vascular malformations which respond to mosaic ras/mapk ... file(avm). methods. to investigate the...
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Amendment history:Erratum (November 2018)
Mosaic RAS/MAPK variants cause sporadicvascular malformations which respond totargeted therapy
Lara Al-Olabi, … , E. Elizabeth Patton, Veronica A. Kinsler
J Clin Invest. 2018. https://doi.org/10.1172/JCI98589.
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BACKGROUND. Sporadic vascular malformations (VMs) are complex congenitalanomalies of blood vessels that lead to stroke, life-threatening bleeds, disfigurement,overgrowth, and/or pain. Therapeutic options are severely limited and multi-disciplinarymanagement remains challenging, particularly for high-flow arteriovenous malformations(AVM).
METHODS. To investigate the pathogenesis of sporadic intracranial and extracranial VMsin 160 children in which known genetic causes had been excluded, we sequenced DNAfrom affected tissue and optimised analysis for detection of low mutant allele frequency.
RESULTS. We discovered multiple mosaic activating variants in four genes of the RAS-MAPK pathway, KRAS, NRAS, BRAF, and MAP2K1, a pathway commonly activated incancer and responsible for the germ-line RAS-opathies. These variants were more frequentin high-flow than low-flow VMs. In vitro characterisation and two transgenic zebrafish AVMmodels which recapitulated the human phenotype validated the pathogenesis of the mutantalleles. Importantly, treatment of AVM-BRAF mutant zebrafish with the BRAF inihibitor,Vemurafinib, restored blood flow in AVM.
CONCLUSIONS. Our findings uncover a major […]
Clinical Medicine Therapeutics Vascular biology
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Title
Mosaic RAS/MAPK variants cause sporadic vascular malformations which respond to targeted
therapy
Authors
Lara Al-Olabi1*, Satyamaanasa Polubothu1,2*, Katherine Dowsett3*, Katrina A Andrews4,5*,
Paulina Stadnik1, Agnel P Joseph6, Rachel Knox4,5, Alan Pittman7, Graeme Clark8, William
Baird1, Neil Bulstrode9, Mary Glover2, Kristiana Gordon10, Darren Hargrave11, Susan M
Huson12, Thomas S Jacques13, Gregory James14, Hannah Kondolf15, Loshan Kangesu9, Kim M
Keppler-Noreuil15, Amjad Khan2, Marjorie J Lindhurst15, Mark Lipson16, Sahar Mansour17,
Justine O’Hara9, Caroline Mahon2, Anda Mosica2, Celia Moss18, Aditi Murthy2, Juling Ong9,
Victoria E Parker4,5, Jean-Baptiste Rivière19, Julie C Sapp15, Neil J Sebire20, Rahul Shah9, Bran
Sivakumar9, Anna Thomas1, Alex Virasami13, Regula Waelchli2, Zhiqiang Zeng3, Leslie G
Biesecker15, Alex Barnacle21, Maja Topf6, Robert K Semple4,5,22+, E. Elizabeth Patton3+,
Veronica A Kinsler1,2+
*These first authors contributed equally to this work
+These senior authors contributed equally to this work
Affiliations
1. Genetics and Genomic Medicine, University College London GOS Institute of Child
Health, London WC1N 1EH, UK
2. Paediatric Dermatology, Great Ormond St Hospital for Children NHS Foundation Trust,
London WC1N 3JH, UK
3. MRC Human Genetics Unit and CRUK Edinburgh Centre, MRC Institute of Genetics and
Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh
EH4 2XU, UK
4. Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic
Science, University of Cambridge, Cambridge CB2 0QQ, UK
5. The National Institute for Health Research Cambridge Biomedical Research Centre,
Cambridge CB2 0QQ, UK.
6. Biological Sciences, Birkbeck, University of London, London WC1E 7HX, UK
7. Molecular Neuroscience, UCL Institute of Neurology, London WC1N 3BG, UK
8. Department of Medical Genetics, University of Cambridge, Cambridge Biomedical
Campus, Cambridge CB2 0QQ, UK
9. Plastic Surgery, Great Ormond St Hospital for Children NHS Foundation Trust, London
WC1N 3JH, UK
10. Dermatology and Lymphovascular Medicine, St. George’s Hospital NHS Trust, London
SW17 0QT, UK
11. Paediatric Oncology, Great Ormond St Hospital for Children NHS Foundation Trust,
London WC1N 3JH, UK
12. Manchester centre for Genomic Medicine, St Mary’s Hospital, Manchester M13 9WL,
UK
13. Developmental Biology and Cancer Programme, UCL GOS Institute of Child Health
and Department of Histopathology, Great Ormond Street Hospital for Children NHS
Foundation Trust, London
14. Paediatric Neurosurgery, Great Ormond St Hospital for Children NHS Foundation
Trust, London, WC1N 3JH, UK
15. National Human Genome Research Institute, National Institute of Health, Bethesda,
MD 20892, USA
16. Paediatrics and Clinical Genetics, Kaiser Permanente Medical Center, Sacramento, CA
95825, USA
17. Clinical Genetics, St. George’s Hospital NHS Trust, London SW17 0QT
18. Paediatric Dermatology, Birmingham Women’s and Children’s NHS Foundation Trust
Birmingham B4 6NH and University of Birmingham, UK
19. McGill University Health Centre and Research Institute, 1001 Boulevard Décarie,
Montréal (QC) H4A 3J1
20. Paediatric Pathology, Great Ormond St Hospital for Children NHS Foundation Trust,
London, WC1N 3JH, UK
21. Interventional Radiology, Great Ormond St Hospital for Children NHS Foundation
Trust, London, WC1N 3JH, UK
22. University of Edinburgh Centre for Cardiovascular Science, Queen’s Medical
Research Institute, Edinburgh EH16 4TJ
Licensing
This work was funded or supported by grants from the Wellcome Trust (UK), the Medical
Research Council (UK) and the UK National Institute for Health Research, and therefore
requires a Creative Commons CC-BY license in order to support publication fees for this
manuscript.
Key words Vascular malformation, Gene discovery, Targeted therapy, Mosaicism, MAPK, RAS
25 word summary
Activating mosaic mutations in four MAPK pathway genes are discovered to cause sporadic
intracranial and extracranial malformations, and respond to targeted inhibitors in a zebrafish
model.
Conflict of interest
LGB is an uncompensated advisor to the Illumina Corp, Receives royalties from Genentech,
Inc., and honoraria from Wiley-Blackwell. All other authors declare no conflict of interest.
Abstract
Background
Sporadic vascular malformations (VMs) are complex congenital anomalies of blood vessels
that lead to stroke, life-threatening bleeds, disfigurement, overgrowth, and/or pain.
Therapeutic options are severely limited and multi-disciplinary management remains
challenging, particularly for high-flow arteriovenous malformations (AVM).
Methods
To investigate the pathogenesis of sporadic intracranial and extracranial VMs in 160 children
in which known genetic causes had been excluded, we sequenced DNA from affected tissue
and optimised analysis for detection of low mutant allele frequency.
Results
We discovered multiple mosaic activating variants in four genes of the RAS-MAPK pathway,
KRAS, NRAS, BRAF and MAP2K1, a pathway commonly activated in cancer and responsible for
the germ-line RAS-opathies. These variants were more frequent in high-flow than low-flow
VMs. In vitro characterisation and two transgenic zebrafish AVM models which recapitulated
the human phenotype validated the pathogenesis of the mutant alleles. Importantly,
treatment of AVM-BRAF mutant zebrafish with the BRAF inihibitor, Vemurafinib, restored
blood flow in AVM.
Conclusions
Our findings uncover a major cause of sporadic vascular malformations of different clinical
types, and thereby offer the potential of personalised medical treatment by repurposing
existing licensed cancer therapies.
Funding
This work was funded or supported by grants from AVM Butterfly Charity, the Wellcome Trust
(UK), the Medical Research Council (UK), the UK National Institute for Health Research,
L’Oreal-Melanoma Research Alliance, the European Research Council and the National
Human Genome Research (US).
Sporadic vascular malformations (VMs) are congenital malformations of blood vessels, with
high associated morbidity and limited treatment options (Figure 1, Figure 2). VMs have
traditionally been divided into diagnostic groups according to anatomical site (intracranial
versus extracranial), and flow characteristics (high versus low), with detailed subclassification
incorporating multiple historical diagnostic labels(1). In high-flow, or arteriovenous,
malformations (AVM), direct complex interconnections between arteries and veins without
the normal interposed small-bore capillary network permits dangerous flow of high pressure
arterial blood into thin-walled veins leading to bleeds or stroke. In low-flow, capillary and/or
venous malformations, interconnections between anatomically abnormal capillaries and/or
veins can lead to sludging of blood, perilesional tissue anoxia, thrombosis, and overgrowth.
Application of next generation sequencing to a range of sporadic syndromes featuring VMs
has rapidly established the paradigm that such disorders are commonly caused by postzygotic
variants activating key cellular growth pathways(2-11). Variants overlap with those
documented in cancer, but the allelic spectra may differ. Accurate genotype-based
stratification of affected patients has begun to improve prognostication and in conditions
affecting the PI3K-AKT-MTOR signalling pathway has led to early clinical trials of targeted
therapies(12, 13). Despite these discoveries, however, a substantial proportion of patients
have no mutations in known associated genes(9, 14, 15). We sought to address this issue
using ultra-deep next generation sequencing and bio-informatic analyses aimed at detection
of low mutant allele frequency in affected tissue. Here, we discover multiple mosaic activating
variants in four genes of the RAS-MAPK pathway cause VM, and model therapy in an animal
model.
