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Genomic landscape and chronological reconstruction of driver events in multiple myeloma Francesco Maura1,2,3*, Niccoló Bolli1,2,3*, Nicos Angelopoulos3, Kevin J. Dawson3, Daniel Leongamornlert3, Inigo Martincorena3, Thomas J. Mitchell3, Anthony Fullam3, Santiago Gonzalez4, Raphael Szalat5, Bernardo Rodriguez-Martin6, Mehmet Kemal Samur5, Dominik Glodzik3, Marco Roncador3, Mariateresa Fulciniti5, Yu Tzu Tai5, Stephane Minvielle7, Florence Magrangeas7, Philippe Moreau7, Paolo Corradini1,2, Kenneth C. Anderson5, Jose M. C. Tubio3,6, David C. Wedge8, Moritz Gerstung4, Herve Avet-Loiseau9, Nikhil Munshi5,10 # and Peter J. Campbell3 #
*These authors contributed equally to this work; # Co-corresponding authors 1 Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy 2 Department of Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; 3 The Cancer, Ageing and Somatic Mutation Programme, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, United Kingdom 4 European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI) 5 Jerome Lipper Multiple Myeloma Center, Dana–Farber Cancer Institute, Harvard Medical School, Boston, MA; 6 CIMUS - Molecular Medicine and Chronic Diseases Research Centre University of Santiago de Compostela, Spain 7 CRCINA, INSERM, CNRS, Université d’Angers, Université de Nantes, Nantes, France 8 University of Oxford, Big Data Institute 9 IUC-Oncopole, and CRCT INSERM U1037, 31100, Toulouse, France. 10 Veterans Administration Boston Healthcare System, West Roxbury, MA; Running Title: Multiple Myeloma Driver Events Key words: Multiple Myeloma, Whole Genome Sequencing, Driver Events, Structural Variations, Chromothripsis Corresponding Authors: Dr Peter J Campbell, Cancer Genome Project, Wellcome Sanger Institute, Hinxton CB10 1SA, United Kingdom. Phone: +44 1223 494745 e-mail: [email protected]
Dr Nikhil C. Munshi Dana-Farber Cancer Institute 450 Brookline Avenue, Dana B106 Boston, MA 02215, USA Phone: +1-617-632-4218 Fax +1-617-582-8608 e-mail: [email protected]
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Abstract
Multiple myeloma (MM) has a heterogeneous genome, evolving through both
pre-clinical and post-diagnosis phases. Here, using sequences from 67 MM
genomes serially collected from 30 patients together with public datasets, we
establish a hierarchy of driver lesions. Point mutations, structural variants and copy
number aberrations define at least 7 genomic subgroups of MM, each with distinct
sets of co-operating driver mutations. Complex structural events are major drivers of
MM, including chromothripsis, chromoplexy and a replication-based mechanism of
templated insertions: these typically occur early. Hyperdiploidy also occurs early,
with individual chromosomes often gained in more than one chronological epoch of
MM evolution, showing a preferred order of acquisition. Positively selected point
mutations frequently occur in later phases of disease development, as do structural
variants involving MYC. Thus, initiating driver events of MM, drawn from a limited
repertoire of structural and numerical chromosomal changes, shape preferred
trajectories of subsequent evolution.
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The genome of multiple myeloma (MM) is complex and heterogeneous, with a
high frequency of structural variants (SVs) and copy-number abnormalities (CNAs)1-
3. Translocations between the immunoglobulin heavy chain (IGH) locus and
recurrent oncogenes are found in ~40% of patients. Cases without IGH
translocations often have a distinctive pattern of hyperdiploidy affecting odd-
numbered chromosomes, where the underlying target genes remain mysterious.
These SVs and recurrent CNAs are considered early drivers, being detectable also
in pre-malignant stages of the disease1,2,4. Cancer genes are also frequently altered
by driver point mutations, with MAPK and NF-κB signaling as major targets5-8.
Many blood cancers develop along preferred evolutionary trajectories. Early
driver events, drawn from a restricted set of possible events, differ in which
subsequent cancer genes confer clonal advantage, leading to considerable
substructures of co-operativity and mutual exclusivity among cancer genes. These
subtypes vary in chemosensitivity and survival, suggesting that although patients
share a common histological and clinical phenotype, the underlying biology is
distinctly heterogeneous. Preliminary studies have suggested that these patterns
exist in MM as well5,7,9-12, but have not yet been systematically defined in large
cohorts with broad sequencing coverage.
