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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: pc8@sanger.ac.uk

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: nikhil_munshi@dfci.harvard.edu

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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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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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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

●

●●●●●●●●●

●●●●●●●●●●●●●●●●●● ●●●●●●

●

●●

●●●●●●●●●

●●

●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●

●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●

●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●

●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●

●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●

●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●

●

●●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●●

●

●

●

●

●●

●

●●

●

●●●

●

●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●

●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●

●●●●●●●●●●●●●

●●●

●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●

●

●

●

01234

Cop

y nu

mbe

r

2020

●

PD26420c

chr12 position (Mb)0 20 40 60 80 100 120

●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●●●●

●●

●

●

●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●

●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●

●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●

●

●●●

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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PD26422e

chr22 position (Mb)0 10 20 30 40 50

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0.00.51.01.52.02.53.0

Cop

y nu

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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)

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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

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PD26422d

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PD26435e

0

20

40

60

80

100

120

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Num

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chr6 position (Mb)0 50 100 150

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chr19 position (Mb)0 10 20 30 40 50

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0.00.51.01.52.02.53.0

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PD26425e

chr17 position (Mb)0 20 40 60 80

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0.00.51.01.52.02.53.0

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PD26414e

PD26424a

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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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335

5

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PD26419a

chr8 position (Mb)0 20 40 60 80 100 120 140

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15 151515

151515 1515

1515 1515

151515 14

14

●

PD26419achr5 position (Mb)

0 50 100 150

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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)

●

●

●

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

●

●

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

●

●

●

●

●

●

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

●

●

●

●●

●

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

●

●

●

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

●●

●

●

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)

●

●

●

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

●

●●

●

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)

●

●●

●

●

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)

●

●

●

●

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

●

●

●

●

PD26414

1st MGdel 13, 1p and 6q

1st WGD

2nd WGD

BRAFChromothripsis 17p

t(4p16;14q32)

●

●

●

●

PD26415

1nd MG (3,5,9,11)

Complex 6p

●

●

●

●

PD26427

1st MG (1,9,11,15)

2st MGt(12q21;15q21)

del 16gain 9qdel 17

t(11q13;14q32)Complex 3p

●

●

●●

●

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

●

●

●

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

●

●

●

●

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

●

●●

●

●

●

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)

●

●

●

●

●

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