Results
25 patients with high-flow and 135 patients with low-flow VMs, in whom known VM-related
pathogenic variants had previously been excluded (Methods), were investigated to identify
the cause of the clinical phenotype. Using deep next generation sequencing of affected tissue
known or predicted pathogenic variants in RAS/MAPK pathway genes were identified in 9 of
the 25 patients with high-flow VMs (Table 1, Figure 3), and confirmed by a second method.
Identified variants were in KRAS (n=4) and BRAF (n=1), encoding key proximal components of
the RAS/MAPK signaling pathway, known to be pathogenic, but previously undescribed as
causal in any type of VM. In addition, a cluster of variants was identified in exon 2 of MAP2K1
(n=4), confirming a hotspot very recently reported in extracranial AVM but not known prior
to our study(9), and adding one novel small intragenic deletion (c.159_173del,
p.(F53_Q58delinsL)) (Table 1, Figure 3) to the allelic spectrum. Variant allele frequencies
ranged from 3-26% in affected tissue, but with no detectable variant in paired blood samples
where these were available (n=4/9 Table 1). One KRAS-variant patient had a sporadic AVM
restricted to the intra-cranial cavity, which presented with an intracranial haemorrhage at the
age of 13. The other eight RAS/MAPK variant patients had high-flow VMs centred in the skin
or soft tissues at various anatomical sites, with intra-cranial extension documented in two
(Table 1).
Of the 135 patients with low-flow VMs, five had mosaic RAS gene variants, four in KRAS and
one in NRAS, known to be pathogenic. Variants were present in each affected tissue tested
and were consistent within an individual (Table 1), with a variant allele load of 3-29%, but
undetectable in blood (n=4/5 Table 1). These patients exhibited a spectrum of phenotypic
manifestations as is typical of mosaic disorders (Table 1).
Structural modelling was undertaken of the four mosaic variants detected in exon 2 of the
MAP2K1 gene, two identical missense variants (p.(K57N)), and two small intra-exonic
deletions removing respectively codons 53-58 (novel c.159_173del, p.(F53_Q58delinsL)) and
58-62 (c.173_187del, p.(Q58_E62del)) (Uniprot Q02750.2 (MP2K1_HUMAN). All were found
to affect helix A in the 3D protein structure (residues 44-58). The deletions of residues 53-58
and 58-62 are predicted to affect the integrity of helix A, and K57 is a critical amino acid
involved in a hydrogen bond interaction with the backbone of a beta strand at the active site
(Figure 3c), a critical 3D-structure stabilizing interaction. Numerous interactions involving
Q46, R49, L50, F53, K57, V60 and the rest of the kinase domain, are found in the inhibited
form of MAP2K1 (Figure 3c), consistent with critical involvement of helix A in protein function.
Helix A forms an integral part of the Negative Regulatory Region of kinase function(16), and
these variants are therefore predicted to destabilise the conformation of the inactive state.
Transient overexpression of MAP2K1 and BRAF mutants in HEK293T cells led to increased
phosphorylation of ERK compared either to overexpression of corresponding wildtype genes
or to mock-transfected controls at 24 hours (Figure 4a,b). Overexpression of two of the same
mutants in human umbilical vein endothelial cells (HUVEC) led to disruption and disordering
of spontaneous vascular tube formation between 6-24 hours compared to mock-transfected
controls (Figure 4c,d), with significant reductions in mean number of master junctions, total
vascular tube length, and total mesh area (Figure 4e,f,g).
Two zebrafish models of VM were then developed to validate our findings in vivo and to serve
as a platform for screening of potential drug treatments. Artery and vein development in
zebrafish is regulated by similar mechanisms to those in humans(17), and blood flow through
the vasculature is clearly visible by two days of development (Supplementary Movie). We
injected separately BRAFV600E and MAPK2K1Q58del expressed from a pan-endothelial promoter,
flia, into single-cell zebrafish embryos to generate post-zygotic expression of BRAFV600E or
MAPK2K1Q58del in vessels, that like in the patients, is expressed in a mosaic fashion (Figure
5a). For some animals, both BRAF and BRAFV600E expression led to shortening along the
anterior-posterior axis, as reported previously in zebrafish with high MAPK expression, and
these were removed from the analysis (Supplementary Figure S1; Anastasaki et al., 2009;
Anastasaki et al., 2012). Notably, BRAFV600E, but not expression of wild type BRAF, led to
disordered vessel formation leading to severely impeded blood flow, and recapitulated the
clinical features of patient VMs (Figure 5c, d, e; Supplementary Movie). Interestingly, these
VM formed preferentially at the junction of the caudal artery and vein(18). Mosaic expression
of MAP2K1Q58del, but not wild type MAP2K1, also generated VM (n=5/37) (Figure 5f).
Zebrafish with established VM were then treated for two days with a low, continuous dose of
Vemurafenib (0.1uM), the approved anti-cancer BRAF inhibitor, and assessed by blind scoring
for improved blood flow (Figure 5g). Strikingly, almost all Vemurafenib-treated zebrafish
exhibited improved blood flow (Figure 5g). In contrast, drug treatment had no effect on
control zebrafish, and only a minority of BRAFV600E VMs demonstrated improved blood flow
spontaneously. These important results of improvement in phenotype from RAS-RAF-MAPK
targeted therapy in an animal model echo recent murine models of VM ameliorated by
targeted pathway inhibition of the PI3K-AKT-MTOR pathway(19, 20).
Discussion
We discover mosaic activating variants in oncogenes at several levels of the RAS/MAPK
signaling pathway as a major cause of sporadic VMs, and particularly of the clinically high-risk
group of AVMs. This discovery identifies the RAS-RAF-MAPK pathway as a major cause of
sporadic VMs, and opens the door to repurposing of targeted medical therapies on a
personalized medicine basis. The pathogenicity of these variants is supported by several lines
of evidence including the well-established pathogenicity of the BRAF, KRAS and NRAS variants
in other disorders and tissues, the mosaic occurrence of these variants in the lesions and their
absence in peripheral blood, and by the existence of a hotspot of MAP2K1 variants in the
COSMIC database, comprising 65 tumor variants from F53 to E62.
Several genetic causes of human inherited and sporadic vascular malformation are already
known(21). Inherited susceptibility to cerebral cavernous (low-flow) malformations is
conferred by germline mutations in KRIT1(22), CCM2(23) and PDCD10(24), however
malformations themselves require a somatic ‘second hit’(25). The same paradigm of an
inherited genetic diathesis interacting with a somatic mutation applies to heritable extra-
cranial low-flow malformations caused by mutations in TEK(10) and GLMN(26, 27), and
heritable (high-flow) arteriovenous malformations associated with mutations in PTEN,
ACVR1, ENG, RASA1(28, 29). The same mechanism is also likely in the recently described gene
for CM-AVM syndrome EPHB4(30). Known causes of sporadic vascular malformations are
post-zygotic mutations in TEK(10, 11), AKT1(2), PIK3CA(7), GNAQ(3, 4), GNA11(4) and
MAP3K3(8) in low-flow VMs, and recently described MAP2K1 mutations in high flow extra-
cranial malformations(9) (Figure 6). Thus, there is a pattern of milder predisposing mutations
in the germline requiring a second hit to lead to phenotype, and more severe mutations
leading directly to a phenotype only seen as post-zygotic hits. Our discovery that RAS-MAPK
VM mutations are strong activators of the MAPK signaling pathway and overlap with the
cancer allele spectrum is in line with the hypothesis that lethal genes survive by
mosaicism(31).
In silico protein-interaction analysis(32) of the full spectrum of genes associated with VMs,
including our new findings, demonstrates a strong network of functional interaction among
the gene products (Supplementary Figure S2). This aligns with recent mechanistic work on
vascular malformations secondary to germline variants in CCM2, PCD10 and KRIT1, which
drive vascular malformations by increasing MAP3K3 (MEKK3) signaling in endothelial
cells(33). MAP3K3 is essential for the development of embryonic cardiovascular system in
mice(34) and zebrafish(35), and is considered a critical nexus between the Congenital
Cavernous Malformation complex and downstream signaling pathways(33, 35, 36) such as
those mediated by Rho signaling(36), p38 MAPK(37) and MEK5/ERK5(35, 37). We hypothesise
that congenital vascular malformations ultimately result from dysregulation of vascular cell
MAPK and/or PI3K signaling during human embryonic development.
Analysis of multiple different affected tissues in two of the patients revealed consistency of
mutation within an individual, confirming a post-zygotic hit to a multipotent precursor in
those cases. Although several mosaic disorders have been described in association with
postzygotic activating variants in RAS oncogenes, vascular malformations have not been
described in those phenotypes(38-44). Arterial abnormalities have been described in
association with epidermal nevi, but without genotype data (45-47). Interestingly, post-natal
somatic second-hit RAS and RAF gene family variants have been described in the small
acquired vascular tumours pyogenic granulomas, arising on a background of a post-zygotic
GNAQ-variant congenital capillary malformation(48). In these cases, RAS variants were not
the cause of the underlying VM, but consistent with somatic RAS variants leading to tumours
of many types.
These findings are particularly important in the context of the lack of effective therapy for
complex VMs, particularly for AVMs. Embolization and surgical intervention are not always
possible for safety reasons, and where possible can have limited short-term results due to
very frequent localised recanalization and recurrence, or be associated with disfiguring
results. Identification of mosaic mutations in a third of our AVM cohort, including intracranial
AVMs, will radically alter the concept of management of these VMs by introducing the
possibility of targeted medical therapy.