We performed whole genome sequencing (WGS) of 67 tumor samples
collected at different time points from 30 MM patients, together with matched
germline controls (Supplementary Fig. 1, Supplementary Table 1, Methods). We
also included in our analyses published whole exome data from 804 patients13,14. To
discover significant cancer genes, we analyzed the ratio of non-synonymous to
synonymous mutations, correcting for mutational spectrum and covariates of
mutation density across the genome using a published algorithm15,16. Overall, 55
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genes were significantly mutated with a false discovery rate of 1% (Fig. 1a,
Supplementary Table 2). A significant fraction of these driver mutations was
detected at subclonal level, suggesting a major role in late phases of cancer
development (Supplementary Fig. 2a). Beyond well-known myeloma genes such as
KRAS, NRAS, DIS3 and FAM46C5-8, several other interesting candidate genes
emerged. The linker histones HIST1H1B, HIST1H1D, HIST1H1E and HIST1H2BK
all showed a distinctive pattern of missense mutations clustered in the highly
conserved globular domain (Supplementary Figure 2b-e), as reported in follicular
lymphoma17. Many of the mutations were nearby, or directly affected, conserved
positively charged residues critical for nucleosome binding, suggesting that they
disrupt the histones’ role in regulating higher order chromatin structure. FUBP1, an
important regulator of MYC transcription18, showed an excess of splice site and
nonsense mutations, suggesting it may be a tumor suppressor gene in MM
(Supplementary Figure 2f). MAX, a DNA-binding partner of MYC, showed an
interesting pattern of start-lost mutations, nonsense and splice site mutations,
together with hotspot missense mutations at residues Arg35, Arg36 and Arg60,
known to abrogate DNA binding7 (Supplementary Fig. 2g). Genes with rather more
mysterious function were also significant: the zinc finger ZNF292, recently described
as mutated in chronic lymphocytic leukemia and diffuse large B-cell lymphoma19,20,
showed an excess of protein-truncating variants (Supplementary Fig. 2h); the
uncharacterized TBC1D29 gene showed two hotspots of missense mutations21
(Supplementary Fig. 2i).
In pairwise comparisons, these cancer genes showed distinct patterns of co-
mutation and mutual exclusivity (Supplementary Fig. 2j). To define the logic rules
underpinning the conditional dependencies of driver events, we employed Bayesian
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networks and the hierarchical Dirichlet process (Fig. 1b-c, Supplementary Fig. 3).
This confirmed that the strongest determinants of genomic substructure in myeloma
are IGH translocations and recurrent CNAs. Some co-operating genetic lesions were
non-randomly distributed across these main groups: a significant fraction of patients
without IGH translocations were generally enriched for 1q gain and deletions on
1p13, 1p32, 13q, TRAF3 and CYLD (Cluster 1). RAS signaling mutations, especially
NRAS and KRAS, were associated with hyperdiploidy and MYC translocations
(Cluster 2). A significant fraction (33%) of patients with t(11;14) were characterized
by low genomic complexity and high prevalence of IRF4 and CCDN1 mutations
(Cluster 3). Patients harboring TP53 bi-allelic inactivation were clustered in an
independent sub group (Cluster 4). A significant fraction of MMSET (51%) and
CCND1 (19%) translocated patients were characterized by multiple cytogenetic
aberrations, with low prevalence of CYLD/FAM46C deletions and TRAF3 deletion
respectively (Cluster 5). A second fraction of patients with MMSET translocation
(46%) were grouped with deletion of 13q14, gain of 1q21, DIS3 and FGFR3
mutations (Cluster 6); finally, patients with either MAF/MAFB translocations or no
IGH translocations was characterized by a high driver mutation rate (Cluster 7).
Thus, there is evidence for at least 7 distinct genomic subtypes of myeloma, each
with distinct combinations of driver mutations and recurrent SVs (Figure 1c).
Straightforward reciprocal translocations such as the canonical IGH-oncogene
translocations only accounted for 6% (127/2113) of SVs in the 67 samples from 30
patients studied by WGS (Figure 2a, Supplementary Fig. 4a-b). Other structural
variants included many unbalanced translocations and complex events
(Supplementary Fig. 4c-f, Methods)22. Most (24/30; 80%) patients had at least one
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complex SV, of which chromothripsis was the most frequent (11/30; 36%) (Fig. 2b-
c)22-26. Chromoplexy occurred in 3 patients (Fig. 2b, Supplementary Fig. 5a-c)22,27.
In 6/30 (20%) patients, we found a novel complex pattern characterized by
cycles of templated insertions. Here, several low-amplitude copy number gains on
different chromosomes were linked together through SVs demarcating the region of
duplication (Fig. 2b,d; Supplementary Fig. 5d-h). The most plausible explanation
for this pattern is that the templates are strung together into a single chain, hosted
within one of the chromosomes. We have observed such events in some solid
cancers22, where the copy number gains suggest a mutational process that is
replication-based, rather than the break-and-ligate processes generating
chromothripsis and chromoplexy23.
This complex landscape of SVs in myeloma often involved known driver
genes: MYC (14/30 cases; 46%), CCND1 (7/30; 23%) and MMSET (3/30; 10%) were
common targets (Supplementary Fig. 4b) of these non-canonical events. The
juxtaposition of CCND1 to the IGH locus was caused by either unbalanced
translocations or insertional events in 5/8 patients (Supplementary Fig. 6). Similarly,
MYC translocations showed unanticipated complexity, with four cases of templated
insertions involving MYC or its regulatory regions (Supplementary Fig. 7). Such
events are the structural basis of oncogene amplification observed by FISH in many
cases of t(11;14) and t(8;14)28,29. Interestingly, many of the MYC SVs involved the
immunoglobulin light chain loci, IGK or IGL, rather than the heavy chain IGH locus,
and were seen in patients with hyperdiploidy (Supplementary Fig. 4b). Although
sometimes occurring late, these events were under strong selective pressure: we
identified a striking case of convergent evolution where a subclone bearing an
IGL:MYC translocation was lost and one bearing an IGH:MYC was acquired at
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relapse (Supplementary Fig. 8). SVs also led to loss of tumor suppressor genes
such as BIRC2/3, CDKN2A/B, CDKN2C, TRAF330 and FAM46C, either within focal
deletions or more complex events. These data confirm that SVs, accessing both
simple and complex mechanisms of genome rearrangement, is a major force
shaping the myeloma genome.
