was performed using the GSEA software [50]. Statistical analysis was performed using R Statistical Software (http: //www. r-project. org/ version 3. 1. 2, R Foundation for Statistical Computing, Vienna, Austria). Student’s T test was used for comparison of two groups with normal distribution, otherwise Mann-Whitney’s U test was used. For comparison of multiple groups against each other, we used ANOVA and Tukey’s test. To determine whether the distribution of mutations within the degron was the same in germline and somatic mutations, we used Fisher’s test and performed Bonferroni multiple test correction.
Several Mendelian disorders are caused by germline de novo mutations in genes in which somatic mutations have been implicated as cancer driver mutations. Germline de novo mutations in a hotspot of SETBP1 cause Schinzel-Giedion syndrome (SGS), a rare developmental disorder characterized by neurological alterations, malformations and increased cancer risk. Overlapping somatic SETBP1 mutations have been identified recurrently in myeloid leukemia. In this study, we characterize at the molecular and clinical level the largest cohort yet of individuals with SGS. We analyze the distribution and magnitude of effect of germline and somatic SETBP1 mutations in SGS and leukemia, respectively. SETBP1 mutations with weak effect are almost exclusively germline events, while strongly activating SETBP1 mutations occur both in SGS and leukemia. Strikingly, most cancer cases in SGS are observed in patients with strongly activating germline SETBP1 mutations. Our findings support a genotype-phenotype correlation for SGS and suggest the existence of a functional threshold required to drive malignancy both for germline and somatic SETBP1 mutations. This finding could be extrapolated to mutations in other genes implicated in developmental disorders and cancer, showing that the fields of cancer and developmental genetics can learn from the other discipline to gain insight into their own subject.
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Overlapping SETBP1 gain-of-function mutations in Schinzel-Giedion syndrome and hematologic malignancies