SUPPLEMENTARY METHODS
Granulocytes and CD3+ T-cells purification and DNA extraction
Granulocytes were obtained by density gradient centrifugation of peripheral
blood samples, made free of contaminating red blood cells by cell lysis, and
stored frozen until use. CD3+ cells were immunomagnetically selected (Miltenyi
Biotec GmbH, Bergisch Gladbach, Germany) from recovered mononuclear cell
fraction and in-vitro expanded for 7 days at 37°C with 5% CO2 in an expansion
medium containing 20ng per milliliter of human IL-2 (Miltenyi Biotec GmbH,
Bergisch Gladbach). The purity of the CD3+ cells was determined by flow
cytometry after labeling with FITC-conjugated anti-CD3 monoclonal antibody
(Becton, Dickinson and Company, San Jose, CA). Genomic DNA was purified using
the Wizard DNA genomic purification kit (Promega, Madison, WI, USA).
DNA from salivary samples was obtained using the Oragene-Discover DNA
Extraction Kit (DNA Genotek, Kanata, Ontario, Canada); there was no visual
blood contamination in the samples that were processed. Quantity and purity of
nucleic acid samples were assessed using Nanodrop 1000 (Thermo Fisher
Scientific, Freemont, CA, USA) and 2100 Bioanalyzer (Agilent Technologies, Palo
Alto, CA, USA).
Liquid capture and 454 Sequencing
Sample library preparation was carried out starting from 500ng of DNA of
somatic and germline samples; DNA was fragmented by nebulization to obtain
an average fragment length between 600 and 900 bp. Fragments were purified,
end-repaired, ligated to unique Multiplex Identifiers (MID), purified to remove
small fragments and finally quantified on TBS Fluorometer (Turner Biosystem,
Sunnyvale, CA, USA) according to the Rapid library Preparation Method Manual
(454 Life Sciences, Roche, Branford, CT, USA).
Single sample libraries were pre-amplified, purified onto QIAquick columns
(Qiagen, Valencia, CA, USA) and checked for quality with the Agilent DNA 7500
kit (Agilent Technologies, Palo Alto, CA, USA) before proceeding to hybridization.
Pools of up to 12 barcoded samples were prepared by mixing equimolar
quantities of each purified pre-amplified sample library. A total of 1 μg of each
MID-tagged DNA sample library pool was hybridized to the Choice library in the
presence of 2,000 pmol of Hybridization Enhancing Oligo, 5 micrograms of COT
DNA, 2X Hybridation Buffer and Hybridization Component A, according to the
NimbleGen SeqCap EZ Choice Library LR User’s Guide. Hybridization reactions
were performed in a thermal cycler at 47 °C for 72 hours.
After hybridization, captured DNA was bound to Streptavidin Dynabeads
(Invitrogen Corporation, Life Technologies Ltd, Paisley, UK), washed with proper
stringent buffers, PCR amplified, purified onto QIAquick columns and checked
for quality with an Agilent DNA 7500 chip onto a 2100 Bionalayzer(Agilent
Technologies, Palo Alto, CA, USA).
Target enrichment was evaluated by qPCR onto a LightCycler 480 System (Roche
Diagnostics, Mannheim, Germany) checking for a standard set of 4 NimbleGen
Sequence Capture (NSC) control loci which represent a range of known capture
efficiencies. QPCR assays were performed in triplicate in both pre- and postcapture samples according to manufacturer’s recommendations.
Each target enriched sample pool was tested in small volume emPCR to establish
the optimal number of copy per beads to use for large volume emPCR
preparation and therefore for sequencing. Enriched beads with proper
enrichment value (5-20%) were loaded on a 2 regions PicoTiterPlate device and
sequenced in a GS FLX System according to the last version of the Roche
Sequencing Method Manual.