In our cohort of serial WGS samples we could evaluate the temporal evolution
of the disease, integrating SVs, CNAs and point mutations. This included not only
defining clonal and subclonal mutations and CNAs, but also timing the relative order
of acquisition of clonal chromosomal gains, which we estimated with “molecular time”
analysis based on the fraction of duplicated to single-copy point mutations
(Methods)31.
Hyperdiploidy was found in 18/30 patients. Applying our “molecular time”
analysis, we found that chromosomal gains were not necessarily acquired
simultaneously (Fig. 3a). In 11/18 cases, we found evidence of several independent
gains over time, although the other 7 patients acquired all chromosome gains in a
much narrower time window (Fig. 3b). As might be expected if gains occur as
independent events, subclonal evolution within the myeloma cells between diagnosis
and relapse could lead to considerable diversification of chromosome complements.
In fact, we observed significant karyotype changes within the same patient over time,
including loss of some trisomies in hyperdiploid patients (Supplementary Fig. 9a-
b)32. At the extreme end of this cytogenetic dynamism, we found 4 patients acquiring
a whole genome duplication at relapse, suggesting its potential role in
relapsed/refractory stages (Supplementary Fig. 9c-g).
By pairwise comparison of the relative timings of copy number alterations we
reconstructed the preferred chronological order of CNAs acquisition (Methods).
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Gains of chromosomes 19, 11, 9 and 1q were amongst the earliest in our series
(Fig. 3c) and recurrent chromosome losses were generally acquired later than
trisomies, consistent with the proposition that hyperdiploidy is an early driver event in
MM.
Translocations involving CCND1 and MMSET were always fully clonal,
similarly confirming their early driver role in MM pathogenesis. Most chromothripsis
events were clonal and conserved during evolution (17/22; 77%), suggesting they
occurred early in MM pathogenesis. However, a small fraction of patients showed
some evidence of subclonal or late chromothripsis (5/22; 23%), implying a potential
involvement in drug resistance and late cancer progression (Supplementary Fig.
9h).
We integrated all extracted chronological data on SVs, hyperdiploidy and
point mutations to generate phylogenetic trees for each sample (Methods and
Supplementary Fig. 10)5,33. The methodology is worked through for one illustrative
patient carrying i) several chromosome gains, ii) 3 separate chromothripsis events
and iii) a whole genome duplication (Fig. 3d-f). One chromothripsis involved
chromosomes 8 and 15, duplicating the long arm of chromosome 15. Because few
mutations were present on chromosome 15 at the time it duplicated, this must have
occurred early in molecular time (Fig. 3e). Gain of chromosome 3 and copy-neutral
loss-of-heterozygosity of small arm of chromosome 1 (chr1p) occurred not long after,
and were followed by a second chromosomal crisis involving chromosomes 3, 5, 13
and 22. This chromothripsis must have occurred in one of the two duplicated alleles
of chromosome 3 (and therefore after the acquisition of a chromosome 3 trisomy)
because losses within the chromothripsis region had copy number 2 and SNPs were
heterozygous. Within the same time window, a separate chromothripsis event
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occurred on chr1p after copy-neutral loss-of-heterozygosity. Finally, this patient
underwent whole genome duplication after two therapy lines (Supplementary Fig.
9f).
Applying this approach to all patients, we observed that the trunks of the
phylogenetic trees of 29/30 (97%) patients were characterized by few genomic
events generally acquired during different time windows of the MM life history before
emergence of the most recent common ancestor (Fig. 4). Overall, chromothripsis,
cycles of templated insertions, chromosomal gains and other SVs accounted for
most of the earliest events, emerging as key early drivers of the disease and paving
the way for subsequent driver mutations that would confer further selective
advantage to the clone.
Taken together, these data suggest that MM development follows preferred
evolutionary trajectories, with stuttering accumulation of driver events in keeping with
its insidiously progressive but unpredictable clinical course. Critical early events
include immunoglobulin translocation with MMSET and CCND1; hyperdiploidy and
focal complex structural variation processes hitting key myeloma genes. These early
driver mutations shape the subsequent evolution of myeloma, each with preferred
sets of co-operating cancer genes.
Acknowledgements:
FM is supported by A.I.L. (Associazione Italiana Contro le Leucemie-Linfomi e
Mieloma ONLUS) and by S.I.E.S. (Società Italiana di Ematologia Sperimentale).
NB is funded by AIRC (Associazione Italiana per la Ricerca sul Cancro) through a
MFAG (n.17658).
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This work was supported by: Department of Veterans Affairs Merit Review Award
I01BX001584-01 (NCM), NIH grants P01-155258 (N.C.M., H.A.L., M.F., P.J.C., K.