The cause of the difference in frequency of these variants between the high- and low-flow
cohorts is not clear. As a minority of the low-flow cohort skin biopsies were cultured for
fibroblasts before DNA extraction it is possible that the mutations was either lost in culture
or not present in fibroblasts. We would not however expect this to explain the size of the
difference between the groups, and further work will be needed to explore the increased
frequency in high-flow vascular malformations.
In summary, these findings demonstrate a novel cause of sporadic VMs, and suggest a
common pathogenesis for sporadic VMs of different vessel types and at different anatomical
locations, including intra-cranial. Genotyping of affected tissue, where accessible, should
therefore be a key element of management across the diverse medical subspecialties to
which affected patients present. Resulting genetic stratification may not only be of value
prognostically, but may also now serve to guide therapy. Although formal clinical trials will be
required before routine repurposing of such agents is sanctioned in clinical care, licensed
targeted medical therapy on a compassionate basis may already be considered for severe or
life-threatening cases.
Methods
Patient cohorts
Twenty-three patients with high-flow vascular malformation (AVM), confirmed clinically and
radiologically, who were seen in the Paediatric Dermatology Department at Great Ormond
Street Hospital for Children, London (GOSH), were recruited and gave written informed
consent. At the time of recruitment, no genes were known to be causative in sporadic AVM.
After initial results of our study were available two patients with intracranial-only AVM were
also recruited for testing via the Paediatric Neurosurgery department.
135 patients with low-flow vascular malformations and/or overgrowth, and one patient with
a high-flow vascular malformation were recruited with written informed consent to the
Investigation of Segmental Overgrowth Disorders study (REC 12-EE-0405) and found to be
wildtype for genotype of known sporadic vascular and overgrowth-related genes PIK3CA,
AKT1, GNAQ, GNA11 and TEK. One further patient with a low-flow vascular malformation
and overgrowth was identified after genotyping results from the Phase 1 dose-finding trial of
ARQ 092 in children and adults with Proteus syndrome study at the NIH, Bethesda, USA,
bringing the totals of high-flow to 25, and low-flow to 135. Detailed clinical phenotyping was
undertaken in all patients before genotyping (Table 1).
DNA extraction
DNA was extracted directly from samples by DNeasy Blood and Tissue Kit (Qiagen), and from
paraffin embedded tissue using the RecoverAll total nucleic acid extraction kit for FFPE (Life
Technologies).
Next generation sequencing and variant calling
High-flow vascular malformation patients
21 FFPE and 4 fresh samples were sequenced using the SureSeq™ Solid Tumour Panel (Oxford
Gene Technology). This was chosen due to the difficulty in biopsying AVMs due to risk of
bleeding, and because this panel is optimized for FFPE tissue. DNA library preparation was
performed for each sample using the Agilent SureSelect™ XT Reagent Kit, as per the
manufacturers protocols
(http://www.ogt.co.uk/assets/0000/4457/990162_HB_SureSeqSolidTumour_110215.pdf).
Samples were then pooled and sequenced on a MiSeq instrument (Illumina) according to the
manufacturer’s recommendations for paired-end 150-bp reads. In-depth sequencing was
performed to achieve a mean sequencing depth of 500 reads for all targeted coding bases.
For two further patients fresh 4mm skin biopsies were taken from the AVM, and DNA
extracted directly from the whole sample, and from paired blood samples. These were
sequenced by whole exome sequencing, library preparation was with SureSelect™ Agilent
QXT v6 following the manufacturers protocols, and sequencing was on the HiSeq 3000
(Illumina), with a mean read depth of 500X.
Sequence alignment to the human reference genome (UCSC hg19), and variant calling and
annotation was performed with our in-house pipeline. Briefly this involves alignment with
NovoAlign, removal of PCR-duplicates with Picard Tools followed by local realignment around
indels and germline variant calling with HaplotypeCaller according to the Genome Analysis
Toolkit (GATK) best practices. We identified potentially mosaic variants with GATK muTECT2
in tumor-only somatic variant calling mode. The raw list of single nucleotide variants (SNVs)
and indels were then filtered using ANNOVAR. Only exonic and donor/acceptor splicing
variants were considered. Priority was given to rare variants (<1% in public databases,
including 1000 Genomes project, NHLBI Exome Variant Server, Complete Genomics 69, and
Exome Aggregation Consortium). Furthermore, we have an in-house set of approximately six
thousand exomes encompassing controls, rare diseases for cross-checking any shortlisted
candidate variants, and for sequencing artefact removal. Identification of candidate variants
where paired samples were available was also performed using Ingenuity Variant Analysis by
selecting variants present in skin but not in blood (or in mosaic levels in both). For all
candidate variants BAM files were viewed using the Integrative Genomics Viewer (Broad
Institute), and mosaicism percentage taken from the mutant allele reads divided by the total
directly from the BAM. Candidate post-zygotic variants were confirmed by Sanger sequencing
in all DNA samples available from each patient. To maximize detection of mutant alleles at
low percentage mosaicism, restriction enzyme digests of the normal allele were designed
where necessary using validated methods(49) and Sanger sequencing performed. See
Supplementary Table S1 for primer sequences. Touchdown PCR programmes were used
throughout, with 40 cycles for the first PCR (annealing and extension times of 1 minute), and
15 for the second hemi-nested PCR where required.
Low-flow vascular malformation patients
A 4mm punch biopsy of affected tissue was taken from an area of overgrowth and/or vascular
malformations. DNA was extracted either directly from the biopsy (51/134 patients), or from
dermal fibroblasts grown from the biopsy (59/134 patients), using the QiaAMP DNA Micro Kit
(Qiagen). In 9/134 patients, DNA was extracted from FFPE tissue samples using the QIAamp
DNA FFPE Tissue Kit. In cases of facial involvement (15/134 patients), a buccal swab served as
affected tissue, and DNA was extracted via standard methods of phenol-chloroform
extraction followed by ethanol precipitation. Blood samples were collected where possible,
and lymphocyte DNA was extracted via the Illustra BACC3 DNA extraction kit (GE Healthcare).
Targeted next generation sequencing was performed on affected tissue DNA using a custom
panel of overgrowth-related genes on an Illumina MiSeq platform. This panel was designed
for the low flow study as a selection of possible candidate genes for overgrowth, on the basis
of the genes/pathways already known to be involved in this phenotype. 10 ng of DNA was
amplified for 18 cycles of PCR with the Ion Ampliseq custom DNA panel, enriching the 195
target amplicons. This included full coverage of all coding regions of PIK3CA, PTEN and CCND2,
and “hotspot” regions in 57 other genes (regions of coverage listed in Supplementary Table
S2). The panel was split into two primer pools and amplified with 5x Ion Ampliseq HiFi master
mix, followed by FuPa treatment (Ion Ampliseq DNA Library Kit 2.0). The two primer pools for
each sample were then pooled, and purified with 1.8x Agencourt AMPure XP magnetic beads
(Beckman Coulter). Amplicons were 3’ adenylated using the NebNext Ultra II end repair/dA
tailing module (NEB), followed by NextFlex DNA Barcode adapter (Bio Scientific) ligation using
the NebNext Ultra II ligation module (NEB). Ligation products were purified and size-selected
using 0.8x Agencourt AMPure XP beads. Library concentration was determined with Kapa
Biosystems Library qPCR quantification kit on the Lightcycler 480 real-time PCR system
(Roche). Libraries were subsequently diluted to 2 nM and pooled in equimolar amounts.
Pooled libraries were spiked with 1% PhiX DNA (Illumina), and sequenced on the MiSeq
desktop sequencer using version 2 chemistry at 250 bp read length paired end.
VCF files tailored for mosaic variant calling were created in MiSeq Reporter (Illumina) and
annotated in Illumina Variant Studio version 2.2, resulting in a list of 300-1,000 variants per
sample. The programming language R was used to apply hard filters according to the following
parameters: read depth >5; quality score >10; absence of strand bias (as determined by MiSeq
Reporter), cross-sample subtraction of artefactual variants called in >8 samples per batch of
24; exonic non-synonymous variants only. This resulted in a list of 1-4 candidate variants, the
clinical relevance and sequencing quality of which were then assessed.
Mosaic variants considered to be causative were confirmed and tested in other tissue samples
from the same patient, alongside DNA from healthy controls, either by Sanger sequencing
(primers listed in Supplementary Table S1) or by custom RFLP. For RFLP, genomic DNA was
amplified with GoTaq Green (Promega) using the primers listed in Supplementary Table S3.
The PCR products were designed to include a restriction enzyme recognition site allowing
specific digestion of the mutant allele, while leaving the wildtype allele intact. The digested
PCR fragments were then mixed with GeneScan™ 500 LIZ® Size Standard (Applied Biosystems)
and loaded on an ABI3730 capillary sequencer. The area under the curve of
undigested:digested DNA was used to calculate the mutation burden using Genemapper v5.0
software (Applied Biosystems).