Variant detection
All samples were independently processed using GS Reference Mapper Roche
454 Analysis software v2.6 using the CLI (Command-Line Interface) to obtain the
alignment of NGS sequence data to the human reference genome (hg19),
followed by variant detection. For each sample, a set of high-confidence
variations was obtained. Specifically, the following general rules were applied for
determining the high-confidence of a difference: there must be at least 3 nonduplicate reads with the difference, there must be both forward and reverse
reads showing the difference, unless there are at least 7 reads with quality scores
over 20 (or 30 if the difference involves a 5-mer or higher). If the difference is a
single-base overcall or undercall, then the reads with the difference must form
the consensus of the sequenced reads (i.e. at that location, the overall consensus
must differ from the reference) and the signal distribution of the differing reads
must vary from the matching reads (and the number of bases in that
homopolymer of the reference). The frequency of a variant is defined as the
percentage of different reads versus total reads in the sample that fully span the
difference location.
Variant filtering and classification
To evaluate whether the variations detected in the somatic samples were “true”
somatic variations, we compared the somatic with the germline CD3+ samples
using a subtractive approach to filter the genetic background, in order to detect
and consequently discard shared signals arising from germline polymorphisms
or technical noise.
We performed two types of comparisons: (i) within-patients (given each
somatic-germline paired samples) and (ii) between patients (considering all the
germline samples in the dataset as a panel of germline samples).
We proceeded as follows. Let P be the dataset of patients for which we
sequenced both the somatic and germline samples. For each patient p ∈ P, let Sp
be the set of non-synonymous variants identified in the somatic sample. For each
patient p ∈ P, each somatic candidate variant x ∈ Sp was rejected if observed, at
any frequency, (i) in the paired germline sample or (ii) in the germline of another
patient q ∈ P.
Taking into account the problem of possible somatic contamination found in the
germline samples, in case of known mutations (like JAK2 V617) we retained the
variant even if observed in the germline counterpart.
The selected variants were then further filtered, discarding the ones having
frequency in 1000 genomes > 1% (1). Furthermore, we searched our SNPs for
functional predictions in the dbNSFP database (2), a database for Nonsynonymous SNPs' Functional Predictions, that compiles prediction scores from
four algorithms (SIFT (3), Polyphen2 (4), LTR (5) and Mutation Taster (6)), along
with other related information, for every potential non-synonymous SNP in the
human genome. We also searched for functional predictions of coding indels
using Provean (7). Thus, for each somatic variant we reported the predictions of
all these five algorithms, indicating if the mutation was likely to be damaging or
neutral. In addition, for each variant we also provided COSMIC annotation, (8) if
present.
All used databases for variant annotation and classification were freely available
for download. The dbSNP (9) database version 135 was downloaded from
ftp://hgdownload.cse.ucsc.edu/goldenPath/hg19/database/snp135.txt.gz. The
dbNSFP database version 1.3 was downloaded as .zip file (together with
search_dbNSFP13.class, a java program used for querying the database dbNSFP
v1.3 on local machine), from
dbnsfp.houstonbioinformatics.org/dbNSFPzip/dbNSFP1.3.zip. The 1000
genomes data was downloaded from
ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20110521. Regarding the
COSMIC database release v60, the mutation data were obtained from the Sanger
Institute Catalogue Of Somatic Mutations In Cancer web site,
http://www.sanger.ac.uk/cosmic.
Validation testing of somatic mutations
A recurrence testing for true somatic variants was performed with Ion Torrent
PGM (Life Technologies). A bed file containing chromosomes coordinates of
mutations (see Supplementary Table 3) was submitted to Ion AmpliSeq Designer
(www.ampliseq.com), pipeline version 2.0 (Life Technologies Ltd, Paisley, UK).