C.A.) and 5P50CA100707-13 (N.C.M., H.A.L., K.C.A).
Authorship Contributions:
F.M., N.B., and P.J.C. designed the study, collected and analyzed the data and
wrote the paper; H.A.L., N.C.M. designed the study and collected the data; K.J.D.,
D.L., N.A., I.M., T.J.M., A.F., D.G., S.G., M.G., M.R., F.A., B.R.M., J.M.C.T. and
D.W. analyzed the data; S.M., R.S., M.K.S., M.F., Y.T.T., M.F., P.M., P.C., K.C.A.,
collected the data.
Disclosure of Conflicts of Interest:
No conflict of interests to declare.
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11
Figure Legend
Figure 1. a) Landscape of Driver Mutations in Multiple Myeloma (MM). Each bar
represents a distinct driver gene and each bar’s colour indicate its prevalence across
the main MM cytogenetic sub-groups. b) We built the optimal Bayesian network by
considering the recurrent SVs/ CNAs (n 14) and driver SNVs (n 55) across 724 MM
patients where the final list of 69 variables was assessed. To further investigate the
type of recurrence patterns we fitted logic gates between parent and child nodes in
the network. The gate combination with the highest Fisher exact test p value was
selected. The line width is proportional to the log hazard ratio of the test. Dashed
lines represent non-significant associations (p>0.05). CNAs and translocations were
coloured by red and light blue respectively. The width of the boundary line of each
drawn box is proportional to its prevalence across the entire series. c) Heat map
showing the main MM genomic subgroups across 724 MM patients. The genomic
profile of each cluster was generated by integrating the hierarchical Dirichlet process
and Bayesian network data. Rows in the graph represent individual genomic lesions,
and the columns represent patients.
Figure 2. a) SVs prevalence across the entire series. b) Heatmap representing the
distribution and prevalence of the main complex SVs: chromothripsis, chromoplexy
and templated insertion. c) Three examples of chromothripsis. d) Example of
templated insertion. In the middle, the genome plot of patient PD26422 represents all
main genomic events: mutations (external circle), indels (middle circle; dark green
and brown lines represent insertion and deletion respectively), copy number variants
(red = deletions, green = gain) and rearrangements (blue = inversion, red =
deletions, green = ITD, black = translocation). Externally, a copy
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number/rearrangement plot of each chromosome involved by the templated insertion
is provided, highlighting a focal CNA around each breakpoint. This case represents a
clear example of how templated insertion may involve critical driver oncogenes, like
CCND1 in this case. A schematic representation of this sample templated insertion is
reported on the right.
Figure 3. a-b) Molecular time estimation on all chromosomal gains observed in 2
hyperdiploid MMs. On the left the copy number profile is reported, where gold line =
total copy number, grey = copy number of the minor allele. The presence of more
than 1 cytogenetic segment is compatible with the existence of a subclonal CNA
whose CCF is proportional to the segment thickness [see for example the gain on 4q
in PD26410d (a)]. On the right, the molecular time (blue dots) estimated for each
clonal gain and copy neutral loss of heterozygosity (Methods). Red dots represent
the molecular time of a second extra gain occurred on a previous one. Dashed green
lines separate multi gain events occurring at different time windows c) Bradley Terry
model based on the integration between the CCF and molecular time of each
recurrent MM CNAs (gains and deletions). Segments were ordered from the earliest
(top) to the latest (bottom) occurring in relative time from sampling (X-axis). d)
Genome plot of patient PD26419a where the three chromothripsis events [(8;15),
(3;5;13;22) and 1p] were highlighted with different colored dashed lines connected to
specific rearrangements/copy number plots. In these plots, the red arch represents a
deletion, the green arch represents an ITD and the blue arch represents an
inversion. e) Molecular time of the main clonal gains and LOH in the PD26419a
sample. This data suggested the existence of at least 2 different and independent
time windows: the first involving alterations on chromosome 3, 15 and 1p and the
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second on chromosome 1q. f) The driver events of patient PD26419 are
reconstructed in chronological order.
Figure 4. The most likely phylogenetic trees generated from the Dirichlet process
analysis (Methods). The root (always colored in red) and branch length is
proportional to the (sub)clone mutational load. All main drivers (CNAs, SNVs and
SVs) were annotated according to their chronological occurrence. Early clonal
events (root), where it was possible to establish a specific time window, were
chronologically annotated on the right. All different “root” time windows were
separated by a green line; conversely, early drivers without a clear timing were
grouped together on the left of the root. All driver events that occurred in the root
were reported with larger font size. Patients were grouped according to the genomic
clustering showed in Figure 1c. Templated insertion is abbreviated with TI.
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28 Affer, M. et al. Promiscuous MYC locus rearrangements hijack enhancers but mostly super-enhancers to dysregulate MYC expression in multiple myeloma. Leukemia 28, 1725-1735, doi:10.1038/leu.2014.70 (2014).
29 Fabris, S. et al. Characterization of oncogene dysregulation in multiple myeloma by combined FISH and DNA microarray analyses. Genes Chromosomes Cancer 42, 117-127, doi:10.1002/gcc.20123 (2005).