Mutant plasmid construction, HEK293T and HUVEC cell transfection
pCMV6-MAP2K1:
The pCMV6-MAP2K1 plasmid for in vivo expression in mammalian cells was ordered from
Origene (ID: SC118424). To generate mutant MAP2K1 expression vector, an improved
QuickChangeTM site-directed mutagenesis protocol was used(50). p.(K57N) is a predicted
missense alteration caused by a single nucleotide change (g>c); p.(Q58_E62del) (hereafter
termed Q58del) is a deletion mutation caused by a deletion of 15 bp. The sequences of
mutagenesis PCR primers are: K57N-Fw: 5'-gaggcctttcttacccagaaccagaaggtggg-3’ K57N-Rev:
5'-cccaccttctggttctgggtaagaaaggcctc-3' Q58del-Fw: 5’-
cttacccagaagctgaaggatgacgactttgagaagatcag-3' Q58del-Rev: 5’-
gtcgtcatccttcagcttctgggtaagaaaggcctcaagg-3' The mutagenesis PCR runs for 15 cycles and
each cycle consists of denaturation at 95 qC for 30 sec, annealing at 58 qC for 1 min and
extension at 72 qC for 5 min.
pDEST26-BRAF:
The wildtype and mutant (p.V600E) human BRAF cDNA are in the same Gateway� middle
entry clones used in a previous study(51). These two BRAF cDNAs were cloned into the
destination vector pDEST26 for expression in mammalian cells using the Gateway� cloning
system (Invitrogen) according to the manufacturers instructions.
HEK293T cell line transfection:
HEK293T cells (ATCC, Catalogue Number CRL-11268) were maintained as per established
protocols and were transfected with mutant and wildtype cDNA expression plasmids, and
an empty vector control, using Lipofectamine® 2000. One day before transfection, 6 x
105 cells were plated per well of a 6-well culture vessel in 500 μl of growth medium without
antibiotics so that cells would be 70-90% confluent at the time of transfection. For each
transfection sample, 4.0 μg of plasmid DNA was diluted in 250 μl of Opti-MEM® I Reduced
Serum Medium and mixed gently. Lipofectamine® 2000 was gently mixed before use, then
10 μl was diluted in 250 μl of Opti-MEM® I Medium, then incubated for 5 minutes at room
temperature before combining with the diluted DNA (total volume = 500 μl), mixed gently
and incubated for 20 minutes at room temperature. 500 μl of complexes were added to
each well containing cells and medium and mixed gently by rocking the plate back and forth.
Finally cells were incubated cells at 37 °C in a CO2 incubator for 30 hours prior to testing for
transgene expression.
HUVEC cells transfection :
Based on transfection optimisation Human Umbilical Vein Endothelial Cells (HUVEC,
(ThermoFisher, catalogue number C0035C) were incubated in transfection reagents with a
1:3 DNA:Lipofectamine®LTX ratio at 37 °C, 5% (v/v) CO2 for 48 h. Volumes described in this
section are representative of a single well in a 6-well plate. 2.5 µg of either plasmids
containing the wild-type (WT) or mutated gene of interest (BRAFWT, BRAFV600E, MAP2K1WT,
MAP2K1K57N and MAP2K1Q58_E62del as detailed above), or pDest26 empty vector or a mock
transfection that represented an additional control was diluted in 500 µl in Opti-MEM®I
Reduced Serum Medium without serum (#31985062). Next, 2.5 µl of PLUS™Reagent
(#11514015) was added to the DNA dilution and incubated for 10 minutes at room
temperature. Transfection complexes were formed after adding 7.5 µl Lipofectamine®LTX to
DNA:PLUS™Reagent solution prior to 30 minutes incubation at room temperature and then
added to a well containing 2 ml fresh growth supplemented medium.
Quantitative real time PCR
To assess the efficiency of transfection of plasmid DNA in the cells, quantitative expression
analysis of the genes of interest MAP2K1 and BRAF as well as the endogenous control GAPDH
was determined by real-time qPCR with TaqMan gene expression assays using the StepOne
plus instrument. Standard protocol as per manufacturer’s guidelines for Applied Biosystems
TaqMan Gene Expression Assay on the StepOne plus instrument. Probes used for quantitative
analysis were: MAP2K1 (Assay ID: Hs00983247_g1), BRAF (Assay ID: Hs00269944_m1) and
GAPDH (Assay ID: Hs02786624_g1) and were all from Life Technologies). Results of the
quantitative gene expression levels were obtained after the amplification reaction using the
StepOne software (version 2.3). Results are based on analysis of two biological replicates,
with triplicate technical replicates in each experiment, and quantitative values of the cycle
threshold (Ct) averaged. The relative expression of the genes of interest was determined by
calculating the ratio of their expression compared to that of the GAPDH endogenous control
in the same sample.
Western Blotting
Cell lysates were prepared using standard protocols. Primary and secondary antibodies are
shown in Supplementary Table S4. Western Blot basic protocol: 40ug of protein was used
after heating at 95 °C with 2x Laemmli sample buffer in 5% Beta-mercaptoethanol was run on
4–20% Mini-PROTEAN® TGX™ Precast Protein Gels (#4561096 BIORAD). The transfer was
blocked at room temperature for 1hr in 5% dry milk or 5% BSA dissolved in TBS-0.05%Tween.
The transfer was incubated with primary antibody (1:1000 dilution in 3% BSA (BSA in 1xTBST)
at room temperature overnight. The membrane was then washed 3 times for 15 minutes in
TBST. Incubation with the secondary antibody was conducted at room temperature for 1hr.
As a secondary antibody we used anti rabbit RB96 in 1:7000 dilution and diluted in 3% BSA
(BSA in 1xTBST) or 3% milk.
Endothelial cell tube formation assay and microscopy
Cells and all reagents in this subsection were obtained from Invitrogen (Paisley, UK) unless
otherwise stated. The formation of endothelial tubes by Human Umbilical Vein Endothelial
Cells (HUVEC, (ThermoFisher, catalogue number C0035C) on growth factor-reduced Geltrex®
(#A1413202) was conducted according to the manufacturer’s protocol (#MAN0001687) using
Medium 200PRF supplemented with Low Serum Growth Supplement. Briefly, 24 well culture
plates were coated with 100 µl/well (50 µl/ cm2) Geltrex® and incubated for 30 minutes at 37
°C. After harvesting transfected and untreated HUVECs (P2) cultured on 6 well plates, they
were seeded on coated plates at a density of 4.5x104/cm2 (9x104 cells/well) in 200 µl/cm2
(400µl/well) supplemented 200PRF medium and cultured in a CO2 incubator (37 °C, 5% (v/v)
CO2, 95% humidity). 30 minutes before the end of the incubation period cells were treated
with 2 µg/ml (0.8μl/well) calcein AM (#C3099) and incubated at 37 °C, 5% (v/v) CO2. Tube
formation observed at 14 h time point was imaged with a 5x objective lens of Olympus IX71
inverted fluorescence and bright field microscope using HCImage software. The degree of
tube formation was assessed by measuring all aspects of tubule, node and mesh growth in
triplicate, using randomly chosen fields from each well using the angiogenesis analyzer for
ImageJ (http://image.bio.methods.free.fr/ImageJ/?Angiogenesis-Analyzer-for-ImageJ).
Transgenic zebrafish
The zebrafish fli1a promoter was generated by gateway® PCR with primers (forward: 5’-
GGGGACAACTTTGTATAGAAAAGTTGCCTGGCTGTCAAGCTCCAGC-3’, reverse:
GGGGACTGCTTTTTTGTACAAACTTGATATGTGGCGGAGAGACAGAG-3’, promoter specific
sequences are underlined). The promoter comprises 2.2 kb immediately upstream of the
first ATG of the fli1a gene. The PCR product was then clone into the gateway® 5’ donor
vector pDONRP4-P1R to obtain the 5’ entry clone p5Efli1a2.2k. Middle entry clones
containing human BRAFwt, BRAFV600E, MAP2K1wt or MAP2K1Q58del cDNA were recombined
with the fl1a promoter in p5Efli1a2.2k and the pDestTol2CG2 expression vector using the
Tol2kit gateway® cloning method(52), resulting fli1a-BRAFwt, fli1a-BRAFV600E , fli1a-
MAP2K1wt, fli1a- MAP2K1Q58del constructs. One nl of mixed fli1a-BRAF or fli1a-MAP2K1
plasmid DNA and Tol2 mRNA (37 ng/µl and 35 ng/µl respectively) was injected into 1-cell
stage of fli1a:GFP zebrafish embryos (Species Danio rerio, AB line)(53). Embryos were
raised at 28.5 °C and screened for phenotypes. Embryos were then fixed in 4% PFA.
Drug treatments
Zebrafish embryos were treated with the BRAF inhibitor Vemurafenib (PLX4032). Embryos
were incubated with 0.1 µM of the drug from 2.5 dpf after initial imaging, refreshed daily.
Control embryos were incubated in E3 with DMSO at the same concentration as drug used.
During live imaging, embryos were kept in 1:5,000 MS222 and 1.5% LMP agar. Leica stereo
brightfield microscopy was used for live colour imaging. Fluorescence images were taken
using Leica Sp5 confocal microscopy. Images were processed using FIJI(ImageJ). Graph pad
prism was used to analyse data.
Statistics
Western blot (WB) data (Figure 4a,b) was analysed using one-way ANOVA comparing mock
transfection to wild-type and mutant allele groups, per mutant. Densitometry data was
pooled from biological replicates and used to calculate means and SDs. A p-value of <0.05
was used for 95% confidence. Angiogenesis data (Figure 4e,f,g) was analysed using one-way
ANOVA comparing mock transfection controls to wild-type and mutant allele groups, per
mutant. An initial one-way ANOVA was undertaken to demonstrate that biological replicates
were significantly different, and therefore data between replicates was first standardized to
the within-experiment control before being pooled for analysis of standardized means and
SD. Correction for multiple testing was applied after the ANOVA, reducing the 95%
confidence p-value to <0.0167.