Assay design was optimized so that each mutation occurred in the middle of an
amplicon. A custom Ion AmpliSeq panel was designed (Life Technologies Ltd,
Paisley, UK). In this multiplex PCR-based library preparation method, two pools
of 200bp amplicons encompass the variants previously confirmed to be true
somatic mutations. The overall coverage rate was 97.8% and it was possible to
cover all the mutations identified except for POLI variant. The custom Ion
AmpliSeq panel was processed with Ion AmpliSeq Library kit 2.0 according to
manifacturer’s recommendations. Samples were barcoded with IonExpress
Barcode Adapter (Life Technologies Ltd, Paisley, UK) in order to optimize
patients pooling on the same sequencing chip. Template preparation was
performed with Ion One Touch System (DL configuration) and Ion One Touch ES,
following Ion One Touch 200 Template Kit v2 DL manuals. Enriched, templatepositive Ion One Touch 200 Ion Sphere Particles were loaded on the Ion 318 Chip
following Ion PGM 200 Sequencing kit protocol.
All samples were processed using Torrent Suite Software 3.6. Variant calling was
performed running Torrent Variant Caller plugin version 3.6.56708. Moreover,
samples were analyzed using a different pipeline: starting from the unaligned
bam files, alignment to human reference genome hg19 and variant calling were
performed using Burrows-Wheeler Aligner version 0.6.2-r126 (http://biobwa.sourceforge.net/) (10) and SAMtools version 0.1.18
(http://samtools.sourceforge.net/) (11) followed by Varscan v2.3.5
(http://varscan.sourceforge.net/) (12). Results of the two procedures were
compared and merged.
NRAS and KRAS High Resolution Melting (HRM) mutation analysis
Genomic DNA from 139 patients with PMF was extracted from granulocytes that
had been collected at the time of diagnosis. NRASG12V of (rs121913237: G> A;
p.Gly12Asp in codon 12) and K-RAS (exon2, codons 12-13 and exon3, codons 5961) mutation analysis was performed using High-resolution melting (HRM) in a
Light Cycler 480 System (Roche Diagnostics, Mannheim, Germany), using the
following primers:
NRAS
codons
12-13
KRAS
codons
12-13
KRAS
codons
59-61
Forward primer
Reverse primer
5’-GGTTTCCAACAGGTTCTTGC-3’
5’-CACTGGGCCTCACCTCTATG3’
5’GGCCTGCTGAAAATGACTGAATATAA3’
5’CCAGACTGTGTTTCTCCCTTCTCAGG3’
5’AAAGAATGGTCCTGCACCAGTA3’
5’AGAAAGCCCTCCCCAGTCCTCA3’
The HRM reactions were performed in a total volume of 20 microliters in the
presence of 1X High Resolution Melting Master Mix (Roche Diagnostics,
Mannheim, Germany), 0.2 micromolar of both forward and reverse primers
(Integrated DNA Technologies, Coralville, IA USA), 3.5 mM of MgCl2, and 10
nanograms of gDNA. The HRM step was preceded by a pre-incubation step for
FastStart Taq DNA Polymerase activation and DNA denaturation at 95°C for 10
minutes (min) and a touchdown PCR step of 45 cycles at 95°C for 10 seconds
(sec), from 65° to 53° C for 15 sec (decreasing 0.5° C every cycle), 72°C for 10
sec. In the following melting step, the temperature was increased from 73°C to
95°C (ramping 0.02 °C/sec, 25 acquisitions per °C).
In order to identify homozygous mutations, in samples that showed a melt curve
similar to control DNA, a subsequent analysis was performed by mixing test DNA
(90%) with DNA from healthy controls (10%). All samples showing abnormal
melt pattern were subjected to PCR amplification for direct sequencing. The
conditions were as follows: 95°C for 13 min, 35 cycles at 95°C for 30 sec,
annealing at 59°C for 30 sec, extension at 72°C for 10 min. PCR reactions were
carried out on a 2720 Thermal Cycler (Applied Biosystems, Life-Tech company,
Paisley, UK). Direct sequencing was performed using SANGER technology by
means of ABI PRISM 3100 Genetic Analyzer (Applied Biosystems, Life-Tech
company, Paisley, UK) and all sequence traces were manually reviewed using
Mutation Surveyor (SoftGenetics, State College, PA, USA).
SUPPLEMENTARY DISCUSSION
Brief summary of biological features of genes found recurrently mutated in the
validation cohort.