30 Chavan, S. S. et al. Bi-allelic inactivation is more prevalent at relapse in multiple myeloma, identifying RB1 as an independent prognostic marker. Blood Cancer J 7, e535, doi:10.1038/bcj.2017.12 (2017).
31 Gerstung, G. et al. The evolutionary history of 2,658 cancers. bioRxiv, doi:http://dx.doi.org/10.1101/161562. (2018).
32 Rasche, L. et al. Spatial genomic heterogeneity in multiple myeloma revealed by multi-region sequencing. Nat Commun 8, 268, doi:10.1038/s41467-017-00296-y (2017).
33 Nik-Zainal, S. et al. The life history of 21 breast cancers. Cell 149, 994-1007, doi:10.1016/j.cell.2012.04.023 (2012).
certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was notthis version posted August 12, 2018. ; https://doi.org/10.1101/388611doi: bioRxiv preprint
17
34 Walker, B. A. et al. Characterization of IGH locus breakpoints in multiple myeloma indicates a subset of translocations appear to occur in pregerminal center B cells. Blood 121, 3413-3419, doi:10.1182/blood-2012-12-471888 (2013).
certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was notthis version posted August 12, 2018. ; https://doi.org/10.1101/388611doi: bioRxiv preprint
Hyperdiploidt.11.14.t.4.14.t.14.16.t.14.20.ampMYCdel13q14del17p13delCDKN2CdelCYLDdelFAM46CdelTRAF2delTRAF3gain1q21KRASNRASIGLL5DIS3BRAFTRAF3TP53FAM46CDUSP2ACTG1HIST1H1EKLHL6CYLDCCND1IRF4PABPC1PIM1TCL1AFGFR3SP140PRDM1SETD2TRAF2NFKB2RB1BTG1RFTN1TBC1D29HIST1H1BRASA2DTX1HIST1H2BKHIST1H1DBCL7AFUBP1CDKN1BXBP1RPL5LCE1DRPRD1BBHLHE41POT1RPS3AIRF1TGDSRPL10ZNF292PTPN11NFKBIASAMHD1KMT2BLTBPRKD2EGR1MAX
cluster
Hyperdiploidt.11.14.t.4.14.t.14.16.t.14.20.ampMYCdel13q14del17p13delCDKN2CdelCYLDdelFAM46CdelTRAF2delTRAF3gain1q21KRASNRASIGLL5DIS3BRAFTRAF3TP53FAM46CDUSP2ACTG1HIST1H1EKLHL6CYLDCCND1IRF4PABPC1PIM1TCL1AFGFR3SP140PRDM1SETD2TRAF2NFKB2RB1BTG1RFTN1TBC1D29HIST1H1BRASA2DTX1HIST1H2BKHIST1H1DBCL7AFUBP1CDKN1BXBP1RPL5LCE1DRPRD1BBHLHE41POT1RPS3AIRF1TGDSRPL10ZNF292PTPN11NFKBIASAMHD1KMT2BLTBPRKD2EGR1MAX
clusterHyperdiploidt.11.14.t.4.14.t.14.16.t.14.20.ampMYCdel13q14del17p13delCDKN2CdelCYLDdelFAM46CdelTRAF2delTRAF3gain1q21KRASNRASIGLL5DIS3BRAFTRAF3TP53FAM46CDUSP2ACTG1HIST1H1EKLHL6CYLDCCND1IRF4PABPC1PIM1TCL1AFGFR3SP140PRDM1SETD2TRAF2NFKB2RB1BTG1RFTN1TBC1D29HIST1H1BRASA2DTX1HIST1H2BKHIST1H1DBCL7AFUBP1CDKN1BXBP1RPL5LCE1DRPRD1BBHLHE41POT1RPS3AIRF1TGDSRPL10ZNF292PTPN11NFKBIASAMHD1KMT2BLTBPRKD2EGR1MAX
cluster
KMT2B
SAMHD1
PTPN11
RPRD1B
XBP1
RB1
IRF4
IGLL5
gain1q21
delTRAF3
delFAM46C
del17p13
del13q14
t_4_14
HDR
ACTG1 BCL7A BHLHE41
BRAF
BTG1CCND1
t_11_14
EGR1
FUBP1
HIST1H1B
HIST1H1E
KRAS
NFKBIA
RPS3A
TCL1A
TGDS
delCDKN2C
delCYLD
CYLD
t_14_16
ampMYCMAX
FGFR3
NRASDIS3
TP53
TRAF3
NOT gateXOR gateOR gateAND gate# events (shown med=15,max=382)0.05 < q.valCo-occur (shown odds=4)Mut.excl (shown odds=0.25)Fisher test oddsa
c
b
●
0.6 0.8 1.0 1.2 1.4
0.6
0.8
1.0
1.2
1.4
Index
1
wtCNA/SVMissenseNonsenseStop/LossEssential Splice
Cluster 1Cluster 2Cluster 3Cluster 4Cluster 5Cluster 6Cluster 7
●
0.6 0.8 1.0 1.2 1.4
0.6
0.8
1.0
1.2
1.4
Index
1
wtCNA/SVMissenseNonsenseStop/LossEssential Splice
Cluster 1Cluster 2Cluster 3Cluster 4Cluster 5Cluster 6Cluster 7
0
50
100
150
Hyperdiploidt(11;14)t(14;16)t(14;20)t(4;14)None
KRAS
NRAS
IGLL5
DIS3
BRAF
TP53
TRAF3
DUSP2
FAM46C
HIST1H1E LTB
ACTG1
EGR1
PRKD2
FGFR3
KLHL6
MAX
IRF4
PABPC1
KMT2B
SP140
PRDM
1SETD2
CYLD
PIM1
PTPN11
SAMH
D1CCND1
NFKB2
RPL10
TCL1A
TRAF2
RFTN1
TBC1D29
BTG1
ZNF292
BCL7A
HIST1H1B RB1
BHLHE41
NFKBIA
POT1
RPS3A
TGDS
DTX1
FUBP1
HIST1H1D
HIST1H2BK
RASA2
IRF1
RPL5
XBP1
CDKN1B
RPRD1B
LCE1D
Num
ber o
f pat
ient
s (o
f 834
ana
lyse
d)
certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was notthis version posted August 12, 2018. ; https://doi.org/10.1101/388611doi: bioRxiv preprint
PD26400a
PD26400c
PD26401a
PD26401c
PD26402a
PD26402c
PD26403a
PD26403c
PD26403d
PD26404a
PD26404c
PD26405a
PD26405c
PD26406a
PD26406c
PD26408a
PD26408c
PD26409a
PD26409c
PD26410d
PD26411a
PD26411c
PD26411d
PD26412a
PD26412c
PD26412d