Zebrafish data – significance was assessed for data in Figure 5b using unpaired parametric t-
test with Welch’s correction, and in Figure 5c using paired t-test.
Study approval
These studies were conducted according to Declaration of Helsinki principles, and were
approved by the local Research Ethics Committees of each centre involved (London
Bloomsbury, University of Cambridge and University of Edinburgh). All participants were
recruited with written informed consent. Separate written informed consent was obtained
for publication of all clinical photographs.
All zebrafish work was done in accordance with United Kingdom Home Office Animals
(Scientific Procedures) Act (1986) and approved by the University of Edinburgh Ethical Review
Committee.
Acknowledgements
We gratefully acknowledge the participation of all patients and families in this study. We
gratefully acknowledge Craig Nicol’s help with figure preparation. VAK and RKS are funded by
the Wellcome Trust (Grants WT104076MA and WT098498 respectively). Support was also
provided by the Medical Research Council [MRC_MC_UU_12012/5] and by the UK National
Institute for Health Research (through Biomedical Research Centres at Great Ormond Street
Hospital for Children NHS Foundation Trust, University College London and in Cambridge, and
through the Rare Disease Translational Research Collaboration). KA is funded by Health
Education East of England and the Wellcome Trust Translational Medicine and Therapeutics
programme. EEP is funded by the Medical Research Council, L’Oreal-Melanoma Research
Alliance Team Award for Women in Science, and the European Research Council. LGB is
funded by the Intramural Research Program of the National Human Genome Research
Institute (Grants HG200328 11 and HG200388 03).
Author contributions
LA-O and SP were responsible for patient sample DNA extraction, sequencing and
confirmation, patient recruitment and phenotyping of the low and high flow cohorts,
HEK293T cell work, and figure preparation. PS was responsible for the HUVEC cell work and
figure preparation. KAA and VEP were responsible for patient recruitment and phenotyping
of the low-flow cohort. RK, GC and WB contributed to sequencing and cell culture
maintenance. KD, ZZ and EEP were responsible for the zebrafish work and figure preparation.
AJ and MT were responsible for the protein modelling work and figure preparation. AP and
JBR contributed to the design of the sequencing data analysis. Authors listed in the
alphabetical section of the authorship contributed patient samples and phenotypic data to
the cohort, and for HJ, KMKN, MJL and JS also to the mutation discovery of their patient. LGB
contributed patient genotype/phenotype and critical review of the manuscript. AB reviewed
all the imaging and contributed radiological images for figures. RKS conceived, designed and
directed the research for the low-flow cohort, as well as contributing a large number of
patients and the genotypic and phenotypic data to that cohort, with contribution to and
critical review of the manuscript. EEP conceived, designed and directed the zebrafish
research, with contribution to and critical review of the manuscript. VAK conceived,
designed, directed the research and contributed patients to the high-flow cohort, contribute
patients to the low-flow cohort, analysed the sequencing and angiogenesis data, wrote the
manuscript and prepared figures.
Table 1 - Phenotypic and genotypic characterisation of 15 individuals with M
APK pathway variants and sporadic vascular m
alformations.
VM – vascular m
alformation; AVM
– arteriovenous malform
ation; R – right; L = left; FFPE – formalin-fixed paraffin-em
bedded. Patient
# Age
Phenotype gDN
A (hg19) cDN
A, aa change M
utant allele count
Total allele count
Percentage m
osaicism by
sample origin
1 19
years High flow
AVM
L face, recurrent bleeding,
progressive enlargem
ent
chr7:g.140453136T>A N
M_004333.4: c.1799T>A;
BRAF p.(V600E) 27
103 FFPE tissue
from vascular
malform
ation tissue from
surgical
resection 26%
Blood 0%
2
33 years
High flow
AVM R face,
recurrent bleeding, progressive
enlargement
chr12:g.25380275A>C
NM
_004985.4; NM
_033360.3 :c.183A>C;
KRAS p.(Q61H)
114 2241
FFPE tissue from
vascular m
alformation
tissue from
surgical resection of VM
5%
Blood 0%
3
12 years
High flow
AVM R face,
recurrent bleeding, loss of vision R eye,
progressive enlargem
ent
chr12:g.25398284G>T
NM
_004985.4; NM
_033360.3: c.35G>T;
KRAS p.(G12V)
5 174
Fresh skin biopsy from
VM
3%
Blood 0%
4 24
years High flow
AVM
L buttock, recurrent bleeding,
progressive enlargem
ent
chr15: g.66727443
NM
_002755.3: c.159_173delTCTTACCCAGAAGCA;
MAP2K1 p.(F53_Q
58delinsL)
44 752
FFPE tissue from
vascular m
alformation
tissue from
surgical resection of
vascular m
alformation
tissue 6%
5 20
years High flow
AVM
R temple area,
recurrent bleeding, progressive
enlargement
chr15:g.66727455G>C
NM
_002755.3 : c.171G>C; M
AP2K1 p.(K57N)
10 136
FFPE tissue from
vascular m
alformation
tissue from
surgical resection 7%
6
9 years
High flow
AVM R external ear,
and posterior auricular soft tissues
chr15:g.66727456
NM
_002755.3: c.173_187delAGAAGGTG
GGAGAAC; M
AP2K1 p.(Q58_E62del)
31 782
FFPE tissue from
vascular m
alformation
tissue from
surgical resection 4%
Blood 0%
7A
24 years
High flow
Deep vessel mixed
arterial and venous m
alformation of the
left posterior chest w
all and overlying skin. Extensive
chr12:g.25398284G>A N
M_004985.4; N
M_033360.3:
KRAS c.35G>A; KRAS, p.(G12D)
Multiple
samples
Cultured
fibroblasts from
skin biopsy of epiderm
al nevus 39%
asymm
etric linear verrucous
keratinocytic epiderm
al nevus of the back w
ith a few
areas suggestive of sebaceous nevus.
Hypertension caused by bilateral renal
artery stenosis, with
long strictures of the descending aorta,
coeliac axis and superior m
esenteric artery also
abnormal. Surgery
for removal of
symptom
atic spinal root plexiform
neurofibrom
as on tw
o occasions and an intra-spinal lipom
a on one occasion. Post-
surgical kyphoscoliosis.
Mutations in NF1
and PTEN genes excluded.
Fresh skin biopsy of epiderm
al nevus 30%
Paraspinal ‘N
eurofibroma-
like’ overgrow
th 30%
8 13
years High flow
AVM
L external ear, posterior auricular
soft tissues, intracranial extension,
progressive enlargem
ent
chr15:g.66727455G>C
NM
_002755.3 : c.171G>C; M
AP2K1 p.(K57N)
18 992
Fresh skin biopsy 2%
9 14 years
High flow
AVM in the right
frontal lobe, supplied by a branch of the right anterior
cerebral artery. Presented aged 13
with intracranial
haemorrhage and
intraventricular extension,
previously well.
Required craniotomy
and resection of AVM
.
chr12:25398285G>T N
M_004985.4; N
M_033360.3:
c.34G>T; KRAS, p.(G12C)
23 841
FFPE tissue 3%
10 18
years Low
flow
Mild overgrow
th of right arm
and shoulder girdle from
age 10, w
ith prom
inent superficial veins and
chr12:g.25398284G>A N
M_004985.4; N
M_033360.3:
c.35G>A; KRAS p.(G12D)
275 7628
Fresh skin biopsy of capillary
malform
ation 4%
Blood – 0%
reticulate capillary m
alformation on the
right upper arm. N
o deep vessel
malform
ation detectable, chronic
pain in palpably w
arm right hand,
with brow
nish-pink uniform
capillary m
alformation and
scattered telangiectasia.
11 39
years Low
flow
Subtle congenital right foot
overgrowth w
hich gradually progressed
and extended to buttock by second decade. Prom
inent superficial veins and dependent edem
a from
20 years old, still progressing. N
o capillary
malform
ation.
chr1:g.114713908A>G
N
M_002524.4:c.182A>G;
NRAS p.(Q61R)
524 7715
Fresh skin biopsy of VM
7%
Blood – 0%
Saliva – 0%
12 14
years Low
flow
Non-progressive
congenital mild
chr12:g.25398284G>T
NM
_004985.4; NM
_033360.3: c.35G>T;
KRAS p.(G12V)
193 7105
Fresh skin biopsy of VM
3%
overgrowth w
ith co-localised capillary
malform
ation of the left arm
, hand, shoulder girdle, chest w
all and breast w
ith clear m
idline dem
arcation. The capillary
malform
ation was
uniform brow
nish-red and punctuated
by telangiectasia w
ith a pale halo. The overgrow
n area was
painful and palpably w
arm, but
hematological
indices and deep vessels w
ere normal.
Blood – 0%
13 7 years
Low flow
O
vergrowth of the
third and fourth fingers on the right hand (length and breadth), forearm
sm
aller in girth on R than L. Venous
prominence on the
chr12:g.25398284G>A N
M_004985.4; N
M_033360.3:
c.35G>A: KRAS p.(G12D)
Cultured fibroblasts from
skin biopsy of
capillary m
alformation
29%
Blood – 0%
right forearm and
hand, and confluence of
hyperpigmentation
and increased vascularity of the
right chest, shoulder and back. Pain on
palpation of his right third finger. O
ne fracture of his left
distal radius. Skeletal X-rays
showed
enlargement of his
phalanges and m
etacarpals of the right third and
fourth fingers, and m
ultifocal osteal lesions described as
lucent, expansile, and lytic lesions
involving the fingers, foot, tibia, hum
erus, fem
ur and clavicle on the right. N
eedle biopsy and surgical
pathology of the right tibia, including
small fragm
ents of bone associated
with scant fibrous
tissue and skeletal m
uscle, which
showed spindle and giant cell
proliferation diagnosed as nonossifying
fibroma. Clinical
genetic testing of the germ
line with a
neurofibromatosis
panel and whole
exome sequencing
were negative.