SCRIB H1217P; rs148494356
SCRIB encodes a cytoplasmic scaffolding protein consisting of leucine-rich
repeats and PDZ domains that regulate protein-protein interactions (13). SCRIB
is implicated in Planar Cell Polarity (PCP) differentiation, in particular in
coordinating apicobasal cell polarity (14, 15) and may negatively regulate the
RAS/MAPK cascade to maintain polarity and tissue homeostasis (16, 17).
H1217P is a missense mutation predicted to be damaging by SIFT and PolyPhen2,
whose validation status has yet to be established. Missense mutations in the
same Scrib c-terminal domain region significantly disrupt the membrane
subcellular localization of the protein and this was suggested to be one possible
pathogenic mechanism of PCP mutation in mammals (18, 19). Furthermore,
studies in Drosophila and mammalian cell lines show that SCRIB loss and RAS
activation cooperate (interclonally or intraclonally) to promote invasion (20-22).
In Drosophila interclonal cooperation in RasV12 and scrib-minus tumor clones,
uncover a two-level mechanism by which scrib-minus cells promote neoplastic
development of RasV12 cells: (1) spread of stress-induced JNK activity from
scrib-minus cells to RasV12 activated cells; and (2) expression of the JAK/STATactivating cytokines downstream of JNK (22).
- MIR662, rs74656628
Human miR-662 is an intragenic microRNA that resides in a non-coding exon
sequence of mesothelin-like (MSLNL) gene (23). This microRNa was found
differentially expressed in chronic heart failure (CHF) secondary to ischemic
cardiomyopathy (ICM) verus non-ischemic cardiomyopathy (NICM) e in
germinal vesicle (GV)-stage mouse oocytes versus oocytes matured at
conventional FSH levels (24, 25).
The rs74656628 is a missense mutation, occurring in the precursor sequence of
the micro-RNA (26). To assess if this mutation could lead to the production of a
different mature miRNA, we run In-Silico-Dicer (http://bibiserv.techfak.unibielefeld.de/insilicodicer/), a program that simulate the cleavage steps mediated
by Dicer for the prediction of mature miRNA from known precursors. For wild
type human pre-miR-662, the algorithm predicts a mature sequence that is
concordant to the one found in miRBase (nucleotides 61-81 of the pre-miRNA).
For the mutated pre-mir-662 (rs74656628), instead, the predicted mature
miRNA has a completely different nucleotide composition (nucleotides 0-21)
(Supplementary Figure 2).
We run also RNAFold (http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi), a
thermodynamic structure prediction tool for the prediction of RNA secondary
structure. With the wild type pre-mir-662 sequence, we obtained a centroid
secondary structure resembling the one found in the non-coding RNA database
Rfam (http://rfam.janelia.org/), with a minimum free energy of -36.60 kcal/mol.
The mutated sequence, instead, led to a different structure, with a minimum free
energy of -45.90 kcal/mol, that doesn't contain the known stem-loop described
in miRBase, and that doesn't fit with the typical secondary structure of a premiRNA (Supplementary Figure 3). It is therefore conceivable that this mutation
leads to a decrease of the mature mir-662 expression level, whose functional
impact has to be established.
BARD1 C557S, rs28997576
BRCA1 Associated RING Domain 1 (BARD1) encodes for a protein which
interacts with the N-terminal region of BRCA1. C557S is a G>C transversion in
codon 557 that cause an amino acid change Cys>Ser in exon 7; it’s a missense
mutation that resides in the flexible linker between the ankyrin repeats and the
BRCA1 carboxy-terminal (BRCT) domain of the BARD1 protein. BARD1 is
implicated as a BRCA1-independent mediator between genotoxic stress and p53dependent apoptosis (27). The C-terminal portion of BARD1 protein, that
includes the residue 557, is recognized as the minimum region sufficient for
induction of apoptosis (28) and necessary for binding to p53. The BARD1C557S
is demonstrated to be a pathogenic mutation; the variant protein indeed is
defective in growth-suppressive and apoptotic activities of BARD1 and has an
effect on p53 stabilization in breast and ovarian cancers (29). Moreover, the
region is also involved in binding to the Ewing's sarcoma protein (30) to Bcl3,
thus modulating transcription factor NFKB (31) and to Cstf1, repressing the
polyadenylation machinery in vitro (32, 33).