PD26414a
PD26414b
PD26414e
PD26414f
PD26414g
PD26415c
PD26415g
PD26416d
PD26416e
PD26418a
PD26418c
PD26418d
PD26418e
PD26419a
PD26419c
PD26419d
PD26420a
PD26420c
PD26422d
PD26422e
PD26422f
PD26423e
PD26423g
PD26423h
PD26424a
PD26424c
PD26425e
PD26425f
PD26426e
PD26427a
PD26427c
PD26428a
PD26428c
PD26429a
PD26432c
PD26432e
PD26434c
PD26435c
PD26435e
0
20
40
60
80
100
120
140 DeletionInversionITDTranslocation
Complex SV
Chromothripsis
Templated Insertion
Chromoplexy
b
chr15 position (Mb)0 20 40 60 80 100
●
●●●●●●●●●
●●●●●●●●●●●●●●●●●● ●●●●●●
●
●●
●●●●●●●●●
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●
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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
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●
●●●●●●●●●●●●●●●●●●●●●●●●●
●
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●●●
●
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●
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●
●
●
●
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●
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●
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●
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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
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●●●●●●●●●●●●●
●●●
●●●●●●●●●●●●●●●●●●●●●●
●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●
●●●●●●●●●●●●●●●
●
●
●
01234
Cop
y nu
mbe
r
2020
●
PD26420c
chr12 position (Mb)0 20 40 60 80 100 120
●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●
●
●●●●●●●●●●●●●●●●●●
●●
●
●
●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
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●
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●●●
●
●●●
0.00.51.01.52.02.53.0
Cop
y nu
mbe
r
2215
●
PD26422echr14 position (Mb)
0 20 40 60 80 100
●●●
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●
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y nu
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2211
111 1
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chr11 position (Mb)0 20 40 60 80 100 120
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y nu
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r
1414
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chr1 position (Mb)0 50 100 150 200
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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●
●
01234
Cop
y nu
mbe
r
1414
XX
●
PD26422e
chr22 position (Mb)0 10 20 30 40 50
●
●
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●
●●
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●●
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●
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●
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●
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●
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●
●
●
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●●●●●●●●●●
●●
0.00.51.01.52.02.53.0
Cop
y nu
mbe
r
1214
●
PD26422e
Chr 1(Mb)
Chr 11(Mb)
Chr 22(Mb)PD26422e
Chr 14(Mb)
Chr 12(Mb)
CCND1
IGH
Chr 12
Chr 1
Chr 11
Chr 14
Chr 22
Chr 15Chr 15(Mb)
c
PD26429aPD26425fPD26435ePD26435cPD26400cPD26400aPD26401aPD26401cPD26425ePD26419dPD26411aPD26411cPD26411dPD26408aPD26408cPD26422dPD26422ePD26422fPD26423gPD26423hPD26404aPD26404cPD26410dPD26419aPD26419cPD26405aPD26405cPD26420aPD26420cPD26424aPD26424cPD26409aPD26409cPD26416dPD26423ePD26432cPD26432ePD26416ePD26403dPD26403aPD26403cPD26415cPD26415gPD26418aPD26418cPD26418dPD26418ePD26427aPD26427cPD26414aPD26414bPD26414ePD26414fPD26414gPD26426ePD26402aPD26402cPD26406aPD26406cPD26407aPD26407cPD26412aPD26412cPD26412dPD26428aPD26428cPD26434c
OtherComplex1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0
Chromotripsis1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
Cyclo_Temp_more_chr0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 2 2 2 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