14
10 m
onths
Low flow
W
idespread linear keratinocytic
epidermal nevus in a
Blaschko-linear distribution,
localised to the right side except on the
mid back w
here there is a sm
all streak on the left.
Affects trunk and leg
chr12:g.25398284G>T
KRAS c.35G>T: KRAS p.(G12V)
177 3328
Skin biopsy from
capillary m
alformation
5%
Skin biopsy epiderm
al nevus 13%
but not head. M
oderate right-sided
hemihypertrophy
mainly affecting the
leg. Capillary vascular
malform
ation apparent on right foot and buttock. N
evus simplex on
glabella and nape of neck.
15
36 years
Low flow
Left low
er limb
hypertrophy requiring epiphyseal
fusion, lym
phoedema,
varicose veins with
previous recurrent DVT and cutaneous
vascular m
alformation.
Complicated by
recurrent cellulitis and left hip pain.
chr12:g.25398284G>A N
M_004985.4; N
M_033360.3:
c.35G>A: KRAS p.(G12D)
200 9510
Affected skin biopsy from
left low
er limb 2%
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34. Yang J, Boerm M, McCarty M, Bucana C, Fidler IJ, Zhuang Y, and Su B. Mekk3 is essential for early embryonic cardiovascular development. Nature genetics. 2000;24(3):309-13.
35. Cullere X, Plovie E, Bennett PM, MacRae CA, and Mayadas TN. The cerebral cavernous malformation proteins CCM2L and CCM2 prevent the activation of the MAP kinase MEKK3. Proceedings of the National Academy of Sciences of the United States of America. 2015;112(46):14284-9.
36. Fisher OS, Deng H, Liu D, Zhang Y, Wei R, Deng Y, Zhang F, Louvi A, Turk BE, Boggon TJ, et al. Structure and vascular function of MEKK3-cerebral cavernous malformations 2 complex. Nature communications. 2015;6(7937.
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38. Groesser L, Herschberger E, Ruetten A, Ruivenkamp C, Lopriore E, Zutt M, Langmann T, Singer S, Klingseisen L, Schneider-Brachert W, et al. Postzygotic HRAS and KRAS mutations cause nevus sebaceous and Schimmelpenning syndrome. Nature genetics. 2012;44(7):783-7.
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41. Igawa S, Honma M, Minami-Hori M, Tsuchida E, Iizuka H, and Ishida-Yamamoto A. Novel postzygotic KRAS mutation in a Japanese case of epidermal nevus syndrome presenting with two distinct clinical features, keratinocytic epidermal nevi and sebaceous nevi. The Journal of dermatology. 2016;43(1):103-4.
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43. Peacock JD, Dykema KJ, Toriello HV, Mooney MR, Scholten DJ, 2nd, Winn ME, Borgman A, Duesbery NS, Hiemenga JA, Liu C, et al. Oculoectodermal syndrome is a mosaic RASopathy associated with KRAS alterations. American journal of medical genetics Part A. 2015.
44. Boppudi S, Bogershausen N, Hove HB, Percin EF, Aslan D, Dvorsky R, Kayhan G, Li Y, Cursiefen C, Tantcheva-Poor I, et al. Specific mosaic KRAS mutations affecting codon 146 cause oculoectodermal syndrome and encephalocraniocutaneous lipomatosis. Clinical genetics. 2016;90(4):334-42.
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49. Kinsler VA, Thomas AC, Ishida M, Bulstrode NW, Loughlin S, Hing S, Chalker J, McKenzie K, Abu-Amero S, Slater O, et al. Multiple congenital melanocytic nevi and neurocutaneous melanosis are caused by postzygotic mutations in codon 61 of NRAS. The Journal of investigative dermatology. 2013;133(9):2229-36.
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Figure 1 – A broad clinical spectrum of vascular malformations in somatic RAS/MAPK mutations Inexorable enlargement of high-flow arteriovenous malformations with age, affecting the face and leading to loss of vision in the right eye (a-d), and the right ear helix and posterior auricular soft tissues leading to eventual resection of the helix (e-g). Varied clinical examples of the spectrum of high-flow VMs of the temple, left leg/buttock and left face (h,i). Segmental overgrowth of the left arm, chest wall and breast with a co-localised low-flow VM, detectable by a uniform brownish-pink macular capillary malformation and superimposed scattered telangiectasia, with clear midline demarcation (j-l). Segmental overgrowth of the right arm and hand, with a co-localised uniform brownish- pink capillary malformation with superimposed scattered telangiectasia (m,n).
a b c d
e f g h i
j k
l
m n
Fig. 1
Figure 2 – Imaging of sporadic VMs secondary to mutations in MAPK pathway genes demonstrating involvement of all blood vessel sizes Lateral image from a digitally subtracted angiogram showing a leash of small, abnormal vessels shunting through a dense capillary bed to early-filling veins (a); axial contrast-enhanced fat-saturated T1 weighted MRI image showing a grossly enlarged right pinna and thickened posterior auricular soft tissues. The abnormal tissue is filled with multiple signal voids, representing enlarged abnormal vessels. The pinna enhances avidly. (b). Lateral image from a digitally subtracted angiogram, with the catheter tip in the grossly enlarged left internal maxillary artery which supplies a leash of abnormal high flow vessels in the face (c). Thermography of low-flow VMs with overgrowth of the left chest wall and arm demonstrates increased temperature (shown in magenta) compared to the right-sided structures (d), and in the right forearm and thumb compared to the left (f). 3D reconstruction of an abdominal CT angiogram demonstrating multifocal vascular disease, with severe stenoses of the descending aorta, coeliac axis, superior mesenteric artery origin, and right renal artery (e).
a b c
d e f
Fig. 2
Figure 3 – Somatic variants in MAP2K1 cluster in exon 2 and are predicted to destabilise the 3D structure of the inactive form of the kinase (a) Schematic representation of clustered somatic mutations in exon 2 of MAP2K1; (b) Low allele frequency mutations on IGV visualization of deep next generation sequencing data from VM tissue samples of three patients; (c) 3D structural modelling of an inhibitor(4BM)-bound form (PDB ID: 3EQG) of MAP2K1 demonstrating the mutated residues. Deletions are highlighted in magenta (53-58) and orange (residues 58-62, with residue 58 common to both in pink). Critical residue K57 which is substituted as a result of the missense mutation is shown using ball and stick representation, with the dashed line indicating a hydrogen-bond interaction with the beta-sheet of the kinase. Residues involved in interaction between helix A and the core kinase domain are also shown.
a
b
c
Fig. 3
Na
Helix-CL63
V60
K57
L92
F53E144 MG ADP
4BMF129G128Helix-A
Activation loop
393 aa residues
39336144331 67
p.F5
3_Q
58de
linsL
K57N
p.Q
58_E
62de
lD Kinase DomainNES
Figure 4 - Mutations MAPK pathway-encoding genes lead to activation of downstream signaling, and disruption of vascular endothelial tube formation in vitro (a,b) Expression of mutant BRAFV600E, MAP2K1K57N and MAP2K1Q58_E62del in HEK293T cells leads to significantly increased phosphorylation of ERK detected by immunoblotting (representative blot shown from duplicate biological replicates), compared to wild-type gene overexpression and controls. Error bars represent mean +/- SD. Significance was determined using one-way ANOVA, and p values <0.05 are indicated by an asterisk. (c) Expression of mutant BRAFV600E and MAP2K1K57N in HUVEC cells seeded onto Geltrex® Matrix leads to visible disruption of endothelial vascular tube formation compared to controls, with (d,e,f) significant reductions in mean number of master junctions, total length of tubes, and total mesh area indicated by asterisks. Error bars represent mean +/- SD. Means were taken from triple technical replicates, for each of duplicate biological replicates, standardised to within-replicate controls, and analysed by one way ANOVA with correction for multiple testing (p value for significance reduced to <0.0167).