TCF12 G300S, rs12442879
TCFF12 protein, also known as HEB, is a member of the basic helix-loop-helix
(bHLH) E-protein family that recognizes the consensus E-box CANNTG. This
protein is expressed in many tissues and participates in lineage-specific gene
expression regulation throughout the formation of heterodimers with other
bHLH E-proteins and with chimeric protein AML1-ETO (34-36). TCF12 can work
as a transcriptional repressor of E-cadherin and play an important role in cancer
cell progression by enhancing the epithelial-mesenchymal transition process
(37). The missense mutation G300S occurs in the protein region between TCF12
activation domain 1 and 2 (38); imputation tools consider it as a
tolerated/benign variant and at the moment it is not associated to any clinical
significance.
FAT4 R175L, rs143534324
FAT4 belongs to the E-cadherin family and may control noncanonical
Wnt/planar cell polarity signaling (39); it is broadly expressed in many tissues
and seems to have a central function in gastrointestinal tract development (40,
41); in mouse mammary epithelial cells FAT4 induces tumorigenesis (42).
Somatic inactivation of FAT4 may be a key tumorigenic event in a subset of
gastric cancers (43) and recently Zang and colleagues observed that FAT4 exerts
a tumor-suppressor activity in gastric adenocarcinomas (44). R175L mutation is
located in the extracellular cadherin domain and Polyphen and MutationTaster
analysis revealed that this FAT4 mutation is predicted to adversely affect protein
function. Actually, if this mutation has a clinical or pathogenetic relevance has to
be established.
DAP3 G5R, rs61755343
Death-associated protein 3 (DAP3), also known as mitochondrial ribosomal
protein S29 (MRP-S29) is a protein located in the small subunit of the ribosome.
It is a pro-apoptotic protein whose essential Ser and Thr residues in the GTP
binding domain need to be phosphorylated for the induction of apoptosis (45).
Moreover, DAP3-mediated mitochondrial fragmentation also depends on its
correct localization to this organelle, because removal of the N-terminal
mitochondrial signal (the first 17 amino acids) abolished the effects of DAP3 on
mitochondrial morphology (46). It’s in this N-terminal domain that the mutation
we tested occurs. SIFT predicts DAPG5E is a damaging missense mutation, even
if actually there is no information about any possible role of this mutation in
preventing sub-cellular localization and therefore cellular function of human
DAP3.
POLG, A154T
The protein encoded by this gene is the catalytic subunit of mitochondrial DNA
polymerase. It has been implicated in base excision repair and cancer (47), and
also in erythroid dysplasia (48).
A154T mutation resides in the N-terminal part of POLG protein that includes the
mitochondrial targeting sequence and, to our knowledge, is described here for
the first time. Imputation algorithms predict it is a damaging mutation and its
biological effect has to be verified.
NRASG12V, rs121913237,rs121913250
N-RAS is a guanine nucleotide-binding protein that regulates signal transduction
on binding to a variety of membrane receptors and plays an important role in the
physical processes including proliferation, differentiation and apoptosis.
Different mutations in this gene have been accepted as oncogenic events in the
tumorigenesis of numerous malignancies, including hematologic malignancies
such as AML (49). In AML indeed, the most frequent mutations in N-RAS occur
nearly exclusively by one base change in codon 12, 13 or 61 (50-52). These
activating point mutations abrogate intrinsic RAS GTPase activity and thus
confer constitutive activation of RAS proteins. A recent study of 504 AML
patients reported that between the different N-RAS mutations analyzed, the one
we found, the c.35 G> A (p.Gly12Asp) was described to be one of the most
common base substitutions (53).
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