Chromoplexy 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
PD26400a
PD26400c
PD26401a
PD26401c
PD26402a
PD26402c
PD26403a
PD26403c
PD26403d
PD26404a
PD26404c
PD26405a
PD26405c
PD26406a
PD26406c
PD26408a
PD26408c
PD26409a
PD26409c
PD26410d
PD26411a
PD26411c
PD26411d
PD26412a
PD26412c
PD26412d
PD26414a
PD26414b
PD26414e
PD26414f
PD26414g
PD26415c
PD26415g
PD26416d
PD26416e
PD26418a
PD26418c
PD26418d
PD26418e
PD26419a
PD26419c
PD26419d
PD26420a
PD26420c
PD26422d
PD26422e
PD26422f
PD26423e
PD26423g
PD26423h
PD26424a
PD26424c
PD26425e
PD26425f
PD26426e
PD26427a
PD26427c
PD26428a
PD26428c
PD26429a
PD26432c
PD26432e
PD26434c
PD26435c
PD26435e
0
20
40
60
80
100
120
140DeletionInversionITDTranslocation
Num
ber o
f SVs
a
d
chr6 position (Mb)0 50 100 150
●●●
●
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●
01234567
Cop
y nu
mbe
r
888
142121 1414
1414
1419
19
●
PD26424a
chr19 position (Mb)0 10 20 30 40 50
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●●●●●●●●●
0.00.51.01.52.02.53.0
Cop
y nu
mbe
r
●
PD26425e
chr17 position (Mb)0 20 40 60 80
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0.00.51.01.52.02.53.0
Cop
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PD26414e
PD26424a
PD26414a
PD26425e
Chr 6 (Mb)
Chr 17 (Mb)
Chr 9 (Mb)
certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was notthis version posted August 12, 2018. ; https://doi.org/10.1101/388611doi: bioRxiv preprint
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01234
Cop
y nu
mbe
r
335
5
●
PD26419a
chr8 position (Mb)0 20 40 60 80 100 120 140
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012345
Cop
y nu
mbe
r
15 151515
151515 1515
1515 1515
151515 14
14
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PD26419achr5 position (Mb)
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Cop
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2213
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PD26419achr1 position (Mb)
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01234567
Cop
y nu
mbe
r
●
PD26419a
Chr 8 (Mb)
Chr 1 (Mb)
Chr 13 (Mb)
Chr 15 (Mb)
Chromothripsis on (8;15)
Chromothripsis (3,5,13,22)
Chromothripsis on 1p
Treatments
Chr 3 (Mb)
Chr 5 (Mb)
e
Gain 3, 15, LOH 1p
PD26419a – Molecular Time
Early
Late
1q gain
Whole Genome
Duplication
1st 2nd
PD26419a
d
Chr 22 (Mb)
f
2nd MG
1st MGEarly
Late
a
b
Ploi
dy
543210
PD26410d
PD26404a
Ploi
dy
543210
1st MGEarly
Late
PD26404a - Molecular Time
PD26410d - Molecular Timec
Relative Order Time
2nd MG
1st MG
certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was notthis version posted August 12, 2018. ; https://doi.org/10.1101/388611doi: bioRxiv preprint
●
●
PD26434
t(11q13;14q32)
●
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●
PD26424
1st MG (6,7,9,14,18,19,21)
2nd MG (5)Complex 6p
DIS3PRKD2
LOH 3q22del14q
Chromothripsis t(6;8;14;21)t(2p25;9p24)
●
●
●
PD26426
TI t(1;5;7;8;9;11;15;22)
NRASPRDM1FAM46c
del 1p 1st MG (3,4,5,6,7,11,19)
gain 15del 14qdel 13q342nd gain 1q21-23 2nd gain 8q24
amp MYC2nd gain 8
●
●
●
PD26402
t(11q13;14q32)
NRAS
t(8q24;16q21)1st gain 8
gain 18
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PD26429
1st MG (5,19)
2nd MG (5,9,11,15,16)Complex 5Complex 19q
Complex 1pComplex t(6;8)
Complex 2TP53
FAM46cChromothripsis 16Chromothripsis 12
del 13
del 17p
t(6q14;16p11)Chromothripsis 1pgain 9 (extra)
Complext(4;18)Complex5
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●
PD26400
1st MG (1,3,5,6,9,16,18,19)
2nd MG (12nd,16) Complex 6qPTPRD deldel 6q
del 14qChromothripsis
t(1;6,13,16)
del 13q14-q21Chromoplexy
t(2;8)
2nd del 14q del 12p
●
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●
PD26403
1st MG (3,5,7,10,11,19)
gain 3LOH Xq
del 8pdel 3q
bi-del CDKN2C
del CDKN2Cdel13
NRASComplex 16p
del Xq25 x 3Chromoplexy t(3;8;18;X)del 6q, 9p, 19gain 18q
t(6q13;7p12)
del 6qdel Xq27
bi-del RB1t(4p16.1;18q21)
del 6q16del 6q27
●
●
PD26404