ERKGAPDH
WT
MAP
2K1
K57N
MAP
2K1
Q58
_E62
del
MAP
2K1
WT
BRAF
BRAF
V60
0E
Empt
y ve
ctor
P-ERKGAPDH
WT
MAP
2K1
K57N
MAP
2K1
Empt
y ve
ctor
Empt
y ve
ctor
Q58
_E62
del
MAP
2K1
GAPDHMAP2K1
a b
c d
e
Fig. 4
0 0.5
1 1.5
2 2.5
3
Mean ratio phospho-ERK to total ERK
0 0.2 0.4 0.6 0.8
1 1.2 1.4 1.6 1.8
Empty vector
WT BRAF
BRAF V600E
Mean ratio phospho-ERK to total ERK
* * *
Empty vector
WTMAP2K1
K57N MAP2K1
Q58del MAP2K1
0 0.2 0.4 0.6 0.8
1 1.2 1.4
Mock BRAF WT BRAF V600E
0 0.2 0.4 0.6 0.8
1 1.2 1.4 1.6
Standardised mean number master junctions
Standardised mean totallength channels
Standardised mean totalarea meshes
Standardised mean number master junctions
Standardised mean totallength channels
Standardised mean totalarea meshes
MAPK2K1 WT MAPK2K1 K57N MAP2K1 Q58del Mock
* *
* * *
*
* * * *
Figure 5 – BRAF and MAP2K mutations induce VM phenotypes in zebrafish that respond to targeted therapy. (a) Schematic of zebrafish embryos injected with Tg(fli1a:GFP) at the one-cell stage generate zebrafish larvae that are mosaic for the transgene integration and expression. (b) Image of mosaic expression of Tg(fli1a:GFP) in a zebrafish vessel. (c) Images of zebrafish expressing wild type or mutant BRAFV600E in a mosaic fashion from a fli1a promoter in endothelial cells. Accumulation of blood is visible at the junction of the caudal vein and artery in the BRAFV600E
–expressing zebrafish and outlined in dashed red line. (d) Quantification of VM phenotype in BRAFWT (n=511) and BRAFV600E (n=779) -expressing zebrafish. (e) BRAFWT and BRAFV600E mosaic expression in stable Tg(fli1a:GFP) larvae to visualize all vessels in the zebrafish in the VM lesion. Increased numbers of vascular channels and disorganized architecture of VM lesions are clearly detectable. (f) Schematic of VM treatment protocol, and quantification of the percentage of VM BRAFV600E zebrafish with improved blood flow following treatment with vemurafenib. VM BRAFV600E zebrafish were randomized prior to DMSO (n=31) or vemurafenib (n=19) treatment, and blind scored. (g) Images of zebrafish expressing MAPK2K1Q58del in a mosaic fashion from a fli1a promoter in endothelial cells (n=5/37). Zebrafish larvae in 5b were analyzed by an unpaired parametric t-test with Welch’s correction, and in 5d by a paired t-test comparing matched pairs (before and after treatment). Error bars are SEM.
a
gf
Fig. 5
1 Day 2 3 4 5
Treatment Select VM phenotypes Image Injection
Perc
ent
0
20
40
60
80
100
no phenotype VM phenotype
BRAF n=511BRAFV600E n=779
***
% b
lood
flow
rest
ored
0
20
40
60
80
100
DMSO BRAFi
*** Tg(fli1a:GFP)
DMSO n=31BRAFi n=19
b
mosaic Tg(fli1:gfp) expression
BRAF V600E c d
e
MAP2K1Q58del
VM phenotypeTg(fli1a:GFP)
VM phenotypeno phenotype
Tg(fli1:gfp) DNA
Mos
aic
BRAF
V6
00E
Control Mosaic
Con
trol Mosaic
Figure 6 - Schematic summary of the known and newly-identified signalling proteins affected by mosaic mutations which lead to a vascular malformation phenotype. Key signalling pathways PI3K-AKT-MTOR and RAS-RAF-MEK-ERK control cellular growth, apoptosis, and differentiation through complex transcriptional regulation. Multiple receptor types feed into one or both pathways. In addition, there is cross-talk between the two pathways at multiple levels (not shown). Proteins affected by the genetic mutations presented in this paper are shown in red, with previously identified sites shown in blue. Key classes of potential targeted therapeutics are shown in green boxes. RTK – receptor tyrosine kinase; GPCR – G-protein coupled receptor.
PTEN
PIP2
PIP3
AKT1
TSC1/2
PI3K
AKTInhibitors
MTORInhibitors
RASA1
RAS GTP
KRAS/NRAS
GPCR
GNAQ/GNA11
BRAF
RAS GDP
BRAFInhibitors
MEK 1/2(MAP2K1)
MEKInhibitors
REGULATION OF TRANSCRIPTION
mTORC1ERK1/2MAPK1
TIE2 (TEK) RTK
1
SUPPLEMENTARY MATERIAL
Figure S1 – the effects of BRAF overexpression on tail development in zebrafish larvae. (a) Image of an example of a zebrafish larvae expressing high levels of MAPK signaling, leading to a "stunting" phenotype, as previously described(1, 2) (b) Graph of zebrafish embryos expressing BRAF WT or V600E alleles. Both WT and mutant alleles lead to a stunted phenotype that confounds analysis of the vasculature in those animals, and were excluded from further analysis.
2
Figure S2 - In silico modelling using STRING of networks of genes implicated in human
vascular malformations gene products.
3
Table S1: Primers used for Sanger sequencing
Mosaic variant Forward primer sequence (5’ to 3’) Reverse primer sequence (5’ to 3’)
KRAS c.35G>A, p.Gly12Asp
AGCGTCGATGGAGGAGTTTG
ACAGAGAGTGAACATCATGGACC
MAP2K1 • c.171G>C,
p.(K57N) • c.159_173delTCTT
ACCCAGAAGCA, p.(F53_Q58delinsL)
• c.173_187delAGAAGGTGGGAGAAC, p.(Q58_E62del)
TGGGTTGACTTCTCTGGTGA
GAGACCTTGAACACCACACC
4
Table S2: Gene targets covered by the custom-designed 60 gene overgrowth sequencing
panel (AmpliSeq, Life Technologies).
195 amplicons ranging from 125-275 bp in size were designed to cover the codons of interest listed below, except in the case of PIK3CA, PTEN and CCND2, where full coverage of all coding regions is provided. Annotations are according to reference genome hg19. Where multiple transcript variants exist, the longest transcript variant is stated for the purpose of amino acid numbering.
Gene Regions covered Amino acids covered
AKT1 Chr14: 105246445 – 105246583 p.G16 – p.L52
Chr14: 105241352 – 105241535 p.E151 – p.K189
AKT2 Chr19: 40762852 – 40763002 p.G16 – p.L52
AKT3 Chr1: 243858913 – 243859106 p.G16 – p.L51
ALK Chr2: 29443490 – 29443714 p.K1173 – p.P1215
Chr2: 29436788 – 29437003 p.S1216 – p.H1247
Chr2: 29432582 – 29432804 p.D1249 – p.Y1278
BRAF Chr7: 140481298 – 140481511 p.K439 – p.H477
Chr7: 140453028 – 140453243 p.I582 – p.M620
CCND2 All coding regions
CDK2 Chr12: 56361535 – 56361762 p.E40 – p.V64
Chr12: 56362526 – 56362676 p.Y107 – p.L143
DEPTOR Chr8: 121018956 – 121019175 p.L310 – p.T332
EGFR Chr7: 55241601 – 55241801 p.L688 – p.K728
Chr7: 55248900 – 55249123 p.E762 – p.D807
Chr7: 55249121 – 55249200 p.D807 – p.K823
Chr7: 55259353 – 55259582 p.G824 – p.K875
ERBB2 Chr17: 37868167 – 37868373 p.N302 – p.R340
Chr17: 37880147 – 37880352 p.G737 – p.D769
ERBB3 Chr12: 56478786 – 56479009 p.R81 – p.A155
EZH2 Chr7: 148508619 – 148508841 p.H618 – p.E649
FGFR1 Chr8: 38285848 – 38286070 p.A121 – p.M149
Chr8: 38282094 – 38282318 p.R281 – p.L321
FGFR2 Chr10: 123279547 – 123279766 p.R251 – p.E295
Chr10: 123274672 – 123274890 p.P364 – p.V416
Chr10: 123257952 – 123258121 p.D523 – p.D558
FGFR3 Chr4: 1803433 – 1803647 p.G235 – p.C275
Chr4: 1806061 – 1806208 p.E362 – p.V413
FLT3 Chr13: 28610030 – 28610230 p.K438 – p.P472
Chr13: 28608204 – 28608422 p.Q569 – p.F612
Chr13: 28602195 – 28602418 p.K649 – p.S684
Chr13: 28592526 – 28592736 p.C807 – p.N847
GNA11 Chr19: 3118790 – 3118993 p.M203 – p.I226
5
GNAQ Chr9: 80409380 – 80409598 p.M203 – p.E245
GNAS Chr20: 57484401 – 57484626 p.D839 – p.F862
HRAS Chr11: 534102 – 534306 p.K5 – p.E37
Chr11: 533780 – 533936 p.R41 – p.I93
IDH1 Chr2: 209113051 – 209113255 p.E84 – p.Q138
IDH2 Chr15: 90631752 – 90631976 p.F126 – p.Q178
IGF1R Chr15: 99440011 – 99440237 p.E325 – p.G367
IGF2R Chr6: 160485824 – 160485949 p.P1340 – p.F1371
Chr6: 160496879 – 160497103 p.D1723 – p.M1772