Complex 12qgain 9 and 15 t(8q24;22q11)t(2p14;19p13)
NRAS 1st MG (3,5,7,10,11,19)
Complex 3pdel 3p
●
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●
PD26407
1st MG (3,5,6,9,11,15)
del 13
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●
PD26408
1st MG (1,5,9,11,15)
Chromothripsis 4gain 3t(8q24;20q11)Complex 11
NRASComplex 19
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●
PD26412
1st MG (1,18)
2nd MG (2,7,182nd)t(7p21;Xq21)
t(8q24;22)
3rd MG (1,3)
del 6qt(8q24;14q32)del 13del 1p
4th MG
●●
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●
PD26432del 8p
del 13q22-31del 12pgain 21
Complex t(5;10;19) Complex t(2;9;16)
2nd MG event(1q22;7q32)
1st MG (3,5,7,19)
TI t(8;11;15;17;20)
t(1p36;17q21)
●
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●
PD26428
gain 9 and 19inv 1qKRAS
t(11q13;14q32)
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●
PD26418
t(11q13;14q32)
Complex t(17;22)
TP53t(16p13;Xq21)
1st MG (5,11)
2nd MG t(3p24;17q22)
Focal 5q14 del
Focal 5q31 delLOH 13
t(11q23;14q24)Cluster 1
Cluster 2
Driver EventsClusters
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●
PD26420
1st MG (1,8)t(7p21;8q21)t(1q23;12q23)
Chromothripsis 16Complex t(15;20)
t(3q11;20p11)t(6q14;Xq21)
BRAFdel 13
2nd MG events
t(11q13;14q32)
●
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●
Complex 6TI t(3;6;16)
del 17q11-q21del 13del 1p
PD26422
TI t(1;11;12;14;15;22)
del4p
Complex 14q
del17p
t(11q13;14q32)
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●
2nd MG (6,9)TI t(3;7;8;22)t(1q32;19p13)Complex 7q
PD26411
Complex 151nd MG (1,3,7,10,15)
1st Chromothripsis t(11;16)del 20qBRAF
2st Chromothripsis t(11;16)del 8p
ITD FAM46c
●
●
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●
PD26414
1st MGdel 13, 1p and 6q
1st WGD
2nd WGD
BRAFChromothripsis 17p
t(4p16;14q32)
●
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●
PD26415
1nd MG (3,5,9,11)
Complex 6p
●
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●
PD26427
1st MG (1,9,11,15)
2st MGt(12q21;15q21)
del 16gain 9qdel 17
t(11q13;14q32)Complex 3p
●
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●
PD26416Complex t(4;21)t(16p12;17p11)
amp MYCdel 9p
1st MG (3,5,9,11,19)
2nd MG (7)del 5p
NRASCYLDdel 1p
t(9q21;17q21)t(11p11;20q13)
TI t(2;8;16)
Chromoplexy (10;12;19)Complex 12qComplex 1q
●
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●
PD26410
2nd MG (7,8,112nd)
1nd MG (3,5,9,11,21)
t(6p24;8q24)del 1pdel 8p
3rd MG event (4, 113rd)t(11q21;16q23)
●
●
●
●
PD26405
t(4p16;14q32)
LOH 4p
Chromothripsis 18q
Chromothripsis 4inv(2p22;2p13)
gain 1qdel 13
del 1q and 14qgain 15, 16t(2p25;6q15)t(7p15;14q32)Complex 2p
del 12pdel 6qdel 5q
●
●
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●
PD26435
1st MG (9, 19)
2nd MG (1,3,11)
t(1q32;15q15)Complex 20,14q, XChromothripsis 1p
Chromothripsis 8KRAS
PRDM1RASA2
del 13
Chromothripsis 20WGA
●
●●
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●
3nd MG
PD26423
t(8q24;14q32)del 17p
ITD FAM46cComplex 14q
TI t(2;10;11;12;20)WGD – 2nd MG (14)
1st MG (1,2,3,4,6)
Focal MYC amp
del 4pextra gain 5q22del 13
t(3p22;9p21)t(9q22;15q23)
●
●
●
PD26409
1st MG (5,7,15)
BRAFdel 1p
t(2p24;21q22)Complex 14q
TI t(1;6;8;22)t(4q31;8q23)
t(11q13;14q32)
●
●
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●
PD26425
Complex 18 Chromothripsis x 4
(2, 11, 18, 19)
Chromothripsis 16
bi-del CDKN2A/Bbi-del BIRC2/BIRC3
Chromothripsis 7p
Del13qComplex 20q
●
●●
●
●
PD26406
del 6q gain 2
bi-del 13q11-q21
IRF4del 11q bi-del BIRC2/YAP1bi-del TRAF3
gain 1q
del 13del 14DIS3
t(4p16;14q32)
●
●
●
PD26401
del 14qComplex 5qComplex t(2;14)Complex 10qt(16q21;Xq27)
inv (1p22;1q21) del 13inv(Xp22;Xq25)
●
●
●
PD26419
1nd Chromothripsis t(8;15)
1nd MG (1p,3,15)
3rd Chromothripsis 1p2nd Chromothripsis t(3;5;13;21)gain 1q
WGD
t(8q24; 14q32)Complex 4p
Cluster 3
Cluster 5
Cluster 4
Cluster 6
Cluster 7
SV with CNA
Complex Event Chromothripsis
Driver SNV
Multi Gain Event (MG)/Whole Genome Duplication