Chr6: 160517434 – 160517663 p.G2220 – p.L2280
JAK2 Chr9: 5073668 – 5073862 p.S593 – p.E621
JAK3 Chr19: 17954041 – 17954267 p.E113 – p.Q140
Chr19: 17947870 – 17948080 p.S568 – p.D595
Chr19: 17945623 – 17945811 p.L684 – p.K733
KDR Chr4: 55980271 – 55980456 p.Y221 – p.K266
Chr4: 55979507 – 55979727 p.Q268 – p.M314
Chr4: 55972826 – 55973041 p.Q472 – p.K512
Chr4: 55962395 – 55962621 p.G873 – p.G909
Chr4: 55960908 – 55961127 p.T940 – p.E990
Chr4: 55955033 – 55955251 p.Y1136 – p.Q1170
Chr4: 55953691 – 55953917 p.G1172 – p.I1220
Chr4: 55946189 – 55946355 p.G1284 – p.I1330
Chr4: 55946011 – 55946232 p.I1330 – p.V1356
KIT Chr4: 55561667 – 55561888 p.S24 – p.G93
Chr4: 55592066 – 55592292 p.S464 – p.K513
Chr4: 55593338 – 55593546 p.Q515 – p.Q549
Chr4: 55593499 – 55593700 p.K550 – p.L589
Chr4: 55594136 – 55594358 p.S628 – p.G663
Chr4: 55595409 – 55595630 p.P665 – p.L707
Chr4: 55597389 – 55597603 p.S715 – p.I744
Chr4: 55599232 – 55599442 p.C788 – p.N828
Chr4: 55602591 – 55602803 p.A829 – p.L865
KRAS Chr12: 25398183 – 25398385 p.M1 – p.E37
Chr12: 25380260 – 25380337 p.R41 – p.A66
Chr12: 25378561 – 25378743 p.E98 – p.A146
LAMTOR1 Chr11: 71810184 – 71810406 p.D15 – p.L54
Chr11: 71809744 – 71809973 p.N64 – p.Y88
LAMTOR2 Chr1: 156025008 – 156025204 p.L24 – p.M74
MAP2K1 Chr15: 66729047 – 66729265 p.L98 – p.M146
Chr15: 66774032 – 66774239 p.V191 – p.S231
Chr15: 66727373 – 66727563 p.T28 – p.A95
6
MAPKAP1 Chr9: 128246741 – 128246970 p.S357 – p.F396
Chr9: 128201149 – 128201292 p.V482 – p.Q522
MET Chr7: 116339530 – 116339753 p.I131 – p.F206
Chr7: 116340170 – 116340389 p.G344 – p.R400
Chr7: 116403120 – 116403338 p.S812 – p.K879
Chr7: 116411806 – 116412001 p.L982 – p.V1014
Chr7: 116417424 – 116417614 p.H1106 – p.N1131
Chr7: 116423291 – 116423508 p.L1230 – p.T1280
MLST8 Chr16: 2256502 – 2256711 p.Q63 – p.L114
Chr16: 2258233 – 2258463 p.L199 – p.S232
MTOR Chr1: 11190760 – 11190931 p.A1789 – p.E1813
Chr1: 11190565 – 11190770 p.Q1807 – p.E1871
Chr1: 11187658 – 11187880 p.V2012 – p.Q2072
Chr1: 11174371 – 11174529 p.V2389 – p.D2433
Chr1: 11169263 – 11169482 p.G2484 – p.T2509
NRAS Chr1: 115258627 – 115258821 p.M1 – p.E37
Chr1: 115256452 – 115256669 p.D38 – p.S87
Chr1: 115252147 – 115252254 p.T127 – p.Q150
PDGFRA Chr4: 55140927 – 55141154 p.K552 – p.L595
Chr4: 55144059 – 55144277 p.T632 – p.S667
Chr4: 55151970 – 55152162 p.C814 – p.S854
PDK1 Chr2: 173427380 – 173427601 p.R138 – p.M156
Chr2: 173450928 – 173451139 p.M336 – p.L372
Chr2: 173457684 – 173457906 p.P380 – p.K410
PHLPP1 Chr18: 60642573 – 60642794 p.K1253 – p.S1307
PHLPP2 Chr16: 71683541 – 71683769 p.A999 – p.G1075
PIK3CA All coding regions
PIK3CB Chr3: 138374192 – 138374406 p.D1026 – p.S1070
PIK3R1 Chr5: 67593218 – 67593445 p.V663 – p.R724
PIK3R2 Chr19: 18273734 – 18273817 p.K371 – p.G385
PTEN All coding regions
PTPN11 Chr12: 112888117 – 112888297 p.R47 – p.C104
Chr12: 112926780 – 112926999 p.V484 – p.Q533
RHEB Chr7: 151187964 – 151188182 p.K19 – p.N41
Chr7: 151167603 – 151167827 p.V128 – p.Q154
RICTOR Chr5: 38959878 – 38959945 p.I663 – p.Q683
Chr5: 38952408 – 38952632 p.T967 – p.D1006
Chr5: 38950550 – 38950776 p.S1058 – p.L1134
RPS6KB1 Chr17: 58011763 – 58011967 p.A261 – p.A290
Chr17: 58013815 – 58014032 p.A348 – p.L373
RPS6KB2 Chr11: 67201650 – 67201787 p.R324 – p.L349
7
RPTOR Chr17: 78882538 – 78882765 p.V802 – p.K840
Chr17: 78899135 – 78899346 p.T937 – p.K973
Chr17: 78933883 – 78934090 p.D1160 – p.E1201
RRAGA Chr9: 19049675 – 19049856 p.T4 – p.Q66
RRAGB ChrX: 55748556 – 55748778 p.V43 – p.T75
ChrX: 55757816 – 55758046 p.E132 – p.L200
ChrX: 55779786 – 55780009 p.A233 – p.L273
RRAGC Chr1: 39322645 – 39322863 p.V80 – p.D116
Chr1: 39322526 – 39322746 p.D116 – p.Q147
Chr1: 39321410 – 39321639 p.D148 – p.A204
RRAGD Chr6: 90077747 – 90077976 p.L352 – p.L400
SMAD4 Chr18: 48575081 – 48575265 p.H92 – p.D142
Chr18: 48575548 – 48575763 p.D142– p.N151
Chr18: 48581005 – 48581225 p.A152 – p.H177
Chr18: 48584490 – 48584654 p.S223 – p.H262
Chr18: 48586137 – 48586349 p.P303 – p.P318
Chr18: 48591742 – 48591964 p.A319 – p.I376
Chr18: 48593403 – 48593514 p.G384 – p.P422
Chr18: 48603025 – 48603205 p.Q442 – p.I482
Chr18: 48604603 – 48604826 p.S483 – p.P550
SOS1 Chr2: 39281647 – 39281866 p.E198 – p.N240
Chr2: 39249808 – 39250023 p.E515 – p.I587
SRC Chr20: 36031585 – 36031773 p.R472 – p.E534
STAT3 Chr17: 40474350 – 40474557 p.K631 – p.G684
8
Table S3: Restriction fragment length polymorphism assay reagents.
PCR products were designed to cover the codon of interest. One primer was labelled with 6-carboxyfluorescein (6FAM) for detection via Genemapper software on an AB13730 capillary sequencer. The other primer was designed to include a restriction enzyme recognition site (altered bases depicted in capitals), resulting in specific digestion of the mutant but not the wildtype allele.
Mosaic
variant
Forward primer
sequence (5’ to 3’) Reverse primer
sequence (5’ to 3’) Restriction
enzyme
Size of
wildtype
fragment
(bp)
Size of
mutant
fragment
following
digestion
(bp)
KRAS, c.35G>A, p.Gly12Asp
aaacttgtggtagttggagcGg
[6FAM]aagaatggtcctgcaccagta
FokI 145 111
NRAS c.182A>G, p.Gln61Arg
gacatactggatacagcCgTac
[6FAM]tggggaaatgaggttaccaca
BsiWI 206 188
KRAS c.35G>T, Gly12Val
[6FAM]aaaaggtactggtggagtatttga
tcaaggcactcttgcctacgTTa
HpaI 158 136
9
Table S4: Antibodies used for immunoblotting
Antibody name Dilution Catalogue number
MAP2K1 (MEK1) Antibody 1:1000 Cell Signalling Technology #9124 p44/p42 MAPK (Erk1/2)(137F5) Rabbit mAb
1:500 Cell Signalling Technology #4695
Phospho-p44/42 MAPK (Erk1/2)(Thr202/Tyr204)(197G2) Rabbit mAb
1:1000 Cell Signalling Technology #4377
GAPDH (14C10) Rabbit mAb 1:3000 Cell Signalling Technology #2118 Anti-Rabbit IgG (γ-chain specific)–Peroxidase antibody, Mouse monoclonal RG-96 (secondary antibody used in all immunoblotting experiments)
1:7000 Sigma A1949
10
Table S5: Results of genotyping for PIK3CA and KRAS in multiple tissue samples in patient
7. MAF = minor allele frequency; FFPE = formalin-fixed, paraffin-embedded; RFLP = fluorescent Restriction Fragment Length Polymorphism assay; NGS = next generation sequencing
Sample Genotype MAF Technique Comment
Intradural, extra-medullary spinal plexiform tumour (FFPE)
PIK3CA H1047L KRAS G12D
7% 0% 0%
RFLP NGS NGS
Poor quality FFPE DNA. PIK3CA variant only present in 1 FFPE block out of 4. Low read depth in NGS (mean read depth < 50)
Neurofibroma (FFPE)
KRAS G12D PIK3CA H1047L
30% 0%
Sanger Sanger, RFLP
Lipoma (FFPE) PIK3CA H1047L 3% 0%
RFLP Sanger
Poor quality FFPE DNA.
Epidermal nevus fresh tissue
KRAS G12D PIK3CA H1047L
30% 0%
NGS, Sanger NGS, RFLP
Fibroblasts grown from epidermal nevus
KRAS G12D PIK3CA H1047L
39% 0%
NGS, Sanger NGS, RFLP
Blood PIK3CA H1047L KRAS WT
0% 0%
RFLP, Sanger Sanger
References
1. Anastasaki C, Estep AL, Marais R, Rauen KA, and Patton EE. Kinase-activating and
kinase-impaired cardio-facio-cutaneous syndrome alleles have activity during zebrafish development and are sensitive to small molecule inhibitors. Human molecular genetics. 2009;18(14):2543-54.
2. Anastasaki C, Rauen KA, and Patton EE. Continual low-level MEK inhibition ameliorates cardio-facio-cutaneous phenotypes in zebrafish. Dis Model Mech. 2012;5(4):546-52.